F. I. Woodward

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

At eight European field sites, the impact of loss of plant diversity on primary productivity was simulated by synthesizing grassland communities with different numbers of plant species. Results differed in detail at each location, but there was an overall log-linear reduction of average aboveground biomass with loss of species. For a given number of species, communities with fewer functional groups were less productive. These diversity effects occurred along with differences associated with species composition and geographic location . Niche complementarity and positive species interactions appear to play a role in generating diversity-productivity relationships within sites in addition to sampling from the species pool.

Summary The possible responses of ecosystem processes to rising atmospheric CO 2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO 2 ( Wigley et al . 1991 ), and by climate changes resulting from effective CO 2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2‐SUL. Simulations with changing CO 2 alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y −1 during the 1990s, rising to 3.7–8.6 Pg C y −1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y −1 ) and a century later (0.3–6.6 Pg C y −1 ) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO 2 effects at high CO 2 concentrations. Four out of the six models show a further, climate‐induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO 2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO 2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO 2 and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO 2 and climate change.

Efforts to control climate change require the stabilization of atmospheric carbon dioxide concentrations. An assessment of the trends in sources and sinks of atmospheric carbon dioxide suggests that the sinks are not keeping up with the increase in carbon dioxide emissions, but uncertainties are still large. Efforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties.

This paper is the first global study of the extent to which fire determines global vegetation patterns by preventing ecosystems from achieving the potential height, biomass and dominant functional types expected under the ambient climate (climate potential). To determine climate potential, we simulated vegetation without fire using a dynamic global-vegetation model. Model results were tested against fire exclusion studies from different parts of the world. Simulated dominant growth forms and tree cover were compared with satellite-derived land- and tree-cover maps. Simulations were generally consistent with results of fire exclusion studies in southern Africa and elsewhere. Comparison of global 'fire off' simulations with landcover and treecover maps show that vast areas of humid C(4) grasslands and savannas, especially in South America and Africa, have the climate potential to form forests. These are the most frequently burnt ecosystems in the world. Without fire, closed forests would double from 27% to 56% of vegetated grid cells, mostly at the expense of C(4) plants but also of C(3) shrubs and grasses in cooler climates. C(4) grasses began spreading 6-8 Ma, long before human influence on fire regimes. Our results suggest that fire was a major factor in their spread into forested regions, splitting biotas into fire tolerant and intolerant taxa.

Preface Acknowledgements 1. History and demonstration 2. Scale 3. World climate 4. Climate and vegetation 5. Climate and the distribution of taxa 6. Digest Index.

Abstract This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO 2 , to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO 2 content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO 2 on plant production are not considered, implying a positive terrestrial climate‐carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra‐tropics in response to future climate. When both counteracting effects of climate and atmospheric CO 2 on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO 2 from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.

The Triassic-Jurassic boundary marks a major faunal mass extinction, but records of accompanying environmental changes are limited. Paleobotanical evidence indicates a fourfold increase in atmospheric carbon dioxide concentration and suggests an associated 3 degrees to 4 degrees C "greenhouse" warming across the boundary. These environmental conditions are calculated to have raised leaf temperatures above a highly conserved lethal limit, perhaps contributing to the >95 percent species-level turnover of Triassic-Jurassic megaflora.

A global primary productivity and phytogeography model is described. The model represents the biochemical processes of photosynthesis and the dependence of gas exchange on stomatal conductance, which in turn depends on temperature and soil moisture. Canopy conductance controls soil water loss by evapotranspiration. The assignment of nitrogen uptake to leaf layers is proportional to irradiance, and respiration and maximum assimilation rates depend on nitrogen uptake and temperature. Total nitrogen uptake is derived from soil carbon and nitrogen and depends on temperature. The long‐term average annual carbon and hydrological budgets dictate canopy leaf area. Although observations constrain soil carbon and nitrogen, the distribution of vegetation types is not specified by an underlying map. Variables simulated by the model are compared to experimental results. These comparisons extend from biochemical processes to the whole canopy, and the comparisons are favorable for both current and elevated CO 2 atmospheres. The model is used to simulate the global distributions of leaf area index and annual net primary productivity. These distributions are sufficiently realistic to demonstrate that the model is useful for analyzing vegetation responses to global environmental change.

List of contributors Preface Part I: 1. What are functional types and how should we seek them? H. Gitay and I. R. Noble 2. Plant and ecosystem functional types H. H. Shugart Part II: 3. Plant functional types: towards a definition by environmental constraints F. I. Woodward and C. K. Kelly 4. Can we use plant functional types to describe and predict responses to environmental change? R. J. Hobbs 5. Functional types in non-equilibrium ecosystems B. H. Walker 6. Categorizing plant species into functional types M. Westoby and M. Leishman 7. Functional types: testing the concept in Northern England J. P. Grime, J. G. Hodgson, R. Hunt, K. Thopson, G. A. F. Hendry, B. D. Campbell, A. Jalili, S. H. Hillier, S. Diaz and M. J. W. Burke Part III: 8. Plant functional types and ecosystem change in arctic tundras G. R. Shaver, A. E. Giblin, K. J. Nadelhoffer and E. B. Rastetter 9. Functional types for predicting changes in biodiversity: a case study in Cape Fynbos W. J. Bond 10. Defining functional types for models of desertification J. F. Reynolds, R. A. Virginia and W. H. Schlesinger 11. Plant functional types in temperate semi-arid regions O. E. Sala, W. K. Lauenroth and R. A. Golluscio 12. Interactions between demographic and ecosystem processes in a semi-arid and an arid grassland: a challenge for plant functional types W. K. Lauenroth, D. P. Coffin, I. C. Burke and R. A. Virginia 13. Plant functional types in African savannas and grasslands R. J. Scholes, G. Pickett, W. N. Ellery and A. C. Blackmore Part IV: 14. Using plant functional types in a global vegetation model W. Cramer 15. The use of plant functional type classifications to model the global land cover and simulate the interactions between the terrestrial biosphere and the atmosphere R. Leemans Part V: 16. Examining the consequences of classifying species into functional types: a simulation model analysis T. M. Smith 17. Ecosystem function of biodiversity: the basis of the viewpoint H. A. Mooney 18. Defining plant functional types: the end view F. I. Woodward, T. M. Smith and H. H. Shugart Index.

Ecological MonographsVolume 75, Issue 1 p. 37-63 Regular Article ECOSYSTEM EFFECTS OF BIODIVERSITY MANIPULATIONS IN EUROPEAN GRASSLANDS E. M. Spehn, E. M. Spehn Institute of Botany, University of Basel, Schoenbeinstrasse 6, Basel, Switzerland, CH-4056 E-mail: [email protected]Search for more papers by this authorA. Hector, A. Hector Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PY Present address: Institute of Environmental Sciences, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland, CH-8057Search for more papers by this authorJ. Joshi, J. Joshi Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorM. Scherer-Lorenzen, M. Scherer-Lorenzen Max-Planck-Institute for Biogeochemistry, Postfach 10 01 64, Jena, Germany, D-07701 Present address: Swiss Federal Institute of Technology Zürich (ETH), Institute of Plant Sciences, Universitätsstrasse 2, Zürich, Switzerland, CH-8092Search for more papers by this authorB. Schmid, B. Schmid Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorE. Bazeley-White, E. Bazeley-White Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. Beierkuhnlein, C. Beierkuhnlein Lehrstuhl Biogeographie, Universität Bayreuth, Bayreuth, Germany, D-95440Search for more papers by this authorM. C. Caldeira, M. C. Caldeira Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399Search for more papers by this authorM. Diemer, M. Diemer Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorP. G. Dimitrakopoulos, P. G. Dimitrakopoulos Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorJ. A. Finn, J. A. Finn Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, Ireland Present address: Teagasc Environmental Research Centre, Johnstown Castle, Wexford, IrelandSearch for more papers by this authorH. Freitas, H. Freitas Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399 Present address: Departamento de Botánica, Universidade de Coimbra, 3000 Coimbra, PortugalSearch for more papers by this authorP. S. Giller, P. S. Giller Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorJ. Good, J. Good Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorR. Harris, R. Harris Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorP. Högberg, P. Högberg Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183Search for more papers by this authorK. Huss-Danell, K. Huss-Danell Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403Search for more papers by this authorA. Jumpponen, A. Jumpponen Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183 Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403 Present address: Division of Biology, Kansas State University, Manhattan, Kansas 66506 USASearch for more papers by this authorJ. Koricheva, J. Koricheva Section of Ecology, Department of Biology, University of Turku, 20014 Turku, FinlandSearch for more papers by this authorP. W. Leadley, P. W. Leadley Institute of Botany, University of Basel, Schoenbeinstrasse 6, Basel, Switzerland, CH-4056 Present address: Ecologie des Populations et Communautés, Université Paris Sud XI, URA CNRS 2154, Bátiment 326, Orsay Cedex, France, FR-91405Search for more papers by this authorM. Loreau, M. Loreau Laboratoire d'Écologie, UMR 7625, École Normale Supérieure, 46 Rue d'Ulm, Paris Cedex 05, France, FR-75230Search for more papers by this authorA. Minns, A. Minns Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. P. H. Mulder, C. P. H. Mulder Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183 Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403 Present address: Department of Biology and Wildlife and Institute of Arctic Biology, University of Alaska, 410 Irving I, Fairbanks, Alaska 99775-7000 USASearch for more papers by this authorG. O'Donovan, G. O'Donovan Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, Ireland Present address: Department of Environmental Resource Management, University College of Dublin, Belfield, Dublin, IrelandSearch for more papers by this authorS. J. Otway, S. J. Otway Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. Palmborg, C. Palmborg Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403Search for more papers by this authorJ. S. Pereira, J. S. Pereira Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399Search for more papers by this authorA. B. Pfisterer, A. B. Pfisterer Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorA. Prinz, A. Prinz Lehrstuhl Biogeographie, Universität Bayreuth, Bayreuth, Germany, D-95440 Present address: Landesbund für Vogelschutz, Hilpoltstein, Germany, D-91157Search for more papers by this authorD. J. Read, D. J. Read Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorE.-D. Schulze, E.-D. Schulze Max-Planck-Institute for Biogeochemistry, Postfach 10 01 64, Jena, Germany, D-07701Search for more papers by this authorA.-S. D. Siamantziouras, A.-S. D. Siamantziouras Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorA. C. Terry, A. C. Terry Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorA. Y. Troumbis, A. Y. Troumbis Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorF. I. Woodward, F. I. Woodward Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorS. Yachi, S. Yachi Laboratoire d'Écologie, UMR 7625, École Normale Supérieure, 46 Rue d'Ulm, Paris Cedex 05, France, FR-75230 Present address: Research Institute for Humanity & Nature (RINH), Kamigyo-ku, Kyoto 606-0878, JapanSearch for more papers by this authorJ. H. Lawton, J. H. Lawton Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this author E. M. Spehn, E. M. Spehn Institute of Botany, University of Basel, Schoenbeinstrasse 6, Basel, Switzerland, CH-4056 E-mail: [email protected]Search for more papers by this authorA. Hector, A. Hector Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PY Present address: Institute of Environmental Sciences, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland, CH-8057Search for more papers by this authorJ. Joshi, J. Joshi Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorM. Scherer-Lorenzen, M. Scherer-Lorenzen Max-Planck-Institute for Biogeochemistry, Postfach 10 01 64, Jena, Germany, D-07701 Present address: Swiss Federal Institute of Technology Zürich (ETH), Institute of Plant Sciences, Universitätsstrasse 2, Zürich, Switzerland, CH-8092Search for more papers by this authorB. Schmid, B. Schmid Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorE. Bazeley-White, E. Bazeley-White Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. Beierkuhnlein, C. Beierkuhnlein Lehrstuhl Biogeographie, Universität Bayreuth, Bayreuth, Germany, D-95440Search for more papers by this authorM. C. Caldeira, M. C. Caldeira Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399Search for more papers by this authorM. Diemer, M. Diemer Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorP. G. Dimitrakopoulos, P. G. Dimitrakopoulos Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorJ. A. Finn, J. A. Finn Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, Ireland Present address: Teagasc Environmental Research Centre, Johnstown Castle, Wexford, IrelandSearch for more papers by this authorH. Freitas, H. Freitas Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399 Present address: Departamento de Botánica, Universidade de Coimbra, 3000 Coimbra, PortugalSearch for more papers by this authorP. S. Giller, P. S. Giller Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorJ. Good, J. Good Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorR. Harris, R. Harris Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, IrelandSearch for more papers by this authorP. Högberg, P. Högberg Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183Search for more papers by this authorK. Huss-Danell, K. Huss-Danell Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403Search for more papers by this authorA. Jumpponen, A. Jumpponen Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183 Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403 Present address: Division of Biology, Kansas State University, Manhattan, Kansas 66506 USASearch for more papers by this authorJ. Koricheva, J. Koricheva Section of Ecology, Department of Biology, University of Turku, 20014 Turku, FinlandSearch for more papers by this authorP. W. Leadley, P. W. Leadley Institute of Botany, University of Basel, Schoenbeinstrasse 6, Basel, Switzerland, CH-4056 Present address: Ecologie des Populations et Communautés, Université Paris Sud XI, URA CNRS 2154, Bátiment 326, Orsay Cedex, France, FR-91405Search for more papers by this authorM. Loreau, M. Loreau Laboratoire d'Écologie, UMR 7625, École Normale Supérieure, 46 Rue d'Ulm, Paris Cedex 05, France, FR-75230Search for more papers by this authorA. Minns, A. Minns Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. P. H. Mulder, C. P. H. Mulder Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183 Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403 Present address: Department of Biology and Wildlife and Institute of Arctic Biology, University of Alaska, 410 Irving I, Fairbanks, Alaska 99775-7000 USASearch for more papers by this authorG. O'Donovan, G. O'Donovan Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, Ireland Present address: Department of Environmental Resource Management, University College of Dublin, Belfield, Dublin, IrelandSearch for more papers by this authorS. J. Otway, S. J. Otway Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this authorC. Palmborg, C. Palmborg Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403Search for more papers by this authorJ. S. Pereira, J. S. Pereira Departmentos de Engenharia Florestal, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399Search for more papers by this authorA. B. Pfisterer, A. B. Pfisterer Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland, CH-8057Search for more papers by this authorA. Prinz, A. Prinz Lehrstuhl Biogeographie, Universität Bayreuth, Bayreuth, Germany, D-95440 Present address: Landesbund für Vogelschutz, Hilpoltstein, Germany, D-91157Search for more papers by this authorD. J. Read, D. J. Read Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorE.-D. Schulze, E.-D. Schulze Max-Planck-Institute for Biogeochemistry, Postfach 10 01 64, Jena, Germany, D-07701Search for more papers by this authorA.-S. D. Siamantziouras, A.-S. D. Siamantziouras Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorA. C. Terry, A. C. Terry Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorA. Y. Troumbis, A. Y. Troumbis Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Mytilene, Lesbos, Greece, GR-811 00Search for more papers by this authorF. I. Woodward, F. I. Woodward Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, UK, GB-S10 2TNSearch for more papers by this authorS. Yachi, S. Yachi Laboratoire d'Écologie, UMR 7625, École Normale Supérieure, 46 Rue d'Ulm, Paris Cedex 05, France, FR-75230 Present address: Research Institute for Humanity & Nature (RINH), Kamigyo-ku, Kyoto 606-0878, JapanSearch for more papers by this authorJ. H. Lawton, J. H. Lawton Natural Environmental Research Council (NERC) Centre for Population Biology, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK, GB-SL5 7PYSearch for more papers by this author First published: 01 February 2005 https://doi.org/10.1890/03-4101Citations: 384 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract We present a multisite analysis of the relationship between plant diversity and ecosystem functioning within the European BIODEPTH network of plant-diversity manipulation experiments. We report results of the analysis of 11 variables addressing several aspects of key ecosystem processes like biomass production, resource use (space, light, and nitrogen), and decomposition, measured across three years in plots of varying plant species richness at eight different European grassland field sites. Differences among sites explained substantial and significant amounts of the variation of most of the ecosystem processes examined. However, against this background of geographic variation, all the aspects of plant diversity and composition we examined (i.e., both numbers and types of species and functional groups) produced significant, mostly positive impacts on ecosystem processes. Analyses using the additive partitioning method revealed that complementarity effects (greater net yields than predicted from monocultures due to resource partitioning, positive interactions, etc.) were stronger and more consistent than selection effects (the covariance between monoculture yield and change in yield in mixtures) caused by dominance of species with particular traits. In general, communities with a higher diversity of species and functional groups were more productive and utilized resources more completely by intercepting more light, taking up more nitrogen, and occupying more of the available space. Diversity had significant effects through both increased vegetation cover and greater nitrogen retention by plants when this resource was more abundant through N2 fixation by legumes. However, additional positive diversity effects remained even after controlling for differences in vegetation cover and for the presence of legumes in communities. Diversity effects were stronger on above- than belowground processes. In particular, clear diversity effects on decomposition were only observed at one of the eight sites. The ecosystem effects of plant diversity also varied between sites and years. In general, diversity effects were lowest in the first year and stronger later in the experiment, indicating that they were not transitional due to community establishment. These analyses of our complete ecosystem process data set largely reinforce our previous results, and those from comparable biodiversity experiments, and extend the generality of diversity–ecosystem functioning relationships to multiple sites, years, and processes. Supporting Information Filename Description https://dx.doi.org/10.6084/m9.figshare.c.3309093 Research data pertaining to this article is located at figshare.com: Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Biomes are areas of vegetation that are characterized by the same life–form. Traditional definitions of biomes have also included either geographical or climatic descriptors. This approach describes a wide range of biomes that can be correlated with characteristic climatic conditions, or climatic envelopes. The application of remote sensing technology to the frequent observation of biomes has led to a move away from the often subjective definition of biomes to one that is objective. Carefully characterized observations of life–form, by satellite, have been used to reconsider biome classification and their climatic envelopes. Five major tree biomes can be recognized by satellites based on leaf longevity and morphology: needleleaf evergreen, broadleaf evergreen, needleleaf deciduous, broadleaf cold deciduous and broadleaf drought deciduous. Observations indicate that broadleaf drought deciduous vegetation grades substantially into broadleaf evergreen vegetation. The needleleaf deciduous biome occurs in the world's coldest climates, where summer drought and therefore a drought deciduous biome are absent. Traditional biome definitions are quite static, implying no change in their life–form composition with time, within their particular climatic envelopes. However, this is not the case where there has been global ingress of grasslands and croplands into forested vegetation. The global spread of grasses, a new super–biome, was probably initiated 30–45 Myr ago by an increase in global aridity, and was driven by the natural spread of the disturbances of fire and animal grazing. These disturbances have been further extended over the Holocene era by human activities that have increased the land areas available for domestic animal grazing and for growing crops. The current situation is that grasses now occur in most, if not all biomes, and in many areas they dominate and define the biome. Croplands are also increasing, defining a new and relatively recent component to the grassland super–biome. In the case of both grassland and croplands, various forms of disturbance, particularly frequent disturbance, lead to continued range extensions of the biomes.

Abstract The distribution and abundance of trees can be strongly affected by disturbance such as fire. In mixed tree/grass ecosystems, recurrent grass‐fuelled fires can strongly suppress tree saplings and therefore control tree dominance. We propose that changes in atmospheric [CO 2 ] could influence tree cover in such metastable ecosystems by altering their postburn recovery rates relative to flammable herbaceous growth forms such as grasses. Slow sapling recovery rates at low [CO 2 ] would favour the spread of grasses and a reduction of tree cover. To test the possible importance of [CO 2 ]/fire interactions, we first used a Dynamic Global Vegetation Model (DGVM) to simulate biomass in grassy ecosystems in South Africa with and without fire. The results indicate that fire has a major effect under higher rainfall conditions suggesting an important role for fire/[CO 2 ] interactions. We then used a demographic model of the effects of fire on mesic savanna trees to test the importance of grass/tree differences in postburn recovery rates. We adjusted grass and tree growth in the model according to the DGVM output of net primary production at different [CO 2 ] relative to current conditions. The simulations predicted elimination of trees at [CO 2 ] typical of the last glacial period (180 ppm) because tree growth rate is too slow (15 years) to grow to a fire‐proof size of ca. 3 m. Simulated grass growth would produce an adequate fuel load for a burn in only 2 years. Simulations of preindustrial [CO 2 ] (270 ppm) predict occurrence of trees but at low densities. The greatest increase in trees occurs from preindustrial to current [CO 2 ] (360 ppm). The simulations are consistent with palaeo‐records which indicate that trees disappeared from sites that are currently savannas in South Africa in the last glacial. Savanna trees reappeared in the Holocene. There has also been a large increase in trees over the last 50–100 years. We suggest that slow tree recovery after fire, rather than differential photosynthetic efficiencies in C 3 and C 4 plants, might have been the significant factor in the Late Tertiary spread of flammable grasslands under low [CO 2 ] because open, high light environments would have been a prerequisite for the spread of C 4 grasses. Our simulations suggest further that low [CO 2 ] could have been a significant factor in the reduction of trees during glacial times, because of their slower regrowth after disturbance, with fire favouring the spread of grasses.

