Jonathan A. Foley

Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

Identifying and quantifying planetary boundaries that must not be transgressed could help prevent human activities from causing unacceptable environmental change, argue Johan Rockström and colleagues.

In the coming years, continued population growth, rising incomes, increasing meat and dairy consumption and expanding biofuel use will place unprecedented demands on the world's agriculture and natural resources. Can we meet society's growing food needs while reducing agriculture's environmental harm? Here, an international team of environmental and agricultural scientists uses new geospatial data and models to identify four strategies that could double food production while reducing environmental impacts. First, halt agricultural expansion. Second, close 'yield gaps' on underperforming lands. Third, increase cropping efficiency. And finally, we need to change our diets and shift crop production away from livestock feed, bioenergy crops and other non-food applications. Increasing population and consumption are placing unprecedented demands on agriculture and natural resources. Today, approximately a billion people are chronically malnourished while our agricultural systems are concurrently degrading land, water, biodiversity and climate on a global scale. To meet the world’s future food security and sustainability needs, food production must grow substantially while, at the same time, agriculture’s environmental footprint must shrink dramatically. Here we analyse solutions to this dilemma, showing that tremendous progress could be made by halting agricultural expansion, closing ‘yield gaps’ on underperforming lands, increasing cropping efficiency, shifting diets and reducing waste. Together, these strategies could double food production while greatly reducing the environmental impacts of agriculture.

Rockström, J., W. Steffen, K. Noone, Å. Persson, F. S. Chapin, III, E. Lambin, T. M. Lenton, M. Scheffer, C. Folke, H. Schellnhuber, B. Nykvist, C. A. De Wit, T. Hughes, S. van der Leeuw, H. Rodhe, S. Sörlin, P. K. Snyder, R. Costanza, U. Svedin, M. Falkenmark, L. Karlberg, R. W. Corell, V. J. Fabry, J. Hansen, B. Walker, D. Liverman, K. Richardson, P. Crutzen, and J. Foley. 2009. Planetary boundaries:exploring the safe operating space for humanity. Ecology and Society 14(2): 32. https://doi.org/10.5751/ES-03180-140232

Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.

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.

Human activities over the last three centuries have significantly transformed the Earth's environment, primarily through the conversion of natural ecosystems to agriculture. This study presents a simple approach to derive geographically explicit changes in global croplands from 1700 to 1992. By calibrating a remotely sensed land cover classification data set against cropland inventory data, we derived a global representation of permanent croplands in 1992, at 5 min spatial resolution [Ramankutty and Foley, 1998]. To reconstruct historical croplands, we first compile an extensive database of historical cropland inventory data, at the national and subnational level, from a variety of sources. Then we use our 1992 cropland data within a simple land cover change model, along with the historical inventory data, to reconstruct global 5 min resolution data on permanent cropland areas from 1992 back to 1700. The reconstructed changes in historical croplands are consistent with the history of human settlement and patterns of economic development. By overlaying our historical cropland data set over a newly derived potential vegetation data set, we analyze our results in terms of the extent to which different natural vegetation types have been converted for agriculture. We further examine the extent to which croplands have been abandoned in different parts of the world. Our data sets could be used within global climate models and global ecosystem models to understand the impacts of land cover change on climate and on the cycling of carbon and water. Such an analysis is a crucial aid to sharpen our thinking about a sustainable future.

Global demand for agricultural products such as food, feed, and fuel is now a major driver of cropland and pasture expansion across much of the developing world. Whether these new agricultural lands replace forests, degraded forests, or grasslands greatly influences the environmental consequences of expansion. Although the general pattern is known, there still is no definitive quantification of these land-cover changes. Here we analyze the rich, pan-tropical database of classified Landsat scenes created by the Food and Agricultural Organization of the United Nations to examine pathways of agricultural expansion across the major tropical forest regions in the 1980s and 1990s and use this information to highlight the future land conversions that probably will be needed to meet mounting demand for agricultural products. Across the tropics, we find that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This study underscores the potential consequences of unabated agricultural expansion for forest conservation and carbon emissions.

Agricultural activities have dramatically altered our planet's land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite‐derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite‐derived products (Boston University's MODIS‐derived land cover product and the GLC2000 data set). Our data are presented at 5 min (∼10 km) spatial resolution in longitude by longitude, have greater accuracy than previously available, and for the first time include statistical confidence intervals on the estimates. According to the data, there were 15.0 (90% confidence range of 12.2–17.1) million km 2 of cropland (12% of the Earth's ice‐free land surface) and 28.0 (90% confidence range of 23.6–30.0) million km 2 of pasture (22%) in the year 2000.

Exploiting multiple feedstocks, under new policies and accounting rules, to balance biofuel production, food security, and greenhouse-gas reduction.

Croplands cover ∼15 million km 2 of the planet and provide the bulk of the food and fiber essential to human well‐being. Most global land cover data sets from satellites group croplands into just a few categories, thereby excluding information that is critical for answering key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information about agricultural land use practices like crop selection, yield, and fertilizer use is even more limited. Here we present land use data sets created by combining national, state, and county level census statistics with a recently updated global data set of croplands on a 5 min by 5 min (∼10 km by 10 km) latitude‐longitude grid. The resulting land use data sets depict circa the year 2000 the area (harvested) and yield of 175 distinct crops of the world. We aggregate these individual crop maps to produce novel maps of 11 major crop groups, crop net primary production, and four physiologically based crop types: annuals/perennials, herbaceous/shrubs/trees, C 3 /C 4 , and leguminous/nonleguminous.

Here we present a new terrestrial biosphere model (the Integrated Biosphere Simulator ‐ IBIS) which demonstrates how land surface biophysics, terrestrial carbon fluxes, and global vegetation dynamics can be represented in a single, physically consistent modeling framework. In order to integrate a wide range of biophysical, physiological, and ecological processes, the model is designed around a hierarchical, modular structure and uses a common state description throughout. First, a coupled simulation of the surface water, energy, and carbon fluxes is performed on hourly timesteps and is integrated over the year to estimate the annual water and carbon balance. Next, the annual carbon balance is used to predict changes in the leaf area index and biomass for each of nine plant functional types, which compete for light and water using different ecological strategies. The resulting patterns of annual evapotranspiration, runoff, and net primary productivity are in good agreement with observations. In addition, the model simulates patterns of vegetation dynamics that qualitatively agree with features of the natural process of secondary succession. Comparison of the model's inferred near‐equilibrium vegetation categories with a potential natural vegetation map shows a fair degree of agreement. This integrated modeling framework provides a means of simulating both rapid biophysical processes and long‐term ecosystem dynamics that can be directly incorporated within atmospheric models.

Reducing carbon emissions from deforestation and degradation in developing countries is of central importance in efforts to combat climate change. Key scientific challenges must be addressed to prevent any policy roadblocks. Foremost among the challenges is quantifying nations’ carbon emissions from deforestation and forest degradation, which requires information on forest clearing and carbon storage. Here we review a range of methods available to estimate national-level forest carbon stocks in developing countries. While there are no practical methods to directly measure all forest carbon stocks across a country, both ground-based and remote-sensing measurements of forest attributes can be converted into estimates of national carbon stocks using allometric relationships. Here we synthesize, map and update prominent forest biomass carbon databases to create the first complete set of national-level forest carbon stock estimates. These forest carbon estimates expand on the default values recommended by the Intergovernmental Panel on Climate Change’s National Greenhouse Gas Inventory Guidelines and provide a range of globally consistent estimates.

In the coming decades, continued population growth, rising meat and dairy consumption and expanding biofuel use will dramatically increase the pressure on global agriculture. Even as we face these future burdens, there have been scattered reports of yield stagnation in the world's major cereal crops, including maize, rice and wheat. Here we study data from ∼2.5 million census observations across the globe extending over the period 1961-2008. We examined the trends in crop yields for four key global crops: maize, rice, wheat and soybeans. Although yields continue to increase in many areas, we find that across 24-39% of maize-, rice-, wheat- and soybean-growing areas, yields either never improve, stagnate or collapse. This result underscores the challenge of meeting increasing global agricultural demands. New investments in underperforming regions, as well as strategies to continue increasing yields in the high-performing areas, are required.

Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts of critical ecosystem services requires a process that engages scientists and decision-makers. Interdisciplinary linkages are necessary because of the climate and societal controls on ecosystems, the feedbacks involving social change, and the decision-making relevance of forecasts.

The concurrent effects of increasing atmospheric CO 2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process‐based terrestrial biosphere models. Over the long‐term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long‐term analysis based on ice core and atmospheric CO 2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO 2 . During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr −1 , which is within the uncertainty of analysis based on CO 2 and O 2 budgets. Three of the four models indicated (in accordance with O 2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long‐term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO 2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)‐scale variability in the atmospheric CO 2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO 2 suggested that the observed trend may be a consequence of CO 2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process‐based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand‐level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO 2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system.

Conversion of land to grow crops, raise animals, obtain timber, and build cities is one of the foundations of human civilization. While land use provides these essential ecosystem goods, it alters a range of other ecosystem functions, such as the provisioning of freshwater, regulation of climate and biogeochemical cycles, and maintenance of soil fertility. It also alters habitat for biological diversity. Balancing the inherent trade-offs between satisfying immediate human needs and maintaining other ecosystem functions requires quantitative knowledge about ecosystem responses to land use. These responses vary according to the type of land-use change and the ecological setting, and have local, short-term as well as global, long-term effects. Land-use decisions ultimately weigh the need to satisfy human demands and the unintended ecosystem responses based on societal values, but ecological knowledge can provide a basis for assessing the trade-offs.

While a new class of Dynamic Global Ecosystem Models (DGEMs) has emerged in the past few years as an important tool for describing global biogeochemical cycles and atmosphere‐biosphere interactions, these models are still largely untested. Here we analyze the behavior of a new DGEM and compare the results to global‐scale observations of water balance, carbon balance, and vegetation structure. In this study, we use version 2 of the Integrated Biosphere Simulator (IBIS), which includes several major improvements and additions to the prototype model developed by Foley et al. [1996]. IBIS is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO 2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). In order to test the performance of the model, we have assembled a wide range of continental and global‐scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO 2 flux. Using these field data and model results for the contemporary biosphere (1965–1994), our evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO 2 flux agree reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results.

