Carol Barford

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.

We report a new method for measurement of the isotopic composition of nitrate (NO3-) at the natural-abundance level in both seawater and freshwater. The method is based on the isotopic analysis of nitrous oxide (N2O) generated from nitrate by denitrifying bacteria that lack N2O-reductase activity. The isotopic composition of both nitrogen and oxygen from nitrate are accessible in this way. In this first of two companion manuscripts, we describe the basic protocol and results for the nitrogen isotopes. The precision of the method is better than 0.2‰ (1 SD) at concentrations of nitrate down to 1 μM, and the nitrogen isotopic differences among various standards and samples are accurately reproduced. For samples with 1 μM nitrate or more, the blank of the method is less than 10% of the signal size, and various approaches may reduce it further.

Net uptake of carbon dioxide (CO2) measured by eddy covariance in a 60- to 80-year-old forest averaged 2.0 +/- 0.4 megagrams of carbon per hectare per year during 1993 to 2000, with interannual variations exceeding 50%. Biometry indicated storage of 1.6 +/- 0.4 megagrams of carbon per hectare per year over 8 years, 60% in live biomass and the balance in coarse woody debris and soils, confirming eddy-covariance results. Weather and seasonal climate (e.g., variations in growing-season length or cloudiness) regulated seasonal and interannual fluctuations of carbon uptake. Legacies of prior disturbance and management, especially stand age and composition, controlled carbon uptake on the decadal time scale, implying that eastern forests could be managed for sequestration of carbon.

We analyzed 13 years (1992−2004) of CO 2 flux data, biometry, and meteorology from a mixed deciduous forest in central Massachusetts. Annual net uptake of CO 2 ranged from 1.0 to 4.7 Mg‐C ha −1 yr −1 , with an average of 2.5 Mg‐C ha −1 yr −1 . Uptake rates increased systematically, nearly doubling over the period despite forest age of 75–110 years; there were parallel increases in midsummer photosynthetic capacity at high light level (21.5−31.5 μ mole m −2 s −1 ), woody biomass (101−115 Mg‐C ha −1 from 1993−2005, mostly due to growth of one species, red oak), and peak leaf area index (4.5−5.5 from 1998–2005). The long‐term trends were interrupted in 1998 by sharp declines in photosynthetic capacity, net ecosystem exchange (NEE) of CO 2 , and other parameters, with recovery over the next 3 years. The observations were compared to empirical functions giving the mean responses to temperature and light, and to a terrestrial ecosystem model (IBIS2). Variations in gross ecosystem exchange of CO 2 (GEE) and NEE on hourly to monthly timescales were represented well as prompt responses to the environment, but interannual variations and long‐term trends were not. IBIS2 simulated mean annual NEE, but greatly overpredicted the amplitude of the seasonal cycle and did not predict the decadal trend. The drivers of interannual and decadal changes in NEE are long‐term increases in tree biomass, successional change in forest composition, and disturbance events, processes not well represented in current models.

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.

Quantifying net carbon (C) storage by forests is a necessary step in the validation of carbon sequestration estimates and in assessing the possible role of these ecosystems in offsetting fossil fuel emissions. In eastern North America, five sites were established in deciduous forests to provide measurements of net ecosystem CO2 exchange (NEE) using micro-meteorological methods, and measures of major carbon pools and fluxes, using a combination of forest mensurational, eco-physiological, and other biometric methods. The five study sites, part of the AmeriFlux network, ranged across 10° of latitude and 18° of longitude, but were all of similar age, canopy height, and stand basal area. Here we present a cross-site synthesis of annual carbon storage estimates, comparing meteorological and biometric approaches, and also comparing biometric estimates based on analyses of autotrophic carbon pools and heterotrophic carbon fluxes (net ecosystem production, NEP) versus those based on measurements of change in two major carbon pools (ΔC). Annual above-ground net primary production (ANPP) varied nearly two-fold among sites and was strongly correlated with average annual temperature and with annual soil nitrogen mineralization (Nmin). Estimates of NEP ranged from 0.7 Mg C per hectare per year in northern lower Michigan to 3.5 Mg C per hectare per year in central Indiana, and were also well correlated with Nmin. There was less variation among sites in estimates of ΔC (range, 1.8–3.2 Mg C per hectare per year). In general, ΔC more closely matched NEE than did NEP, but there was no systematic pattern among sites in over- versus under-estimation of the biometric compared to the meteorologically based measures. Root and soil carbon dynamics were significant sources of uncertainty in our biometric measures and represent a prerequisite area of study needed for accurate estimates of forest carbon storage.