Conservation BiologyVolume 16, Issue 1 p. 264-268 Conservation of Biodiversity in a Changing Climate L. Hannah, Corresponding Author L. Hannah Center for Applied Biodiversity Science, Conservation International, Washington, D.C, 20037, U.S.A. ††† email [email protected]Search for more papers by this authorG. F. Midgley, G. F. Midgley Climate Change Research Group , Ecology and Conservation, National Botanical Institute, Cape Town, South AfricaSearch for more papers by this authorT. Lovejoy, T. Lovejoy The World Bank , Washington, D.C. 20433, U.S.A.Search for more papers by this authorW. J. Bond, W. J. Bond Botany Department , University of Cape Town, Cape Town, South AfricaSearch for more papers by this authorM. Bush, M. Bush Department of Biological Sciences , College of Science and Liberal Arts, Florida Institute of Technology, Melbourne,FL 32901–6975, U.S.A.Search for more papers by this authorJ. C. Lovett, J. C. Lovett Environment Department , University of York, York, Y010 5DD, United KingdomSearch for more papers by this authorD. Scott, D. Scott Adaptation and Impacts Research Group , Environment Canada at the Faculty of Environmental Studies, University of Waterloo, Waterloo, Ontario, N2L 3G1, CanadaSearch for more papers by this authorF. I. Woodward, F. I. Woodward Department of Animal and Plant Sciences , University of Sheffield, Sheffield, S10 2TN, United KingdomSearch for more papers by this author L. Hannah, Corresponding Author L. Hannah Center for Applied Biodiversity Science, Conservation International, Washington, D.C, 20037, U.S.A. ††† email [email protected]Search for more papers by this authorG. F. Midgley, G. F. Midgley Climate Change Research Group , Ecology and Conservation, National Botanical Institute, Cape Town, South AfricaSearch for more papers by this authorT. Lovejoy, T. Lovejoy The World Bank , Washington, D.C. 20433, U.S.A.Search for more papers by this authorW. J. Bond, W. J. Bond Botany Department , University of Cape Town, Cape Town, South AfricaSearch for more papers by this authorM. Bush, M. Bush Department of Biological Sciences , College of Science and Liberal Arts, Florida Institute of Technology, Melbourne,FL 32901–6975, U.S.A.Search for more papers by this authorJ. C. Lovett, J. C. Lovett Environment Department , University of York, York, Y010 5DD, United KingdomSearch for more papers by this authorD. Scott, D. Scott Adaptation and Impacts Research Group , Environment Canada at the Faculty of Environmental Studies, University of Waterloo, Waterloo, Ontario, N2L 3G1, CanadaSearch for more papers by this authorF. I. Woodward, F. I. Woodward Department of Animal and Plant Sciences , University of Sheffield, Sheffield, S10 2TN, United KingdomSearch for more papers by this author First published: 18 January 2002 https://doi.org/10.1046/j.1523-1739.2002.00465.xCitations: 310Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Literature Cited Bartlein, P. J., C. Whitlock, S. L. Shafer. 1997. Future climate in the Yellowstone National Park region and its potential impact on vegetation. Conservation Biology 16: 782– 792. Broecker, W. S. 1999. What if the conveyor were to shut down? Reflections on a possible outcome of the great global experiment. GSA Today 16: 1– 5. Cowling, R. M. 1999. Planning for persistence: systematic reserve design in southern Africa's Succulent Karoo Desert. Parks 16: 17– 30. Dansgaard, W., S. J. Johnsen, H. B. Clausen, D. Dahl-Jensen, N. S. Gundestrup, C. U. Hammer, C. S. Hvidberg, J. P. Steffensen, A. E. Sveinbjornsdottir, J. Jouzel, G. Bond. 1993. Evidence for general instability of past climate from a 250 kyr ice-core record. Nature 16: 218– 220. Environment Canada. 1997. The Canada country study. Environmental Adaptation Research Group, Environment Canada, Toronto. Gascon, C., G. B. Williamson, G. A. B. Da Fonseca. 2000. Receding forest edges and vanishing reserves. Science 16: 1356– 1358. Hughes, L. 2000. Biological consequences of global warming: is the signal already apparent? Trends in Ecology and Evolution 16: 56– 61. IPCC ) Intergovernmental Panel on Climate Change ( . 2001a. Climate Change 2001: The scientific basis. 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Trombulak. 1999. Core areas: where nature reigns. Pages 99– 128 in M. E. Soulé and J. Terborg, editors. Continental conservation: scientific foundations of regional reserve networks. Island Press, Washington, D.C. Peters, R. L. 1992. Conservation of biological diversity in the face of climate change. Pages 15– 26 in R. L. Peters and T. E. Lovejoy, editors. Global warming and biological diversity. Yale University Press, New Haven, Connecticut. Peters, R. L. & T. Lovejoy. 1992. Global warming and biological Diversity. Yale University Press, New Haven, Connecticut. Rosenzweig, C., A. Iglesias, X. B. Yang, P. R. Epstein, E. Chivian. 2000. Climate change and U.S. agriculture: the impacts of warming and extreme weather events on productivity, plant diseases and pests. Harvard Medical School, Boston. Rutherford, M. C., L. W. Powrie, R. E. Schulze. 1999. Climate change in conservation areas of South Africa and its potential impact on floristic composition: a first assessment. Diversity and Distributions 16: 253– 262. Rutherford, M. C., G. F. Midgley, W. J. Bond, L. W. Powrie, R. Roberts, and J. Allsopp. 2000. Plant biodiversity. In Kiker, G., editor. Climate change impacts in southern Africa. Report to the National Climate Change Committee, Department of Environmental Affairs and Tourism, Pretoria, South Africa. Scott, D. & R. Suffling. 2000. Climate change and Canada's national park system. Catalogue En56–155/ 2000E. Environment Canada, Toronto. Soulé, M. E. & J. Terborg. 1999. Continental conservation. Island Press, Washington, D.C. U.S. National Assessment Synthesis Team. 2000. Climate change impacts on the United States: the potential consequences of climate variability and change. U.S. Global Change Research Program and Cambridge University Press, Cambridge, United Kingdom. Citing Literature Volume16, Issue1February 2002Pages 264-268 ReferencesRelatedInformation

Understanding variation of plant nutrients is largely limited to nitrogen and to a lesser extent phosphorus. Here we analyse patterns of variation in 11 elements (nitrogen/phosphorus/potassium/calcium/magnesium/sulphur/silicon/iron/sodium/manganese/aluminium) in leaves of 1900 plant species across China. The concentrations of these elements show significant latitudinal and longitudinal trends, driven by significant influences of climate, soil and plant functional type. Precipitation explains more variation than temperature for all elements except phosphorus and aluminium, and the 11 elements differentiate in relation to climate, soil and functional type. Variability (assessed as the coefficient of variation) and environmental sensitivity (slope of responses to environmental gradients) are lowest for elements that are required in the highest concentrations, most abundant and most often limiting in nature (the Stability of Limiting Elements Hypothesis). Our findings can help initiate a more holistic approach to ecological plant nutrition and lay the groundwork for the eventual development of multiple element biogeochemical models.

Anthropogenic increases in the atmospheric concentration of carbon dioxide and other greenhouse gases are predicted to cause a warming of the global climate by modifying radiative forcing1. Carbon dioxide concentration increases may make a further contribution to warming by inducing a physiological response of the global vegetation—a reduced stomatal conductance, which suppresses transpiration2. Moreover, a CO2-enriched atmosphere and the corresponding change in climate may also alter the density of vegetation cover, thus modifying the physicalcharacteristics of the land surface to provide yet another climate feedback3,4,5,6. But such feedbacks from changes in vegetation structure have not yet been incorporated into general circulation model predictions of future climate change. Here we use a general circulation model iteratively coupled to an equilibrium vegetation model to quantify the effects of both physiological and structural vegetation feedbacks on a doubled-CO2 climate. On a global scale, changes in vegetation structure are found to partially offset physiological vegetation–climate feedbacks in the long term, but overall vegetation feedbacks provide significant regional-scale effects.

Stomata are microscopic pores on the surfaces of leaves, the number and density of which vary in response to changes in environmental conditions, such as carbon dioxide concentration and light. We show here that mature leaves of Arabidopsis thaliana detect and transmit this external information to new leaves of the same plant, producing an appropriate adjustment of stomatal development. As CO2 concentration controls both stomatal opening1 and number2,3, and stomatal numbers also increase with higher light intensity4, the large gradients of CO2 and light found within plant communities5 have the potential to influence stomatal development.

summary A survey of 100 species and 122 observations has shown an average reduction in stomatal density of 14.3% (SE ±2.2 %) with CO 2 enrichment, with 74% of the cases exhibiting a reduction in stomatal density. A sign test demonstrated that stomatal density decreases, in response to CO 2 , significantly more often than expected by chance. Repeated observations on the same species indicated a significant repeatability in the direction of the stomatal response. Analyses which removed the potential effect of taxonomy on this data set showed no significant patterns in the dependency of the degree of stomatal change on growth form (woodiness vs. non‐woodiness; trees vs. shrubs), habitat (cool vs. warm) or stomatal distribution on the leaf (amphi‐ vs. hypostomatous). Forty‐three of the observations had been made in controlled environments and under a typical range in CO., enrichment of 350–700 μmol mol −1 . For these cases the average stomatal density declined by 9% (SE ± 3.3%) and 60% of the cases showed reductions in stomatal density. When analyses were restricted to these 43 observations, amphistomatous samples more frequently had greater changes in stomatal density than did hypostomatous samples. The degree of reduction in stomatal density with increasing CO 2 increases with initial stomatal density, after the influence of taxonomy is removed using analyses of independent contrasts. When the data were examined for patterns that might be due explicitly to the effects of relatedness, the subclasses of the Hamamelidae and the Rosidae showed highly significant reductions in stomatal density with CO 2 (87% of the species studied in the Hamamelidae and 80% of the species in the Rosidae showed reduction with CO 2 enrichment) and correlations between initial stomatal density and degree of reduction in stomatal density. The species sampled in the Hamamelidae were dominantly trees, whereas herbs dominated the species in the Rosidae. There were insufficient species studied at lower taxonomic levels to warrant further statistical analyses. This problem results from experimental and observational data being most often restricted to one species per taxonomic level, typically up to the level of order, a feature which can severely limit the extraction of taxonomically‐related and ecologically‐related plant responses.

Abstract Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation ( V cmax ) and the maximum rate of electron transport ( J max ). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area ( SLA ). Correlations between V cmax and J max and leaf nitrogen (N) are typically derived from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area ( SLA ) have typically been derived at a local scale. Thus, there is no global‐scale relationship between V cmax and J max and P or SLA limiting the ability of global‐scale carbon flux models do not account for P or SLA . We gathered published data from 24 studies to reveal global relationships of V cmax and J max with leaf N, P, and SLA . V cmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of V cmax to leaf N. J max was strongly related to V cmax , and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm −2 ), increasing leaf P from 0.05 to 0.22 gm −2 nearly doubled assimilation rates. Finally, we show that plants may employ a conservative strategy of J max to V cmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.

ABSTRACT A modelling approach to simulating vegetation dynamics is described, incorporating critical processes of carbon sequestration, growth, mortality and distribution. The model has been developed to investigate the responses of vegetation to environmental change, at time scales from days to centuries and from the local to the global scale. The model is outlined and subsequent tests, against independent data sources, are relatively successful, from the small scale to the global scale. Tests against eddy covariance observations of carbon exchange by vegetation indicated significant differences between measured and simulated net ecosystem production (NEP). NEP is the net of large fluxes due to gross primary production and respiration, which are not directly measured and so there is some uncertainty in explaining differences between observations and simulations. In addition it was noted that closer agreement of fluxes was achieved for natural, or long‐lived managed vegetation than for recently managed vegetation. The discrepancies appear to be most closely related to respiratory carbon losses from the soil, but this area needs further exploration. The differences do not scale up to the global scale, where simulated and measured global net biome production were similar, indicating that fluxes measured at the managed observed sites are not typical globally. The model (the Sheffield Dynamic Global Vegetation Model, SDGVM) has been applied to contemporary vegetation dynamics and indicates a significant CO 2 fertilisation effect on the sequestration of atmospheric CO 2 . The terrestrial carbon sink for the 20th century is simulated to be widespread between latitudes 40° S and 65° N. but is greatest between 10° S and 6° N, excluding the effects of human deforestation. The mean maximum sink capacity over the 20th century is small, at 25 gCm ‐2 year ‐1 , or approximately 1% of gross primary production. Simulations of vegetation dynamics under a scenario of future global warming indicate a gradual decline in the terrestrial carbon sink, with the capacity to absorb human emissions of CO 2 being reduced from 20% in 2000 to approximately 2% between 2075 and 2100. The responses of carbon sequestration and vegetation structure and distribution to stabilisation of climate and CO 2 may extend for up to 50 years after stabilisation has occurred.

The role of fire in determining biome distribution in South Africa has long been debated. Acocks labelled veld types that he thought were ‘fire climax’ as ‘false’. He hypothesised that their current extent was due to extensive forest clearance by Iron Age farmers. We tested the relative importance of fire and climate in determining ecosystem characteristics by simulating potential vegetation of South Africa with and without fire using a Dynamic Global Vegetation Model (DGVM). The simulations suggest that most of the eastern half of the country could support much higher stem biomass without fire and that the vegetation would be dominated by trees instead of grasses. Fynbos regions in mesic winter rainfall areas would also become tree dominated. We collated results of long term fire exclusion studies to further test the relative importance of fire and climate. These show that grassy ecosystems with rainfall > 650mm tend towards fire-sensitive forests with fire excluded. Areas below 650mm showed changes in tree density and size but no trend of changing composition to forest. We discuss recent evidence that C4 grasslands first appeared between 6 and 8M years BP, long before the appearance of modern humans. However these grassy ecosystems are among the most recently developed biomes on the planet. We briefly discuss the importance of fire in promoting their spread in the late Tertiary.

Experiments on a range of species of tree, shrub and herb have shown that stomatal density and stomatal index increase as the partial pressure of CO2 decreases over the range from the current level of 34 Pa to 22.5 Pa. Stomatal density responds to the reduced partial pressure of CO2 in a simulation of high altitude (3000 m), when the CO2 mole fraction is unchanged. When the partial pressure of CO2 is increased from 35 to 70 Pa stomatal density decreases slightly, with a response to unit change in CO2 which is about 10% of that below 34 Pa. Measurements of gas exchange on leaves which had developed in different CO2 partial pressures, but at low saturation vapour pressure deficits in the range of 0.7 to 0.9 kPa, indicated lower photosynthetic rates but higher stomatal conductances at reduced CO2 partial pressures. Experiments on populations of Nardus stricta originating from altitudes of 366 m and 810 m in Scotland, indicated genetic differences in the responses of stomatal density to CO2 in pressures simulating altitudes of sea level and 2 000 m. Plants from the higher altitude showed greater declines in stomatal density when the CO2 partial pressure was increased.

*Second-generation Dynamic Global Vegetation Models (DGVMs) have recently been developed that explicitly represent the ecological dynamics of disturbance, vertical competition for light, and succession. Here, we introduce a modified second-generation DGVM and examine how the representation of demographic processes operating at two-dimensional spatial scales not represented by these models can influence predicted community structure, and responses of ecosystems to climate change. *The key demographic processes we investigated were seed advection, seed mixing, sapling survival, competitive exclusion and plant mortality. We varied these parameters in the context of a simulated Amazon rainforest ecosystem containing seven plant functional types (PFTs) that varied along a trade-off surface between growth and the risk of starvation induced mortality. *Varying the five unconstrained parameters generated community structures ranging from monocultures to equal co-dominance of the seven PFTs. When exposed to a climate change scenario, the competing impacts of CO(2) fertilization and increasing plant mortality caused ecosystem biomass to diverge substantially between simulations, with mid-21st century biomass predictions ranging from 1.5 to 27.0 kg C m(-2). *Filtering the results using contemporary observation ranges of biomass, leaf area index (LAI), gross primary productivity (GPP) and net primary productivity (NPP) did not substantially constrain the potential outcomes. We conclude that demographic processes represent a large source of uncertainty in DGVM predictions.

Summary 1. Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO 2 , CH 4 and N 2 O) to the climate system. 2. Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale. 3. In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps. 4. We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large‐scale multifactor experiments and data from observatory gradients. 5. Synthesis . This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions.