Humans have transformed the surface of the planet through agricultural activities, and today, ∼12% of the land surface is used for cultivation and another 22% is used for pastures and rangelands. In this paper, we have synthesized satellite‐derived land cover data and agricultural census data to produce global data sets of the distribution of 18 major crops across the world. The resulting data are representative of the early 1990s, have a spatial resolution of 5 min. (∼10 km), and describe the fraction of a grid cell occupied by each of the 18 crops. The global crop data are consistent with our knowledge of agricultural geography, and compares favorably to another existing data set that partially overlaps with our product. We have also analyzed how different crops are grown in combination to form major crop belts throughout the world. Further, we analyzed the patterns of crop diversification across the world. While these data are not sufficiently accurate at local scales, they can be used to analyze crop geography in a regional‐to‐global context. They can also be used to understand the global patterns of farming systems, in analyses of food security, and within global ecosystem and climate models to understand the environmental consequences of cultivation.

Abstract Aim This study makes quantitative global estimates of land suitability for cultivation based on climate and soil constraints. It evaluates further the sensitivity of croplands to any possible changes in climate and atmospheric CO 2 concentrations. Location The location is global, geographically explicit. Methods The methods used are spatial data synthesis and analysis and numerical modelling. Results There is a cropland ‘reserve’ of 120%, mainly in tropical South America and Africa. Our climate sensitivity analysis indicates that the southern provinces of Canada, north‐western and north‐central states of the United States, northern Europe, southern Former Soviet Union and the Manchurian plains of China are most sensitive to changes in temperature. The Great Plains region of the United States and north‐eastern China are most sensitive to changes in precipitation. The regions that are sensitive to precipitation change are also sensitive to changes in CO 2 , but the magnitude is small compared to the influence of direct climate change. We estimate that climate change, as simulated by global climate models, will expand cropland suitability by an additional 16%, mainly in the Northern Hemisphere high latitudes. However, the tropics (mainly Africa, northern South America, Mexico and Central America and Oceania) will experience a small decrease in suitability due to climate change. Main conclusions There is a large reserve of cultivable croplands, mainly in tropical South America and Africa. However, much of this land is under valuable forests or in protected areas. Furthermore, the tropical soils could potentially lose fertility very rapidly once the forest cover is removed. Regions that lie at the margins of temperature or precipitation limitation to cultivation are most sensitive to changes in climate and atmospheric CO 2 concentration. It is anticipated that climate change will result in an increase in cropland suitability in the Northern Hemisphere high latitudes (mainly in developed nations), while the tropics will lose suitability (mainly in developing nations).

The Amazon Basin is one of the world's most important bioregions, harboring a rich array of plant and animal species and offering a wealth of goods and services to society. For years, ecological science has shown how large-scale forest clearings cause declines in biodiversity and the availability of forest products. Yet some important changes in the rainforests, and in the ecosystem services they provide, have been underappreciated until recently. Emerging research indicates that land use in the Amazon goes far beyond clearing large areas of forest; selective logging and other canopy damage is much more pervasive than once believed. Deforestation causes collateral damage to the surrounding forests – through enhanced drying of the forest floor, increased frequency of fires, and lowered productivity. The loss of healthy forests can degrade key ecosystem services, such as carbon storage in biomass and soils, the regulation of water balance and river flow, the modulation of regional climate patterns, and the amelioration of infectious diseases. We review these newly revealed changes in the Amazon rainforests and the ecosystem services that they provide.

Worldwide demand for crops is increasing rapidly due to global population growth, increased biofuel production, and changing dietary preferences. Meeting these growing demands will be a substantial challenge that will tax the capability of our food system and prompt calls to dramatically boost global crop production. However, to increase food availability, we may also consider how the world's crops are allocated to different uses and whether it is possible to feed more people with current levels of crop production. Of particular interest are the uses of crops as animal feed and as biofuel feedstocks. Currently, 36% of the calories produced by the world's crops are being used for animal feed, and only 12% of those feed calories ultimately contribute to the human diet (as meat and other animal products). Additionally, human-edible calories used for biofuel production increased fourfold between the years 2000 and 2010, from 1% to 4%, representing a net reduction of available food globally. In this study, we re-examine agricultural productivity, going from using the standard definition of yield (in tonnes per hectare, or similar units) to using the number of people actually fed per hectare of cropland. We find that, given the current mix of crop uses, growing food exclusively for direct human consumption could, in principle, increase available food calories by as much as 70%, which could feed an additional 4 billion people (more than the projected 2–3 billion people arriving through population growth). Even small shifts in our allocation of crops to animal feed and biofuels could significantly increase global food availability, and could be an instrumental tool in meeting the challenges of ensuring global food security.

ABSTRACT Aim To assemble a data set of global crop planting and harvesting dates for 19 major crops, explore spatial relationships between planting date and climate for two of them, and compare our analysis with a review of the literature on factors that drive decisions on planting dates. Location Global. Methods We digitized and georeferenced existing data on crop planting and harvesting dates from six sources. We then examined relationships between planting dates and temperature, precipitation and potential evapotranspiration using 30‐year average climatologies from the Climatic Research Unit, University of East Anglia (CRU CL 2.0). Results We present global planting date patterns for maize, spring wheat and winter wheat (our full, publicly available data set contains planting and harvesting dates for 19 major crops). Maize planting in the northern mid‐latitudes generally occurs in April and May. Daily average air temperatures are usually c . 12–17 °C at the time of maize planting in these regions, although soil moisture often determines planting date more directly than does temperature. Maize planting dates vary more widely in tropical regions. Spring wheat is usually planted at cooler temperatures than maize, between c . 8 and 14 °C in temperate regions. Winter wheat is generally planted in September and October in the northern mid‐latitudes. Main conclusions In temperate regions, spatial patterns of maize and spring wheat planting dates can be predicted reasonably well by assuming a fixed temperature at planting. However, planting dates in lower latitudes and planting dates of winter wheat are more difficult to predict from climate alone. In part this is because planting dates may be chosen to ensure a favourable climate during a critical growth stage, such as flowering, rather than to ensure an optimal climate early in the crop's growth. The lack of predictability is also due to the pervasive influence of technological and socio‐economic factors on planting dates.

ABSTRACT Aim As the demands for food, feed and fuel increase in coming decades, society will be pressed to increase agricultural production – whether by increasing yields on already cultivated lands or by cultivating currently natural areas – or to change current crop consumption patterns. In this analysis, we consider where yields might be increased on existing croplands, and how crop yields are constrained by biophysical (e.g. climate) versus management factors. Location This study was conducted at the global scale. Methods Using spatial datasets, we compare yield patterns for the 18 most dominant crops within regions of similar climate. We use this comparison to evaluate the potential yield obtainable for each crop in different climates around the world. We then compare the actual yields currently being achieved for each crop with their ‘climatic potential yield’ to estimate the ‘yield gap’. Results We present spatial datasets of both the climatic potential yields and yield gap patterns for 18 crops around the year 2000. These datasets depict the regions of the world that meet their climatic potential, and highlight places where yields might potentially be raised. Most often, low yield gaps are concentrated in developed countries or in regions with relatively high‐input agriculture. Main conclusions While biophysical factors like climate are key drivers of global crop yield patterns, controlling for them demonstrates that there are still considerable ranges in yields attributable to other factors, like land management practices. With conventional practices, bringing crop yields up to their climatic potential would probably require more chemical, nutrient and water inputs. These intensive land management practices can adversely affect ecosystem goods and services, and in turn human welfare. Until society develops more sustainable high‐yielding cropping practices, the trade‐offs between increased crop productivity and social and ecological factors need to be made explicit when future food scenarios are formulated.

Biofuels from land-rich tropical countries may help displace foreign petroleum imports for many industrialized nations, providing a possible solution to the twin challenges of energy security and climate change. But concern is mounting that crop-based biofuels will increase net greenhouse gas emissions if feedstocks are produced by expanding agricultural lands. Here we quantify the 'carbon payback time' for a range of biofuel crop expansion pathways in the tropics. We use a new, geographically detailed database of crop locations and yields, along with updated vegetation and soil biomass estimates, to provide carbon payback estimates that are more regionally specific than those in previous studies. Using this cropland database, we also estimate carbon payback times under different scenarios of future crop yields, biofuel technologies, and petroleum sources. Under current conditions, the expansion of biofuels into productive tropical ecosystems will always lead to net carbon emissions for decades to centuries, while expanding into degraded or already cultivated land will provide almost immediate carbon savings. Future crop yield improvements and technology advances, coupled with unconventional petroleum supplies, will increase biofuel carbon offsets, but clearing carbon-rich land still requires several decades or more for carbon payback. No foreseeable changes in agricultural or energy technology will be able to achieve meaningful carbon benefits if crop-based biofuels are produced at the expense of tropical forests.

Human activities have shaped significantly the state of terrestrial ecosystems throughout the world. One of the most direct manifestations of human activity within the biosphere has been the conversion of natural ecosystems to croplands. In this study, we present an analysis of the geographic distribution and spatial extent of permanent croplands. This analysis represents the area in permanent croplands during the early 1990s for each grid cell on a global 5 min (∼10 km) resolution latitude‐longitude grid. To create this data set, we have combined a satellite‐derived land cover data set with a variety of national and subnational agricultural inventory data. A simple calibration algorithm was used so that the spatial land cover data were generally consistent with nonspatial agricultural inventory data. The spatial distribution of croplands represented in this analysis presents a quantitative depiction of global agricultural geography. The regions of the world known to have intense cultivation (e.g., the North American corn belt, the European wheat‐corn belt, the Ganges floodplain, and eastern China) are clearly portrayed in this analysis. It also captures the less intensely cultivated regions of the world, usually surrounding the regions mentioned above, and regions characterized by subsistence agriculture (e.g., Sahelian Africa). Data generated from this kind of analysis can be used within global climate models and global ecosystem models to assess the importance of permanent croplands on environmental processes. In particular, these data, combined with models, could help evaluate the role of changing land cover on regional climate and carbon cycling. Future efforts will need to concentrate on other land use systems, including pastures and regions of shifting cultivation. Furthermore, land use and land cover data must be extended to include an historical dimension so as to evaluate the changing state of the biosphere over time. This article contains supplementary material.

