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Marginal land has received wide attention for its potential to produce bioenergy feedstocks while minimizing diversion of productive agricultural land from food crop production. However, there has been no consensus in the literature on how to define or identify land that is marginal for food crops and beneficial for bioenergy crops. Studies have used different definitions to quantify the amount of such land available; these have largely been based on assumed biophysical thresholds for soil quality and productivity that are unchanging over space and time. We discuss the limitations of these definitions and the rationale for considering economic returns and environmental outcomes in classifying land as marginal. We then propose the concept of "socially" marginal which is defined as land that is earning close to zero returns after accounting for the monetized costs of environmental externalities generated. We discuss a broad set of criteria for classifying land as socially marginal for food crops and suitable for bioenergy crops; with these criteria, this classification depends on spatially varying and time‐varying factors, such as climate and market conditions and policy incentives. While there are challenges related to identifying this marginal land, satellite and other large‐scale datasets increasingly enable such analysis at a fine spatial resolution. We also discuss reasons why landowners might choose not to convert bioenergy‐suitable land to bioenergy crops, and thus the need for policy incentives to support conversion of land that is socially beneficial for bioenergy crop production. [ABSTRACT FROM AUTHOR]

Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield‐scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed. [ABSTRACT FROM AUTHOR]

Crop production in the Central High Plains is at an all-time high due to increased demand for biofuels, food, and animal products. Despite the need to produce more food by mid-century to meet expected population growth, under current management and genetics, crop production is likely to plateau or decline in the Central High Plains due to groundwater withdrawal at rates that greatly exceed recharge to the aquifer. The Central High Plains has experienced a consistent decline in groundwater storage due to groundwater withdrawal for irrigation greatly exceeding natural recharge. In this heavily irrigated region, water is essential to maintain yields and economic stability. Here, we evaluate how current trends in irrigation demand may impact groundwater depletion and quantify the impacts of these changes on crop yield and production through to 2099 using the well-established System Approach to Land Use Sustainability (SALUS) crop model. The results show that status quo groundwater management will likely reduce irrigated corn acreage by ~60% and wheat acreage by ~50%. This widespread forced shift to dryland farming, coupled with the likely effects of climate change, will contribute to overall changes in crop production. Taking into account both changes in yield and available irrigated acreage, corn production would decrease by approximately 60%, while production of wheat would remain fairly steady with a slight increase of about 2%. [ABSTRACT FROM AUTHOR]

Switchgrass ( Panicum virgatum) productivity on marginal and fertile lands has not been thoroughly evaluated in a systematic manner that includes soil-crop-weather-management interactions and to quantify the risk of failure or success in growing the crop. We used the Systems Approach to Land Use Sustainability ( SALUS) model to identify areas with low risk of failing to having more than 8000 kg ha−1 yr−1 switchgrass aboveground net primary productivity ( ANPP) under rainfed and unfertilized conditions. In addition, we diagnosed constraining factors for switchgrass growth, and tested the effect of nitrogen fertilizer application on plant productivity across Michigan for 30 years under three climate scenarios (baseline climate in 1981-2010, future climate with emissions using RCP 2.6 and RCP 6.0). We determined that <16% of land in Michigan may have at least 8 Mg ha−1 yr−1 ANPP under rainfed and unfertilized management with a low risk of failure. Of the productive low-risk land, about 25% was marginal land, with more than 80% of which was affected by limited water availability due to low soil water-holding capacity and shallow depth. About 80% of the marginal land was N limited under baseline conditions, but that percentage decreased to 58.5% and 42.1% under RCP 2.6 and RCP 6.0 climate scenarios, respectively, partly due to shorter growing season, smaller plants and less N demand. We also found that the majority of Michigan's land could have high switchgrass ANPP and low risk of failure with no more than 60 kgN ha−1 fertilizer input. We believe that the methodology used in this study works at different spatial scales, as well as for other biofuel crops. [ABSTRACT FROM AUTHOR]

Reactive nitrogen loss from agricultural fertilizer use remains a crucial environmental problem in the United States, contributing to ecosystem degradation and global climate change. This intractable problem requires a coupled human and natural systems approach that combines biophysical, sociological, and economic knowledge into an integrative analysis. Much is known about the biogeochemistry of nitrogen and agricultural nitrogen loss; however, much is not known about how soil variability and climate change will affect farmer decisionmaking. Although it is widely understood that personal values and beliefs, social norms, economics, and policies influence farmer decisionmaking, very little is known about decisionmaking specific to fertilizer management. In addition, little is known about the socioeconomic influences on decisionmaking across scales and how ecological change is perceived and responded to. Combining sociological, economic, and biophysical knowledge can provide key insights regarding how these factors interact and can support more effective strategies to address this persistent problem. [ABSTRACT FROM AUTHOR]