The habitability of our planet depends on interlocking climate and biogeochemical systems. Living organisms have played key roles in the evolution of these systems. Now man is perturbing the climate/biogeochemical systems at an unprecedented pace. In particular, the global carbon cycle is being forced directly by changes in carbon fluxes (e.g. fossil fuel burning and deforestation/reforestation), and indirectly through changes in atmospheric chemistry (e.g. stratospheric ozone depletion and increases of green house gases). Nutrient cycles are also being perturbed, with implications for the carbon cycle. It is imperative that we learn how these changing conditions will influence terrestrial and oceanic photosynthesis and biogeochemistry. Understanding the controls on primary productivity of the biosphere is one of the fundamental aims of global change research. This forum addresses several key questions regarding the role of the biota in the carbon cycle. It begins with Ian Woodward's overview of the global carbon cycle and concludes with John Raven's historical perspective of the negative feedbacks that influenced the evolution of embryophytes in the Devonian. In between, the forum focuses on the process of net primary production (NPP). Despite differences in the structures of planktonic and terrestrial ecosystems, notably of response of biomass to environmental change, there are common problems affecting both terrestrial and oceanic studies of NPP. This has resulted in the parallel evolution of approaches to NPP research in very different milieux involving advances in the technology required to study interacting processes that cut across a range of space and time scales (Table 1). The problems include estimating NPP of whole plants and phytoplankton populations from gas exchange measurements on leaves or subpopulations, accounting for heterotrophic metabolism in gas exchange measurements, extrapolating from small scales to global NPP (Table 2), developing mechanistic models of NPP and biomass accumulation, and relating NPP to the cycling of other elements. Although small-scale measurements will continue to be a staple tool in investigations of NPP, use of open system measurements systems have necessarily come to the fore. These include free-air CO2 exchange in terrestrial systems and water mass tracking in aquatic systems. Deliberate experimental manipulations will increasingly supplement correlative studies to derive insights into environmental regulation of NPP and the feedback between plant productivity and biogeochemical cycles. The net primary production of planet earth has recently been estimated to equal about 1017 g C year−1 (Field et al. 1998; Table 3). The recent estimate for terrestrial production of 56 Pg C year−1 is remarkably similar to Whittaker & Likens (1975) value of 59 Pg C year−1. The estimates for oceanic production have converged on values of around 40–50 Pg C year−1 (Longhurst et al. 1995; Field et al. 1998). Despite the consistency of these estimates, their accuracy is still an open question. John Grace notes, based on free-air techniques, that we may find that the terrestrial biosphere is 20–50% more productive than hitherto supposed. There also remains difficulty in reconciling biogeochemical evidence of high productivity on the annual and longer time scales with measurements of marine NPP made on physiological time scales (Jenkins & Goldman 1985). Our current understanding of global NPP is based on the extrapolation of local studies to the global scale (Field et al. 1998). Satellite sensors provide measurements of vegetation cover on land and chlorophyll a concentrations in the sea from which the rates of light absorption are calculated. These are converted to estimates of NPP using algorithms that describe the dependence of photosynthesis on the rate of light absorption. These algorithms, and hence estimates of global NPP, depend critically on a data base of gas exchange measurements. As emphasized by Tom Vogelmann, an understanding of the fundamental determinants of photosynthesis within leaves will facilitate the scaling of photosynthesis from the leaf to the whole plant. Similarly, an understanding of the fundamentals of light absorption and photosynthetic responses of phytoplankton cells will facilitate scaling to water column NPP. Shubha Sathyendranath, Trevor Platt and Venetia Stuart describe the dual role of phytoplankton absorption that influences both the rate of light-limited photosynthesis and the quantity and spectral quality of underwater light. Todd Kana describes the common mechanisms of acclimation of the photosynthetic apparatus to multiple environmental factors that should facilitate extrapolation at the global scale. There is still considerable uncertainty in the physical and chemical factors and ecological interactions that limit NPP in both terrestrial and aquatic systems. Colin Prentice points out that major uncertainties and discrepancies among models when projected into different climates arise because basic theoretical issues have not been resolved. It has become increasingly evident in recent years that integration of investigations from basic biochemistry and biophysics of photosynthesis to whole plant responses to regional and global studies are essential for developing a predictive understanding of NPP. Steve Long notes the potential for intensive studies of individual stands subjected to field-scale manipulation of climate and atmosphere to provide a way forward in the development of more mechanistic models of terrestrial NPP. Similarly, Lagrangian studies, in which parcels of water are marked with the tracer SF6 and subjected to deliberate manipulation, such as addition of iron, are providing a new and powerful tool for investigating plankton systems (Coale et al. 1996). The wedding of ecology with biogeochemistry presents a challenge to oceanographers and terrestrial systems scientists. It is widely recognized that NPP cannot be isolated from other biogeochemical considerations. Less widely recognized are the ecological interactions that determine community structure and, in turn, influence NPP. Bottom-up controls provide a link between NPP and biogeochemistry. There is a need to move from single factor models, to multifactor models that recognize a multiplicity of controls. Julie La Roche describes the need to establish a hierarchy of controls by N, P, Si and Fe for understanding oceanic primary productivity and selection of functional groups of phytoplankton. However, Victor Smetacek warns that plankton evolution is driven by efficacy of defence systems rather than competitiveness of resource-acquisition mechanisms, and that bottom-up processes will be insufficient to describe plankton population dynamics. Steve Long notes the need for mechanistic models capable of predicting biological feedback to the carbon cycle under atmospheric change. In contrast, Philip Grime argues that models based on plant functional types are more likely to lead to insights into the ecological responses of NPP to climate change than are the more traditional plant growth models that have been derived from agronomy. Evan DeLucia and colleagues conclude that NPP of young forests will increase as the level of CO2 in the atmosphere continues to rise, but that the magnitude and duration of these increases are highly uncertain. More needs to be learned about the modulation of NPP and maximum biomass by the availability of other resources. On seasonal, annual and decadal time scales, the dynamics of O2 and CO2 reservoirs provide a rich data set for validation of global carbon cycle models. However, these integrative measurements can only be interpreted within the context of models of the geographical distribution of sources and sinks. Colin Prentice indicates the need to keep an open mind about the structure of terrestrial carbon budget models and that the atmospheric observations and experimental evidence should be critically evaluated in the light of alternative theories. Paul Falkowski has a similar message regarding marine systems. He warns that ocean primary productivity is unlikely to be in steady state on any time scale and that the feedbacks between marine productivity and the climate/biogeochemical cycle system are not easily predicted. Predictive models of the responses of the interlinked climate and biogeochemical systems to anthropogenic forcing are essential for providing rational decisions on the use of fossil fuel and the potential for deliberate manipulation of the carbon system to mitigate against rising atmospheric CO2. However, at this stage in our understanding of planet earth, we lack predictive power and it is important that we recognize the limits of our knowledge. Whether the climate/biogeochemical systems will ever be wholly predictable is uncertain. What is certain, however, is that avenues for fruitful research continue to open up as technological opportunities and our knowledge-base expands. The pool of carbon in the atmosphere and its monthly, annual and decadal dynamics is the best-quantified component of the global carbon cycle (Keeling & Whorf, 2000). The terrestrial and oceanic carbon pools exchange primarily with the atmosphere, but none of the individual pools or fluxes are known with great precision, due to their marked spatial variability and large sizes. However, the net effect of large terrestrial and oceanic source and sink fluxes on the atmospheric pool of carbon can be determined from the trends in atmospheric CO2 recorded since continuous monitoring was instituted in 1958 (Keeling & Whorf, 2000). Between 1991 and 1997 only about 45% of industrial CO2 emissions accumulated in the atmosphere (Battle et al. 2000), indicating that the terrestrial and oceanic sinks must influence the atmospheric accumulation. There is also now an improving capacity to differentiate between terrestrial and oceanic fluxes (e.g. Battle et al. 2000). These measurements show that the carbon cycle is out of equilibrium as a result of human activities. Releases of carbon through fossil fuel burning are quite well quantified but the impacts of deforestation on carbon release are less well characterized (Nepstad et al. 1999) and are not readily distinguishable, by atmospheric measurements, from fluxes to and from vegetation. The current situation is that a poorly quantified pre-industrial global carbon cycle is being subjected to human forcing, directly through changes in carbon fluxes and pools and indirectly through changes in climate. In terms of anthropogenic concern there are two major questions regarding the global carbon cycle. How will the cycle respond in this non-equilibrium mode, in particular how will increasing concentrations of atmospheric CO2 influence terrestrial and oceanic photosynthesis and chemistry? In an era when mitigation strategies are on the international agenda, how effective and for how long will natural carbon sinks absorb significant fractions of anthropogenic carbon releases? Most of the early ocean work was concerned with defining environmental impacts on the solubility of CO2 in water − the so-called solubility pump. The effectiveness of the solubility pump at sequestering anthropogenic releases of CO2 depends on ocean temperature, vertical mixing and global circulation patterns (Falkowski et al. 2000). More recent work has also considered biological uptake of CO2 in the oceans − the biological pump. The biological pump describes the processes by which phytoplankton absorb CO2 from the surface waters by photosynthesis. Following respiratory losses, dead organic matter and commonly associated calcium carbonate descend from the photic ocean surface to the ocean interior, effectively locking carbon away from the atmosphere for extended periods. This pump has not generally been considered important in absorbing further increases in anthropogenic CO2 because CO2 uptake by phytoplankton is primarily limited by the supply of nutrients such as nitrogen, phosphorus and iron, and increasing CO2 supply should have little impact (Heimann 1997). Future changes in ocean circulation patterns and stratification, in response to global warming, will exert significant impacts on the availability of nutrients and the effectiveness of the biological pump. Sarmiento et al. (1998) suggest that changes in the biology of the pump may be the most critical component of the oceanic responses to future changes in climate and CO2. Unfortunately, for future projections, Sarmiento et al. (1998) conclude that the response of the biological oceanic community to the climate change is difficult to predict on present understanding. Perhaps the future approach may need to be closer to that taken for terrestrial ecosystems, with a greater emphasis on carbon flux physiology, nutrient exchange capacity and community dynamics. The turnover of marine phytoplankton is very rapid, on the order of a week, and so any increases in productivity, through CO2 and nutrient enrichment, will have rather little impact on standing stocks. This contrasts with the decadal-scale turnover for trees, the dominant terrestrial sinks and for which even small increases in productivity could lead to substantial increases in carbon storage. The longevity and dynamics of trees, particularly through natural and anthropogenic disturbances, are critical for defining the terrestrial part of the global carbon cycle. There is abundant evidence that plants can increase their photosynthetic capacity with CO2 enrichment. However this response slows with increasing CO2 and, like the phytoplankton, is also influenced by the supply of other nutrients, in particular nitrogen and phosphorus. Modelling (Cao & Woodward 1998) and experiment (DeLucia et al. 1999) now indicate clearly that ecosystems can increase their carbon sequestering capacity with CO2 enrichment, but that the oft-vaunted impacts of pollutant N deposition are rather small (Nadelhoffer et al. 1999). Increased oceanic sequestration of atmospheric CO2 as organic matter causes a transfer to the ocean interior. Unfortunately, this also locks away the nutrients that limit carbon sequestration. Projections of the future climate indicate warming and an increase in precipitation, both of which will tend to increase stratification and reduce upwelling of nutrients. In addition, the supply of wind-blown iron, a limiting marine nutrient, from the dry continents may be reduced with a wetter climate. In combination, these features should decrease the capacity of the biological pump (Falkowski et al. 1998) to sequester anthropogenic carbon. However, changes in oceanic circulation patterns and, in areas with increased precipitation, increased estuarine runoff with high concentrations of nutrients, may partially compensate for this reduced oceanic activity. Experimental observations on plants suggest that CO2 enrichment can stimulate the carbon sequestering capacity but warming, with no change in water supply will tend to reduce this capacity. Models at the global scale (e.g. Cao & Woodward 1998) indicate that global climate model simulations of future climatic warming alone would cause a global decrease in the terrestrial sink capacity for sequestering carbon, with vegetation and soils adding to the atmospheric pool of carbon. The inclusion of the direct effects of increasing atmospheric CO2 with this warming reverses this trend, with vegetation and soils increasing their carbon sequestration capacity. However, there is evidence for a decline in this capacity as the CO2 stimulation of productivity reaches saturation. Estimates of oceanic and terrestrial sink capacities for carbon are currently quite uncertain but the best that can be achieved to date comes from three major and largely independent methods of estimation. The three methods are, broadly, the inversion of time series of atmospheric composition (e.g. CO2, O2 and δ13C), in situ observations and model simulations. No single technique is currently adequate for a full and accurate global picture of the spatial and temporal activities of the global carbon sinks. The measurements of atmospheric composition are sparse, particularly over the terrestrial biosphere, and sinks can only be estimated from measurements after the use of atmospheric transport models. In some cases maps of vegetation distribution are also required. This is particularly so for the interpretation of δ13C data, where the distribution of species with the C4 pathway of photosynthesis is required. In situ observations of CO2 fluxes, or temporal changes in the sizes of carbon pools, are also sparse, particularly over the oceans and between the tropics. In addition, observations on land need to track impacts on CO2 fluxes of processes such as disturbance, harvesting and changes in land use. Finally, models have the problems of insufficient understanding of processes, of oversimplification and of severe limitations to adequate testing. Reducing these uncertainties will require improved interactions between these three approaches. This will involve the assimilation of observations, such as from remote sensing, into models and the wider use of statistical techniques for investigating model and data uncertainties. There is still some way to go before the uncertainties of the carbon cycle can be minimized so that, for example, continental-scale sinks can be identified and quantified with precision and small-scale observations can converge with global-scale model simulations. Variations in the optical characteristics of phytoplankton can influence primary production in two ways. First, they affect the rate of light transmission underwater, and hence the magnitude of photosynthetically active photon flux density (I) at depth. Second, they determine the rate of light absorption by phytoplankton and hence the rate of light-limited photosynthesis. Absorption and scattering by pure water, the coloured component of dissolved organic matter, and particulate material (which includes phytoplankton) determine the rate of light attenuation with depth. When computing the phytoplankton contribution to light attenuation, it is not important to distinguish between photosynthetic pigments, degradation products, or photoprotective pigments. What is required in this context is that the phytoplankton component account for all pigments, regardless of their role in photosynthesis. The requirements are, however, quite different and far more stringent if one is interested in calculating the amount of light that reaches the photosystems of phytoplankton at a particular depth. In this context, it becomes important to distinguish between absorption and scattering; between absorption by phytoplankton and absorption by other components of the system; and between absorption by photosynthetic pigments and non-photosynthetic pigments (in which group one might combine degradation products and photoprotective pigments). This is important, since the realized maximum quantum yield of photosynthesis, φm, will depend on whether or not the absorption is by photosynthetic or non-photosynthetic pigments. In addition to modifying the amount of light available at depth, phytoplankton influence the spectral quality of light at depth. The spectral dependence of photosynthesis ensures that primary production is a function of both the magnitude of the underwater radiant flux (I) and the spectral quality of the light field. There is ample evidence in the literature that these spectral effects, if ignored, can lead to significant errors in computed production (Kyewalyanga et al. 1992). In all models of photosynthesis (PB) as a function of I, the initial slope, αB, and the available light, I, are coupled together as a product. Note that the superscript B indicates normalization to the concentration of the main phytoplankton pigment chlorophyll a (including divinyl chlorophyll a), treating chlorophyll as an index of phytoplankton biomass (B). The proper way to incorporate fully the spectral dependence of photosynthesis is to replace the product αBI in non-spectral models by the spectrally weighted integral ∫αB(λ) I(λ) dλ, where λ is the wavelength, and the wavelength integral is taken over the whole of the photosynthetically active range from 400 to 700 nm. To introduce the biomass-normalized absorption coefficient (a*B(λ)), explicitly into the spectral model, we can write αB(λ) = φm(λ)a*B (λ) by which we recognize that αB, φm and a*B are all wavelength dependent. An interesting consequence of the spectral dependence in light absorption by phytoplankton is that the presence of phytoplankton in the surface layers of the ocean contributes to the rapid depletion of flux at those wavelengths favourable for phytoplankton absorption. Thus, the light regime at depth may be spectrally unfavourable for absorption by pigments, and hence for photosynthesis (that is to say, the wavelength integral of the product of αB(λ) and I(λ) may be small, even if I(λ) is high at some wavelengths). This effect may be mitigated if the phytoplankton are able to adapt chromatically to the light field at depth by modifying their pigment composition. The high amounts of divinyl chlorophyll b relative to divinyl chlorophyll a that are often found at depth in some marine prochlorophytes (Moore et al. 1998) may reflect, in part, an adaptation to the spectral quality of the light field. All these considerations demonstrate that primary production in the water column is strongly influenced by the absorption characteristics of phytoplankton. This has led to a considerable interest in understanding natural variability in the optical properties of phytoplankton. The biomass normalized absorption spectra, referred to as specific absorption spectra, can be treated as an intrinsic property of phytoplankton at the time of measurement, independent of their concentration. All measurements confirm certain common traits in the specific absorption spectra: they all have a broad absorption maximum in the blue part of the spectrum and a secondary absorption maximum in the red. However, measurements made in the last decade confirm that these spectra also exhibit a great deal of variability around the common trends. Specifically, the magnitude of the specific absorption maximum in the blue can vary over a factor of five from one sample to another, whereas the magnitude of the red peak can vary by a factor of two or more. The shapes of the peaks are also variable. Two factors are responsible for most of the observed variations in phytoplankton absorption: changes in pigment packaging and in pigment composition. Based on theoretical considerations, it has long been demonstrated that the absorption efficiency of pigments within cells depends on how the pigments are packaged into discrete particles (Duysens 1956). When packaged into cells, the pigments tend to shade themselves, such that the total absorption by the pigments would be less than the absorption by the same pigments if they were distributed uniformly in solution. Using simple mathematical models, Duysens (1956) showed that the ‘package effect’ would increase (or the efficiency of absorption decrease) as a function of the spherical equivalent diameter of the cells and the intracellular absorption coefficient of the pigments. The decrease in efficiency of absorption due to packaging is most pronounced at the absorption maxima and least pronounced at the absorption minima, such that the absorption spectra of pigments packaged into particulate matter would appear flatter than those of the same pigments in solution. The second well-known cause of variation in phytoplankton specific absorption spectra is the varying influence of absorption by pigments other than chlorophyll a (Sathyendranath et al. 1987). Phytoplankton are known to have pigment complements that are characteristic of their taxa. Nutritional status and photoacclimation can superimpose additional variations. Normalizing the absorption spectra to chlorophyll a eliminates variations in the magnitude of the spectra due to variations in the absolute quantity of chlorophyll a, but it does not account for changes in the composition and relative concentrations of other pigments in the sample. Typically, phytoplankton cells in oligotrophic oceanic waters are small and contain relatively high amounts of non-photosynthetic carotenoids, favouring high absorption efficiencies (Bricaud et al. 1995). The specific absorption spectra tend to get flatter and lower in magnitude towards eutrophic waters with large cells, and towards greater depths where the concentration of photoprotective pigments is low. Adaptation of cells to low light tends to increase pigment concentration per cell, which will also tend to decrease the specific absorption with an increase in depth. The last decade has seen considerable progress in our understanding of the factors that cause variations in phytoplankton absorption characteristics. However, we do not have enough information for quantitative parameterization of phytoplankton absorption in vivo, given the pigment composition and particle size distribution. A major impediment is our imperfect knowledge of the in vivo absorption characteristics of individual phytoplankton pigments. Whereas the absorption and fluorescence characteristics of major phytoplankton pigments are well known, we still know very little about how these characteristics may vary once the pigments are bound to proteins and arranged in complex structures within cells. In spite of encouraging beginnings (Hoepffner & Sathyendranath 1991), we are still a long way from establishing a definitive catalogue of the intracellular absorption characteristics of individual pigments. An open question at the moment is whether the characteristics of individual pigments vary significantly between different types of phytoplankton cells, due to differences in internal cell structure and organization. Phytoplankton absorption has a strong effect on the quantity and spectral quality of the underwater light available for aquatic photosynthesis. Furthermore, absorption influences primary production through its effect on the light-limited photosynthesis rate. Clearly, any study of aquatic primary production would be grossly inadequate if it did not account correctly for this dual role of phytoplankton absorption. Efforts to do this properly are, however, confounded by the fact that there is a considerable variability in the absorption characteristics of phytoplankton in the natural environment, about which we still have much to learn. An important issue in understanding the effects of global change on NPP is partly one of understanding how the photosynthetic process is regulated by multiple environmental factors. Physiological regulation is under genetic control at the level of gene transcription and translation for key photosynthetic components and under biochemical control at the level of enzyme activation and excitation energy quenching (Falkowski & Raven 1997). Algae can provide important insights into physiological regulation of photosynthesis, because they are evolutionarily diverse and exhibit broad variations in metabolism, cell size, pigmentation, photosynthetic biochemistry and biophysics, and habitat preference. Evolution of light harvesting components, in particular, has been extensive, and the importance of spectral light absorption in the ecology of algae, both within and between species, has been documented (Kirk 1994). Moreover, there are significant differences among taxa in the regulation of energy flow through the photosynthetic apparatus. Despite this diversity, there exists a general pattern of regulation of light harvesting in response to light, temperature and nutrient availability. Algae are able to alter key photosynthetic attributes that affect utilization of light energy. These include cellular light absorption, quantum efficiency and maximum photosynthetic capacity. A change in cellular pigment concentration is an important mechanism that modifies these attributes. Pigment concentrations respond to the immediate environment and are influenced by a variety of factors, including irradiance, nutrient availability and temperature. Pigment concentrations are also affected by the ‘physiological state’ of the cell, which depends on the cell's environmental history (Geider et al. 1998). Given the number of factors involved, it is not surprising that quantitative relationships among pigment concentration, photosynthesis and environmental variables are complex. Despite the complexity, broad patterns are consistent among taxa and across environmental factors and it is possible to define unifying principals of photosynthetic regulation in response to environmental cues. All algae are exposed to environments with fluctuations of irradiance, temperature and nutrient availability at multiple frequencies. Despite this environmental complexity, algal cells maintain a relatively constant elemental (e.g. C, N and P) composition. This is accomplished partly through mechanisms that modulate photosynthesis. These mechanisms operate at several dominant frequencies including seconds (energy quenching), minutes (xanthophyll cycle quenching) and hours to days (acclimation). Light, temperature and nutrient availability are important environmental factors that affect the concentration of photosynthetic pigments in algal cells. Changes of cell pigment concentrations directly affect the efficiency of light utilization and instantaneous photosynthesis rate, and are thus important in algal ecology. Recent models integrate these factors and predict acclimated pigment concentrations for an arbitrary environment (Kana et al. 1997; Geider et al. 1998). The various models incorporate an energy balance ‘signal’ that affects the rate of synthesis or degradation of pigmentation. The energy bala

Abstract Evaluating the role of terrestrial ecosystems in the global carbon cycle requires a detailed understanding of carbon exchange between vegetation, soil, and the atmosphere. Global climatic change may modify the net carbon balance of terrestrial ecosystems, causing feedbacks on atmospheric CO 2 and climate. We describe a model for investigating terrestrial carbon exchange and its response to climatic variation based on the processes of plant photosynthesis, carbon allocation, litter production, and soil organic carbon decomposition. The model is used to produce geographical patterns of net primary production (NPP), carbon stocks in vegetation and soils, and the seasonal variations in net ecosystem production (NEP) under both contemporary and future climates. For contemporary climate, the estimated global NPP is 57.0 Gt C y –1 , carbon stocks in vegetation and soils are 640 Gt C and 1358 Gt C, respectively, and NEP varies from –0.5 Gt C in October to 1.6 Gt C in July. For a doubled atmospheric CO 2 concentration and the corresponding climate, we predict that global NPP will rise to 69.6 Gt C y –1 , carbon stocks in vegetation and soils will increase by, respectively, 133 Gt C and 160 Gt C, and the seasonal amplitude of NEP will increase by 76%. A doubling of atmospheric CO 2 without climate change may enhance NPP by 25% and result in a substantial increase in carbon stocks in vegetation and soils. Climate change without CO 2 elevation will reduce the global NPP and soil carbon stocks, but leads to an increase in vegetation carbon because of a forest extension and NPP enhancement in the north. By combining the effects of CO 2 doubling, climate change, and the consequent redistribution of vegetation, we predict a strong enhancement in NPP and carbon stocks of terrestrial ecosystems. This study simulates the possible variation in the carbon exchange at equilibrium state. We anticipate to investigate the dynamic responses in the carbon exchange to atmospheric CO 2 elevation and climate change in the past and future.

Abstract Measurements of the net CO 2 flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO 2 source–sink patterns, CO 2 flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO 2 (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO 2 uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO 2 measurements. Combining the PEM, DGVM, and inversion results suggests that CO 2 fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO 2 uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr −1 for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO 2 fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO 2 uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO 2 variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO 2 exchange.

• Experimental evidence demonstrates a higher efficiency of water and nitrogen use in C4 compared with C3 plants, which is hypothesized to drive differences in biomass allocation between C3 and C4 species. However, recent work shows that contrasts between C3 and C4 grasses may be misinterpreted without phylogenetic control. • Here, we compared leaf physiology and growth in multiple lineages of C3 and C4 grasses sampled from a monophyletic clade, and asked the following question: which ecophysiological traits differ consistently between photosynthetic types, and which vary among lineages? • C4 species had lower stomatal conductance and water potential deficits, and higher water-use efficiency than C3 species. Photosynthesis and nitrogen-use efficiency were also greater in C4 species, varying markedly between clades. Contrary to previous studies, leaf nitrogen concentration was similar in C4 and C3 types. Canopy mass and area were greater, and root mass smaller, in the tribe Paniceae than in most other lineages. The size of this phylogenetic effect on biomass partitioning was greater in the C4 NADP-me species than in species of other types. • Our results show that the phylogenetic diversity underlying C4 photosynthesis is critical to understanding its functional consequences. Phylogenetic bias is therefore a crucial factor to be considered when comparing the ecophysiology of C3 and C4 species.

Abstract. Plant functional types are a necessary device for reducing the complex and often uncharted characteristics of species diversity in function and structure when attempting to project the nature and function of species assemblages into future environments. A workshop was held to review the current methods commonly used for defining plant functional types, either globally or for particular biomes, and to compare them with the field experiences of specialists for specific biomes of the world. The methods fall into either an objective and inductive approach or a subjective and deductive approach. When the different methods were tested, it was generally found that the classification for one site or environment was not wholly applicable to a different site or environment. However, the degree of change which is necessary for adjustment between environments may not prove to be a major limitation in the use of functional types.

Models describing the evolution of the partial pressure of atmospheric oxygen over Phanerozoic time are constrained by the mass balances required between the inputs and outputs of carbon and sulfur to the oceans. This constraint has limited the applicability of proposed negative feedback mechanisms for maintaining levels of atmospheric O 2 at biologically permissable levels. Here we describe a modeling approach that incorporates O 2 -dependent carbon and sulfur isotope fractionation using data obtained from laboratory experiments on carbon-13 discrimination by vascular land plants and marine plankton. The model allows us to calculate a Phanerozoic O 2 history that agrees with independent models and with biological and physical constraints and supports the hypothesis of a high atmospheric O 2 content during the Carboniferous (300 million years ago), a time when insect gigantism was widespread.