Abstract An accurate estimate of carbon fluxes associated with tropical deforestation from the last two decades is needed to balance the global carbon budget. Several studies have already estimated carbon emissions from tropical deforestation, but the estimates vary greatly and are difficult to compare due to differences in data sources, assumptions, and methodologies. In this paper, we review the different estimates and datasets, and the various challenges associated with comparing them and with accurately estimating carbon emissions from deforestation. We performed a simulation study over legal Amazonia to illustrate some of these major issues. Our analysis demonstrates the importance of considering land‐cover dynamics following deforestation, including the fluxes from reclearing of secondary vegetation, the decay of product and slash pools, and the fluxes from regrowing forest. It also suggests that accurate carbon‐flux estimates will need to consider historical land‐cover changes for at least the previous 20 years. However, this result is highly sensitive to estimates of the partitioning of cleared carbon into instantaneous burning vs. long‐timescale slash pools. We also show that carbon flux estimates based on ‘committed flux’ calculations, as used by a few studies, are not comparable with the ‘annual balance’ calculation method used by other studies.

Expanding croplands to meet the needs of a growing population, changing diets, and biofuel production comes at the cost of reduced carbon stocks in natural vegetation and soils. Here, we present a spatially explicit global analysis of tradeoffs between carbon stocks and current crop yields. The difference among regions is striking. For example, for each unit of land cleared, the tropics lose nearly two times as much carbon (∼120 tons·ha −1 vs. ∼63 tons·ha −1 ) and produce less than one-half the annual crop yield compared with temperate regions (1.71 tons·ha −1 ·y −1 vs. 3.84 tons·ha −1 ·y −1 ). Therefore, newly cleared land in the tropics releases nearly 3 tons of carbon for every 1 ton of annual crop yield compared with a similar area cleared in the temperate zone. By factoring crop yield into the analysis, we specify the tradeoff between carbon stocks and crops for all areas where crops are currently grown and thereby, substantially enhance the spatial resolution relative to previous regional estimates. Particularly in the tropics, emphasis should be placed on increasing yields on existing croplands rather than clearing new lands. Our high-resolution approach can be used to determine the net effect of local land use decisions.

Frontiers in Ecology and the EnvironmentVolume 6, Issue 6 p. 313-320 Review Changing feedbacks in the climate–biosphere system F Stuart Chapin III, Corresponding Author F Stuart Chapin III Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK*([email protected])Search for more papers by this authorJames T Randerson, James T Randerson Department of Earth System Science, University of California, Irvine, CASearch for more papers by this authorA David McGuire, A David McGuire US Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, University of Alaska Fairbanks, Fairbanks, AKSearch for more papers by this authorJonathan A Foley, Jonathan A Foley Center for Sustainability and the Global Environment, University of Wisconsin, Madison, WISearch for more papers by this authorChristopher B Field, Christopher B Field Department of Global Ecology, Carnegie Institution of Washington, Stanford, CASearch for more papers by this author F Stuart Chapin III, Corresponding Author F Stuart Chapin III Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK*([email protected])Search for more papers by this authorJames T Randerson, James T Randerson Department of Earth System Science, University of California, Irvine, CASearch for more papers by this authorA David McGuire, A David McGuire US Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, University of Alaska Fairbanks, Fairbanks, AKSearch for more papers by this authorJonathan A Foley, Jonathan A Foley Center for Sustainability and the Global Environment, University of Wisconsin, Madison, WISearch for more papers by this authorChristopher B Field, Christopher B Field Department of Global Ecology, Carnegie Institution of Washington, Stanford, CASearch for more papers by this author First published: 01 August 2008 https://doi.org/10.1890/080005Citations: 221Read 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 Abstract Ecosystems influence climate through multiple pathways, primarily by changing the energy, water, and greenhouse-gas balance of the atmosphere. Consequently, efforts to mitigate climate change through modification of one pathway, as with carbon in the Kyoto Protocol, only partially address the issue of ecosystem–climate interactions. For example, the cooling of climate that results from carbon sequestration by plants may be partially offset by reduced land albedo, which increases solar energy absorption and warms the climate. The relative importance of these effects varies with spatial scale and latitude. We suggest that consideration of multiple interactions and feedbacks could lead to novel, potentially useful climate-mitigation strategies, including greenhouse-gas reductions primarily in industrialized nations, reduced desertification in arid zones, and reduced deforestation in the tropics. Each of these strategies has additional ecological and societal benefits. Assessing the effectiveness of these strategies requires a more quantitative understanding of the interactions among feedback processes, their consequences at local and global scales, and the teleconnections that link changes occurring in different regions. Citing Literature Volume6, Issue6August 2008Pages 313-320 RelatedInformation

Irrigation consumes more water than any other human activity, and thus the challenges of water sustainability and food security are closely linked. To evaluate how water resources are used for food production, we examined global patterns of water productivity—food produced (kcal) per unit of water (l) consumed. We document considerable variability in crop water productivity globally, not only across different climatic zones but also within climatic zones. The least water productive systems are disproportionate freshwater consumers. On precipitation-limited croplands, we found that ∼40% of water consumption goes to production of just 20% of food calories. Because in many cases crop water productivity is well below optimal levels, in many cases farmers have substantial opportunities to improve water productivity. To demonstrate the potential impact of management interventions, we calculated that raising crop water productivity in precipitation-limited regions to the 20th percentile of productivity would increase annual production on rainfed cropland by enough to provide food for an estimated 110 million people, and water consumption on irrigated cropland would be reduced enough to meet the annual domestic water demands of nearly 1.4 billion people.

The world's agricultural systems face the challenge of meeting the rising demands from population growth, changing dietary preferences, and expanding biofuel use. Previous studies have put forward strategies for meeting this growing demand by increasing global crop production, either expanding the area under cultivation or intensifying the crop yields of our existing agricultural lands. However, another possible means for increasing global crop production has received less attention: increasing the frequency of global cropland harvested each year. Historically, many of the world's croplands were left fallow, or had failed harvests, each year, foregoing opportunities for delivering crop production. Furthermore, many regions, particularly in the tropics, may be capable of multiple harvests per year, often more than are harvested today.

Abstract Expansion of agricultural lands and inherent variability of climate can influence the water cycle in the Amazon basin, impacting numerous ecosystem services. However, these two influences do not work independently of each other. With two once-in-a-century-level droughts occurring in the Amazon in the past decade, it is vital to understand the feedbacks that contribute to altering the water cycle. The biogeophysical impacts of land cover change within the Amazon basin were examined under drought and pluvial conditions to investigate how land cover and drought jointly may have enhanced or diminished recent precipitation extremes by altering patterns and intensity. Using the Weather Research and Forecasting (WRF) Model coupled to the Noah land surface model, a series of April–September simulations representing drought, normal, and pluvial years were completed to assess how land cover change impacts precipitation and how these impacts change under varied rainfall regimes. Evaporative sources of water vapor that precipitate across the region were developed with a quasi-isentropic back-trajectory algorithm to delineate the extent and variability that terrestrial evaporation contributes to regional precipitation. A decrease in dry season latent heat flux and other impacts of deforestation on surface conditions were increased by drought conditions. Coupled with increases in dry season moisture recycling over the Amazon basin by ~7% during drought years, land cover change is capable of reducing precipitation and increasing the amplitude of droughts in the region.

It is generally expected that the Amazon basin will experience at least two major environmental changes during the next few decades and centuries: 1) increasing areas of forest will be converted to pasture and cropland, and 2) concentrations of atmospheric CO2 will continue to rise. In this study, the authors use the National Center for Atmospheric Research GENESIS atmospheric general circulation model, coupled to the Integrated Biosphere Simulator, to determine the combined effects of large-scale deforestation and increased CO2 concentrations (including both physiological and radiative effects) on Amazonian climate. In these simulations, deforestation decreases basin-average precipitation by 0.73 mm day−1 over the basin, as a consequence of the general reduction in vertical motion above the deforested area (although there are some small regions with increased vertical motion). The overall effect of doubled CO2 concentrations in Amazonia is an increase in basin-average precipitation of 0.28 mm day−1. The combined effect of deforestation and doubled CO2, including the interactions among the processes, is a decrease in the basin-average precipitation of 0.42 mm day−1. While the effects of deforestation and increasing CO2 concentrations on precipitation tend to counteract one another, both processes work to warm the Amazon basin. The effect of deforestation and increasing CO2 concentrations both tend to increase surface temperature, mainly because of decreases in evapotranspiration and the radiative effect of CO2. The combined effect of deforestation and doubled CO2, including the interactions among the processes, increases the basin-average temperature by roughly 3.5°C.

An integrated biosphere model (IBIS) and a hydrological routing algorithm (HYDRA) are used in conjunction with long time‐series climate data to investigate the response of the Lake Chad drainage basin of northern Africa to climate variability and water use practices over the last 43 years. The simulated discharge, lake level, and lake area of the drainage basin for the period 1953–1979 are in good agreement with the observations. For example, the correlation coefficient ( r 2 ) between the simulated and the observed level of Lake Chad for the 288 months of available observations is 0.93. Although irrigation is only a modest portion of the hydrology in the period 1953–1979; representing only 5 of the 30% decrease in simulated lake area for the decade 1966–1975, the simulated lake level and area are in better agreement with the observations when irrigation is included. For the period 1983–1994 the observed water use for irrigation increased fourfold compared to 1953–1979. A comparison of the simulated surface water area, with and without irrigation, suggests that climate variability still controls the interannual fluctuations of the water inflow but that human water use accounts for roughly 50% of the observed decrease in lake area since the 1960s and 1970s.