Abstract We present a decadal (1994–2004) record of carbon dioxide flux in a 160‐year‐old black spruce forest/veneer bog complex in central Manitoba, Canada. The ecosystem shifted from a source (+41 g C m −2 , 1995) to a sink (−21 g C m −2 , 2004) of CO 2 over the decade, with an average net carbon balance near zero. Annual mean temperatures increased 1–2° during the period, consistent with the decadal trend across the North American boreal biome. We found that ecosystem carbon exchange responded strongly to air temperature, moisture status, potential evapotranspiration, and summertime solar radiation. The seasonal cycle of ecosystem respiration significantly lagged that of photosynthesis, limited by the rate of soil thaw and the slow drainage of the soil column. Factors acting over long time scales, especially water table depth, strongly influenced the carbon budget on annual time scales. Net uptake was enhanced and respiration inhibited by multiple years of rainfall in excess of evaporative demand. Contrary to expectations, we observed no correlation between longer growing seasons and net uptake, possibly because of offsetting increases in ecosystem respiration. The results indicate that the interactions between soil thaw and water table depth provide critical controls on carbon exchange in boreal forests underlain by peat, on seasonal to decadal time scales, and these factors must be simulated in terrestrial biosphere models to predict response of these regions to future climate.

[1] Climate change is expected to significantly impact global food production, and it is important to understand the potential geographic distribution of yield losses and the means to alleviate them. This study presents a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) that integrates, in addition to climate, the effect of planting dates and cultivar choices, irrigation, and fertilizer application on crop yield for maize, soybean, and spring wheat. PEGASUS combines carbon dynamics for crops with a surface energy and soil water balance model. It also benefits from the recent development of a suite of global data sets and analyses that serve as model inputs or as calibration data. These include data on crop planting and harvesting dates, crop-specific irrigated areas, a global analysis of yield gaps, and harvested area and yield of major crops. Model results for present-day climate and farm management compare reasonably well with global data. Simulated planting and harvesting dates are within the range of crop calendar observations in more than 75% of the total crop-harvested areas. Correlation of simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop-harvested area, of 0.81 for maize, 0.66 for soybean, and 0.45 for spring wheat. We found that changes in temperature and precipitation as predicted by global climate models for the 2050s lead to a global yield reduction if planting and harvesting dates remain unchanged. However, adapting planting dates and cultivar choices increases yield in temperate regions and avoids 7–18% of global losses.

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.

Livestock husbandry in the U.S. significantly contributes to many environmental problems, including the release of methane, a potent greenhouse gas (GHG). Anaerobic digesters (ADs) break down organic wastes using bacteria that produce methane, which can be collected and combusted to generate electricity. ADs also reduce odors and pathogens that are common with manure storage and the digested manure can be used as a fertilizer. There are relatively few ADs in the U.S., mainly due to their high capital costs. We use the MIT Emissions Prediction and Policy Analysis (EPPA) model to test the effects of a representative U.S. climate stabilization policy on the adoption of ADs which sell electricity and generate methane mitigation credits. Under such policy, ADs become competitive at producing electricity in 2025, when they receive methane reduction credits and electricity from fossil fuels becomes more expensive. We find that ADs have the potential to generate 5.5% of U.S. electricity.

Nitrogen stable-isotope compositions (delta15N) can help track denitrification and N2O production in the environment, as can knowledge of the isotopic discrimination, or isotope effect, inherent to denitrification. However, the isotope effects associated with denitrification as a function of dissolved-oxygen concentration and their influence on the isotopic composition of N2O are not known. We developed a simple steady-state reactor to allow the measurement of denitrification isotope effects in Paracoccus denitrificans. With [dO2] between 0 and 1.2 microM, the N stable-isotope effects of NO3- and N2O reduction were constant at 28.6 per thousand +/- 1.9 per thousand and 12.9 per thousand +/- 2.6 per thousand, respectively (mean +/- standard error, n = 5). This estimate of the isotope effect of N2O reduction is the first in an axenic denitrifying culture and places the delta15N of denitrification-produced N2O midway between those of the nitrogenous oxide substrates and the product N2 in steady-state systems. Application of both isotope effects to N2O cycling studies is discussed.