This chapter highlights the evolutionary and ecophysiological responses of mountain plants to the growing season environment. The responses of mountain plants to their environment are due to a complex mixture of genetic and environmental influences. Plants growing on mountains experience reduced temperatures and vapor pressures with altitude, as well as a reduction in the partial pressure of air. There are many morphological, physiological, and biochemical features of plants that change with altitude, such as decrease in stature. Model simulations of canopy energy balance and CO2 fixation indicate that canopy structure and leaf area index (LAI) strongly influence both photosynthetic rate (A) and the ratio of 13C to 12C (δ13C) in leaves. δ13C measurements on expanded leaves provide a time integral of CO2 discrimination during the photosynthetic life of the leaf; they also include some unknown δ13C contribution from photosynthate exported or remobilized from other leaves and organs. The model simulations, for just the period of peak irradiance during the day, indicate that the energy balance and gas exchange of a leaf are dependent on its aerodynamic coupling with other leaves in the plant canopy, and with the air at some reference height above the canopy.

Changes in the atmospheric concentration of CO2, over periods of millennia, are positively correlated with the temperature of the world. It is expected that this positive correlation will be manifested in the future, warmer ‘greenhouse world’ with higher concentrations of CO2. The predicted changes in temperature and precipitation are expected to cause significant changes in the distribution patterns of the world's terrestrial vegetation (Woodward and McKee, 1991). In addition to this indirect effect, CO2 influences plants directly and an increase in the concentration of CO2 may increase the rate of photosynthesis in plants with the C3 pathway of fixation. Experimental observations often differ in the degree and length of this stimulation, reflecting the stronger impact of other photosynthetic limitations. Where photosynthetic stimulation does occur there is a general decrease in leaf protein, which may stimulate rates of leaf herbivory. The well established and associated increase in the C/N ratio of individual leaves should reduce rates of leaf decomposition. However the few community experiments at elevated CO2 suggest little change in the rate of nutrient cycling in communities. Stomatal opening is generally reduced as CO2 concentration increases. This feature scales up through to the community level, however, it appears that the total volume of water used by a community is unlikely to alter with CO2 alone, because plants tend to develop leafier canopies. This change, plus enhanced rates of root development, indicate a greater potential for carbon sequestration by terrestrial ecosystems. Monthly observations of atmospheric CO2 concentration above the tundra over the last 14 years indicate these expected increases in the rates of CO2 drawdown by the northern ecosystems of the tundra and the boreal and temperate deciduous forests. However, some of this change may be due to interactions with the warmer climate of the 1980s and perhaps an increased aerial supply of pollutant nitrogen.

Abstract The response of plant respiration ( R ) to temperature is an important component of the biosphere's response to climate change. At present, most global models assume that R increases exponentially with temperature and does not thermally acclimate. Although we now know that acclimation does occur, quantitative incorporation of acclimation into models has been lacking. Using a dataset for 19 species grown at four temperatures (7, 14, 21, and 28 °C), we have assessed whether sustained differences in growth temperature systematically alter the slope and/or intercepts of the generalized log–log plots of leaf R vs. leaf mass per unit leaf area (LMA) and vs. leaf nitrogen (N) concentration. The extent to which variations in growth temperature account for the scatter observed in log–log R –LMA–N scaling relationships was also assessed. We show that thermal history accounts for up to 20% of the scatter in scaling relationships used to predict R , with the impact of thermal history on R –LMA–N generalized scaling relationships being highly predictable. This finding enabled us to quantitatively incorporate acclimation of R into a coupled global climate–vegetation model. We show that accounting for acclimation of R has negligible impact on predicted annual rates of global R , net primary productivity (NPP) or future atmospheric CO 2 concentrations. However, our analysis suggests that accounting for acclimation is important when considering carbon fluxes among thermally contrasting biomes (e.g. accounting for acclimation decreases predicted rates of R by up to 20% in high‐temperature biomes). We conclude that acclimation of R needs to be accounted for when predicting potential responses of terrestrial carbon exchange to climatic change at a regional level.

Light intensity and atmospheric CO 2 partial pressure are two environmental signals known to regulate stomatal numbers.It has previously been shown that if a mature Arabidopsis leaf is supplied with either elevated CO 2 (750 ppm instead of ambient at 370 ppm) or reduced light levels (50 lmol m 22 s 21 instead of 250 lmol m 22 s 21 ), the young, developing leaves that are not receiving the treatment grow with a stomatal density as if they were exposed to the treatment.But the signal(s) that it is believed is generated in the mature leaves and transmitted to developing leaves are largely unknown.Photosynthetic rates of treated, mature Arabidopsis leaves increased in elevated CO 2 and decreased when shaded, as would be expected.Similarly, the levels of sugars (glucose, fructose, and sucrose) in the treated mature leaves increased in elevated CO 2 and decreased with shade treatment.The levels of sugar in developing leaves were also measured and it was found that they mirrored this result even though they were not receiving the shade or elevated CO 2 treatment.To investigate the effect of these treatments on global gene expression patterns, transcriptomics analysis was carried out using Affymetrix, 22K, and ATH1 arrays.Total RNA was extracted from the developing leaves after the mature leaves had received either the ambient control treatment, the elevated CO 2 treatment, or the shade treatment, or both elevated CO 2 and shade treatments for 2, 4, 12, 24, 48, or 96 h.The experiment was replicated four times.Two other experiments were also conducted, one to compare and contrast gene expression in response to plants grown at elevated CO 2 and the other to look at the effect of these treatments on the mature leaf.The data were analysed and 915 genes from the untreated, signalled leaves were identified as having expression levels affected by the shade treatment.These genes were then compared with those whose transcript abundance was affected by the shade treatment in the mature treated leaves (1181 genes) and with 220 putative 'stomatal signalling' genes previously identified from studies of the yoda mutant.The results of these experiments and how they relate to environmental signalling are discussed, as well as possible mechanisms for systemic signalling.

Summary The evolution of C 4 photosynthesis in plants has allowed the maintenance of high CO 2 assimilation rates despite lower stomatal conductances. This underpins the greater water‐use efficiency in C 4 species and their tendency to occupy drier, more seasonal environments than their C 3 relatives. The basis of interspecific variation in maximum stomatal conductance to water ( g max ), as defined by stomatal density and size, was investigated in a common‐environment screening experiment. Stomatal traits were measured in 28 species from seven grass lineages, and comparative methods were used to test for predicted effects of C 3 and C 4 photosynthesis, annual precipitation and habitat wetness on g max . Novel results were as follows: significant phylogenetic patterns exist in g max and its determinants, stomatal size and stomatal density; C 4 species consistently have lower g max than their C 3 relatives, associated with a shift towards smaller stomata at a given density. A direct relationship between g max and precipitation was not supported. However, we confirmed associations between C 4 photosynthesis and lower precipitation, and showed steeper stomatal size–density relationships and higher g max in wetter habitats. The observed relationships between stomatal patterning, photosynthetic pathway and habitat provide a clear example of the interplay between anatomical traits, physiological innovation and ecological adaptation in plants.

Plant growth plays a key role in the functioning of the terrestrial biosphere, and there have been substantial efforts to understand why growth varies among species.To this end, a large number of experimental analyses have been undertaken; however, the emergent patterns between growth rate and its components are often contradictory.We believe that these conflicting results are a consequence of the way growth is measured.Growth is typically characterized by relative growth rate (RGR); however, RGR often declines as organisms get larger, making it difficult to compare species of different sizes.To overcome this problem, we advocate using nonlinear mixed-effects models so that RGR can be calculated at a standard size, and we present easily implemented methods for doing this.We then present new methods for analyzing the traditional components of RGR that explicitly allow for the fact that log (RGR) is the sum of its components.These methods provide an exact decomposition of the variance in log (RGR).Finally, we use simple analytical and simulation approaches to explore the effect of size variation on growth and its components and show that the relative importance of the components of RGR is influenced by the extent to which analyses standardize for plant size.

The distribution limits of three species, in the British Isles are discussed. For Verbena officinalis and Tilia cordata low temperatures are shown to influence distribution, by limiting the capacity either to flower or to fertilize ovules, respectively. In the case of Umbilicus rupestris , a long-term transplant population beyond the natural geographical limit of the species has evolved new low-temperature responses of seed germination and winter survival. The effect is a marked change of phenology, compared with populations of the species within its natural range, which enhances the capacity of the population to survive in a colder environment.

The observation that stomatal density (number mm(-2)) on herbarium leaves had decreased over the last century represents clear evidence that plants have responded to anthropogenic increases in CO2 concentration. The mechanism of the response has proved elusive but here it is shown that density responses to both CO2 concentration and humidity are correlated with changes in whole-plant transpiration and leaf abscisic acid (ABA) concentration. The transpiration rate of a range of accessions of Arabidopsis thaliana was manipulated by changing CO2 concentration, humidity and by exogenous application of ABA. Stomatal density increased with transpiration and leaf ABA concentration. A common property of signal transduction systems is that they rapidly lose their ability to respond to the co-associated stimulus. Pathways of water movement within the plant are connected and so variations in supply and demand can be signalled throughout the plant directly, modifying stomatal aperture of mature leaves and stomatal density of developing leaves. Furthermore, the system identified here does not conform to the loss of ability to respond. A putative mechanism is proposed for the control of stomatal density by transpiration rate and leaf ABA concentration.

The maximum photosynthetic carboxylation rate (Vcmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr-1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes.

Abstract Free‐air CO 2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model‐data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model‐data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO 2 treatments. Model outputs were compared against observations using a range of goodness‐of‐fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness‐of‐fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model‐data synthesis therefore goes beyond goodness‐of‐fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions.

Global climate change is expected to shift regional rainfall patterns, influencing species distributions where they depend on water availability. Comparative studies have demonstrated that C4 grasses inhabit drier habitats than C3 relatives, but that both C3 and C4 photosynthesis are susceptible to drought. However, C4 plants may show advantages in hydraulic performance in dry environments. We investigated the effects of seasonal variation in water availability on leaf physiology, using a common garden experiment in the Eastern Cape of South Africa to compare 12 locally occurring grass species from C4 and C3 sister lineages. Photosynthesis was always higher in the C4 than C3 grasses across every month, but the difference was not statistically significant during the wettest months. Surprisingly, stomatal conductance was typically lower in the C3 than C4 grasses, with the peak monthly average for C3 species being similar to that of C4 leaves. In water-limited, rain-fed plots, the photosynthesis of C4 leaves was between 2.0 and 7.4 μmol m−2 s−1 higher, stomatal conductance almost double, and transpiration 60% higher than for C3 plants. Although C4 average instantaneous water-use efficiencies were higher (2.4–8.1 mmol mol−1) than C3 averages (0.7–6.8 mmol mol−1), differences were not as great as we expected and were statistically significant only as drought became established. Photosynthesis declined earlier during drought among C3 than C4 species, coincident with decreases in stomatal conductance and transpiration. Eventual decreases in photosynthesis among C4 plants were linked with declining midday leaf water potentials. However, during the same phase of drought, C3 species showed significant decreases in hydrodynamic gradients that suggested hydraulic failure. Thus, our results indicate that stomatal and hydraulic behaviour during drought enhances the differences in photosynthesis between C4 and C3 species. We suggest that these drought responses are important for understanding the advantages of C4 photosynthesis under field conditions.

Stomatal numbers are tightly controlled by environmental signals including light intensity and atmospheric CO(2) partial pressure. This requires control of epidermal cell development during the early phase of leaf growth and involves changes in both the density of cells on the leaf surface and the proportion of cells that adopt a stomatal fate. This paper reviews the current understanding of how stomata develop and describes recent advances that have given insights into the regulatory mechanisms involved using mutant Arabidopsis plants that implicates a role for long-chain fatty acids in cell-to-cell communication. Evidence is presented which indicates that long-distance signalling from mature to newly developing leaves forms part of the mechanism by which stomatal development responds to environmental cues. Analysis of mutant plants suggests that the plant hormones abscisic acid, ethylene and jasmonates are implicated in the long-distance signalling pathway and that the action may be mediated by reactive oxygen species.

ABSTRACT Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean‐atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long‐term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean.

Summary • Patterns in population density and abundance, community composition, seed production and morphological traits were assessed across the UK geographical range of Cirsium acaule, Cirsium heterophyllum and Cirsium arvense based on the expectation that environmental favourability declines from core to periphery of a species range. • These traits were measured in natural populations along a latitudinal transect in the UK and using botanical survey data. • A significant decline in population density and seed production occurs approaching the range edges of C. acaule and C. heterophyllum. There is no latitudinal trend in these traits in the widespread C. arvense and no latitudinal pattern to variation in morphological traits or community composition in any of these species. • Although seed production is reduced at the range edge of C. acaule and C. heterophyllum, peripheral populations of these species may persist through clonal reproduction. Low seed production may interact with reduced availability of favourable habitat to limit range expansion in these species.

Summary • Stomatal density responses by 48 accessions of Arabidopsis, to CO2 enrichment, broadly parallel interspecific observations. • Accessions differing in the degree of stomatal response to both CO2 and drought differed in flower production. Under well watered conditions flowering benefits from a small reduction in stomatal density with CO2 enrichment, but benefits from a large reduction under drought. • Stomatal density increases with altitude in Vaccinium myrtillus but is also strongly influenced by exposure. Exposed plants had higher stomatal densities than plants at the same altitude but in a community of individuals. This difference might be explained by systemic signalling within the plant as mature leaves detect both irradiance and [CO2], subsequently controlling the response of stomatal development in developing leaves. • Plants with the highest stomatal densities also had the highest stomatal conductances and photosynthetic rates. This suggests that signalling from mature to developing leaves predetermines the potential of the developing leaf to maximize its photosynthetic potential, including associated features such as nitrogen allocation, during early stages of development in the enclosed bud.

Acknowledgements Preface 1. Introduction 2. Investigating the past from the present 3. Climate and terrestrial vegetation of the present 4. The global climate system and terrestrial carbon cycle 5. The late Carboniferous 6. The Jurassic 6. The Cretaceous 8. The Eocene 9. The late Quaternary 10. Climate and terrestrial vegetation in the future 11. Endview References Index.

Abstract We present a first assessment of the potential impacts of anthropogenic climate change on the endemic flora of Namibia, and on its vegetation structure and function, for a projected climate in ∼2050 and ∼2080. We used both niche‐based models (NBM) to evaluate the sensitivity of 159 endemic species to climate change (of an original 1020 plant species modeled) and a dynamic global vegetation model (DGVM) to assess the impacts of climate change on vegetation structure and ecosystem functioning. Endemic species modeled by NBM are moderately sensitive to projected climate change. Fewer than 5% are predicted to experience complete range loss by 2080, although more than 47% of the species are expected to be vulnerable (range reduction >30%) by 2080 if they are assumed unable to migrate. Disaggregation of results by life‐form showed distinct patterns. Endemic species of perennial herb, geophyte and tree life‐formsare predicted to be negatively impacted in Namibia, whereas annual herb and succulent endemic species remain relatively stable by 2050 and 2080. Endemic annual herb species are even predicted to extend their range north‐eastward into the tree and shrub savanna with migration, and tolerance of novel substrates. The current protected area network is predicted to meet its mandate by protecting most of the current endemicity in Namibia into the future. Vegetation simulated by DGVM is projected to experience a reduction in cover, net primary productivity and leaf area index throughout much of the country by 2050, with important implications for the faunal component of Namibia's ecosystems, and the agricultural sector. The plant functional type (PFT) composition of the major biomes may be substantially affected by climate change and rising atmospheric CO 2 – currently widespread deciduous broad leaved trees and C 4 PFTs decline, with the C 4 PFT particularly negatively affected by rising atmospheric CO 2 impacts by ∼2080 and deciduous broad leaved trees more likely directly impacted by drying and warming. The C 3 PFT may increase in prominence in the northwestern quadrant of the country by ∼2080 as CO 2 concentrations increase. These results suggest that substantial changes in species diversity, vegetation structure and ecosystem functioning can be expected in Namibia with anticipated climate change, although endemic plant richness may persist in the topographically diverse central escarpment region.

The impact of elevated CO 2 and drought on the architecture and development of root systems of Senecio vulgaris was examined and implications for water and nutrient uptake discussed. Plants were grown in miniature rhizotrons to non-destructively monitor the development of roots in situ at both an elevated (700 μmol mol #751 ) and ambient (350 μmol mol #751 ) atmospheric CO 2 concentration and a high or a low supply of water. CO 2 and water had a significant impact on the way that S. vulgaris root systems filled the soil matrix. Elevated CO 2 resulted in more branched, longer root systems that foraged through larger volumes of soil (...)

Plant ecology offers two main lines of investigation for predicting the ecological consequences of the changes in climate and atmospheric chemistry associated with the man-made greenhouse effect. The first approach is based on mechanistic studies of individual plants, often in response to a range of carefully controlled environments. These responses of individual plants must be aggregated and scaled up in order to predict community, ecosystem or vegetation responses (Harper, 1977; Jarvis & McNaughton, 1986; Woodward, 1987, 1991; Paw U & Gao, 1988). This aggregation can lead to quite inaccurate predictions of community and ecosystem processes (Polanyi, 1968; Martin, 1989; Roberts, Skeffington & Blank, 1989). At the other extreme of scale and difficulty of experimental manipulation are community or ecosystem studies. In some instances present day correlations between ecosystems and climate have been used to predict distributions in a future, warmed climate (Emanuel, Shugart & Stevenson, 1985). This technique, based on the climatic classification of vegetation developed by Holdridge (Holdridge 1947, 1964), has no explicit mechanistic base. Such models are liable to be inaccurate when important features of the environment change and influence ecosystem behaviour but which are excluded from the correlations. Examples include changes in CO2 concentration and climatic extremes and the influx of potentially dominant alien species (Vitousek,

Phylogenetic analyses show that C₄ grasses typically occupy drier habitats than their C₃ relatives, but recent experiments comparing the physiology of closely related C₃ and C₄ species have shown that advantages of C₄ photosynthesis can be lost under drought. We tested the generality of these paradoxical findings in grass species representing the known evolutionary diversity of C₄ NADP-me and C₃ photosynthetic types. Our experiment investigated the effects of drought on leaf photosynthesis, water potential, nitrogen, chlorophyll content and mortality. C₄ grasses in control treatments were characterized by higher CO₂ assimilation rates and water potential, but lower stomatal conductance and nitrogen content. Under drought, stomatal conductance declined more dramatically in C₃ than C₄ species, and photosynthetic water-use and nitrogen-use efficiency advantages held by C₄ species under control conditions were each diminished by 40%. Leaf mortality was slightly higher in C₄ than C₃ grasses, but leaf condition under drought otherwise showed no dependence on photosynthetic-type. This phylogenetically controlled experiment suggested that a drought-induced reduction in the photosynthetic performance advantages of C₄ NADP-me relative to C₃ grasses is a general phenomenon.

SUMMARY Predicting the future responses of plants and ecosystems to further changes in the CO 2 concentration of the atmosphere and to the possibility of global warming are important current concerns. Predictions have been most frequently attempted using short‐term, single‐factor experiments in controlled environments. However, these experiments have failed to indicate the outcome of field experiments at larger spatial and temporal scales. Some of this failure is due to ignorance of environmental conditions and interactions while some is due to the use of inappropriate short‐cuts, such as the addition of fertilizers for simulating enhanced mineralization, and some is due to ignorance of the processes involved in scaling‐up from individual plants to populations. Long‐term observations on plants in ecosystems nevertheless indicate that community‐scale experiments may provide a useful but imperfect capacity to predict ecosystem responses. Although difficult to implement in practice, it is concluded that catchment‐scale experiments offer the best opportunity to predict plant, community and ecosystem responses to environmental change. CONTENTS Summary 239 I. Introduction 239 II. CO 2 ‐enrichment experiments 240 III. Experiments with applied nitrogen fertilizer 243 IV. Population ecophysiology 245 V. Ecosystem predictions 248 Acknowledgements 249 References 250

Early experiments investigating the effects of CO2 enrichment on plants frequently showed photosynthetic stimulation and reduced stomatal aperture over short time periods. Work on the effects of elevated CO2 has advanced in two major areas: by the extension of long-term and field experiments, and through investigations on the wide range of negative feedbacks affecting plant responses to CO2. Downward photosynthetic acclimation in response to CO2 enrichment is frequently observed over the short and long term, and indicates the activity of diverse feedback mechanisms. CO2 is generally viewed as a limiting photosynthetic resource. However, recent work on stomatal development has shown that this view is simplistic: long- and short-distance signalling of CO2 concentration are necessary components of normal plant development.

The potential for feedbacks between terrestrial vegetation, climate, and the atmospheric CO 2 partial pressure have been addressed by modelling. Previous research has established that under global warming and CO 2 enrichment, the stomatal conductance of vegetation tends to decrease, causing a warming effect on top of the driving change in greenhouse warming. At the global scale, this positive feedback is ultimately changed to a negative feedback through changes in vegetation structure. In spatial terms this structural feedback has a variable geographical pattern in terms of magnitude and sign. At high latitudes, increases in vegetation leaf area index (LAI) and vegetation height cause a positive feedback, and warming through reductions in the winter snow–cover albedo. At lower latitudes when vegetation becomes more sparse with warming, the higher albedo of the underlying soil leads to cooling. However, the largest area effects are of negative feedbacks caused by increased evaporative cooling with increasing LAI. These effects do not include feedbacks on the atmospheric CO 2 concentration, through changes in the carbon cycle of the vegetation. Modelling experiments, with biogeochemical, physiological and structural feedbacks on atmospheric CO 2 , but with no changes in precipitation, ocean activity or sea ice formation, have shown that a consequence of the CO 2 fertilization effect on vegetation will be a reduction of atmospheric CO 2 concentration, in the order of 12% by the year 2100 and a reduced global warming by 0.7°C, in a total greenhouse warming of 3.9°C.