Numerous studies have underscored the importance of terrestrial ecosystems as an integral component of the Earth's climate system. This realization has already led to efforts to link simple equilibrium vegetation models with Atmospheric General Circulation Models through iterative coupling procedures. While these linked models have pointed to several possible climate–vegetation feedback mechanisms, they have been limited by two shortcomings: (i) they only consider the equilibrium response of vegetation to shifting climatic conditions and therefore cannot be used to explore transient interactions between climate and vegetation; and (ii) the representations of vegetation processes and land-atmosphere exchange processes are still treated by two separate models and, as a result, may contain physical or ecological inconsistencies. Here we present, as a proof concept, a more tightly integrated framework for simulating global climate and vegetation interactions. The prototype coupled model consists of the GENESIS (version 2) Atmospheric General Circulation Model and the IBIS (version 1) Dynamic Global Vegetation Model. The two models are directly coupled through a common treatment of land surface and ecophysiological processes, which is used to calculate the energy, water, carbon, and momentum fluxes between vegetation, soils, and the atmosphere. On one side of the interface, GENESIS simulates the physics and general circulation of the atmosphere. On the other side, IBIS predicts transient changes in the vegetation structure through changes in the carbon balance and competition among plants within terrestrial ecosystems. As an initial test of this modelling framework, we perform a 30 year simulation in which the coupled model is supplied with modern CO2 concentrations, observed ocean temperatures, and modern insolation. In this exploratory study, we run the GENESIS atmospheric model at relatively coarse horizontal resolution (4.5° latitude by 7.5° longitude) and IBIS at moderate resolution (2° latitude by 2° longitude). We initialize the models with globally uniform climatic conditions and the modern distribution of potential vegetation cover. While the simulation does not fully reach equilibrium by the end of the run, several general features of the coupled model behaviour emerge. We compare the results of the coupled model against the observed patterns of modern climate. The model correctly simulates the basic zonal distribution of temperature and precipitation, but several important regional biases remain. In particular, there is a significant warm bias in the high northern latitudes, and cooler than observed conditions over the Himalayas, central South America, and north-central Africa. In terms of precipitation, the model simulates drier than observed conditions in much of South America, equatorial Africa and Indonesia, with wetter than observed conditions in northern Africa and China. Comparing the model results against observed patterns of vegetation cover shows that the general placement of forests and grasslands is roughly captured by the model. In addition, the model simulates a roughly correct separation of evergreen and deciduous forests in the tropical, temperate and boreal zones. However, the general patterns of global vegetation cover are only approximately correct: there are still significant regional biases in the simulation. In particular, forest cover is not simulated correctly in large portions of central Canada and southern South America, and grasslands extend too far into northern Africa. These preliminary results demonstrate the feasibility of coupling climate models with fully dynamic representations of the terrestrial biosphere. Continued development of fully coupled climate-vegetation models will facilitate the exploration of a broad range of global change issues, including the potential role of vegetation feedbacks within the climate system, and the impact of climate variability and transient climate change on the terrestrial biosphere.

It is well known that Atlantic tropical cyclone activity varies strongly over time, and that summertime dust transport over the North Atlantic also varies from year to year, but any connection between tropical cyclone activity and atmospheric dust has been limited to a few case studies. Here we report new results that demonstrate a strong relationship between interannual variations in North Atlantic tropical cyclone activity and atmospheric dust cover as measured by satellite, for the years 1982–2005. While we cannot conclusively demonstrate a direct causal relationship, there appears to be robust link between tropical cyclone activity and dust transport over the Tropical Atlantic.

Summary 1. We present a simple algorithm for reconstructing spatially explicit historical changes in croplands. We initialize our simulation with a satellite‐derived characterization of present‐day croplands c. 1992. This data set of croplands is then used within a simple model, along with historical cropland inventory data at the national and subnational level, to reconstruct historical crop cover. We present an annual data set of cropland areas in North America between 1850 and 1992, at a spatial resolution of 5 min (≈10 km). 2. The reconstructed changes in North American crop cover are generally consistent with qualitative descriptions of change. Crop cover is initially concentrated in the eastern portions of the continent, and subsequently migrates westward into the Midwestern United States and the Prairie Provinces of Canada. We also see cropland abandonment in the eastern portions of the continent during the 20th century. The simulation, however, fails to characterize adequately the changes in crop cover in Mexico. 3. We also estimate the extent to which the different vegetation types of North America have been cleared for cultivation. We find that savannas/grasslands/steppes and forests/woodlands have undergone the most extensive conversion (1.68 and 1.40 million km 2 cleared, respectively, since 1850). We further discuss the wider implications of such large‐scale changes in land cover.

Abstract Numerous studies have underscored the importance of terrestrial ecosystems as an integral component of the Earth's climate system. This realization has already led to efforts to link simple equilibrium vegetation models with Atmospheric General Circulation Models through iterative coupling procedures. While these linked models have pointed to several possible climate–vegetation feedback mechanisms, they have been limited by two shortcomings: (i) they only consider the equilibrium response of vegetation to shifting climatic conditions and therefore cannot be used to explore transient interactions between climate and vegetation; and (ii) the representations of vegetation processes and land‐atmosphere exchange processes are still treated by two separate models and, as a result, may contain physical or ecological inconsistencies. Here we present, as a proof concept, a more tightly integrated framework for simulating global climate and vegetation interactions. The prototype coupled model consists of the GENESIS (version 2) Atmospheric General Circulation Model and the IBIS (version 1) Dynamic Global Vegetation Model. The two models are directly coupled through a common treatment of land surface and ecophysiological processes, which is used to calculate the energy, water, carbon, and momentum fluxes between vegetation, soils, and the atmosphere. On one side of the interface, GENESIS simulates the physics and general circulation of the atmosphere. On the other side, IBIS predicts transient changes in the vegetation structure through changes in the carbon balance and competition among plants within terrestrial ecosystems. As an initial test of this modelling framework, we perform a 30 year simulation in which the coupled model is supplied with modern CO 2 concentrations, observed ocean temperatures, and modern insolation. In this exploratory study, we run the GENESIS atmospheric model at relatively coarse horizontal resolution (4.5° latitude by 7.5° longitude) and IBIS at moderate resolution (2° latitude by 2° longitude). We initialize the models with globally uniform climatic conditions and the modern distribution of potential vegetation cover. While the simulation does not fully reach equilibrium by the end of the run, several general features of the coupled model behaviour emerge. We compare the results of the coupled model against the observed patterns of modern climate. The model correctly simulates the basic zonal distribution of temperature and precipitation, but several important regional biases remain. In particular, there is a significant warm bias in the high northern latitudes, and cooler than observed conditions over the Himalayas, central South America, and north‐central Africa. In terms of precipitation, the model simulates drier than observed conditions in much of South America, equatorial Africa and Indonesia, with wetter than observed conditions in northern Africa and China. Comparing the model results against observed patterns of vegetation cover shows that the general placement of forests and grasslands is roughly captured by the model. In addition, the model simulates a roughly correct separation of evergreen and deciduous forests in the tropical, temperate and boreal zones. However, the general patterns of global vegetation cover are only approximately correct: there are still significant regional biases in the simulation. In particular, forest cover is not simulated correctly in large portions of central Canada and southern South America, and grasslands extend too far into northern Africa. These preliminary results demonstrate the feasibility of coupling climate models with fully dynamic representations of the terrestrial biosphere. Continued development of fully coupled climate‐vegetation models will facilitate the exploration of a broad range of global change issues, including the potential role of vegetation feedbacks within the climate system, and the impact of climate variability and transient climate change on the terrestrial biosphere.

Numerical models of Earth's climate system must consider the atmosphere and terrestrial biosphere as a coupled system, with biogeophysical and biogeochemical processes occurring across a range of timescales. On short timescales (i.e., seconds to hours), the coupled system is dominated by the rapid biophysical and biogeochemical processes that exchange energy, water, carbon dioxide, and momentum between the atmosphere and the land surface. Intermediate-timescale (i.e., days to months) processes include changes in the store of soil moisture, changes in carbon allocation, and vegetation phenology (e.g., budburst, leaf-out, senescence, dormancy). On longer timescales (i.e., seasons, years, and decades), there can be fundamental changes in the vegetation structure itself (disturbance, land use, stand growth). In order to consider the full range of coupled atmosphere–biosphere processes, we must extend climate models to include intermediate and long-term ecological phenomena. This paper reviews early attempts at linking climate and equilibrium vegetation models through iterative coupling techniques, and some important insights gained through this procedure. We then summarize recent developments in coupling global vegetation and climate models, and some of the applications of these tools to modeling climate change. Furthermore, we discuss more recent developments in vegetation models (including a new class of models called “dynamic global vegetation models”), and how these models are incorporated with atmospheric general circulation models. Fully coupled climate–vegetation models are still in the very early stages of development. Nevertheless, these prototype models have already indicated the importance of considering vegetation cover as an interactive part of the climate system.

Abstract Lakes process terrigenous carbon. The carbon load processed by lakes may partially offset estimates made for terrestrial net ecosystem exchange ( NEE ). The balance within lakes between carbon burial and evasion to the atmosphere determines whether lakes are net sinks or net sources of atmospheric carbon. Here we develop a model to study processing of both autochthonous and allochthonous carbon sources in lakes. We run the model over gradients of dissolved organic carbon ( DOC ) and total phosphorus ( TP ) concentrations found in the Northern Highlands Lake District of Wisconsin. In our model, lakes processed between 5 and 28 g C m −2 (watershed) yr −1 derived from the watershed, which approximates one‐tenth of NEE for similar terrestrial systems without lakes. Most lakes were net heterotrophic and had carbon evasion in excess of carbon burial, making them net sources of carbon to the atmosphere. Only lakes low in DOC and moderate to high in TP were net autotrophic and net sinks of carbon from the atmosphere.

The El Niño–Southern Oscillation (ENSO) phenomenon is one of the dominant drivers of environmental variability in the tropics. In this study, we examine the connections between ENSO and the climate, ecosystem carbon balance, surface water balance, and river hydrology of the Amazon and Tocantins river basins in South America. First we examine the climatic variability associated with ENSO. We analyze long‐term historical climate records to document the “average” climatic signature of the El Niño and La Niña phases of the ENSO cycle. Generally speaking, the “average El Niño” is drier and warmer than normal in Amazonia, while the “average La Niña” is wetter and cooler. While temperature changes are mostly uniform through the whole year and are spatially homogeneous, precipitation changes are stronger during the wet season (January‐February‐March) and are concentrated in the northern and southeastern portions of the basin. Next we use a land surface/ecosystem model (IBIS), coupled to a hydrological routing algorithm (HYDRA), to examine how ENSO affects land surface water and carbon fluxes, as well as changes in river discharge and flooding. The model results suggest several responses to ENSO: (1) During the average El Niño, there is an anomalous source of CO 2 from terrestrial ecosystems, mainly due to a decreased net primary production (NPP) in the north of the basin. There is also a decrease in river discharge along many of the rivers in the basin, which causes a decrease in flooded area along the main stem of the Amazon. (2) During the average La Niña, there is an anomalous sink of CO 2 into terrestrial ecosystems, largely due to an increase in NPP in the northern portion of the basin. In addition, there is a large increase in river discharge in the Amazon basin, especially from the northern and western tributaries. There is a corresponding increase in flooded area, largely in the northern rivers. These results illustrate that changes in water and carbon balance associated with ENSO have complex, spatially heterogeneous features across the basin. This underscores the need for comprehensive analyses, using long‐term observational data and model simulations, of regional environmental systems and their response to climatic variability.

Significance We assess how to meet growing demand for agricultural production to minimize impact on the environment. Higher levels of population and affluence may require expanding land in agriculture by converting grasslands and forests to cropland. Such conversions often reduce valuable ecosystem services. Our research identifies where are the best places to expand agricultural production that minimize the loss of one ecosystem service, carbon storage. We show that selectively choosing where to expand agriculture saves over $1 trillion (2012 US dollars) worth of carbon storage relative to a proportional expansion.