We utilized eddy-covariance observations of carbon dioxide (CO2) and water vapor exchange at three AmeriFlux mid-latitude forest stands to evaluate IBIS, a Dynamic Global Vegetation Model (DGVM). Measurements of leaf area index (LAI), soil moisture and temperature, runoff, soil carbon (C), and soil respiration (R) were also compared with model output. An experimental approach was designed to help attribute model errors to the vegetation dynamics and phenology formulations versus simulated biological processes. Continental scale phenology sub-models poorly represented the timing of budburst and evolution of canopy LAI in deciduous forests. Biases of vegetation green-up of 6 weeks and delayed senescence were noted. Simulated soil temperatures were overestimated (underestimated) during the summer (winter) on average by 2–5 °C. Ecosystem R was overestimated during the growing season, on average, by 20–60 g C m−2 month−1, and underestimated during the winter by 10–20 g C m−2 month−1 at all sites. Simulated soil R failed to capture observed mid-summer peak rates and was generally lower than observed in winter. The overall comparison of simulated net ecosystem production (NEP) to observations showed a significant underestimate of growing season NEP of 25–100 g C m−2 month−1, and an overall positive bias of 10–40 g C m−2 month−1 during the winter. Excellent agreement between annual average NEP observations and IBIS simulations in “fixed vegetation” mode resulted from offsetting seasonal model biases. The magnitude of simulated variation in seasonal and inter-annual C exchange was generally dampened with respect to observations. The parameterization, and in some cases the formulations (e.g., ecosystem R and phenology) limited model capacity to capture the seasonal fluctuations of C and water exchange. Model parameterizations and formulations were originally constrained and generalized for application to a wide range of global climate and soil conditions and plant functional types (PFTs), likely contributing to model biases. This problem potentially applies to other DGVMs and biosphere models, and will likely become increasingly relevant if investigators apply their models at higher spatial resolution. We suggest that revisions to DGVMs should focus on advancing the capabilities of current phenology formulations to account for photoperiod, soil moisture and frost in addition to temperature. Model representations of PFTs and formulations of ecosystem R need to be rethought, particularly with respect to use of Q10 temperature functions as modifiers. Surface energy balance, C allocation, soil R, and plant response to nutrient stress deserve attention as well.

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.

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.

Atmospheric heat and moisture over land are fundamental drivers of monsoon circulations.However, these drivers are less frequently considered in explaining the development and overall intensity of monsoons than heat and moisture over the ocean.In this study, the roles of turbulent heat fluxes over land in the monsoon system over East Asia are examined using Climatic Research Unit observations and European Centre for Medium-Range Weather Forecasts reanalysis, and they are further explored using simulated sensible (H) and latent (LE) heat fluxes from an ecosystem model (Predicting Ecosystem Goods and Services Using Scenarios or PEGASUS).Changes in the H fluxes over the land during the pre-monsoon season (March-May: MAM) affect the differential heating between land and ocean, which in turn controls monsoon development.In July, an intensified contrast of the mean sea level pressure between land and ocean is observed during the years of stronger land-sea H contrast in MAM, which results in enhanced onshore flows and more rainfall over southern East Asia.After monsoon onset, the contrast of H is influenced by monsoon rainfall through the cooling effect of precipitation on surface air temperature.During the monsoon season (June-September: JJAS), LE fluxes are more important than H fluxes, since LE fluxes over land and ocean affect overall monsoon intensity through changes in the land-sea contrast of turbulent heat fluxes.Significantly increased monsoon rainfall over western East Asia is observed during the years of larger LE over the land in JJAS.In ecosystem modeling, we find that the monsoon can be weakened as potential (natural) vegetation is converted to bare ground or irrigated cropland.Simulated H fluxes in MAM and LE fluxes in JJAS over the land significantly decrease in irrigated crop and bare ground scenarios, respectively, which play crucial roles in controlling monsoon development and overall intensity.