New PhytologistVolume 161, Issue 1 p. 193-198 Free Access Systemic irradiance signalling in tobacco Paul W. Thomas, Corresponding Author Paul W. Thomas FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Author for correspondence: Paul W. Thomas Tel: +44 114 2224649 Fax: +44 114 2220002 Email: P.Thomas@sheffield.ac.ukSearch for more papers by this authorF. Ian Woodward, F. Ian Woodward FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Search for more papers by this authorW. Paul Quick, W. Paul Quick FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Search for more papers by this author Paul W. Thomas, Corresponding Author Paul W. Thomas FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Author for correspondence: Paul W. Thomas Tel: +44 114 2224649 Fax: +44 114 2220002 Email: P.Thomas@sheffield.ac.ukSearch for more papers by this authorF. Ian Woodward, F. Ian Woodward FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Search for more papers by this authorW. Paul Quick, W. Paul Quick FIW Laboratory, Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.Search for more papers by this author First published: 17 November 2003 https://doi.org/10.1046/j.1469-8137.2003.00954.xCitations: 90AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Summary • We report the influence of a systemic irradiance signal, from mature leaves, on the anatomical characteristics of developing leaves. • A systemic signal of reduced irradiance was induced by growing tobacco (Nicotiana tabaccum) plants at high irradiance and then measuring the effect of shading mature leaves on the development of new leaves. The reverse, a systemic signal of increased irradiance was induced by growing plants at low irradiance and then measuring the effect of increasing the irradiance of mature leaves. • Stomatal pore length, stomatal density and index, epidermal cell shape, epidermal cell size and developing leaf size were all influenced by the irradiance signal. These responses were reversible with changing irradiance, except for stomatal pore length. Introduction Changes in the anatomy and physiology of plant organs in response to environmental stimuli are well documented (Corré, 1983a; Corré, 1983b; Schoch et al., 1984; Visser et al., 1997). Environmental stimuli may be sensed by one organ while a response occurs in another. This relay of information is known as a systemic signal. There are several known examples of systemic signalling including wounding responses (Conrath et al., 2002) and floral meristerm initiation, whereby the leaves are the sensing organ and the floral meristerm is the responder (Lang et al., 1977). Recently an additional long-distance systemic signal has been found between mature and developing leaves. Lake et al. (2001) working with Arabidopsis thaliana discovered that the CO2 concentration surrounding mature leaves exerts a control on the stomatal density of developing leaves. They also report a similar effect by changing the light intensity incident on mature leaves. Following the work of Lake et al. (2001), Yano & Terashima (2001) reported that the light environment of mature leaves altered the thickness of developing Chenopodium album leaves along with the anatomy of palisade tissue. However, Yano & Terashima (2001) also reported that the light environment around the developing leaves and not that of the mature leaves controlled the development of chloroplasts. These are the only recorded leaf characteristics that have been shown to be signalled from the mature to developing leaves. Other leaf characteristics may also be affected by this signalling mechanism. For example, one of the most obvious light induced characteristics is leaf size, and yet we still do not know if this is affected by a long distance irradiance signalling mechanism. The lack of a signalling control on chloroplast ultrastructure as reported by Yano & Terashima (2001) clearly highlights the complexity of the environmental and developmental regulation of leaf development. Here, we investigate this systemic signalling system, with a specific focus on light as an environmental signal and focus on those properties that show a classical adaptation to light levels, in particular: epidermal cell size, density and undulation, stomatal pore length, index and density and leaf size. Materials and Methods Experiment one-mature leaves shaded Tobacco (Nicotiana tabacum L. SR1) plants were grown in 9 cm pots containing multipurpose compost (Humax Horticulture, Carlisle, UK) in a growth cabinet (Model PGR15, Conviron, Winnipeg, Manitoba, Canada) for 24 d under a day length of 16 h and a photosynthetically active radiation (PAR) of 250 µmol m−2 s−1 with 60% relative humidity and at a constant 25°C. The seedlings, with the developing true leaf number 6 just visible, were then divided between the control and treatment (signal) groups within the same cabinet and grown for a further 23 d. The PAR of the control group was 250 µmol m−2 s−1. Mature leaves were shaded by suspending a piece of Fig Netlon 45 (neutral filter from Netlon Group Ltd, Blackburn, UK) immediately above the plant (Fig. 1a), with a circular centre (2 cm diameter) punched out to prevent shading of the developing leaf primordia, exposed to a PAR of 250 µmol m−2 s−1. The mature leaves were exposed to a lower intensity of 90 µmol m−2 s−1. The bamboo supports, used in the treatment group to suspend the filter, were also used in the control group for comparability. Figure 1Open in figure viewerPowerPoint Design for experiment one, mature leaves shaded (a) and two, newly developing leaves shaded (b). Only true leaf number 6 (mature and fully expanded) was used for the analysis in this experiment. Experiment two-newly developing leaves shaded Tobacco (Nicotiana tabacum L. SR1) plants were grown in 9 cm pots containing multipurpose compost (Humax Horticulture, Carlisle, UK) in a growth cabinet (Model PGR15, Conviron, Winnipeg, Manitoba, Canada) for 32 days under a day length of 16 h and a PAR of 250 µmol m−2 s−1 with 60% relative humidity and at a constant 25°C. The seedlings, with the developing true leaf number 8 just visible, were then divided between the control and treatment (signal) groups within the same growth room and grown for a further 35 d. The control PAR was 90 µmol m−2 s−1. The mature leaves were exposed to banks of fluorescent lights on either side of the plants. This created an environment exposing the leaf primordial to a PAR of 90 µmol m−2 s−1 while the mature leaves were exposed to the higher intensity of 250 µmol m−2 s−1 (see Fig. 1b). Only true leaf number 8 (mature and fully expanded) was used for the analysis in this experiment. Analysis techniques Impressions from the mid section of leaves, either side of the mid-rib, were taken using dental putty. Clear impressions of the dental putty cast were then taken using clear nail varnish. The nail varnish impressions were mounted onto slides. The number of stomata and epidermal cells were calculated from five areas on each leaf, taken from either side of the mid-rib from the middle section of the leaf. The stomatal index (SI (%)) was calculated using the following equation (Salisbury, 1927): where, SD is stomatal density and ED is the density of epidermal pavement cells. Digital images were taken from the impressions using a digital camera linked to a light microscope. Areas of the leaf impression were selected for measuring the stomatal index. Within these areas, the size and cell wall perimeter of individual cells (25 from each leaf surface) were calculated using Scion Image (software version 1.63). Variations in cell shape were quantified by the undulation index of individual cells. The undulation index (UI), which describes the degree of cell wall undulation independently of cell area, was calculated for epidermal cells using the following equation (Kurschner, 1997): where UI (dimensionless) is the undulation index, Ce (µm) is the circumference of the cell and Ae (µm2) is the area of the cell. Leaf area was measured by scanning whole leaves and using Scion Image (version 1.63) to determine leaf area. Statistics A one-way anova was used for comparison between the abaxial and adaxial leaf surfaces from the control and treatment groups within both experiments. Multiple comparison tests (Tukey test) were also used, the results of which are displayed in 3, 5. The only comparison in which an anova was not used was leaf area and undulation index. A 2-sample t-test was used to compare the responses of leaf area and undulation index. Figure 3Open in figure viewerPowerPoint Mean values ± SE of the adaxial (open squares) and abaxial (closed squares) surfaces of leaves from experiment one (mature leaves shaded). Error bars are one standard error. Within each graph values followed by different letter codes are significantly different (Tukey test, P < 0.05). Control plants, mature and developing leaf PAR 250 µmol m−2 s−1. Treatment plants, mature leaf PAR 90 µmol m−2 s−1, developing leaf PAR 250 µmol m−2 s−1. Figure 5Open in figure viewerPowerPoint Mean values ± SE for the undulation index (dimensionless) of epidermal pavement cells from the control (open squares) and treatment (closed squares) of experiments one and two. Error bars are one standard error. Within each experiment values followed by different letter codes are significantly different (T-test, P < 0.05). Results and Discussion Irradiance is detected and converted to a systemic signal and exerts a significant impact on development. A typical example of this impact is displayed in Fig. 2. Figure 2Open in figure viewerPowerPoint Digital images of impressions from the adaxial leaf surface of a control (a) and a treatment (b) leaf from experiment one. Arrows highlight a stoma in each picture. Bar, 185 µm. Stomatal index The proportion of epidermal cells that develop into stomata increases in response to increasing irradiance and (through changes in stomatal density) allows higher diffusion rates of CO2 entry maintaining higher photosynthetic rates (Schoch et al., 1980). It has been reported that the stomatal index of developing leaves is systemically influenced by the light environment of mature leaves in both Arabidopsis thaliana (Lake et al., 2001) and Chenopodium album (Yano & Terashima, 2001). Our results are in agreement with both studies, with the stomatal index of newly developed tobacco leaves being significantly and reversibly influenced by the light environment of mature leaves within both experiment one (anova: F= 25.5, df = 3, 32, P < 0.001) and two (anova: F= 25.1, df = 3, 16, P < 0.001). There was a 12.7% decrease in the treatment group of experiment one (Fig. 3), and a 24.2% increase in the treatment group of experiment two (Fig. 4). Both leaf surfaces respond to this signal, but within all groups the abaxial surface has a higher stomatal index than the adaxial (see 3, 4). Figure 4Open in figure viewerPowerPoint Mean values ± SE of the adaxial (open squares) and abaxial (closed squares) surfaces of leaves from experiment two (developing leaves shaded). Error bars are one standard error. Within each graph values followed by different letter codes are significantly different (Tukey test, P < 0.05). Control plants, mature and developing leaf PAR 90 µmol m−2 s−1. Treatment plants, mature leaf PAR 250 µmol m−2 s−1, developing leaf PAR 90 µmol m−2 s−1. Stomatal density also increases with irradiance in a range of plants including tomato (Gay & Hurd, 1975), Sinapsis alba (Wild & Wolf, 1980) and Quercus myrsinaefolia (Furukawa, 1997). The results from both signalling experiments are as predicted for a leaf developing in the same light conditions as the mature leaves. The stomatal density of the treatment and control plants were significantly different in both experiments one (anova: F= 62.3, df = 3, 32, P < 0.001) and two (anova: F = 10.8, df = 3, 16, P < 0.001). There was a 50.8% decrease in the stomatal density of the treatment group of experiment one (Fig. 3), and a 92% increase in the treatment group of experiment two (Fig. 4). Although both leaf surfaces respond to this signal, within all groups the abaxial surface has a higher stomatal density than the adaxial, as observed in other studies (Gay & Hurd, 1975). The size of epidermal cells is sensitive to irradiance (Watson, 1942). The size of epidermal pavement cells within both experiments is dependant on the light environment of the mature leaves (Fig. 2) with a significant difference between the treatment and control in experiment one (anova: F = 53.6, df = 3, 32, P < 0.001) and experiment two (anova: F = 5.23, df = 3, 16, P = 0.01). Epidermal cell size within all groups is consistently larger on the adaxial surface than the abaxial surface (see 3, 4). The shape and size of the epidermal pavement cells has long been known to be influenced by irradiance. Metcalfe & Chalk (1979) describe many earlier studies which all seem to agree that the epidermal pavement cell walls are more undulated in leaves grown at reduced irradiance. Additionally, they also report a greater tendency towards 'wavyness' in epidermal cells on the abaxial surface. However, it took until 1997 for a reliable quantitative method to be developed to measure this degree of undulation. The resulting formula, the undulation index (Kurshner, 1997), describes an epidermal cell's degree of 'wavyness' that is independent of changes in cell area. Generally, the response to reduced irradiance is that the cells become wavier (higher undulation index value). It is evident that the degree of epidermal cell wavyness, is strongly influenced by the light environment of mature leaves (see Fig. 5). When mature leaves are exposed to a high irradiance the undulation index of developing leaves is significantly (T = 2.49, df = 7, P < 0.05) lower (10.2%) than the control, and when mature leaves are shaded the undulation index of developing leaves is significantly (T = −2.34, df = 20, P < 0.05) higher (8.3%) than the control (1.66 ± 0.03). The area of a leaf generally shows a strong response to irradiance (Corré, 1983b). Leaves tend to be small under very low irradiance, then increase in size with irradiance until a certain level is reached (species and environmental dependent) after which leaf surface area declines with further increases in irradiance. The results presented here indicate that the surface area of a developing leaf is strongly influenced by the light environment of mature leaves (see Fig. 3), as shown by the significantly (t = 7.66, df = 15, P < 0.001) larger leaves (55.8%) when the mature leaves are shaded in experiment one. Wild & Wolf (1980) noted that in high light the stomatal pores of Sinapis alba were distinctly larger than those grown in low light. However Rawson & Craven (1975), working with tobacco and sunflower, report that although higher mean daily radiation during leaf ontogeny increased stomatal density, area per stoma was reduced. In agreement with the results of Wild & Wolf (1980) and contradictory to Rawson & Craven (1975), tobacco SR-1 shows an increase in stomatal pore length in response to increased irradiance (up to 400 µmol m−2 s−1 (data not shown)). The response of stomatal pore length to signalling is complex. Pore length increases significantly (anova: F= 51.9, df = 3, 32, P < 0.001) when the mature leaves are shaded (experiment one, Fig. 3). Stomatal pore size doesn't change (anova: F= 2.3, df = 3, 16, P > 0.05) when the developing leaves are held at low irradiance (Fig. 4). Within both experiments stomatal pore aperture remained constant between treatment and control groups. Conclusion Stomatal pore length, stomatal density, epidermal cell shape, epidermal cell size, and leaf size of newly developed leaves are all influenced by the light environment of mature leaves. The influence of the systemic signal, produced when the mature leaves are shaded, on stomatal index, stomatal density, epidermal cell shape and epidermal cell size, can be reversed when the mature leaves are exposed to increased irradiance while stomatal pore length can not. These results indicate that systemic signalling of irradiance strongly influences leaf development. Previously only stomatal index and leaf thickness (Lake et al., 2001; Yano & Terashima, 2001) in developing leaves had been shown to be influenced by the light environment of mature leaves. However, the results indicate that the between leaf signalling system is influential in a whole range of leaf properties. This raises many important questions, not least of which is the degree of impact such a signalling pathway exerts in ecological situations. An interesting question that emerges is the mechanism of the signal transduction pathway. Lake et al. (2002) have used mutants with lesions in particular components of known signal transduction pathways and these have indicated that multiple pathways could be involved in systemic signalling of CO2 concentration. Further both light and CO2 impact directly on the rate of photosynthesis and this may have a role in the signalling pathway. Sugars are known to be involved in signal transduction pathways (Sheen et al., 1999) and it has been shown that the transport of sugars can affect plant growth and alter leaf properties (Bürkle et al., 1998). A potential role for sugars in this systemic signalling pathway cannot be ruled out at this stage though it is important to note that increased light and elevated CO2 both enhance rates of photosynthesis but have opposite effects on the stomatal development of new leaves. The results from signalling experiments such as this can be used to help answer many other questions in plant science. For example, by moving away from classical leaf development models whereby leaf development is influenced by its local light environment, we may come closer to understanding the control and causes of several leaf morphological responses. Although ethylene, ABA, fatty acid signalling and ROS-antioxidants may be implicated in such long distance systemic signalling, the exact pathways are far from clear (Lake et al., 2002). Whatever the cause and impacts of the systemic irradiance signal, it will be interesting to explore further and establish whether this type of signalling is common in the plant kingdom. Of great interest will be the exploration of impacts in a range of ecological situations and the identification of the methods of regulation. Acknowledgements This work was supported by a BBSRC studentship grant. References Bürkle L, Hibberd JM, Quick WP, Kuhn C, Hirner B, Frommer WB. 1998. The H+-sucrose cotransporter NtSUT1 is essential for sugar export from tobacco leaves. 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The effect of different light intensities on the frequency and size of stomata, the size of cells, the number, size and chlorophyll content of chloroplasts in the mesophyll and the guard cells during the ontogeny of primary leaves of Sinnapis alba. Pflanzenphysiology 97: 325– 342. CrossrefCASWeb of Science®Google Scholar Yano S, Terashima I. 2001. Separate localization of light signal perception for sun or shade type chloroplast and palisade tissue differentiation in Chenopodium album. Plant and Cell Physiology 42: 1303– 1310. CrossrefCASPubMedWeb of Science®Google Scholar Citing Literature Volume161, Issue1January 2004Pages 193-198 This article also appears in:Plant speciation FiguresReferencesRelatedInformation

Summary During the past century, annual mean temperature has increased by 0.75°C and precipitation has shown marked variation throughout the Mediterranean basin. These historical climate changes may have had significant, but presently undefined, impacts on the productivity and structure of sclerophyllous shrubland, an important vegetation type in the region. We used a vegetation model for this functional type to examine climate change impacts, and their interaction with the concurrent historical rise in atmospheric CO 2 . Using only climate and soil texture as data inputs, model predictions showed good agreement with observations of seasonal and regional variation in leaf and canopy physiology, net primary productivity (NPP), leaf area index (LAI) and soil water. Model simulations for shrubland sites indicated that potential NPP has risen by 25% and LAI by 7% during the past century, although the absolute increase in LAI was small. Sensitivity analysis suggested that the increase in atmospheric CO 2 since 1900 was the primary cause of these changes, and that simulated climate change alone had negative impacts on both NPP and LAI. Effects of rising CO 2 were mediated by significant increases in the efficiency of water‐use in NPP throughout the region, as a consequence of the direct effect of CO 2 on leaf gas exchange. This increase in efficiency compensated for limitation of NPP by drought, except in areas where drought was most severe. However, while water was used more efficiently, total canopy water loss rose slightly or remained unaffected in model simulations, because increases in LAI with CO 2 counteracted the effects of reduced stomatal conductance on transpiration. Model simulations for the Mediterranean region indicate that the recent rise in atmospheric CO 2 may already have had significant impacts on productivity, structure and water relations of sclerophyllous shrub vegetation, which tended to offset the detrimental effects of climate change in the region.

SUMMARY This paper describes experiments carried out to investigate the causes of high leaf nitrogen concentrations and high δ 13 C values in Alchemilla alpina L. growing at high altitudes. We investigated whether genetic adaptation, high levels of nitrogen input or low temperatures could account for these trends. In a field experiment, plants from two altitudes in the Scottish Highlands were transplanted to Great Dun Fell, a site in the Pennines of northern England. The experimental design was fully factorial: two altitudinal origins × two altitudes of growth × two nitrogen levels. A second experiment used a controlled environment to test the effects of temperature alone. The effects of altitude in the field transplant experiment were very similar to those in naturally growing plants. Leaf nitrogen concentration and δ 13 were both higher at the high altitude, whilst growth declined and nitrogen per leaf was unaffected. An increase in potassium concentration with altitude was also found. Nitrogen addition caused increased leaf nitrogen concentrations but also increased nitrogen per leaf; δ 13 C was not affected and potassium and phosphorus concentrations decreased. The addition of nitrogen also increased mortality. Altitude of origin had relatively few effects but the population from the higher altitude did have a higher specific leaf area. Low temperature in the controlled environment caused increased δ 13 C, decreased leaf size and increased nitrogen and carbon contents, although the effect was less clear than the effects of altitude in the field. Gas exchange measurements suggested that the δ 13 C effect was caused by a reduction in stomatal conductance. We conclude that the effects of altitude on this species are principally the result of direct environmental modifications to growth rather than genetic adaptation. Of the various factors that change with altitude, temperature and a short growing season are particularly important; enhanced nitrogen supply through atmospheric deposition promotes increasing leaf nitrogen concentrations but must be considered in conjunction with other variables.

Vegetation plays a part in controlling climate and in turn responds to climatic change. Therefore, projections of future climates must include the responses of vegetation, both in terms of function and distribution. Unfortunately, assessments of future climatic impacts on vegetation are still considered with equilibrium vegetation models-models which exclude processes involved in vegetation dynamics, such as succession and disturbance. The commonly held view that future spatial changes in temperature will outstrip the potential for species to migrate has no theoretical

Major fluctuations in the concentrations of atmospheric CO2and O2are predicted by historical long-term carbon and oxygen cycle models of atmospheric evolution and will have impacted directly on past climates, plant function and evolutionary processes. Here, palaeobotanical evidence is presented from the stomatal density record of fossil leaves spanning the past 400 Myr supporting the predicted changes in atsmopheric CO2. Evidence from experiments on plants exposed to long-term high CO2environments and the newly assembled fossil data indicate the potential for genetic modification of stomatal characters. The influence of the changes in fossil stomatal characteristics and atmospheric composition on the rates of leaf gas exchange over the course of land plant evolution has been investigated through modelling. Three contrasting eras of plant water economies emerge in the Devonian (high), Carboniferous (low) and from the Upper Jurassic to the present-day (high but declining). These patterns of change result from structural changes of the leaves and the impact of atmospheric CO2and O2concentrations on RuBisCo function and are consistent with the fossil evidence of sequential appearances of novel plant anatomical changes. The modelling approach is tested by comparing predicted leaf stable carbon isotope ratios with those measured on fossil plant and organic material. Viewed in a geological context, current and future increases in the concentration of atmospheric CO2might be considered as restoring plant function to that more typically experienced by plants over the majority of their evolutionary history.