The effects of land cover change on the energy and water balance of the Mississippi River basin are analyzed using the Integrated Biosphere Simulator (IBIS) model. Results of a simulated conversion from complete forest cover to crop cover over a single model grid cell show that annual average net radiation and evapotranspiration decrease, while total runoff increases. The opposite effects are found when complete grass cover is replaced with crop cover. Basinwide energy and water balance changes are then analyzed after simulated land cover change from potential vegetation to the current cover (natural vegetation and crops). In general, net radiation decreases over crops converted from forest and increases over crops converted from grasslands. Evapotranspiration rates decrease over summer crops (corn and soybean) converted from forest and increase over summer crops converted from grassland. The largest decreases (∼0.75 mm day−1; 20%) are found in summer over former forests, and the largest increases (∼0.4 mm day−1; 45%) are found in spring over former northern grasslands. Drainage rates increase over summer crops converted from savanna and forest and decrease over summer crops converted from grasslands. The largest increases (∼0.6 mm day−1; 45%) are found in winter over summer crops in former southern forests, and the largest decreases (∼0.4 mm day−1; 25%) are found in summer over summer crops grown in former northern grasslands. The simulated energy and water balance changes resulting from land cover change depend on season, crop type (winter, spring, or summer plantings) and management, and the type of natural vegetation that is removed.

We compared long-term change in two lake districts, one in a forested rural setting and the other in an urbanizing agricultural region, using lakes as sentinel ecosystems. Human population growth and land-use change are important drivers of ecosystem change in both regions. Biotic changes such as habitat loss, species invasions, and poorer fishing were prevalent in the rural region, and lake hydrology and biogeochemistry responded to climate trends and landscape position. Similar biotic changes occurred in the urbanizing agricultural region, where human-caused changes in hydrology and biogeochemistry had conspicuous effects. Feedbacks among ecosystem dynamics, human uses, economics, social dynamics, and policy and practice are fundamental to understanding change in these lake districts. Sustained support for interdisciplinary collaboration is essential to build understanding of regional change.

Nitrogen fertilizer use across the world's croplands enables high-yielding agricultural production, but does so at considerable environmental cost. Imbalances between nitrogen applied and nitrogen used by crops contributes to excess nitrogen in the environment, with negative consequences for water quality, air quality, and climate change. Here we utilize crop input-yield models to investigate how to minimize nitrogen application while achieving crop production targets. We construct a tradeoff frontier that estimates the minimum nitrogen fertilizer needed to produce a range of maize, wheat, and rice production levels. Additionally, we explore potential environmental consequences by calculating excess nitrogen along the frontier using a soil surface nitrogen balance model. We find considerable opportunity to achieve greater production and decrease both nitrogen application and post-harvest excess nitrogen. Our results suggest that current (circa 2000) levels of cereal production could be achieved with ∼50% less nitrogen application and ∼60% less excess nitrogen. If current global nitrogen application were held constant but spatially redistributed, production could increase ∼30%. If current excess nitrogen were held constant, production could increase ∼40%. Efficient spatial patterns of nitrogen use on the frontier involve substantial reductions in many high-use areas and moderate increases in many low-use areas. Such changes may be difficult to achieve in practice due to infrastructure, economic, or political constraints. Increases in agronomic efficiency would expand the frontier to allow greater production and environmental gains.

Changes in vegetation cover are known to influence the climate system by modifying the radiative, momentum, and hydrologic balance of the land surface. To explore the interactions between terrestrial vegetation and the atmosphere for doubled atmospheric CO2 concentrations, the newly developed fully coupled GENESIS–IBIS climate–vegetation model is used. The simulated climatic response to the radiative and physiological effects of elevated CO2 concentrations, as well as to ensuing simulated shifts in global vegetation patterns is investigated. The radiative effects of elevated CO2 concentrations raise temperatures and intensify the hydrologic cycle on the global scale. In response, soil moisture increases in the mid- and high latitudes by 4% and 5%, respectively. Tropical soil moisture, however, decreases by 5% due to a decrease in precipitation minus evapotranspiration. The direct, physiological response of plants to elevated CO2 generally acts to weaken the earth’s hydrologic cycle by lowering transpiration rates across the globe. Lowering transpiration alone would tend to enhance soil moisture. However, reduced recirculation of water in the atmosphere, which lowers precipitation, leads to more arid conditions overall (simulated global soil moisture decreases by 1%), particularly in the Tropics and midlatitudes. Allowing structural changes in the vegetation cover (in response to changes in climate and CO2 concentrations) overrides the direct physiological effects of CO2 on vegetation in many regions. For example, increased simulated forest cover in the Tropics enhances canopy evapotranspiration overall, offsetting the decreased transpiration due to lower leaf conductance. As a result of increased circulation of moisture through the hydrologic cycle, precipitation increases and soil moisture returns to the value simulated with just the radiative effects of elevated CO2. However, in the highly continental midlatitudes, changes in vegetation cover cause soil moisture to decline by an additional 2%. Here, precipitation does not respond sufficiently to increased plant-water uptake, due to a limited source of external moisture into the region. These results illustrate that vegetation feedbacks may operate differently according to regional characteristics of the climate and vegetation cover. In particular, it is found that CO2 fertilization can cause either an increase or a decrease in available soil moisture, depending on the associated changes in vegetation cover and the ability of the regional climate to recirculate water vapor. This is in direct contrast to the view that CO2 fertilization will enhance soil moisture and runoff across the globe: a view that neglects changes in vegetation structure and local climatic feedbacks.

We ran a sequence of climate model experiments for 6000 years ago, with land‐surface conditions based on a realistic map of palaeovegetation, lakes and wetlands, to quantify the effects of land‐surface feedbacks in the Saharan region. Vegetation‐induced albedo and moisture flux changes produced year‐round warming, forced the monsoon to 17°–25°N two months earlier, and shifted the precipitation belt ≈300 km northwards compared to the effects of orbital forcing alone. The addition of lakes and wetlands produced localised changes in evaporation and precipitation, but caused no further extension of the monsoon belt. Diagnostic analyses with biome and continental hydrology models showed that the combined land‐surface feedbacks, although substantial, could neither maintain grassland as far north as observed (≈26°N) nor maintain Lake “MegaChad” (330,000 km²).

To examine the potential for vegetation feedbacks on the climate system at the Last Glacial Maximum (LGM), we operate the new, fully coupled, Global Environmental and Ecological Simulation of Interactive Systems (GENESIS) ‐ Integrated BIosphere Simulator (IBIS) climate‐vegetation model with boundary conditions appropriate for ∼21,000 years before present. Colder and drier conditions (LGM compared to present) lead grasslands and tundra to largely replace present‐day forests in temperate and boreal latitudes. Also, the physiological effects of lowering atmospheric CO 2 to LGM levels (∼200 ppmv) cause a reduction in tropical and subtropical forest cover (compared to present) in favor of C 4 grasslands. These climate‐ and CO 2 ‐induced changes in LGM vegetation cover produce feedbacks on the climate that are, on regional scales, comparable in magnitude to the radiative effects of lowered CO 2 . For example, a positive albedo‐driven feedback, due to changing vegetation cover, contributes to additional middle‐ and high‐latitude cooling. Furthermore, sparser forest cover in the tropics significantly reduces evapotranspiration and further reduces tropical precipitation (0.13 mm d −1 on the annual average compared to the 0.59 mm d −1 decrease without vegetation feedbacks). Our simulations indicate that the physiological effects of lowered CO 2 on the climate‐vegetation system are more clearly manifested through changes in vegetation cover (i.e., changes in leaf area index), than through the dilation of leaf stomata and the enhancement of transpiration.

The availability and geographic distribution of fresh water resources may undergo significant changes in response to global environmental change. In this study, we examine the water balance of the Amazon Basin using a modified version of the LSX land surface model [ Pollard and Thompson , 1995; Thompson and Pollard , 1995a, b] which includes a representation of land surface processes, canopy physiology (stomatal conductance, transpiration, and photosynthesis), and continental‐scale hydrological routing. The model operates on a 0.5° by 0.5° grid and is forced with observed long‐term climatological data. As an initial application of the model, we examine the seasonal variability of water balance within the Amazon Basin. The simulation is evaluated by comparing (1) simulated evapotranspiration with observations for different vegetation cover types and (2) simulated river discharge against the long‐term records of 56 fluviometric stations spread throughout the basin. The model results show that evapotranspiration is strongly dependent on the vegetation cover, especially during the rainy season. Overall, we find good agreement between the simulated and the observed water balance: for most of the fluviometric stations the error is less than 25%. In addition, we perform a model sensitivity study to determine the role of changes in vegetation cover on the water balance, without considering feedbacks on climate. When forests, woodlands, and savannas are replaced with grasslands, annual average evapotranspiration decreases by ∼0.5 mm d −1 (∼12%), which is comparable to observations. Finally, we perform a model sensitivity study in order to assess the potential physiological effects of increased CO 2 on stomatal (canopy) conductance and, as a consequence, on the water balance of the Amazon Basin, again without considering feedbacks on the atmosphere. The model results suggest that doubling atmospheric CO 2 concentrations (from 325 to 650 ppmv) would decrease the canopy conductance by 20 to 35% (depending on the vegetation type) arid would decrease evapotranspiration by ∼4% throughout the region. As a consequence, annual river discharge increases by between 3% and 16.5%, depending on the position within the basin. At the mouth of the Amazon arid Tocantins Rivers, annual discharge increases by 5 and 9%, respectively.

The sensitivity of lake ice phenology to climatic variations is tested using a numerical lake‐ice model (LIMNOS). The model simulates the evolution of ice and snow cover by time‐integrating equations of vertical heat conduction through ice and snow. The required input variables are mean lake depth, air temperature and moisture, wind speed, solar radiation, snowfall, and cloudiness. The model simulates the ice‐on and ice‐off dates of three southern Wisconsin lakes to within 1 week of their historical averages, despite large differences in mean depth. Using hourly meteorological data from 1961–1990 as inputs, LIMNOS simulates the annual ice‐on and ice‐off dates of Lake Mendota with a median absolute error of only 2 d and 4 d, respectively. The atmospheric variables are altered to determine the sensitivity of Lake Mendota ice phenology to climate change. The simulated ice‐off date shows stronger sensitivity than the ice‐on date to air temperature changes, and the sensitivity of both dates is greater for climatic warmings than coolings. Increased snowfall causes a monotonic delay in the breakup date, whereas decreased snowfall nonlinearly hastens ice decay.