To help young people understand socio-environmental systems and develop the confidence that meaningful action can be taken to address socio-environmental problems, young people need interactive simulations that enable them to take consequential actions in a familiar context and see the results. This can be achieved through reduced-form models with appropriate user interfaces, but it is a significant challenge to construct a system capable of producing educational models of socio-environmental systems that are localizable and customizable but accessible to educators and learners. In this paper, we present iPlan, a free, online educational software application designed to enable educators and middle- and high-school-aged learners to create custom, localized land-use simulations that can be used to frame, explore, and address complex land-use problems. We describe in detail the software application and its underlying computational models, and we present robust evidence that the accuracy of iPlan simulations is appropriate for educational contexts and preliminary evidence that educators are able to produce simulations suitable for their pedagogical goals and learner populations.

Growing concerns about environmental impacts of dairy farms have driven producers to address greenhouse gas (GHG) emissions and nitrogen (N) losses from soil following land application of dairy manure. Tannin dietary additives have proved to be a successful intervention for mitigating GHG and ammonia (NH3 ) emissions at the barn scale. However, it is unknown how land application of dairy manure from cows fed tannin diets affects crop-soil nitrogen dynamics and soil GHG flux. To test this, cows were fed diets at three levels of tannins (0.0%, 0.4%, and 1.8% of dry matter intake) and their manure was field applied at two N rates (240 and 360 kg N ha-1 ). Soil NH4+ -N, NO3- -N, corn silage yield, and soil GHG flux were then measured over a full growing season. Soils amended with tannin manure had lower initial NH4+ -N concentrations and lower total mineral N (NH4+ -N + NO3- -N) concentrations 19 days after application, compared to soils amended with no tannin manures. Despite lower early season N availability in tannin-fertilized plots, there were no differences in corn silage yield. No differences in soil GHG and NH3 emissions were observed between manure-amended treatments. These results demonstrate that while tannin addition to dairy cow feed does not offer short-term GHG or NH3 emissions reductions after field manure application, it can promote slower soil N mineralization that may reduce reactive N loss after initial application.

In this paper we consider the risks to Internet infrastructure in the US due to sea level rise. Our study is based on sea level incursion projections from the National Oceanic and Atmospheric Administration (NOAA) [12] and Internet infrastructure deployment data from Internet Atlas [24]. We align the data formats and assess risks in terms of the amount and type of infrastructure that will be under water in different time intervals over the next 100 years. We find that 4,067 miles of fiber conduit will be under water and 1,101 nodes (e.g., points of presence and colocation centers) will be surrounded by water in the next 15 years. We further quantify the risks of sea level rise by defining a metric that considers the combination of geographic scope and Internet infrastructure density. We use this metric to examine different regions and find that the New York, Miami, and Seattle metropolitan areas are at highest risk. We also quantify the risks to individual service provider infrastructures and find that CenturyLink, Inteliquent, and AT&T are at highest risk. While it is difficult to project the impact of countermeasures such as sea walls, our results suggest the urgency of developing mitigation strategies and alternative infrastructure deployments.

Natural disasters can wreak havoc on Internet infrastructure. Short term impacts include impediments to first responders and long term impacts include requirements to repair or replace damaged physical components. In this paper, we present an analysis of the vulnerability of cellular communication infrastructure in the US to one type of natural disaster - wildfires. Three data sets are the basis for our study: historical wildfire records, wildfire risk projections, and cellular infrastructure deployment. We utilize the geographic features in each data set to assess the spatial overlap between historical wildfires and cellular infrastructure and to analyze current vulnerability. We find wide variability in the number of cell transceivers that were within wildfire perimeters over the past 18 years. In a focused analysis of the California wildfires of 2019, we find that the primary risk to cellular communication is power outage rather than cellular equipment damage. Our analysis of future risk based on wildfire hazard potential identifies California, Florida and Texas as the three states with the largest number of cell transceivers at risk. Importantly, we find that many of the areas at high risk are quite close to urban population centers, thus outages could have serious impacts on a large number of cell users. We believe that our study has important implications for governmental communication assurance efforts and for risk planning by cell infrastructure owners and service providers.