Abstract Mean temperature of establishment years for warm‐ and cold‐year subpopulations of a naturally occurring stand of Betula pendula (birch) shows a difference equivalent to that between current temperatures and temperatures projected for 35–55 years hence, given ‘business as usual.’ The existence of ‘pre‐adapted’ individuals in standing tree populations would reduce temperature‐based advantages for invading species and, if general, bring into question assumptions currently used in models of global climate change. Our results demonstrate a methodology useful for investigating the important ecological issue of adaptation vs. range shifts as a means of response to climate change.

Journal Article Experimental Investigations on the Environmental Determination of δ13C at Different Altitudes Get access M. D. MORECROFT, M. D. MORECROFT 1 Botany SchoolDowning Street, Cambridge CB2 3EA, UK 1 To whom correspondence should be addressed. Search for other works by this author on: Oxford Academic PubMed Google Scholar F. I. WOODWARD F. I. WOODWARD Botany SchoolDowning Street, Cambridge CB2 3EA, UK Search for other works by this author on: Oxford Academic PubMed Google Scholar Journal of Experimental Botany, Volume 41, Issue 10, October 1990, Pages 1303–1308, https://doi.org/10.1093/jxb/41.10.1303 Published: 01 October 1990 Article history Received: 02 February 1990 Published: 01 October 1990

summary Rising levels of atmospheric CO 2 , climate change, and fertilizer pollution provide the ecological imperative for investigating the interaction between plant responses to atmospheric CO 2 concentration, temperature and nutrient supply. In this study spring wheat (Triticum aestivum L. cv. Wembley) was grown at 40, 50, 60 and 70 Pa atmospheric CO 2 , pressure and three experiments were conducted to investigate interactions between growth responses to the CO 2 treatment and: (i) temperature (24/16 °C vs. 18/10 °C ‐ day/night), (ii) nutrient solution nitrate concentration (2.5, 5, 10 and 15 mM Ca(NO 3 ) 2 .4H 2 O). and (iii) phosphate concentration (0.025 and 0.5 mM KH 2 PO 4 ), Dry mass and root/shoot ratio increased with CO 2 level at the higher temperature. These responses were reversed at the lower temperature. The increase in yield with CO 2 enhancement was limited by low rates of nutrient supply in both absolute and relative terms. In the elevated CO 2 treatments, the shoot nitrogen concentration was reduced, as was the proportional allocation to the uppermost leaves. These results are discussed with respect to possible physiological mechanisms and potential for improved crop performance in a future, elevated CO 2 world.

Over the last two centuries, man's activities have caused a 30% increase in the atmospheric concentration of CO2, with continued increases seeming inevitable. This change in CO2 concentration will act on vegetation, both directly and indirectly through global climatic change. It is well established that, on a global scale, patterns of vegetation and climate are closely correlated. Such correlations indicate that climatic change will cause the distribution of vegetation to change. However, the use of correlations for predicting vegetation responses to climatic change is fundamentally unreliable because correlations have no mechanistic underpinning of causation. This paper outlines a mechanistic model for predicting the equilibrium state between current climate and vegetation. It is also used to indicate the sensitivity of global vegetation to the changed climate associated with a doubled CO2—greenhouse scenario. The interpretation of this static model is discussed in terms of rates and patterns of vegetation change.

Large‐scale bottom‐up estimates of terrestrial carbon fluxes, whether based on models or inventory, are highly dependent on the assumed land cover. Most current land cover and land cover change maps are based on satellite data and are likely to be so for the foreseeable future. However, these maps show large differences, both at the class level and when transformed into Plant Functional Types (PFTs), and these can lead to large differences in terrestrial CO 2 fluxes estimated by Dynamic Vegetation Models. In this study the Sheffield Dynamic Global Vegetation Model is used. We compare PFT maps and the resulting fluxes arising from the use of widely available moderate (1 km) resolution satellite‐derived land cover maps (the Global Land Cover 2000 and several MODIS classification schemes), with fluxes calculated using a reference high (25 m) resolution land cover map specific to Great Britain (the Land Cover Map 2000). We demonstrate that uncertainty is introduced into carbon flux calculations by (1) incorrect or uncertain assignment of land cover classes to PFTs; (2) information loss at coarser resolutions; (3) difficulty in discriminating some vegetation types from satellite data. When averaged over Great Britain, modeled CO 2 fluxes derived using the different 1 km resolution maps differ from estimates made using the reference map. The ranges of these differences are 254 gC m −2 a −1 in Gross Primary Production (GPP); 133 gC m −2 a −1 in Net Primary Production (NPP); and 43 gC m −2 a −1 in Net Ecosystem Production (NEP). In GPP this accounts for differences of −15.8% to 8.8%. Results for living biomass exhibit a range of 1109 gC m −2 . The types of uncertainties due to land cover confusion are likely to be representative of many parts of the world, especially heterogeneous landscapes such as those found in western Europe.

SUMMARY Field measurements of selected upland and lowland species have demonstrated a decline in specific leaf area with altitude, probably due to changes in both air temperature and wind‐speed. Both field and controlled environment experiments have demonstrated that the upland species have lower specific leaf areas than the lowland species, under similar environmental conditions. Leaf growth and turgor of the upland species, Phleum alpinum , are insensitive to changes in wind‐speed in the range of 0.2 to 3 m s −1 , while both growth and turgor decline with wind‐speed for the lowland P. pratense. Leaf turgor of P. pratense declined with increasing specific leaf area but no such relationship was found for P. alpinum.

Natural variation in moisture availability affects the productivity of tropical ecosystems more profoundly than any other climatic variable. As a result, drought is perhaps the most important climatic threat to tropical forests. Climate-change scenarios for the 21st century have suggested decreased soil-moisture availability in certain regions of the world (Bates et al., 2008). Notably, the rain forests of Amazonia have been considered to be at particular risk, especially when possible climate impacts are examined alongside an increased incidence of land-use change (Scholze et al., 2006; Soares-Filho et al., 2006; Malhi et al., 2008). ‘... a growing body of data is showing that Amazonian rain forests are highly (and negatively) responsive to strong, and especially extended, soil-moisture deficit in terms of aboveground and belowground processes, net ecosystem production (NEP) and mortality.’ Amazonia is home to perhaps 25% of the world’s terrestrial species (Dirzo & Raven, 2003), comprises a total biomass that is equivalent to > 10 times the current annual global CO2 emissions to the atmosphere (IPCC, 2007) and performs c. 15% of global terrestrial photosynthesis (Field et al., 1998). Substantial losses of Amazonian forests and the species diversity they house would impact climate at regional and intercontinental scales through changes in land–atmosphere energy exchange and precipitation (Werth & Avissar, 2002; Marengo, 2006), and globally through increased atmospheric CO2 concentrations and changes to the global balance of other key greenhouse gases such as nitrous oxide and methane. However, despite repeated modelled scenarios for Amazonia of 21st century warming, drought and the resultant dieback of rain forest (White et al., 1999; Cox et al., 2000; Betts et al., 2004; Scholze et al., 2006; Sitch et al., 2008), our ability to understand the true vulnerability to loss of the region’s forests has been hampered, first, by insufficient field data and, second, by a weak understanding of the predictive skill of the models themselves. This is especially so for land-surface processes where large differences in the estimates of global CO2 emissions have been found using different dynamic global vegetation models (DGVMs) driven using the same climate data (Friedlingstein et al., 2006; Meir et al., 2006). In addition, climate scenarios vary substantially among global circulation models (GCMs; Friedlingstein et al., 2006; Li et al., 2006), even when the GCMs are driven forward from observed 20th century data using only the predicted anomalies from the mean. Clearly, the most reliable data for understanding the response by forests to drought are ground measurements, but these inevitably lack reach over space and time. Remote sensing offers a partial solution, especially in the context of assessing vulnerability in relation to changes in land use and to fire incidence (e.g. Aragao et al., 2008), but any remote sensing-based assessment of ecological responses remains uncertain in the absence of good correlations with ground data. In this issue of New Phytologist, a special feature on ‘Amazonian rain forests and drought’ provides important advances in all of these areas. First, it reports new data analyses on growth, mortality, physiological responses and deep-soil-moisture supply during multi-year experimental drought (da Costa et al., pp. 579–591; Markewitz et al., pp. 592–607; Metcalfe et al., 2010b, pp. 608–621; Lima et al. pp. 622–630), also substantially extending recent important findings (Phillips et al., 2009) on the observed impacts of natural drought across the Amazon (Phillips et al., pp. 631–646). Second, it presents new modelling insights evaluating the accuracy of process-level drivers of modelled dieback in different DGVMs (Galbraith et al., pp. 647–665), the possible influence on productivity of poorly modelled demographic processes, such as mortality (Fisher et al., pp. 666–681), an examination of the quality of different GCM climate scenarios used to drive DGVMs (Jupp et al., pp. 682–693) together with their consequences for modelled vegetation responses in one particular DGVM (Rammig et al., pp. 694–706) and a novel, simplified model analysis of the combined response by vegetation to changes in lightning frequency, as well as climate (Hirota et al., pp. 707–719). This modelling analysis is complemented by Ray et al. (pp. 720–732) who use an experimental approach to develop an environmental model of fire risk, relevant where natural or anthopogenic ignition sources may be prevalent. Finally, and in a timely manner given recent disagreement in the literature (Saleska et al., 2007; Samanta et al., 2010), we include a review of the utility of remote sensing to understand drought impacts on Amazon forest processes (Asner & Alencar, pp. 569–578). One element in this review is examined in a second, independent, remote sensing study that uses ground data to suggest that perceived resilience in productivity to moisture deficit inferred from remotely sensed data is probably better explained by structural differences in the canopy that may be related to mortality (Anderson et al., pp. 733–750). Although only about half of the papers in this special feature are based on the analysis of new data, the need for appropriate ecological understanding derived from field-based measurements emerges strongly. As noted for remote sensing (Anderson et al., pp. 733–750), the modelling analyses reported here highlight important weaknesses in the representation of the real world. Galbraith et al. (pp. 647–665) show that the mechanisms underlying the most basic processes in DGVMs, such as soil-water access, photosynthesis and respiration, all vary substantially among models. The outcome is that modelled forest dieback during drought appears – surprisingly – to result more from the modelled physiological response to temperature than from moisture deficit. Underscoring this outcome and the need for model improvement, all of the DGVMs considered by Galbraith et al. (pp. 647–665) (which includes a version of the model ‘LPJ’ also used in this issue by Rammig et al., pp. 694–706) were largely insensitive to moisture deficit when compared against the results from two large-scale multi-year drought experiments (da Costa et al., pp. 579–591; Brando et al., 2008). Does this mean that some DGVMs simulate forest decline during climatic warming and drying, but for the wrong reasons? Accurate ecophysiological parameterization, for example to soil-moisture deficit and acclimation to temperature, clearly needs close attention in ongoing DGVM developments. Natural or experimental droughts will help to guide these improvements in physiological representation, but they are less useful in helping us address the long-standing uncertainty over the decadal-scale response by tropical forests to the increasing concentration of CO2 in the atmosphere (Long et al., 1994; Lloyd & Farquhar, 2008). Increased CO2, shown here by Rammig et al. (pp. 694–706), and previously (Hickler et al., 2008; Lapola et al., 2009), could ameliorate the negative impacts of moisture deficit on photosynthesis, especially at tropical temperatures. If the increased efficiency in water loss per unit of fixed carbon (that often occurs at higher CO2 concentrations) is large and long-lived, then, in the absence of increased fire incidence or land-use change, resilience over the long term to reduced soil moisture is implied, and perhaps also to phosphorus deficiency (Lloyd et al., 2001). Not only is there uncertainty over the size and persistence of this ecophysiological ‘fertilization’ response to increased CO2, but also over its possible impact on forest dynamics and species composition: both effects could counterbalance the gains from ‘CO2 fertilization’ (Körner, 2004,Phillips et al., 2004). Given the importance of this question and the size of the tropical forest biome, a free-air CO2 enrichment experiment in the tropics could usefully complement existing field-scale drought experiments. In addition to enabling better model validation, the measurements reported here also underline the importance of data for new understanding. Resource access by roots remains poorly understood (Silver et al., 2005), as do the drought responses by respiring cells in vegetation and soil (Meir et al., 2008), but both could have profound influences on forest ecosystem resilience to drought. Here, Markewitz et al. (pp. 592–607) suggest that deep-soil-water supply (where available) may only confer drought resistance for up to 1–2 yr, and that hydraulic redistribution processes probably transfer much less water to vegetation than recently supposed. Furthermore, Lima et al. (pp. 622–630) use an irrigation experiment at a site in eastern Para with relatively shallow soil to show strong root-growth responses to soil-moisture deficit (but not to reduced nutrient availability), whilst Metcalfe et al. (2010b, pp. 608–621) use multiple-component flux estimates to build on a recent finding of increased leaf dark respiration during experimental drought (Metcalfe et al., 2010a). The outcome is that extended drought might cause increasing net CO2 emissions from the forest to the atmosphere (Metcalfe et al., 2010b, pp. 608–621). This result requires further careful testing, but may also have consequences for perhaps the most important ecological response to drought: increased mortality. It is possible, although uncertain, that raised autotrophic respiration rates increase the risk of mortality in drought-impacted trees (McDowell et al., 2008; Sala, 2009). The drought experiments referred to in this issue of New Phytologist provide an ideal platform to test such an hypothesis, but irrespective of the outcome, the impact of drought on mortality appears to be strong and relatively similar across Amazonia. The two Amazonian drought (‘throughfall-exclusion’) experiments in eastern Amazonia at Tapajós and Caxiuanã were performed on forests with different soils and probably different natural disturbance histories (Nepstad et al., 2002; Meir & Grace, 2005; Fisher et al., 2007). Yet, despite these differences, the responses to experimental drought were quantitatively similar in terms of increased mortality, the timing of increased mortality and the medium-term decline (5–8 yr) in carbon storage (da Costa et al., pp. 579–591). Furthermore, when these experimental results were placed in the context of a regional-to-global analysis of the impact of natural drought events on mortality in tropical rain forests (Phillips et al., pp. 631–646), the response to soil-moisture deficit was surprisingly predictable for Amazonia, and in one analysis quite linear. Although we might expect important differences in the mortality responses to natural drought events and multi-year experimental reductions in soil moisture, these results hint at surprising generality. In a modelling analysis, Fisher et al. (pp. 666–681) show that when variability in modelled demographic processes, such as mortality, are incorporated in a new DGVM structure, large differences in biomass storage during the 21st century can be expected. Consistent with this, da Costa et al. (pp. 579–591) describe tantalizing evidence to show that distinct adult taxa differ widely in their vulnerability to drought. Conversely, the narrow range of mortality responses observed by da Costa et al. (pp. 579–591), Phillips et al. (pp. 631–646) and Brando et al. (2008) could helpfully constrain part of the theoretical uncertainty highlighted by Fisher et al. (pp. 666–681), although we caution strongly that the mortality/soil-moisture-deficit responses observed in Amazonia do not extend to other tropical regions, such as Borneo, where sensitivity to drought appears to be markedly higher. How do the studies in this special feature advance our overall ability to estimate the vulnerability of Amazon rain forests to drought? The answer lies at the intersection of field data, and our understanding of model realism. On the one hand, the new analyses provide evidence for unexpected consistency in tree mortality and growth under drought. This points to high vulnerability in both eastern and western parts of Amazonia, in some areas at an annual timescale, although where initial resistance to moisture deficit has been observed, this resistance also appears to break down following an imposed drought of 3 yr or longer (da Costa et al., pp. 579–591; Phillips et al., pp. 631–646). Certainly, the measured vulnerability in aboveground biomass storage to drought over a 5–8 yr period is substantially higher than is represented in at least three leading DGVMs (Galbraith et al., pp. 647–665). On the other hand, in an analysis of multiple GCM-generated future climate scenarios weighted by their ability to reproduce observed 20th century precipitation (Jupp et al., pp. 682–693), the variability in the strength and spatial occurrence of 21st century changes in precipitation places constraints on the (estimated) likelihood of declines in moisture availability across the region. This outcome reduces the perceived vulnerability to moisture deficit for some, but not all, regions of Amazonia, and must also be considered in the context of uncertainty in the long-term physiological response to increased atmospheric CO2 concentration. Overall, a growing body of data is showing that Amazonian rain forests are highly (and negatively) responsive to strong, and especially extended, soil-moisture deficit in terms of aboveground and belowground processes, net ecosystem production (NEP) and mortality. The long-term consequences of extended drought for the carbon balance and forest species composition of these forests are therefore substantial. When assessing the future vulnerability to forest loss from soil-moisture deficit alone we remain limited by our ability to predict both future precipitation patterns and some physiological responses. Only long-term research can help us address these fundamental questions, pointing to the central importance of extending the observational and experimental climate and vegetation data sets that have already been developed for this region (e.g. Keller et al., 2009). However, when expected feedbacks between vegetation and climate are combined with fire incidence and land-use change scenarios, we conclude that Amazon rain forests are highly vulnerable to loss during the coming decades. Yet this loss and its consequences are not inevitable: whether or not possible transitions to more depauperate vegetation types are sudden and caused by forest clearance and fire (Hirota et al., pp. 707–719; Nepstad et al., 2008), are strongly mediated by differences in soil fertility and neighbouring species assemblages (Meir & Pennington, 2010), or are constrained successfully through sustainable resource-management practices (Soares-Filho et al., 2006; Nepstad et al., 2008; Ricketts et al., 2010), remain central questions for Amazonian ecosystem science and environmental governance. We conclude by thanking the numerous people involved with the production of this special feature. We thank all the authors for their contributions and are grateful for the time and effort of the referees and editors, and to the incredibly efficient, patient and helpful Central Office team at New Phytologist. Finally, we note that the long-term international collaborative and training research frameworks that have formed the basis of much of this work (e.g. Keller et al., 2009; Phillips et al., 2009) are a privilege to be part of, and indeed are often necessary to advance the capacity required to understand environmental questions of this size.

Research Article| September 01, 2012 Deep-time evidence of a link between elevated CO2 concentrations and perturbations in the hydrological cycle via drop in plant transpiration Margret Steinthorsdottir; Margret Steinthorsdottir * 1School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland *Current address: Department of Geological Sciences, Stockholm University, SE-106 91 Stockholm, Sweden; E-mail: margret.stein@gmail.com. Search for other works by this author on: GSW Google Scholar F. Ian Woodward; F. Ian Woodward 2Department of Animal and Plant Sciences, Sheffield University, Sheffield S10 2TN, UK Search for other works by this author on: GSW Google Scholar Finn Surlyk; Finn Surlyk 3Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen K, Denmark Search for other works by this author on: GSW Google Scholar Jennifer C. McElwain Jennifer C. McElwain 1School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland Search for other works by this author on: GSW Google Scholar Author and Article Information Margret Steinthorsdottir * 1School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland F. Ian Woodward 2Department of Animal and Plant Sciences, Sheffield University, Sheffield S10 2TN, UK Finn Surlyk 3Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen K, Denmark Jennifer C. McElwain 1School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland *Current address: Department of Geological Sciences, Stockholm University, SE-106 91 Stockholm, Sweden; E-mail: margret.stein@gmail.com. Publisher: Geological Society of America Received: 20 Feb 2012 Revision Received: 29 Mar 2012 Accepted: 01 Apr 2012 First Online: 09 Mar 2017 Online ISSN: 1943-2682 Print ISSN: 0091-7613 © 2012 Geological Society of America Geology (2012) 40 (9): 815–818. https://doi.org/10.1130/G33334.1 Article history Received: 20 Feb 2012 Revision Received: 29 Mar 2012 Accepted: 01 Apr 2012 First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Margret Steinthorsdottir, F. Ian Woodward, Finn Surlyk, Jennifer C. McElwain; Deep-time evidence of a link between elevated CO2 concentrations and perturbations in the hydrological cycle via drop in plant transpiration. Geology 2012;; 40 (9): 815–818. doi: https://doi.org/10.1130/G33334.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGeology Search Advanced Search Abstract The physiological effects of high CO2 concentrations, i.e., [CO2], on plant stomatal responses may be of major importance in understanding the consequences of climate change, by causing increases in runoff through suppression of plant transpiration. Radiative forcing by high [CO2] has been the main consideration in models of global change to the exclusion of plant physiological forcing, but this potentially underestimates the effects on the hydrological cycle, and the consequences for ecosystems. We tested the physiological responses of fossil plants from the Triassic–Jurassic boundary transition (Tr–J) succession of East Greenland. This interval marks a major high CO2-driven environmental upheaval, with faunal mass extinctions and significant floral turnover. Our results show that both stomatal size (expressed in fossil material as SL, the length of the stomatal complex opening) and stomatal density (SD, the number of stomata per mm2) decreased significantly during the Tr–J. We estimate, using a leaf gas-exchange model, that the decreases in SD and SL resulted in a 50%–60% drop in stomatal and canopy transpiration at the Tr–J. We also present new field evidence indicating simultaneous increases in runoff and erosion rates. We propose that the consequences of stomatal responses to elevated [CO2] may lead to locally increased runoff and erosion, and may link terrestrial and marine biodiversity loss via the hydrological cycle. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Small‐seeded plant species are often reported to have high relative growth rate or RGR. However, because RGR declines as plants grow larger, small‐seeded species could achieve higher RGR simply by virtue of their small size. In contrast, size‐standardized growth rate or SGR factors out these size effects. Differences in SGR can thus only be due to differences in morphology, allocation, or physiology. We used nonlinear regression to calculate SGR for comparison with RGR for 10 groups of species spanning a wide range of life forms. We found that RGR was negatively correlated with seed mass in nearly all groups, but the relationship between SGR and seed mass was highly variable. We conclude that small‐seeded species only sometimes possess additional adaptations for rapid growth over and above their general size advantage.

summary It is sometimes assumed that because increases in atmospheric CO 2 concentration usually enhance water use efficiency per unit leaf area, there will be a tendency for plants to show greater drought tolerance as well as increased biomass in the future. A critical examination of the responses to elevated CO 2 in three temperate tree species shows that this assumption might be incorrect in the case of two of them. Both beech ( Fagus sylvatica L.) and birch ( Betula pubescens Ehrh.) display minimal stomatal closing responses to elevated CO 2 , and in the case of F. sylvatica the stomatal control of transpiration per unit leaf area appears to be unable to compensate for the greater development of leaf area. By contrast, the stomata of oak ( Quercus robur L.) close appreciably in elevated CO 2 , to an extent which might be sufficient to compensate for an increase in total leaf area. A simple model for the controls on water supply and consumption for the whole tree suggests that in F. sylvatica the potential height attainment for a given sapwood area might decrease as the atmospheric CO 2 concentration rises. The conclusions drawn from experimental data and from modelling are supported by field observations made in the UK in 1995, when the three species responded very differently to severe drought. We suggest that the progressive increase in the concentration of atmospheric CO 2 over the past 200 yr might have accentuated differences in drought sensitivity between these species.