Previous climate model simulations have shown that the configuration of the Earth's orbit during the early to mid‐Holocene (approximately 10–5 kyr) can account for the generally warmer‐than‐present conditions experienced by the high latitudes of the northern hemisphere. New simulations for 6 kyr with two atmospheric/mixed‐layer ocean models (Community Climate Model, version 1, CCMl, and Global ENvironmental and Ecological Simulation of Interactive Systems, version 2, GENESIS 2) are presented here and compared with results from two previous simulations with GENESIS 1 that were obtained with and without the albedo feedback due to climate‐induced poleward expansion of the boreal forest. The climate model results are summarized in the form of potential vegetation maps obtained with the global BIOME model, which facilitates visual comparisons both among models and with pollen and plant macrofossil data recording shifts of the forest‐tundra boundary. A preliminary synthesis shows that the forest limit was shifted 100–200 km north in most sectors. Both CCMl and GENESIS 2 produced a shift of this magnitude. GENESIS 1 however produced too small a shift, except when the boreal forest albedo feedback was included. The feedback in this case was estimated to have amplified forest expansion by approximately 50%. The forest limit changes also show meridional patterns (greatest expansion in central Siberia and little or none in Alaska and Labrador) which have yet to be reproduced by models. Further progress in understanding of the processes involved in the response of climate and vegetation to orbital forcing will require both the deployment of coupled atmosphere‐biosphere‐ocean models and the development of more comprehensive observational data sets.

Abstract We calculated carbon budgets for a chronosequence of harvested jack pine ( Pinus banksiana Lamb.) stands (0‐, 5‐, 10‐, and∼29‐year‐old) and a∼79‐year‐old stand that originated after wildfire. We measured total ecosystem C content (TEC), above‐, and belowground net primary productivity (NPP) for each stand. All values are reported in order for the 0‐, 5‐, 10‐, 29‐, and 79‐year‐old stands, respectively, for May 1999 through April 2000. Total annual NPP (NPP T ) for the stands (Mg C ha −1 yr −1 ±1 SD) was 0.9±0.3, 1.3±0.1, 2.7±0.6, 3.5±0.3, and 1.7±0.4. We correlated periodic soil surface CO 2 fluxes ( R S ) with soil temperature to model annual R S for the stands (Mg C ha −1 yr −1 ±1 SD) as 4.4±0.1, 2.4±0.0, 3.3±0.1, 5.7±0.3, and 3.2±0.2. We estimated net ecosystem productivity (NEP) as NPP T minus R H (where R H was calculated using a Monte Carlo approach as coarse woody debris respiration plus 30–70% of total annual R S ). Excluding C losses during wood processing, NEP (Mg C ha −1 yr −1 ±1 SD) for the stands was estimated to be −1.9±0.7, −0.4±0.6, 0.4±0.9, 0.4±1.0, and −0.2±0.7 (negative values indicate net sources to the atmosphere.) We also calculated NEP values from the changes in TEC among stands. Only the 0‐year‐old stand showed significantly different NEP between the two methods, suggesting a possible mismatch for the chronosequence. The spatial and methodological uncertainties allow us to say little for certain except that the stand becomes a source of C to the atmosphere following logging.

While the earth's climate can affect the structure and functioning of terrestrial ecosystems, the process also works in reverse. As a result, changes in terrestrial ecosystems may influence climate through both biophysical and biogeochemical processes. This two-way link between the physical climate system and the biosphere is under increasing scrutiny. We review recent developments in the analysis of this interaction, focusing in particular on how alterations in the structure and functioning of terrestrial ecosystems, through either human land-use practices or global climate change, may affect the future of the earth's climate.

The export of nitrate by the Mississippi River to the Gulf of Mexico has tripled since the 1950s primarily due to an increase in agricultural fertilizer application and hydrological changes. Here we have adapted two physically based models, the Integrated Biosphere Simulator (IBIS) terrestrial ecosystem model and the Hydrological Routing Algorithm (HYDRA) hydrological transport model, to simulate the nitrate export in the Mississippi River system and isolate the role of hydrological processes in the observed increase and interannual variability in nitrate export. Using an empirical nitrate input algorithm based on constant land cover and variability in runoff, the modeling system is able to represent much of the spatial and interannual variability in aquatic nitrate export. The results indicate that about a quarter of the sharp increase in nitrate export from 1966 to 1994 was due to an increase in runoff across the basin. This illustrates the pivotal role of hydrology and climate in the balance between storage of nitrate in the terrestrial system and leaching.

Although previous studies have considered the long‐term variability of precipitation and river discharge in the Amazon basin, other components of the hydrologic cycle, such as evapotranspiration and the transport of water vapor, have not received the same attention. This study examines the 20‐year variability of the full hydrologic budget of the Amazon basin, using a 1976–1996 time series from the National Centers for Environmental Protection/National Center for Atmospheric Research reanalyzed meteorological data set. Within this 20‐year record, there is a statistically significant decreasing trend in the atmospheric transport of water vapor both into and out of the Amazon basin. This trend is associated with a general relaxation of the southeasterly trade winds, a weakening of the east‐to‐west pressure gradient, and a warming of the sea surface temperatures in the equatorial South Atlantic region. While the atmospheric transport of water vapor through the Amazon basin has decreased, the internal recycling of precipitation within the basin increased and basin‐wide precipitation, evapotranspiration, and runoff have remained nearly constant. Even though basin‐average precipitation and runoff have remained fairly stable, other components of the Amazon basin's hydrologic cycle have been altered significantly by large‐scale changes in atmospheric circulation.

The increased use of nitrogen fertilizer in the Mississippi River Basin since the 1950s has been blamed for declining water quality, the degradation of aquatic ecosystems and the growth of a seasonal hypoxic zone in the Gulf of Mexico. In this study, we use the IBIS terrestrial ecosystem model and the HYDRA aquatic transport model to examine how agricultural practices and climate influenced terrestrial and aquatic nitrogen cycling across the Mississippi Basin and the nitrate export to the Gulf. The modeling system accurately depicts the observed trends and interannual variability in nitrate export by the Mississippi River (r 2 > 0.83), and several of the major tributaries, between 1960 and 1994. The challenge of simulating nitrate export from the central western sub‐basins highlights the key role of processes like denitrification. The simulations demonstrate that three factors led to the doubling of nitrate export by the Mississippi River since 1960: (1) an increase in fertilizer application rates, particularly on maize; (2) an increase in runoff across the basin; and (3) the expansion of soybean cultivation. By the early 1990s, fertilized crops may have accounted for almost 90% of the nitrate leached to the river system, despite representing only 20% of the watershed area. The majority of the nitrate exported to the Gulf appears to originate from “hot spots,” including a stretch of the “Corn Belt” across Iowa, Illinois, and Indiana. The relative contribution of such heavily fertilized lands, particularly those in close proximity to higher order streams, can be even greater during wet years.

Dengue fever is the most significant mosquito-borne viral disease of humans and is a leading cause of childhood deaths and hospitalizations in many countries.Variations in environmental conditions, especially climatic parameters, affect the dengue viruses and their principal mosquito vector, Aedes aegypti, but few studies have attempted to quantify these relationships at the global scale.Here we use a numerical model to simulate the response of Ae. aegypti to observed climatic variations from 1958 to 1995 and to examine how modelled Ae. aegypti populations may be related to dengue and DHF cases worldwide.We find that variations in climate can induce large variations in modelled Ae. aegypti populations at the global scale.Furthermore, these climate-induced variations in modelled Ae. aegypti populations are strongly correlated to reported historical dengue/DHF cases, especially in Central America and Southeast Asia.These results suggest that potential dengue caseloads could be anticipated using seasonal climate forecasts to drive the mosquito model, thus providing a useful tool in public health management.

We use a fully coupled climate‐vegetation model to examine the potential effects of changes in vegetation cover on simulations of CO 2 ‐induced climate change. We find that vegetation feedbacks, acting mainly through changes in surface albedo, enhance greenhouse warming in the northern high latitudes during spring and summer months. In spring and summer, land surfaces north of 45°N are warmed by 3.3 and 1.7°C by a doubling of CO 2 alone; vegetation feedbacks produce an additional warming of between 1.1–1.6 and 0.4–0.5°C, respectively. In winter, however, vegetation feedbacks appear to oppose the 5.6°C radiative warming, particularly over Eurasia. These results demonstrate that vegetation feedbacks are potentially significant and must be included in assessments of anthropogenic climate change.

Complex interactions in the climate system can give rise to strong positive feedback mechanisms that may lead to sudden climatic changes. The prolonged Sahel drought and the Dust Bowl are examples of 20th century abrupt climatic changes that had serious effects on ecosystems and societies. Here we analyze global historical rainfall observations to detect regions that have undergone large, sudden decreases in rainfall. Our results show that in the 20th century about 30 regions in the world have experienced such changes. These events are statistically significant at the 99% level, are persistent for at least ten years, and most have magnitudes of change that are 10% lower than the climatological normal (1901–2000 rainfall average). This analysis illustrates the extent and magnitude of abrupt climate changes across the globe during the 20th century and may be used for studying the dynamics of and the mechanisms behind these abrupt changes.

DEMETER, a new process‐based model of the terrestrial biosphere, is used to simulate global patterns of net primary productivity (NPP). For the modern climate, NPP and vegetation biomass are simulated to be 62.1 Gt C yr −1 and 800.6 Gt C, respectively. Simulated NPP is found to be highly correlated to field observations (r=0.9343) and the results of the empirically based Miami model (r=0.9587).

Since time immemorial, humankind has changed landscapes in attempts to improve the amount, quality, and security of natural resources critical to its well being, such as food, freshwater, fiber, and medicinal products. Through the increased use of innovation, human populations have, slowly at first, and at increasingly rapid pace later on, increased its ability to derive resources from the environment, and expand its territory. Several authors have identified three different phases - the control of fire, domestication of biota, and fossil-fuel use - as being pivotal in enabling increased appropriation of natural resources (Goudsblom and De Vries 2004; Turner II and McCandless 2004).

STEM PhDs increasingly contribute to commercial science, such as patenting. We analyze faculty’s role in training STEM PhD students as new inventors on patents at leading research universities, emphasizing the drivers of gender differences. We ...STEM PhDs are a critical source of human capital in the economy, contributing to commercial as well as academic science. We examine whether STEM PhD students become new inventors (file their first patent) during their doctoral training at the top 25 U.S. ...