Abstract: Appropriate nitrogen management is one of the main challenges of agricultural production and for the environment. The objectives of this study were to evaluate the efficiency of crop N uptake in a long-term wheat crop in a Mediterranean environment of Southern Italy, and to identify optimal N rate for reasonable economic returns and minimum nitrate leaching using SALUS crop simulation model. The study was part of a long-term monoculture wheat system that started in 1991/1992 season, with two levels of nitrogen (0 and 90kgNha−1). Simulations of the treatment with no nitrogen (0N) and 90kgNha−1 (90N) were performed using the SALUS crop model for wheat. The model was tested against measurements of harvested grain yield, final N uptake, soil water content and total soil N. Long-term simulation over 56 years showed that grain yield median value was 3435kgha−1 for 0N and 3876kgha−1 for 90N. Simulation scenarios with different N rates (0, 30, 60, 90, 120, 180kgNha−1) showed that yield response was higher for 120N (3528kgha−1), with the 60 and 90N yields giving the same response, 3010 and 3054kgha−1, respectively. The most profitable treatments were 120N (302Euroha−1), followed by the 60N (220Euroha−1). The simulation results showed that nitrate leaching was higher for the N rate of 120 and 180 with a mean annual value of 49 and 81kgha−1, respectively. Results suggest that in such environment 60kgNha−1 can be the most appropriate as an N fertilization management due to the best trade-off between leaching and economic. Since N fertilization rates are linked to nitrous oxide (N2O) emissions and N leaching, a trade-off between N fertilization rates profit and grain yield should be thought as way to reduce environmental pollution while keeping productivity and profit. The adoption of simulation models to approximate the best N rate for durum wheat in rainfed Mediterranean environment proved to be a useful tool for supporting management decisions through quantifying the temporal variability related to weather uncertainty as it influences on the yield and nutrient dynamics. [Copyright &y& Elsevier]

This paper describes our efforts to integrate economic and biophysical models to evaluate the effects agri-environmental policies have on the value of freshwater ecosystem services. We are developing an integrated assessment model (IAM) that links changes in phosphorus-related management practices on farm fields to changes in the value of key freshwater ecosystem services, including biological condition, water clarity, species-specific fish biomasses, and beach algae. Our IAM approach enables examination of the effects of policies and conservation programs on ecosystem services and values. Results will help policy makers allocate conservation dollars to improve water quality, enhance ecosystem services, and promote more sustainable agricultural production. (JEL Q24, Q51) [ABSTRACT FROM AUTHOR]

Accounting for nitrogen (N) release from organic amendments (OA) can reduce the use of synthetic N-fertiliser, sustain crop production, and potentially reduce soil borne greenhouse gases (GHG) emissions. However, it is difficult to assess the GHG mitigation potential for OA as a substitute of N-fertiliser over the long term due to only part of the organic N added to soil is being released in the first year after application. High-resolution nitrous oxide (N 2 O) and carbon dioxide (CO 2 ) emissions monitored from a horticultural crop rotation over 2.5 years from conventional urea application rates were compared to treatments receiving an annual application of raw and composted chicken manure combined with conventional and reduced N-fertiliser rates. The repeated application of composted manure did not increase annual N 2 O emissions while the application of raw manure resulted in N 2 O emissions up to 35.2 times higher than the zero N fertiliser treatment and up to 4.7 times higher than conventional N-fertiliser rate due to an increase in C and N availability following the repeated application of raw OA. The main factor driving N 2 O emissions was the incorporation of organic material accompanied by high soil moisture while the application of synthetic N-fertiliser induced only short-term N 2 O emission pulse. The average annual N 2 O emission factor calculated accounting for the total N applied including OA was equal to 0.27 ± 0.17%, 3.7 times lower than the IPCC default value. Accounting for the estimated N release from OA only enabled a more realistic N 2 O emission factor to be defined for organically amended field that was equal to 0.48 ± 0.3%. This study demonstrated that accounting for the N released from repeated application of composted rather than raw manure can be a viable pathway to reduce N 2 O emissions and maintain soil fertility. [ABSTRACT FROM AUTHOR]

With world population growing quickly, agriculture needs to produce more with fewer inputs while being environmentally friendly. In a context of changing environments, crop models are useful tools to simulate crop yields. Wheat ( Triticum spp.) crop models have been evolving since the 1960s to translate processes related to crop growth and development into mathematical equations. These have been used over decades for agronomic purposes, and have more recently incorporated advances in the modeling of environmental footprints, biotic constraints, trait and gene effects, climate change impact, and the upscaling of global change impacts. This review outlines the potential and limitations of modern wheat crop models in assisting agronomists, breeders, and policymakers to address the current and future challenges facing agriculture. [ABSTRACT FROM AUTHOR]

Projected global warming and population growth will reduce future water availability for agriculture. Thus, it is essential to increase the efficiency in using water to ensure crop productivity. Quantifying crop water use (WU; i.e. actual evapotranspiration) is a critical step towards this goal. Here, sixteen wheat simulation models were used to quantify sources of model uncertainty and to estimate the relative changes and variability between models for simulated WU, water use efficiency (WUE, WU per unit of grain dry mass produced), transpiration efficiency ( T eff , transpiration per kg of unit of grain yield dry mass produced), grain yield, crop transpiration and soil evaporation at increased temperatures and elevated atmospheric carbon dioxide concentrations ([CO 2 ]). The greatest uncertainty in simulating water use, potential evapotranspiration, crop transpiration and soil evaporation was due to differences in how crop transpiration was modelled and accounted for 50% of the total variability among models. The simulation results for the sensitivity to temperature indicated that crop WU will decline with increasing temperature due to reduced growing seasons. The uncertainties in simulated crop WU, and in particularly due to uncertainties in simulating crop transpiration, were greater under conditions of increased temperatures and with high temperatures in combination with elevated atmospheric [CO 2 ] concentrations. Hence the simulation of crop WU, and in particularly crop transpiration under higher temperature, needs to be improved and evaluated with field measurements before models can be used to simulate climate change impacts on future crop water demand. [ABSTRACT FROM AUTHOR]