The large majority of electrical power in the United States today is generated from fossil feedstocks. While renewable energy sources offer compelling alternatives, there are many challenges and complexities that currently limit their use. The high-level objective of our work is to create an analytic framework to provide decision support for renewable energy use in electrical power generation in the US. For security reasons, many of the details of the infrastructure that would facilitate our work are not openly available. Thus, we seek to infer key properties of the power generation and transmission infrastructures, using alternative data sources and recognizing that grid dynamics are constrained by federal regulation and the laws of physics. In this discussion paper we describe the design space for our study and our initial analyses of energy pricing data. These data are openly available from Regional Transmission Organizations and Independent System Operators. Our results highlight the complexities and dynamics of the relationships between locations in the power grid, and set the stage for inferring physical and behavioral properties of the power grid.

There is a growing sense of the fragility of agricultural production in the Global North and South and of increasing risks to food security, as scientific observations confirm significant changes in the Gulf Stream, polar ice, atmospheric CO2, methane release, and other measures of climate change. This sense is heightened as each of us experiences extreme weather, such as the increasing frequency of droughts, floods, unseasonal temperatures, and erratic seasonality. The central research challenge before us is how global, national, regional, and local food systems may adapt to accelerating climate change stresses and uncertainties to ensure the availability, access, consumption, and stability of healthy food for and by all people. Missing aspects of research fall into two broad categories: the impacts of rapid climate change on the environmental systems supporting food production, and climate change's impact on the predominantly human systems that influence food security. Of particular concern is how different policy and governance mechanisms can support or hinder the collective decision-making needed to promote a swift adaptive response to increase and sustain food security. Human systems research is needed to investigate food system activities beyond production (processing, distribution, consumption, and waste management). It also must consider political, cultural, and regulatory factors that influence behavior and facilitate positive behavioral changes. To accurately envision future scenarios, research is needed to characterize risk comprehensively throughout the food system, assess barriers to and opportunities for changing food systems, and evaluate novel and traditional approaches that may lead to greater food security.

Abstract Agricultural data are crucial to many aspects of production, commerce, and research involved in feeding the global community. However, in most agricultural research disciplines standard best practices for data management and publication do not exist. Here we propose a set of best practices in the areas of peer review, minimal dataset development, data repositories, citizen science initiatives, and support for best data management. We illustrate some of these best practices with a case study in dairy agroecosystems research. While many common, and increasingly disparate data management and publication practices are entrenched in agricultural disciplines, opportunities are readily available for promoting and adopting best practices that better enable and enhance data‐intensive agricultural research and production.

The potential supply of bioenergy from farm-grown biomass is uncertain due to several poorly understood or volatile factors, including land availability, yield variability, and energy prices. Although biomass production for liquid fuel has received more attention, here we present a case study of biomass production for renewable heat and power in the state of Wisconsin (US), where heating constitutes at least 30% of total energy demand. Using three bioenergy systems (50 kW, 8.8 MW and 50 MW) and Wisconsin farm-level data, we determined the net farm income effect of producing switchgrass (Panicum virgatum) as a feedstock, either for on-farm use (50 kW system) or for sale to an off-farm energy system operator (8.8 and 50 MW systems). In southern counties, where switchgrass yields approach 10 Mg ha 1 yr 1 , the main determinants of economic feasibility were the available land area per farm, the ability to utilize bioheat, and opportunity cost assumptions. Switchgrass yield temporal variability was less important. For the state median farm size and switchgrass yield, at least 25% (50 kW system) or 50% (8.8 MW system) bioheat utilization was required to economically offset propane or natural gas heat, respectively, and purchased electricity. Offsetting electricity only (50 MW system) did not generate enough revenue to meet switchgrass production expenses. Although the opportunity cost of small-scale (50 kW) on-farm bioenergy generation was higher, it also held greater opportunity for increasing farm net income, especially by replacing propane-based heat.

Sustainable use of the freshwater resources of the world is an urgent challenge. The World Health Organization recently estimated that 1.1 billion people lack access to safe drinking water, a problem the United Nations highlights in its Millennium Development Goals. To address the scale and urgency of this challenge, IBM, The Nature Conservancy, and the Center for Sustainability and the Global Environment at the University of Wisconsin-Madison are collaborating to develop innovative, technology-based decision-support tools for improved management of water resources worldwide. The Water for Tomorrow modeling framework and decision support system (DSS) is designed to help policy makers and a variety of stakeholders to assess, come to consensus, and act on land-use decisions that balance human use, ecosystem preservation, and ecosystem restoration. Such stakeholders include farmers, fish and wildlife managers, food-processing plant managers, and hydropower operators. Initially focused on the Paraguay-Paraná Basin of Brazil, in partnership with local academic and public-sector collaborators, the DSS integrates data and models from a wide variety of environmental sectors, including water balance, water quality, carbon balance, crop production, and proxies for biodiversity. Intuitive interfaces and complex query support allow users to reach a rich understanding of the effect of changes in management on freshwater ecosystems.