Climate changes are altering patterns of temperature and precipitation, potentially affecting regions of malaria transmission. We show that areas of the Amazon Basin with few wetlands show a variable relationship between precipitation and malaria, while areas with extensive wetlands show a negative relationship with malaria incidence.

The majority of the world's food production capability is inextricably tied to global precipitation patterns. Changes in moisture availability—whether from changes in climate from anthropogenic greenhouse gas emissions or those induced by land cover change (LCC)—can have profound impacts on food production. In this study, we examined the patterns of evaporative sources that contribute to moisture availability over five major global food producing regions (breadbaskets), and the potential for land cover change to influence these moisture sources by altering surface evapotranspiration. For a range of LCC scenarios we estimated the impact of altered surface fluxes on crop moisture availability and potential yield using a simplified linear hydrologic model and a state-of-the-art ecosystem and crop model. All the breadbasket regions were found to be susceptible to reductions in moisture owing to perturbations in evaporative source (ES) from LCC, with reductions in moisture availability ranging from 7 to 17% leading to potential crop yield reductions of 1–17%, which are magnitudes comparable to the changes anticipated with greenhouse warming. The sensitivity of these reductions in potential crop yield to varying magnitudes of LCC was not consistent among regions. Two variables explained most of these differences: the first was the magnitude of the potential moisture availability change, with regions exhibiting greater reductions in moisture availability also tending to exhibit greater changes in potential yield; the second was the soil moisture within crop root zones. Regions with mean growing season soil moisture fractions of saturation >0.5 typically had reduced impacts on potential crop yield. Our results indicate the existence of LCC thresholds that have the capability to create moisture shortages adversely affecting crop yields in major food producing regions, which could lead to future food supply disruptions in the absence of increased irrigation or other forms of water management.

A process‐based ecosystem model, DEMETER, is used to simulate the sensitivity of the terrestrial biosphere to changes in climate. In this study, DEMETER is applied to the two following climatic regimes: (1) the modern observed climate and (2) a simulated mid‐Holocene climate (6000 years before present). The mid‐Holocene climate is simulated using the GENESIS global climate model, where shifts in the Earth's orbital parameters result in warmer northern continents and enhanced monsoons in Asia, North Africa, and North America. DEMETER simulates large differences between modern and mid‐Holocene vegetation cover: (1) mid‐Holocene boreal forests extend farther poleward than present in much of Europe, Asia, and North America, and (2) mid‐Holocene North African grasslands extend substantially farther north than present. The simulated patterns of mid‐Holocene vegetation are consistent with many features of the paleobotanical record. Simulated mid‐Holocene global net primary productivity is approximately 3% larger than present, largely due to the increase of boreal forest and tropical grasslands relative to tundra and desert. Global vegetation carbon is higher at 6 kyr B.P. compared to present by roughly the same amount (4%). Mid‐Holocene global litter carbon is larger than present by 10%, while global soil carbon is approximately 1% less. Despite the regional changes in productivity and carbon storage the simulated total carbon storage potential of the terrestrial biosphere (not including changes in peat) does not change significantly between the two simulations.

Six different estimates of precipitation (three based entirely on rain gauge measurements, one based on a combination of rain gauge measurements and satellite data, and two based on reanalyzed meteorological datasets) for the Amazon basin are compared. Altogether, these different estimates have a mean value of 2130 mm/yr. The long‐term spatial patterns of annual precipitation within the basin are in good agreement for datasets based on rain‐gauges, while data from the reanalyzed meteorological datasets appear to have significant spatial biases resulting from the influence of the spectral representation of topography. While the long‐term average precipitation climatology of the Amazon basin appears to be consistently described by the six different datasets, the interannual variability in precipitation (as represented by the four datasets that contain precipitation time‐series information with various lengths of record) has significant regional discrepancies. These results suggest that some caution be exercised when using precipitation time‐series data over the Amazon basin.

Ecosystems provide multiple benefits to people, including climate regulation. Previous efforts to quantify this ecosystem service have been either largely conceptual or based on complex atmospheric models. Here, we review previous research on this topic and propose a new and simple analytical approach for estimating the physical regulation of climate by ecosystems. The proposed metric estimates how land‐cover change affects the loading of heat and moisture into the atmosphere, while also accounting for the relative contribution of wind‐transported heat and moisture. Although feedback dynamics between land, atmosphere, and oceans are not modeled, the metric compares well with previous studies for several regions. We find that ecosystems have the strongest influence on surface climatic conditions in the boreal and tropical regions, where temperature and moisture changes could substantially offset or magnify greenhouse‐forced changes. This approach can be extended to estimate the effects of changing land cover on local, physical climate processes that are relevant to society.

Aggressive renewable energy policies have helped the biofuels industry grow at a rate few could have predicted. However, while discourse on the energy balance and environmental impacts of agricultural biofuel feedstocks are common, the potential they hold for additional production has received considerably less attention. Here we present a new biofuel yield analysis based on the best available global agricultural census data. These new data give us the first opportunity to consider geographically-specific patterns of biofuel feedstock production in different regions, across global, continental, national and sub-national scales. Compared to earlier biofuel yield tables, our global results show overestimates of biofuel yields by ∼100% or more for many crops. To encourage the use of regionally-specific data for future biofuel studies, we calculated complete results for 20 feedstock crops for 238 countries, states, territories and protectorates.

[1] We find that irrigation significantly affects Asian summer climate, according to model simulations using the Community Atmosphere Model (CAM3.0) coupled to the Community Land Model (CLM3.5). Irrigation over the major river basins in the Middle East and central Asia causes a decrease in sensible heat fluxes and an increase in latent heat fluxes in boreal summer. These changes in heat fluxes lead to a cooling of both the surface and the lower troposphere over the irrigated regions. This atmospheric cooling, in turn, results in a cooling of the layer-averaged temperature (thickness temperature) in the troposphere. The irrigation-induced cooling in the troposphere, therefore, significantly decreases the tropospheric geopotential height over the irrigated regions. Lower height in the upper troposphere alters the upper-level atmospheric circulation over the irrigated and surrounding regions in Asia. Cyclonic differences of atmospheric circulation are simulated around negative differences of height and positive differences of vorticity between the irrigated and control runs, and they result in a weakening of the upper-level anticyclonic circulation over the tropical to midlatitude African-Asian regions. These changes in atmospheric circulation lead to a weakening of the strong upper-level westerly jet (Asian jet) over eastern Europe, the Middle East, and central Asia in 40°N ∼ 55°N. The irrigation impacts on the atmospheric circulation and Asian jet in boreal summer are supported by a comparison with observations.

Five sets of biophysical and hydrological measurements from across the globe are used to test the performance of the Integrated Biosphere Simulator (IBIS) [ Foley et al., 1996] in reproducing short‐term and long‐term evolution of soil moisture and temperature, surface energy fluxes and CO 2 fluxes. The sites include a soybean crop in southwestern France (HAPEX‐MOBILHY, 1986), a meadow in the Netherlands (Cabauw, 1987), a grassland in Russia (Valday‐Usadievskiy, 1966–1983), a prairie in Kansas (FIFE, site 16, 1987–1989), and a tropical forest in Brazil (ABRACOS, Reserva Jaru, 1992–1993). IBIS adequately reproduces the evolution of the soil moisture together with the surface fluxes for those five different sites while only imposing a small number of site specific parameters describing vegetation characteristics and soil texture. The quality of the simulations is improved when detailed information regarding soil texture, rooting profiles, and leaf area index are available.

An atmospheric transport model and observations of atmospheric CO 2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO 2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO 2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO 2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO 2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land‐use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO 2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO 2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability.

Lake ice phenology parameters (dates of ice onset and thaw) provide an integrative climatic description of autumn to springtime conditions. Interannual variations in lake ice duration and thickness allow estimates of local climatic variability. In addition, long‐term changes in lake ice phenology may provide a robust indication of climatic change. The relationship between lake ice and climate enables the use of process‐based models for predicting the dates of freeze‐up and thaw. LIMNOS (Lake Ice Model Numerical Operational Simulator) is one such model, which was originally designed to simulate the ice phenology of several lakes in southern Wisconsin. In this study, LIMNOS is modified to run globally on a 0.5° by 0.5° latitude‐longitude grid using average monthly climate data. We initially simulate the ice phenology for lakes of 5‐ and 20‐m mean depths across the northern hemisphere to demonstrate the effects of lake depth, latitude, and elevation on ice phenology. To evaluate the results of LIMNOS we also simulate the ice phenology of 30 lakes across the northern hemisphere which have long‐term ice records. LIMNOS reproduces the general geographic patterns of ice‐on and ice‐off dates, although ice‐off dates tend to occur later in the model. Lakes with extreme depths, surface areas, or precipitation are simulated less accurately than small, shallow lakes. This study reveals strengths and weaknesses of LIMNOS and suggests aspects which need improving. Future investigations should focus on the use of geographically extensive lake ice observations and modeling to elucidate patterns of climatic variability and/or climate change.

The land surface water balance of the continental United States is analyzed from 1963 to 1995 using a terrestrial biosphere model (IBIS), reanalysis data from NCEP/NCAR, a hydrologic routing model (HYDRA), and numerous observational data sets. Emphasis is placed on evaluating the performance of IBIS and the reanalysis, particularly over the central United States. IBIS is forced with daily climatic inputs from NCEP; an additional simulation is performed using observed precipitation. The NCEP reanalysis is found to have excessive precipitation and evapotranspiration over the central United States (particularly in the summertime), an exaggerated seasonal cycle of runoff, and low snow depths. The net surface water balance exhibits a dry bias that is corrected by nudging soil moisture toward climatology. Unfortunately, this correction term is large and appears to have a detrimental impact on other water balance components (particularly runoff). Fields that are reasonably well simulated in the reanalysis include fall and winter precipitation over the central United States, soil moisture in Illinois, and interannual variations in runoff. Results from the IBIS simulations show generally better agreement with observations than the NCEP reanalysis but continue to have nontrivial errors in certain fields. Over the central United States, these discrepancies include high winter/spring evapotranspiration (1 mm d −1 too high), low snow depth, and weak spring runoff (30–50% too low). The errors are at least partially caused by underestimated cloud cover and early spring green‐up. A spatial analysis of the U.S. water balance reveals that some of the strongest seasonal and interannual variations in precipitation, evapotranspiration, and soil moisture occur over the central United States.