Abstract Increases in the atmospheric concentration of carbon dioxide and associated changes in climate may exert large impacts on plant physiology and the density of vegetation cover. These may in turn provide feedbacks on climate through a modification of surface‐atmosphere fluxes of energy and moisture. This paper uses asynchronously coupled models of global vegetation and climate to examine the responses of potential vegetation to different aspects of a doubled‐CO 2 environmental change, and compares the feedbacks on near‐surface temperature arising from physiological and structural components of the vegetation response. Stomatal conductance reduces in response to the higher CO 2 concentration, but rising temperatures and a redistribution of precipitation also exert significant impacts on this property as well as leading to major changes in potential vegetation structure. Overall, physiological responses act to enhance the warming near the surface, but in many areas this is offset by increases in leaf area resulting from greater precipitation and higher temperatures. Interactions with seasonal snow cover result in a positive feedback on winter warming in the boreal forest regions.

Abstract The Younger Dryas stadial (11 000‐10 000 yr BP) was an abrupt return to a glacial climate during the termination of the last glaciation. We have reconstructed atmospheric CO 2 concentrations from a high‐resolution sequence of fossil Salix herbacea leaves through this climatic oscillation from Kråkenes, western Norway, using the relationship between leaf stomatal density and atmospheric CO 2 concentration. High Allerød CO 2 values (median 273 ppmv) decreased rapidly during 130–200 14 C‐years of the late Allerød to ca. 210 ppmv at the start of the Younger Dryas. They then increased steadily through the Younger Dryas, reaching typical interglacial values once more ( ca. 275 ppmv) in the Holocene. The rapid late Allerød decrease in CO 2 concentration preceded the Younger Dryas temperature drop, possibly by several decades. This striking pattern of changes has not so far been recorded unambiguously in temporally coarse measurements of atmospheric CO 2 from ice cores. Our observed late‐glacial CO 2 changes have implications for global modelling of the ocean‐atmosphere‐biosphere over the last glacial‐interglacial transition.

• Genetic variation was assessed across the UK geographical range of Cirsium acaule and Cirsium heterophyllum. A decline in genetic diversity and increase in population divergence approaching the range edge of these species was predicted based on parallel declines in population density and seed production reported seperately. Patterns were compared with UK populations of the widespread Cirsium arvense. • Populations were sampled along a latitudinal transect in the UK and genetic variation assessed using microsatellite markers. • Cirsium acaule shows strong isolation by distance, a significant decline in diversity and an increase in divergence among range-edge populations. Geographical structure is also evident in C. arvense, whereas no such patterns are seen in C. heterophyllum. • There is a major disparity between patterns of genetic variation in C. acaule and C. heterophyllum despite very similar patterns in seed production and population isolation in these species. This suggests it may be misleading to make assumptions about the geographical structure of genetic variation within species based solely on the present-day reproduction and distribution of populations.

Vegetation phenology is affected by climate change and in turn feeds back on climate by affecting the annual carbon uptake by vegetation. To quantify the impact of phenology on terrestrial carbon fluxes, we calibrate a bud-burst model and embed it in the Sheffield dynamic global vegetation model (SDGVM) in order to perform carbon budget calculations. Bud-burst dates derived from the VEGETATION sensor onboard the SPOT-4 satellite are used to calibrate a range of bud-burst models. This dataset has been recently developed using a new methodology based on the normalized difference water index, which is able to distinguish snowmelt from the onset of vegetation activity after winter. After calibration, a simple spring warming model was found to perform as well as more complex models accounting for a chilling requirement, and hence it was used for the carbon flux calculations. The root mean square difference (RMSD) between the calibrated model and the VEGETATION dataset was 6.5 days, and was 6.9 days between the calibrated model and independent ground observations of bud-burst available at nine locations over Siberia. The effects of bud-burst model uncertainties on the carbon budget were evaluated using the SDGVM. The 6.5 days RMSD in the bud-burst date (a 6% variation in the growing season length), treated as a random noise, translates into about 41 g cm-2 yr-1 in net primary production (NPP), which corresponds to 8% of the mean NPP. This is a moderate impact and suggests the calibrated model is accurate enough for carbon budget calculations. In addition to random differences between the calibrated model and VEGETATION data, systematic errors between the calibrated bud-burst model and true ground behaviour may occur, because of bias in the temperature dataset or because the bud-burst detected by VEGETATION is because of some other phenological indicator. A systematic error of 1 day in bud-burst translates into a 10 g cm-2 yr-1 error in NPP (about 2%). Based on the limited available ground data, any systematic error because of the use of VEGETATION data should not lead to significant errors in the calculated carbon flux. In contrast, widely used methods based on the normalized difference vegetation index from the advanced very high resolution radiometer satellite are likely to confuse snowmelt and vegetation greening, leading to errors of up to 15 days in bud-burst date, with consequent large errors in carbon flux calculations.

SUMMARY Ecophysiological information on the responses of plants to past global environmental changes may be obtained from Quaternary fossil leaves by measurements of (i) stomatal density, (ii) stomatal dimensions and (iii) 13 C discrimination (Δ 13 C). The stomatal density and stomatal dimensions of leaves can be used to calculate stomatal conductance, while leaf Δ 13 C values provide independent information on stomatal conductance and plant water use efficiency. In this paper, stomatal conductance is calculated for a sequence of radiocarbon dated fossil leaves of Salix herbacea L. which, together with herbarium and fresh material, represents a time‐series spanning from the Last Glacial Maximum (LGM) (16500 yr BP) to the present day. The calculated values were then tested against leaf Δ 13 C values previously reported for the same material. Our calculations show that stomatal conductance is negatively correlated with increases in atmospheric CO 2 concentration over the last 16500 yr. This represents the first evidence of long‐term response of stomatal conductance to increases in atmospheric CO 2 concentration and confirms the response observed in experimental systems exposing plants to lower‐than‐present CO 2 concentrations in controlled environments. The calculated decrease in conductance was positively correlated with leaf Δ 13 C values, supporting this interpretation. The mean leaf Δ 13 C value for the 18th and 19th centuries was significantly ( P ≥ 0.05) lower than the mean for the interval LGM‐Holocene (10000 yr BP) implying an increase in plant water‐use‐efficiency over this time. These two lines of evidence, together with the stomatal density record from a glacial cycle, and experimental studies growing C 3 plants in glacial‐to‐present CO 2 concentrations, strongly imply that the water use efficiency of vegetation during the LGM was lower than at present and that it has increased since that time. Further evidence in support of this conclusion comes from the pattern of world vegetation types present during the LGM previously reconstructed using palaeoecological data. This evidence demonstrates that the distribution of vegetation types during the LGM was significantly different from that of the present day and showed a contraction in the area of rain forest and a major expansion of desert areas.

1. At the peak of the growing season, nitrogen and phosphorus concentrations increased with altitude particularly above 500 m. Leaf dry mass and area decreased with altitude, this trend being more pronounced above 500 m. The total amount of nitrogen per leaf, specific leaf area (SLA) and potassium concentration did not change with altitude. δ 13 C increased linearly with altitude. 2. Nitrogen, phosphorus and chlorophyll concentrations decreased throughout the growing season from a maximum in May; the decline at the end of the growing season was most rapid at high altitude. δ 13 C also decreased with time but uniformly at all altitudes

ABSTRACT In two experiments, winter wheat ( Triticum aestivum cv. Cerco) was grown in 350 (ambient) and 700 μmol mol ‐1 (elevated) atmospheric CO 2 concentrations. In the first experiment, plants were grown at five levels of nitrogen fertilization, and in the second experiment, plants were grown at three levels of water supply. All plants were infected with powdery mildew, caused by the fungus Erysiphe graminis. Plants grown in elevated atmospheric CO 2 concentrations had significantly reduced % shoot nitrogen contents and significantly increased % shoot water contents. At elevated atmospheric CO 2 concentrations, where plant nitrogen content was significantly reduced, the severity of mildew infection was significantly reduced, and where host water content was significantly increased, the severity of mildew infection was significantly increased. In a moderate water supply treatment, the plants grown in elevated atmospheric CO 2 concentrations had significantly reduced nitrogen contents (9·9%) and significantly increased water content (4%), the amount of mildew infection was unchanged. The severity of mildew infection appeared to be more sensitive to host water content than to host nitrogen content.

(1) Cirsium palustre, Galeobdolon luteum and Sanicula europaea were used in factorial experiments to investigate the effects of two features of vegetational shade: shade density, measured as the percentage transmission of photosynthetically active radiation (PAR), and shade type, measured as the ratio of red to far-red radiation (R/FR ratio). Neutral shade has an unaltered R/FR ratio, filtered shade a low R/FR ratio as under a deciduous tree canopy in summer. (2) The growth of all species was reduced in shade but not proportionately to shade density, partly because of compensatory increases in specific leaf area. Shade type had little or no effect. Plants died under 1 % PAR: Cirsium quickly, Galeobdolon more slowly and Sanicula most slowly of all, but in all cases more rapidly in filtered than in neutral shade. All grew well at 20% PAR and above. (3) Cirsium leaves and Sanicula petioles were longer the less dense the shade and tended to be longer in filtered shade. The lengths of Galeobdolon internodes and petioles were greater in denser shade and in filtered shade. (4) The flowering of Galeobdolon was reduced in filtered shade as well as in dense shade and independently of plant size. The flowering of Sanicula was not affected by shade type but was related to shade density and plant size. (5) Herbaceous woodland plants respond to filtered shade although increased height growth to overtop the shading plants would not be appropriate. Leaf display responses and increases in leaf and petiole lengths help to optimize PAR interception among the ground vegetation.

The physiological responses of plants to elevated CO2 have not been incorporated into most models of ecosystem function under changed climate. These responses are now well documented, and recent work demonstrates that they can be readily included in ecosystem models. Simulations show that the effects of elevated CO2 levels on transpiration and gas exchange will increase the sensitivity of community structure (particularly of forests) to climate change.

We model plant species diversity globally by country to show that future plant diversity capacity has a strong dependence on changing climate and carbon dioxide concentration. CO2 increase, through its impact on net primary production and warming is predicted to increase regional diversity capacity, while warming with constant CO2 leads to decreases in diversity capacity. Increased CO2 concentrations are unlikely to counter projected extinctions of endemic species, shown in earlier studies to be more strongly dependent on changing land use patterns than climate per se. Model predictions were tested against (1) contemporary observations of tree species diversity in different biomes, (2) an independent global map of contemporary species diversity and (3) time sequences of plant naturalisation for different locations. Good agreements between model, observations and naturalisation patterns support the suggestion that future diversity capacity increases are likely to be filled from a 'cosmopolitan weed pool' for which migration appears to be an insignificant barrier.

Atmospheric temperature is a key factor in determining the distribution of a plant species. Alongside this, plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. We investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes associated with exposure to cold temperatures. Seeds of A. petraea were obtained from populations along a latitudinal gradient, namely Wales, Sweden and Iceland and grown in a controlled cabinet environment. Mannose, glucose, fructose, sucrose and raffinose concentrations were different between cold treatments and populations, especially in the Welsh population, but polyhydric alcohol concentrations were not. The free amino acid compositions were population specific, with fold differences in most amino acids, especially in the Icelandic populations, with gross changes in amino acids, particularly those associated with glutamine metabolism. Metabolic fingerprints and profiles were obtained. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic characteristic phenotypes for each population and temperature. It is suggested that amino acids and carbohydrates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations at different atmospheric temperatures. These findings show that there is significant natural variation in cold metabolism among populations of A. l. petraea which may signify plant adaptation to local climates.

Range margins are spatially complex, with environmental, genetic and phenotypic variations occurring across a range of spatial scales. We examine variation in temperature, genes and metabolomic profiles within and between populations of the subalpine perennial plant Arabidopsis lyrata ssp. petraea from across its northwest European range. Our surveys cover a gradient of fragmentation from largely continuous populations in Iceland, through more fragmented Scandinavian populations, to increasingly widely scattered populations at the range margin in Scotland, Wales and Ireland. Temperature regimes vary substantially within some populations, but within-population variation represents a larger fraction of genetic and especially metabolomic variances. Both physical distance and temperature differences between sites are found to be associated with genetic profiles, but not metabolomic profiles, and no relationship was found between genetic and metabolomic population structures in any region. Genetic similarity between plants within populations is the highest in the fragmented populations at the range margin, but differentiation across space is the highest there as well, suggesting that regional patterns of genetic diversity may be scale dependent.