Microbiological contamination of crops within space-based plant growth research chambers has been postulated as a potentially significant problem. Microbial infestations; fouling of Nutrient Delivery System (NDS) fluid loops; and the formation of biofilms have been suggested as the most obvious and important manifestations of the problem. Strict sanitation and quarantine procedures will reduce, but not eliminate, microbial species introduced into plant growth systems in space habitats. Microorganisms transported into space most likely will occur as surface contaminants on spacecraft components, equipment, the crew, and plant-propagative materials. Illustrations of the potential magnitude of the microbiological contamination issue will be drawn from the literature and from documentation of laboratory and commercial field experience. Engineering strategies for limiting contamination and for the development of countermeasures will be described. Microbiological control technologies and NDS hardware will be discussed. Configurations appropriate for microgravity research facilities, as well as anticipated bio-regenerative life support system implementations, will be explored. An efficiently designed NDS, capable of adequately meeting the environmental needs of crop plants in space, is considered to be critical in both the research and operational domains. Recommended experiments, tests, and technology developments, structured to allow the development of prudent engineering solutions also will be presented.

Water Environment ResearchVolume 69, Issue 4 p. 487-500 Treatment SystemFree Access Biological fixed-film systems Jennifer B. Brower, Jennifer B. BrowerSearch for more papers by this authorCarol C. Barford, Carol C. BarfordSearch for more papers by this author Jennifer B. Brower, Jennifer B. BrowerSearch for more papers by this authorCarol C. Barford, Carol C. BarfordSearch for more papers by this author First published: 15 June 1997 https://doi.org/10.2175/106143097X134795Citations: 2AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Citing Literature Volume69, Issue41997 Literature ReviewJune 1997Pages 487-500 RelatedInformation

Water Environment ResearchVolume 68, Issue 4 p. 469-479 Treatment SystemFree Access Biological fixed-film systems Jennifer B. Brower, Jennifer B. BrowerSearch for more papers by this authorCarol C. Barford, Carol C. BarfordSearch for more papers by this authorOliver J. Hao, Oliver J. HaoSearch for more papers by this author Jennifer B. Brower, Jennifer B. BrowerSearch for more papers by this authorCarol C. Barford, Carol C. BarfordSearch for more papers by this authorOliver J. Hao, Oliver J. HaoSearch for more papers by this author First published: June 1996 https://doi.org/10.2175/106143096X135326Citations: 2AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Citing Literature Volume68, Issue41996 Literature ReviewJune 1996Pages 469-479 RelatedInformation

Determining changes in the composition of cell populations is made possible by technologies like single-cell transcriptomics, CyTOF, and microbiome sequencing. However, existing methods for differential abundance do not model some ...Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to ...