The Amazon basin contains some of the most productive ecosystems on the planet, yet we have little understanding of the long‐term behavior. By examining historical climate records over the Amazon, we identify several modes of climatic variability—including previously undocumented long‐term modes. Furthermore, using a process‐based ecosystem model, we show that these variations in climate generate variations in terrestrial carbon fluxes on short (3–4 year), intermediate (8–9 year), and long (24–28 year) time scales. The long‐term cycles in terrestrial carbon balance have not been previously suggested. Finally, we find that time‐lags between productivity and decomposition enhance the short‐term variations in net carbon balance, while slightly dampening the long‐term variations. Given the worldwide attention on terrestrial carbon cycling, and the potential for “carbon sinks”, we suggest that an improved understanding of long‐term climatic and ecosystem processes is crucial. Other regions should be examined for potential long‐term carbon cycle variations.

The 1973 “Miami Model” was the first global‐scale empirical model of terrestrial net primary productivity (NPP), and its simplicity and relative accuracy has led to its continued use. However, improved techniques to measure NPP in the field and the expanded spatial and temporal range of observations have prompted this study, which reexamines the relationship of climatic variables to NPP. We developed several statistical models with paired climatic variables in order to investigate their relationships to terrestrial NPP. A reference data set of 3023 NPP field observations was compiled for calibration and parameter optimization. In addition to annual mean temperature and precipitation, as in the Miami Model, we chose more ecologically relevant climatic variables including growing degree‐days, a soil moisture stress index, and photosynthetically active radiation (PAR). Calculated annual global NPP ranged from 36 to 74 Pg‐C yr −1 , comparable with previous studies. Comparisons of geographic patterns of NPP were made using biome and latitudinal averages.

Greenhouse gases from the combination of land use change and agriculture are responsible for the largest share of global emissions, but are inadequately considered in the current set of international climate policies. Under the Kyoto protocol, emissions generated in the production of agricultural commodities are the responsibility of the producing country, introducing potential inequities if agricultural products are exported. This study quantifies the greenhouse gas emissions from the production of soybeans and beef in the Amazon basin of Brazil, a region where rates of both deforestation and agricultural exports are high. Integrating methods from land use science and life-cycle analysis, and accounting for producer–consumer responsibility, we allocate emissions between Brazil and importing countries with an emphasis on ultimately reducing the greenhouse gas impact of food production. The mechanisms used to distribute the carbon emissions over time allocate the bulk of emissions to the years directly after the land use change occurred, and gradually decrease the carbon allocation to the agricultural products. The carbon liability embodied in soybeans exported from the Amazon between 1990 and 2006 was 128 TgCO2e, while 120 TgCO2e were embodied in exported beef. An equivalent carbon liability was assigned to Brazil for that time period.

Since the end of World War II, global agriculture has undergone a period of rapid intensification achieved through a combination of increased applications of chemical fertilizers, pesticides, and herbicides, the implementation of best management practice techniques, mechanization, irrigation, and more recently, through the use of optimized seed varieties and genetic engineering. However, not all crops and not all regions of the world have realized the same improvements in agricultural intensity. In this study we examine both the magnitude and spatial variation of new agricultural production potential from closing of 'yield gaps' for 20 ethanol and biodiesel feedstock crops. With biofuels coming under increasing pressure to slow or eliminate indirect land-use conversion, the use of targeted intensification via established agricultural practices might offer an alternative for continued growth. We find that by closing the 50th percentile production gap—essentially improving global yields to median levels—the 20 crops in this study could provide approximately 112.5 billion liters of new ethanol and 8.5 billion liters of new biodiesel production. This study is intended to be an important new resource for scientists and policymakers alike—helping to more accurately understand spatial variation of yield and agricultural intensification potential, as well as employing these data to better utilize existing infrastructure and optimize the distribution of development and aid capital.

Agriculture is a key driver of change in the Anthropocene. It is both a critical factor for human well-being and development and a major driver of environmental decline. As the human population expands to more than 9 billion by 2050, we will be compelled to find ways to adequately feed this population while simultaneously decreasing the environmental impact of agriculture, even as global change is creating new circumstances to which agriculture must respond. Many proposals to accomplish this dual goal of increasing agricultural production while reducing its environmental impact are based on increasing the efficiency of agricultural production relative to resource use and relative to unintended outcomes such as water pollution, biodiversity loss, and greenhouse gas emissions. While increasing production efficiency is almost certainly necessary, it is unlikely to be sufficient and may in some instances reduce long-term agricultural resilience, for example, by degrading soil and increasing the fragility of agriculture to pest and disease outbreaks and climate shocks. To encourage an agriculture that is both resilient and sustainable, radically new approaches to agricultural development are needed. These approaches must build on a diversity of solutions operating at nested scales, and they must maintain and enhance the adaptive and transformative capacity needed to respond to disturbances and avoid critical thresholds. Finding such approaches will require that we encourage experimentation, innovation, and learning, even if they sometimes reduce short-term production efficiency in some parts of the world.

How can human societies thrive within Earth's physical and biological limits?

Summary In order to investigate the hypothesis that the Earth's climate and vegetation patterns may have more than one basic state, we use the fully coupled GENESIS‐IBIS model. GENESIS is an atmospheric general circulation model. IBIS is a dynamic global vegetation model that integrates biophysical, physiological, and ecological processes. GENESIS and IBIS are coupled by way of a common land surface interface to allow for the full and transient interaction between changes in the vegetation structure and changes in the general circulation of the atmosphere. We examine two modern climate simulations of the coupled model initialized with two different initial conditions. In one case, we initialize the model vegetation cover with the modern observed distribution of vegetation. In the other case, we initialize the vegetation cover with evergreen boreal forests extending to the Arctic coast, replacing high‐latitude tundra. We interpret the coupled model's behaviour using a conceptual model for multistability and demonstrate that in both simulations the climate‐vegetation system converges to the same equilibrium state. In the present climate, feedbacks between land, ocean, sea ice, and the atmosphere do not result in the warming required to support an expanded boreal forest.

A fully coupled atmosphere–biosphere model, version 3 of the NCAR Community Climate Model (CCM3) and the Integrated Biosphere Simulator (IBIS), is used to illustrate how vegetation dynamics may be capable of producing long-term variability in the climate system, particularly through the hydrologic cycle and precipitation. Two simulations of the global climate are conducted with fixed climatological sea surface temperatures: one including vegetation as a dynamic boundary condition, and the other keeping vegetation cover fixed. A comparison of the precipitation power spectra over land from these two simulations shows that dynamic interactions between the atmosphere and vegetation enhance precipitation variability at time scales from a decade to a century, while damping variability at shorter time scales. In these simulations, the two-way coupling between the atmosphere and the dynamic vegetation cover introduces persistent precipitation anomalies in several ecological transition zones: between forest and grasslands in the North American midwest, in southern Africa, and at the southern limit of the tropical forest in the Amazon basin, and between savanna and desert in the Sahel, Australia, and portions of the Arabian Peninsula. These regions contribute most to the long-term variability of the atmosphere–vegetation system. Slow changes in the vegetation cover, resulting from a “red noise” integration of high-frequency atmospheric variability, are responsible for generating this long-term variability. Lead and lag correlation between precipitation and vegetation leaf area index (LAI) shows that LAI influences precipitation in the following years, and vice versa. A mechanism involving changes in LAI resulting in albedo, roughness, and evapotranspiration changes is proposed.

Lakes are low‐lying connectors of uplands and wetlands, surface water and groundwater, and though they are often studied as independent ecosystems, they function within complex landscapes. One such highly connected region is the Northern Highland Lake District (NHLD), where more than 7000 lakes and their watersheds cycle water and carbon through mixed forests, wetlands, and groundwater systems. Using a new spatially explicit simulation framework representing these coupled cycles, the Lake, Uplands, Wetlands Integrator (LUWI) model, we address basic regional questions in a 72‐lake simulation: (1) How do simulated water and carbon budgets compare with observations, and what are the implications for carbon stocks and fluxes? (2) How do the strength and spatial pattern of landscape connections vary among watersheds? (3) What is the role of interwatershed connections in lake carbon processing? Results closely coincide with observations at seasonal and annual scales and indicate that the connections among components and watersheds are critical to understanding the region. Carbon and water budgets vary widely, even among nearby lakes, and are not easily predictable using heuristics of lake or watershed size. Connections within and among watersheds exert a complex, varied influence on these processes: Whereas inorganic carbon budgets are strongly related to the number and nature of upstream connections, most organic lake carbon originates within the watershed surrounding each lake. This explicit incorporation of terrestrial and aquatic processes in surface and subsurface connection networks will aid our understanding of the relative roles of on‐land, in‐lake, and between‐lake processes in this lake‐rich region.

Fires in agricultural ecosystems emit greenhouse gases and aerosols that influence climate on multiple spatial and temporal scales. Annex 1 countries of the United Nations Framework Convention on Climate Change (UNFCCC), many of which ratified the Kyoto Protocol, are required to report emissions of CH 4 and N 2 O from these fires annually. In this study, we evaluated several aspects of this reporting system, including the optimality of the crops targeted by the UNFCCC globally and within Annex 1 countries, and the consistency of emissions inventories among different countries. We also evaluated the success of individual countries in capturing interannual variability and long‐term trends in agricultural fire activity. In our approach, we combined global high‐resolution maps of crop harvest area and production, derived from satellite maps and ground‐based census data, with Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) measurements of active fires. At a global scale, we found that adding ground nuts (e.g., peanuts), cocoa, cotton and oil palm, and removing potato, oats, rye, and pulse other from the list of 14 crops targeted by the UNFCCC increased the percentage of active fires covered by the reporting system by 9%. Optimization led to a different recommended list for Annex 1 countries, requiring the addition of sunflower, cotton, rapeseed, and alfalfa and the removal of beans, sugarcane, pulse others, and tuber‐root others. Extending emissions reporting to all Annex 1 countries (from the current set of 19 countries) would increase the efficacy of the reporting system from 6% to 15%, and further including several non‐Annex 1 countries (Argentina, Brazil, China, India, Indonesia, Thailand, Kazakhstan, Mexico, and Nigeria) would capture over 55% of active fires in croplands worldwide. Analyses of interannual trends from the United States and Australia showed the importance of both intensity of fire use and crop production in controlling year‐to‐year variations in agricultural fire emissions. Remote sensing provides an effective means for evaluating some aspects of the current UNFCCC emissions reporting system; and, if combined with census data, field experiments and expert opinion, has the potential to improve the robustness of the next generation inventory system.