New PhytologistVolume 177, Issue 2 p. 380-388 Free Access Population-specific metabolic phenotypes of Arabidopsis lyrata ssp. petraea Matthew P. Davey, Matthew P. Davey Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorMike M. Burrell, Mike M. Burrell Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorF. Ian Woodward, F. Ian Woodward Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorW. Paul Quick, W. Paul Quick Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this author Matthew P. Davey, Matthew P. Davey Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorMike M. Burrell, Mike M. Burrell Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorF. Ian Woodward, F. Ian Woodward Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this authorW. Paul Quick, W. Paul Quick Animal and Plant Sciences, Western Bank, University of Sheffield, Sheffield, UKSearch for more papers by this author First published: 19 November 2007 https://doi.org/10.1111/j.1469-8137.2007.02282.xCitations: 45 Author for correspondence:M. P. DaveyTel: +1 44 (0)114 2224649Fax: +1 44 (0)114 2220002Email: m.davey@sheffield.ac.uk AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Summary • Plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. Here, it was investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes within the plant foliage. • Seeds of A. petraea were obtained from populations along a latitudinal gradient (49–64˚N), namely Germany, Wales, Sweden and Iceland and grown in a controlled cabinet environment. Targeted metabolic profiles and fingerprints were obtained at the same initial developmental stage. • The free amino acid compositions were population specific, with fold differences in arginine, aspartic acid, asparagines, glycine, phenylalanine, alanine, threonine, histidine, serine and gamma-aminobutyric acid (GABA) concentrations. Sucrose, mannose and fructose concentrations were also different between populations but polyhydric alcohol concentrations were not. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic phenotypes for each population. It is suggested that glucosinolates were responsible for discriminating populations within the PCA. • Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations. These findings show that there is significant natural variation in metabolism among populations of A. petraea. Introduction Genetic differentiation between small marginal and isolated plant populations could be caused by founder effects, random genetic drift or genuine adaptation to the local environment (Mandák et al., 2005). Any adaptation to the local environment should result in plant traits that are relevant to the abiotic and biotic conditions of the plants realized niche (Hoffmann, 2005). One technique to investigate gene function and the natural variation of genes in populations is by analysing the formation and concentration of different metabolic products, all of which are controlled by both genetic and environmental factors (Hall, 2005). Metabolic fingerprinting and profiling is an emerging technology and is currently being used for environmental genomics research to identify ecologically important genes and traits (Mitchell-Olds, 2001). An example of the ecological application of environmental metabolomics is the study of the distribution of a European plant species, Arabidopsis lyrata ssp. petraea (hereafter A. petraea). This self-incompatible species occurs in small geographically isolated populations across latitudinal gradient, namely Wales, Scotland, Germany, Norway, Sweden and Iceland, usually growing on rocky or stony cliffs and shores (Jonsell et al., 1995, http://www.petraea.shef.ac.uk). This is in direct contrast to the closely related model species Arabidopsis thaliana (Mitchell-Olds, 2001; Clauss & Koch, 2006), which is broadly distributed across a wide range of habitats, including open habitats. The distribution of A. petraea is currently hypothesized to be a mix of postglacial colonization and glacial relicts of the last ice age (Pamilo & Savolainen, 1999; Clauss & Mitchell-Olds, 2006). It is not clear whether the genetic differentiation between these populations results from adaptation to their local environment or from random factors such as genetic drift. As genetic differences between A. petraea populations have been reported (Jonsell et al., 1995; Gaudeul et al., 2007), any distinct metabolite and growth phenotypes between populations are likely to be a direct consequence of the differences in the genome (Fiehn et al., 2000; Keurentjes et al., 2006). We investigated whether inherent differences among populations of A. petraea would be expressed as distinct metabolic phenotypes within the plant foliage. Therefore, A. petraea selected from populations along a latitudinal gradient were subjected to a controlled environment and the metabolic profiles and fingerprints at the same initial developmental stage were measured. Materials and Methods All method descriptions comply with the Metabolomics Standards Initiative (MSI) on reporting metabolomics experiments of an environmental and plant context (Nikolau et al., 2006; Morrison et al., 2007; http://msi-workgroups.sourceforge.net/bio-metadata/). Growth Seeds of A. lyrata (L.) ssp. petraea were collected from populations in Iceland, Sweden and Wales. The Swedish seeds were collected from two sites within close proximity to each other but with different growth substrates, one from a cobbled beach and the other from a flat rock beach, to test for metabolic differences on a local scale. Seeds from Germany were obtained from original maternal plants from the field that were planted in a common garden (Clauss & Mitchell-Olds, 2006). All seeds were presumed half-sibships from the maternal plants. Arabidopsis thaliana Columbia-0 provided a comparative control species (Lehle seeds, Tucson, AZ, USA). The number of seeds sown for each country, site and maternal parent plant are presented in Table 1. Only seeds of A. l. petraea from Germany were from bulked parent plants. Seeds were sown in Levington M3 compost within individual seed trays covered with an incubator lid (16.5 × 9.5 × 4.5 cm). Trays were placed inside one of two controlled-environment growth cabinets (Conviron Controlled Environments Limited, Winnipeg, Canada). All cabinets were set to equal conditions within a 1.5 m2 growth area with a 12 h day: 12 h night cycle; 20˚C day : 10˚C night; 50% humidity, atmospheric CO2 concentration was c. 400 ppm CO2 and photosynthetically active radiation 250 µmol m−2 s−1. The seedlings were transferred to larger plant pots (9 × 7 cm) (one plant per pot), containing Levington M3 compost, when the cotyledons were fully expanded. Eight plant pots were placed into seed trays, with each seed tray containing a random assignment of populations, and placed into one of the two growth cabinets. Each growth cabinet had an equal amount of plants per population. Plants were watered from the base of the pot when required with reverse osmosis (RO) water. No additional nutrients were added to the soil or water. Table 1. Origin of seeds and germination success for each population of Arabidopsis lyrata ssp. petraea Country Region/site Latitude (min/max) Longitude (min./max.) Altitude (m above sea level) Seeds sown (n) % Germinated Iceland Langjokull 64˚53′705″N 19˚77′681″W 430 23 87 Iceland Langjokull 64˚53′705″N 19˚77′681″W 430 8 75 Sweden Olnskoldsvik – cobble 62˚52′N 18˚24′E 3 25 64 Sweden Olnskoldsvik – flat rock 62˚52′N 18˚24′E 3 14 79 Wales Yr Wyddfa (Snowdon) 53˚05′00″N 04˚03′42″W 770 11 45 Wales Yr Wyddfa (Snowdon) 53˚05′00″N 04˚03′42″W 770 8 100 Wales Yr Wyddfa (Snowdon) 53˚05′00″N 04˚03′42″W 770 6 17 Wales Yr Wyddfa (Snowdon) 53˚05′00″N 04˚03′42″W 770 5 100 Germany Plech (Dornberg)1 49˚37′N 11˚30′E 478 26 69 Germany Plech (Dornberg)1 49˚37′N 11˚30′E 478 17 47 Germination success of field collected seeds of Arabidopsis lyrata ssp. petraea. Multiple country entries indicates same site but seeds from a different maternal parent. 1 Clauss and Mitchell-Olds (2006). The leaf number of each plant was recorded in accordance with Boyes et al. (2001) A. thaliana growth and development scale. When the plants developed 10–11 leaves, 1.10 Boyes stage, the length of the longest leaf was recorded to the nearest millimetre. After 6 h into the daylight period the foliage was excised at soil level with a razor blade. The foliage was immediately weighed (mg) before being placed into a prelabelled aluminium foil wrapper and immersed in liquid nitrogen. Samples were stored at –80˚C. Metabolite extraction Frozen foliage from individual plant samples was homogenized to a fine powder under liquid nitrogen with a chilled pestle and mortar. A subsample was quickly transferred to a preweighed chilled 2 ml plastic Eppendorf tube using a spatula precooled in liquid nitrogen, and weighed to approx. 100 mg. Immediately, 2 ml of chilled (–20˚C) solvent (MeOH–CHCL3–H2O, 2.5 : 1 : 1) was added to the tube, vortexed, and left in ice with occasional shaking. After 30 min, tubes were centrifuged (Eppendorf 5415R centrifuge, 16 110 g, 2 min, 4˚C). The supernatant was removed and placed in a 5 ml prechilled vial on ice. The remaining pellet was re-extracted with 1 ml chilled (–20˚C) MeOH–CHCL3, 1 : 1 for 30 min. After centrifuging as described earlier, the supernatants were combined in the 5 ml tube. The organic CHCl3 phase was separated from the aqueous MeOH–H2O phase by adding 500 µl chilled H2O. The volume of solvent used for each extraction was amended according to the weighed tissue weight. The extracts were stored –80˚C before analysis. The soluble, free carbohydrate, polyhydric alcohol and amino acid concentrations were measured because the regulation of these compounds is known to be affected by abiotic factors (Smirnoff, 1998; Stitt & Hurry, 2002; Hannah et al., 2006). The global metabolic phenotype of the populations was also examined by metabolite fingerprinting using direct injection mass spectrometry (Overy et al., 2005). Amino acids A 20 µl extract (aqueous phase) or 0.2 : 1.8 µl sample–MeOH + H2O for the detection of glutamine and glycine was added to 200 µl of borate buffer (0.15% boric acid; pH 10). Amino acids were then derivatized with 30 µl ortho-phthaldialdehyde (OPA) containing 2 µl mercaptoethanol and shaken for exactly 50 s. At 60 s, the mixture was injected into a Perkin Elmer (Boston, MA, USA) Series 4 high-pressure liquid chromatography (HPLC) connected to a fluorescence detector (Perkin Elmer LS-1) with an excitation wavelength of 340 nm and an emission wavelength of 455 nm, sensitivity 770. Samples were resolved on a Luna C8 column (250 × 4.6 mm; Phenomenex, Torrance, CA, USA) using methanol (solvent A) and 1.5% tetrahydrofuran in aqueous 200 mm sodium acetate pH 5.9 (solvent B) with a gradient of increasing A (initial A : B 25 : 75 (v : v); 2 min at 25 : 75; 16 min at 45 : 70; 32 min at 60 : 40; 44 min at 60 : 40; 46 min at 90 : 10; 55 min at 90 : 10; 60 min at 25 : 75) at a flow rate of 1.4 ml min−1. Amino acids were identified and quantified by cochromatography with 19 amino acid standards (approx. 2–3 µg ml−1). Carbohydrates A 750 µl aliquot of extract (aqueous phase) was added to a 1.5 ml glass analysis vial and reduced to dryness overnight in a 40˚C vacuum drier (Savant-speed vac plus SC210A; Farmingdale, NY, USA). Phenyl α-d glucopyranoside (10 µl 3 mg ml−1) was added to each sample as an internal standard. Samples were then dissolved in 850 µl N-anhydrous pyridine and 150 µl N-trimethylsilylimidazole and placed in a water at 70˚C for 30 min. Samples were cooled to room temperature and sequentially injected into a ZB1 Phenomenex gas chromatography column 30 m × 0.5 mm × 0.2 µm (Varian 3500 Capillary GC, Palo Alto, CA, USA) under the following conditions: hydrogen carrier gas, 40 cm s−1; initial column temperature 120˚C; hold time 2 min; final temperature 350˚C; ramp 7˚C min−1; hold time 10 min; flame ionization detector, 400˚C; injection temp 270˚C; injection volume 1 µl split ratio 50 : 1. Carbohydrates were identified and quantified by cochromatography with 17 carbohydrate/polyhydric alcohol standards (approx. 3 µg ml−1). Metabolite fingerprinting – direct injection mass spectrometry Aqueous and organic phases of the extract were directly injected into a LCT mass spectrometer (Waters Ltd, Manchester, UK) using a MassLynx V.4.0 data system in negative and positive ion mode (Dunn et al., 2005). Instrument conditions for the negative ion mode are described in Overy et al. (2005) with the following changes: extraction cone V, 1.0; scan time, 0.95 s; interscan delay, 0.1 s; cycle time, 0.6 s. Instrument conditions for the positive ion mode were the same as negative ion mode apart from: resolution, 6000; capillary voltage, 3000 V; extraction cone, 8.0 V. Source and desolvation temperatures were maintained at 120˚C and 150˚C, respectively, with a desolvation gas flow of 405 l h−1. Samples were run in triplicate (3 × 3 min per sample) to allow for instrument error. Metabolite fingerprinting – chemometrics Raw centroid m/z values from the triplicate analytical runs were combined into 0.2 mass unit 'bins' using an inhouse program based on binning procedures in Overy et al. (2005). Binned m/z and total ion count values from the aqueous and organic phases, analysed in both negative and positive ion mode on the mass spectrometer, were explored by principal component analysis (PCA) using Simca-P V.11.0 (Umetrics, Umea, Sweden) using Pareto Scaled 0.2 Da binned masses (m/z) as the primary variable and populations as the observation variable (van den Berg et al., 2006; Trygg et al., 2007). To statistically identify m/z values which discriminate between populations on principal component axes, Pareto scaled datasets were transposed so m/z values were the observation variable. Any m/z values that were above the critical value in the 'distance of the observation value to the model plane' test (DModX) and that were outside the Hotelling T2 ellipse were considered outliers and hence likely m/z values in separating populations. Score contribution plots of these m/z values highlighted the contribution that each value had on separating each biological sample. The score contribution values reflect the total ion count, hence abundance, of that m/z value within the mass spectrometer. These m/z values were searched within our inhouse mass search program (Compound Identification by Molecular Mass, CIMMS); KEGG http://www.genome.jp/kegg/; Aracyt http://metacyc.org/and the Dictionary of Natural Products http://www.chemnetbase.com/for putative compound identification. A Univariate General Linear Model analysis of variance (anova) followed by a Tukeys post-hoc test for multiple comparisons was used to test for significant differences in growth, amino acid and carbohydrate composition between populations using SPSS v12.0.1 (Chicago, IL, USA). Results Growth Germination success of the field collected A. l. petraea seeds ranged considerably between populations, with 81% for the population from Iceland, 71% for Sweden, 58% for Germany and 54% for Wales (Table 1). Seeds took approx. 36 d reach the 10–11 mature leaf number (Boyes stage 1.10, 1.11; Boyes et al., 2001). At this stage, the Icelandic and Swedish populations had significantly longer leaves than the Welsh and German populations (P = 0.05) (Table 2). Table 2. Basic plant growth characteristics for selected populations of Arabidopsis lyrata ssp. petraea established within controlled cabinet conditions Iceland Sweden Cobble Sweden Rock Wales Germany Time to 10–11 leaves (d) 35 (1) 35 (1) 37 (1) 37 (1) 37 (1) Length of longest leaf (mm) 38 (1) 44 (2) 43 (3) 24 (3) 30 (1) Data are mean ± (SE). Free amino acids The concentration of free amino acids ranged from 0.02 µmol phenylalanine g−1 FW in the Swedish Rock population to 17.74 µmol glycine g−1 FW in the Swedish cobble population. Serine and glutamate biosynthetic families had the highest concentrations of individual amino acids. There were some significant differences between populations. Table 3 details univariate results but briefly comparing the highest and lowest values for each compound: Iceland had higher concentrations of arginine (c. 3.5 fold), aspartic acid (c. 2 fold) and asparagine (c. 0.5 fold); Sweden Cobble had higher concentrations of glycine (c. 3 fold), phenylalanine (c. 3.5 fold), alanine (c. 3 fold) and threonine (c. 6 fold); Wales had higher concentrations of histidine (c. 2 fold); Germany had higher concentrations of serine (c. 2 fold); and Col-0 had higher concentrations of gamma-aminobutyric acid (GABA; c. 4 fold). There were no significant population differences for tryptophan, valine, leucine, glutamic acid, glutamine, methionine, lysine and isoleucine or for the total amino acid pool. Table 3. Concentrations of free amino acids in populations of Arabidopsis lyrata ssp. petraea and Arabidopsis thaliana (Columbia-0) Biosynthetic family (origin) Mean (µmol amino acid g−1 FW) Metabolite Iceland Sweden cobble Sweden rock Wales Germany Col-0 Serine (glycolysis) Serine 3.00 (0.65) 2.42 (0.19) 3.11 (0.55) 2.55 (0.30) 3.39 (0.58) a 1.42 (0.12) b* Glycine 13.13 (3.91) 17.47 (2.91) a 14.31 (1.68) 4.47 (0.92) b* 10.68 (1.71) 5.20 (0.61) b* Aromatics (glycolysis) Tryptophan 0.06 (0.02) 0.11 (0.02) 0.10 (0.02) 0.09 (0.02) 0.11 (0.01) 0.07 (0.02) Phenylalanine 0.03 (0.01) b* 0.09 (0.02) a 0.02 (0.01) b* 0.03 (0.01) 0.06 (0.01) 0.07 (0.01) Histidine (PPP) Histidine 0.41 (0.06) 0.23 (0.02) b** 0.22 (0.03) b** 0.57 (0.09) a 0.33 (0.04) b* 0.28 (0.03) b** Pyruvate (glycolysis) Alanine 1.64 (0.36) 2.23 (0.37) a 1.51 (0.12) 0.77 (0.06) b* 1.16 (0.12) 1.12 (0.07) b* Valine 0.36 (0.09) 0.31 (0.06) 0.38 (0.03) 0.31 (0.04) 0.30 (0.03) 0.22 (0.02) Leucine 0.08 (0.02) 0.07 (0.02) 0.08 (0.01) 0.08 (0.01) 0.09 (0.01) 0.11 (0.01) Glutamate (citric acid cycle) Glutamic acid 3.24 (0.59) 2.28 (0.12) 1.80 (0.14) 3.05 (0.33) 3.09 (0.21) 2.71 (0.15) Glutamine 11.36 (1.19) 9.41 (1.47) 12.94 (2.03) 8.17 (0.68) 7.80 (0.92) 8.28 (0.96) Arginine 1.46 (0.31) a 0.50 (0.03) b** 0.53 (0.05) b* 0.38 (0.06) b*** 0.56 (0.09) b** 0.39 (0.03) b*** GABA 0.08 (0.01) b*** 0.09 (0.03) b** 0.17 (0.03) 0.07 (0.01) b*** 0.08 (0.01) b*** 0.27 (0.05) a Aspartate (citric acid cycle) Aspartic acid 0.81 (0.17) a 0.39 (0.04) 0.39 (0.04) b* 0.56 (0.06) 0.57 (0.05) 0.50 (0.03) Asparagine 1.06 (0.15) a 0.67 (0.05) 0.69 (0.09) 0.86 (0.11) 0.62 (0.07) b* 0.79 (0.06) Methionine 0.10 (0.02) 0.13 (0.02) 0.09 (0.01) 0.11 (0.03) 0.13 (0.02) 0.13 (0.02) Lysine 0.27 (0.08) 0.26 (0.06) 0.30 (0.05) 0.19 (0.04) 0.17 (0.03) 0.31 (0.05) Threonine 0.69 (0.12) b* 2.46 (1.45) a 0.21 (0.09) b** 0.63 (0.09) 0.52 (0.09) b* 0.36 (0.03) b** Isoleucine 0.07(0.02) 0.11 (0.03) 0.10 (0.02) 0.11 (0.03) 0.10 (0.02) 0.15 (0.03) Total amino acids 35.35 (6.43) 37.87 (4.91) 34.21 (4.58) 21.09 (1.55) 27.82 (1.77) 22.38 (1.55) GABA, gamma-aminobutyric acid; PPP, pentose phosphate pathway. Data are mean (± SE). Different letters for each amino acid denote statistically significant differences between populations. * , ** **, *** , P = 0.05, P = 0.01 and P = 0.001, respectively. Carbohydrates The concentration of free carbohydrates varied from 0.01 µmol arabinose g−1 FW in Col-0–1.80 µmol fructose g−1 FW in the Swedish rock population. The highest concentrations were found in the monosaccharides, followed by disaccharides and then the trisaccharides. Concentrations of polyhydric alcohols were comparable to the saccharides. The most abundant polyhydric alcohol was inositol, the least abundant was erythritol. There were some significant differences between populations. Table 4 details univariate results but briefly comparing the highest and lowest values for each compound: Iceland had higher concentrations of sucrose (c. 3.5 fold) and Sweden Rock had higher concentrations of mannose (c. 3.5 fold) and fructose (c. 3.5 fold). There were no statistically significant population differences for all other carbohydrates. However, there were significant differences in the total monosaccharide pool and total carbohydrates and polyols between the Swedish rock population and Col-0. There was also a significant difference in the total disaccharide and trisaccharide pool between the Icelandic populations and Col-0. Table 4. Concentrations of free carbohydrates and polyhydric alcohols in populations of Arabidopsis lyrata ssp. petraea and Arabidopsis thaliana (Columbia-0) Mean (µmol g−1 FW) (SE) Metabolite Iceland Sweden cobble Sweden rock Wales Germany Col-0 Monosaccharide Arabinose 0.04 (0.03) 0.10 (0.10) 0.03 (0.01) 0.02 (0.02) 0.15 (0.11) 0.01 (0.01) Xylose 0.17 (0.05) 0.15 (0.12) 0.17 (0.05) 0.07 (0.03) 0.20 (0.09) 0.11 (0.04) Mannose 0.77 (0.16) 0.45 (0.15) 1.17 (0.27) a 0.34 (0.07) 0.45 (0.09) b* 0.31 (0.06) b** Galactose 0.24 (0.06) 0.21 (0.09) 0.39 (0.07) 0.58 (0.40) 0.50 (0.21) 0.26 (0.03) Glucose 1.02 (0.24) 0.47 (0.15) 1.50 (0.34) 0.86 (0.27) 0.62 (0.06) 0.88 (0.13) Fructose 0.94 (0.21) 0.58 (0.17) 1.80 (0.45) a 0.51 (0.14) 0.53 (0.06) b** 0.36 (0.14) b*** Disaccharide Sucrose 1.22 (0.16) a 0.39 (0.07) b* 0.66 (0.17) b* 0.34 (0.12) b* 0.48 (0.10) b** 0.53 (0.06) b** Trehalose 0.24 (0.04) 0.29 (0.20) 0.21 (0.06) 0.04 (0.04) 0.31 (0.10) 0.11 (0.04) Maltose 0.14 (0.04) 0.12 (0.08) 0.15 (0.01) 0.12 (0.03) 0.11 (0.04) 0.11 (0.02) Trisaccharide Raffinose 0.04 (0.02) 0.00 (0.00) 0.02 (0.02) 0.00 (0.00) 0.02 (0.02) 0.00 (0.00) Polyhydric alcohol Erythritol 0.09 (0.04) 0.14 (0.12) 0.05 (0.01) 0.07 (0.04) 0.19 (0.12) 0.03 (0.02) Inositol 0.81 (0.15) 0.56 (0.15) 1.26 (0.24) 0.64 (0.17) 0.77 (0.14) 0.92 (0.13) Sorbitol 0.46 (0.21) 0.11 (0.07) 0.72 (0.23) 0.74 (0.33) 0.33 (0.12) 0.48 (0.18) Mannitol 0.41 (0.10) 0.26 (0.15) 0.38 (0.13) 0.37 (0.20) 0.34 (0.10) 0.28 (0.12) Total monosaccharides 3.17 (0.72) 1.96 (0.75) 5.06 (1.11) a 2.38 (0.89) 2.45 (0.53) 1.93 (0.36) b* Total disaccharides and trisaccharides 1.64 (0.25) a 0.80 (0.24) 1.03 (0.24) 0.50 (0.16) 0.92 (0.16) 0.75 (0.07) b* Total polyols 1.76 (0.30) 1.07 (0.35) 2.41 (0.28) 1.81 (0.56) 1.63 (0.28) 1.72 (0.27) Total carbohydrates and polyols 6.57 (1.06) 3.83 (1.26) 8.50 (1.45) a 4.69 (1.52) 5.01 (0.87) 4.40 (0.52) b* Data are mean (± SE). Different letters for each compound denote statistically significant differences between populations. * , ** **, *** , P = 0.05, P = 0.01 and P = 0.001, respectively. Metabolite fingerprinting Masses detected within the aqueous phase analysed in the negative ionization mode showed clustering of A. thaliana and Swedish rock samples that were separate from German and Swedish cobble samples on principal component (PC) 1 (Fig. 1a). Welsh and Icelandic clusters were separate from the other populations on PC2. Aqueous positive masses also clustered A. thaliana and German samples away from the Swedish and Icelandic clusters on PC1 whereas PC4 separated the A. thaliana cluster from the German cluster and Swedish rock from Swedish cobble and Icelandic clusters (Fig. 1b). Three of the masses that contributed to this separation (376, 436 and 450 were putatively identified as glucosinolates (Fig. 2). Figure 1Open in figure viewerPowerPoint Score scatter plots from principal component analysis of m/z values (binned to 0.2 Da) obtained by metabolic fingerprinting of Arabidopsis lyrata ssp. petraea (populations from Iceland (I, diamonds), Sweden Rock (S.R., upward-pointing triangles), Sweden Cobble (S.C., asterisks) and Wales (W, downward-pointing triangles)) and Arabidopsis thaliana Col-0. The percent of the variation of the data explained by each component is provided in each graph. Fingerprints were obtained from direct injection mass spectrometry of (a) the aqueous phase in negative ionization, (b) aqueous phase in positive ionization, (c) organic phase in negative ionization and (d) organic phase in positive ionization. Figure 2Open in figure viewerPowerPoint Score contribution plots of m/z values [M–H+] for 376, 436 and 450 in Arabidopsis lyrata ssp. petraea (populations from Iceland, Sweden Rock and Sweden Cobble and Wales) and Arabidopsis thaliana Col-0 obtained from metabolite fingerprinting the polar aqueous phase in negative ionization mode. The scores indicate which samples of a selected m/z value deviates the most from its average m/z score in X-space, and the direction, positive or negative, of the deviation. Putative compound identification of the m/z values are 3-hydroxypropyl glucosinolate (MW: 377.045); 4-(methylsulfinyl)butyl glucosinolate (437.048) and 5-(methylsulfinyl)pentyl glucosinolate (451.064). In the organic negative phase there was slight separation of Swedish rock from other populations PC4 (Fig. 1c). There was also some separation of populations by masses detected in the positive mode (Fig. 1d) with an Icelandic cluster separating from all other populations on PC3 and a Welsh cluster which was separate from all other populations on PC4. Discussion The metabolic profiles and fingerprints were significantly different among populations of A. petraea. Such metabolic differences between populations occurred in plants of a similar developmental stage and age. The population-specific leaf sizes within our cabinet experiment are comparable to results presented in Jonsell et al. (1995). They measured leaf sizes from field obtained leaves and found that Icelandic plants had longer lamina lengths and widths than plants from Norway, Sweden and Russia. This was also in congruence with patterns of genetic and isoenzyme variation within their study populations. There were significant differences in the amino acid composition among populations (Table 3). The higher concentrations of arginine, asparagine and aspartic acid in the Icelandic population could indicate increased citric acid cycle activity. Asparagine is a major nitrogen (N) transport and storage compound, especially when carbon (C) is limited as it has a high N : C ratio (Lam et al., 1995). An increase in glycolysis activity (Table 3) is indicated in the Swedish cobble and German populations whereas a higher concentration of histidine in the Welsh population indicates increased activity in the pentose phosphate pathway. Additionally, the aromatic phenylalanine is potentially useful for a plant as the major precursor for the phenylpropanoids pathway. Although concentrations of glutamic acid and glutamine did not differ among populations, they are usually the most abundant amino acids in many higher plants and are an important N transport compound (Lam et al., 1995). Local site differences in the amino acid composition were noted for the Swedish populations. The Swedish cobble site had higher concentrations of amino acids (Table 3) derived from glycolysis, whereas the Swedish rock site had the lowest concentration of these amino acids. However, the Swedish rock site had higher concentrations of monosaccharides (Table 4) compared with the cobble site. In contrast to the free amino acid concentrations, there were relatively fewer population differences within the individual carbohydrate concentrations and no differences between the polyhydric alcohol concentrations. Mannose and fructose concentrations were higher in the Swedish rock population and sucrose concentration was significantly higher in the Icelandic population. However, when compared with Col-0, the total pool of monosaccharides was significantly greater in the Swedish rock population and the total pool of disaccharides and trisaccharides was greater in the Icelandic population. Such variation in the individual and tool pools of these compounds suggests some degree of genetic variation, either by adaptation or drift, between species and populations is present (Jonsell et al., 1995) and

SUMMARY When plants of Sedum rosea (L.) Scop, and S. telephium L. ssp. fabaria Syme are grown in competition at different altitudes it is found that the growth of the species is affected differentially. This effect is such that at low altitudes S. telephium is a larger plant than S. rosea , while the reverse is the case at high altitudes. The observed differences are caused by a marked sensitivity of the growth of S. telephium to differences in altitude, while S. rosea is very insensitive. The most probable cause of these responses would appear to be differences of climate. The influence of altitude in northern England on air temperature, saturation deficit and irradiance has been investigated in order to establish the magnitude of the differences which may cause these responses.