and Introduction In order to quantify the impact of shifts in land use patterns on the climate, a complementary approach to global climate models (GCMs) has been developed. The model presented here is specifically designed to investigate the impacts of changing land use on the earth's surface and lower atmosphere. It is capable of testing the impact of an ensemble of land use scenarios quickly and easily with limited input requirements. Here we present a comparison of the modeled land surface and atmospheric boundary layer variables to several field experiment observation sites, as well as initial studies on impacts of a variety of land-use perturbations on regional climate. The motivation for the development of this model comes from observations that use of land by humans has become a strong forcing on the global climate system. Since 1850, changes in anthropogenic land use have accounted for nearly 35% of global CO2 emissions, and croplands and pastures have now become one of the largest biomes on earth (Foley et al 2005). While the carbon emissions associated with land use change are critical, the impact of changing land cover on earth's climate is not limited to the sequestration or release of carbon. Conversion of natural biomes to croplands or pastures also upsets the services that an ecosystem provides by perturbing the surface water, energy and momentum balances. Historically, the tool used to investigate the impacts of changing land use has been the GCM. However, GCM experiments can be both expensive to run and difficult to interpret. In addition, the strength of GCMs lie in their ability to simulate changes of large-scale patterns and circulations of the climate system over long periods of time, and not local and regional scales where results are commonly biased relative to observations. The model presented in this work attempts to alleviate some of these problems. This is partially achieved through the following highlights of the model: o A data driven land surface model that has been simplified to the basic physics necessary to accurately reproduce observed seasonal cycles of fluxes and state variables for both natural biomes and croplands/pastures. o A bulk quasi 3-D boundary layer model that maintains the first order response of the lower atmosphere state variables to changing land surfaces, but discards secondary 3-D effects. o Land cover and phenology that can be easily manipulated. o Statistical impacts of land use change on precipitation using data described in Dirmeyer and Brubaker (1999) The simplicity of our new model comes at the cost of assuming that changes to the land cover are relatively small perturbations to the overall climate. This model does not currently simulate circulation changes in the atmosphere, ocean or sea ice that are important to the distribution and balance of earth's long-term global energy budget. However, for many applications associated with land use scenarios this assumption is valid. poster session GC13A Model Objectives and Poster Focus As shown in figure 1, the current extent of Earth's usable land appropriated for use by humans now stands at approximately 40% (Foley 2005), rivalling global forests in extent. The large majority of this area is appropriated for the production of food necessary to feed 6.7 billion people. While the Green Revolution that began in the 1960's has nearly doubled the global food yield with only a 12% increase in cropland, it has also led to environmental concerns such as large-scale salinization, soil erosion, and loss of native vegetation. With global population expected increase to approximately 9 billion by 2050, it is inevitable that the alterations of the world's will continue. These alterations will directly impact the goods and services that are provided by present vegetation. This work focuses on modeling and assessing changes in ecosystem goods and services associated with land use changes. References [1] J. A. Foley et al., 2005 Science, 309, 570. [2] P. A. Dirmeyer and K. L. Brubaker, 1999 J. of Geophys. Res. 104, 19383-19397 [3] J. H. C. Gash and C. A. Nobre, 1997 BAMS 78, 823-830 [4] C. P. Kim and D. Entekhabi, 1998 Boundary-Layer Met. 88, 1-21 [5] O. Pechony and D. T. Shindell, 2009 JGR 114, D16115 [6] Images courtesy of NASA MODIS webpage: http://rapidfire.sci.gsfc.nasa.gov/firemaps Model Properties In the past, the common tool used to explore the impacts of large scale land use change was the GCM. While the GCM is incredibly powerful, the cost of simulating the earth system is high and resolution is low. Here we take a complementary approach, by specifying the mean climate, and assuming that land use changes represent relatively small perturbations on the global climate. This allows us to greatly simplify our model by reducing the atmosphere to the region directly interacting with the land. We use a bulk model similar to that of [4] to represent the convective boundary layer and interaction of the land with the atmosphere. A schematic of the bulk model is shown in figure 2. Treatment of Precipitation One aspect of land use change that is clear, is that as land cover changes the amount of water that is evaporated into the atmosphere also changes. This will have nonlocal impacts on precipitation. With the importance of precipitation to human enterprise, it is vital that our model is capable of estimating this change. In the absence of an atmospheric circulation model, we use a statistical model to estimate precipitation impacts. Boundary Layer Impacts of Changing Land Cover Initial Comparison of Surface Energy Balance and Boundary Layer Properties to Observations A Simple Fire Parameterization Application Future Work Building off of the work presented here, we have a series of tasks that we plan to carry out. Some of the key tasks include the following: Analyzing observations from the BOREAS and FIFE field campaigns, as well as Wisconsin flux towers to expand our model validation to higher latitude biomes. Integrating precipitation data from locations beyond the Amazon basin. Comparing deforestation scenarios in our model to similar scenarios using GCMs to test the robustness of the boundary layer and statistical precipitation models. Expand the applications of our model. In particular, we are looking at applications where an ensemble of high resolution scenarios are necessary, making Figure 1: The worldwide extent of human land use change. The map gives the extent of croplands (top) and pastures and rangelands (bottom). (From Foley 2005 [1]) BLH Free Atmosphere

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