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Minnesota is the U.S. state with the strongest winter warming in the contiguous United States. We performed regional climate projections at 10 km horizontal resolution using the WRF model forced by...

International audience; Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

The goal of this research is to determine the changes in streamflow, dissolved inorganic nitrogen (DIN) leaching and export to the Gulf of Mexico associated with a range of large-scale dedicated perennial cellulosic bioenergy production scenarios within in the Mississippi-Atchafalaya River Basin (MARB). To achieve this goal, we used Agro-IBIS, a vegetation model capable of simulating the biogeochemistry of row crops, miscanthus and switchgrass, coupled with THMB, a hydrology model capable of simulating streamflow and DIN export. Simulations were conducted at varying fertilizer application rates (0 to 200 kg N ha−1) and fractional replacement (5 to 25%) of current row crops with miscanthus or switchgrass across the MARB. The analysis also includes two scenarios where miscanthus and switchgrass (MRX and MRS respectively) each replace the ca. 40% of maize production currently devoted to ethanol. Across the scenarios, there were minor reductions in runoff and streamflow throughout the MARB, with the largest differences (ca. 6%) occurring for miscanthus at the highest fractional replacement scenarios in drier portions of the region. However, differences in total MARB discharge at the basin outlet were less than 1.5% even in the MRX scenario. Reductions in DIN export were much larger on a percentage basis than reductions in runoff, with the highest replacement scenarios decreasing long-term mean DIN export by ca. 15 and 20% for switchgrass and miscanthus, respectively. Fertilization scenarios show that significant reductions in DIN leaching are possible even with application rates of 100 and 150 kg N ha−1 for switchgrass and miscanthus respectively. These results indicate that, given targeted management strategies, there is potential for miscanthus and switchgrass to provide key ecosystem services by reducing the export of DIN, while avoiding hydrologic impacts of reduced streamflow. This article is protected by copyright. All rights reserved.

Summary The energy and water balance of a Phragmites australis dominated wetland in south central Nebraska was analyzed to assess consumptive water use and the potential for “water savings” as a result of vegetation eradication via herbicide treatment. Energy balance measurements were made at the field site for two growing seasons (treated and untreated), including observations of net radiation, heat storage, and sensible heat flux, which was measured using a large-aperture scintillometer. Latent heat flux was calculated as a residual of the energy balance, and comparisons were made between the two growing seasons and with model simulations to examine the relative impacts of vegetation removal and climate variability. Observed ET rates dropped by roughly 32% between the two growing seasons, from a mean of 4.4 ± 0.7 mm day−1 in 2009 (with live vegetation) to 3.0 ± 0.8 mm day−1 in 2010 (with dead P. australis). These results are corroborated by the Agro-IBIS model simulations, and the reduction in ET implies a total “water savings” of 245 mm over the course of the growing season. The significant decreases in ET were accompanied by a more-than-doubling of sensible heat flux, as well as a ∼60% increase in heat storage due to decreased LAI. Removal of P. australis was also found to cause measurable changes in the local micrometeorology at the wetland. Consistent with the observed increase in sensible heat flux during 2010, warmer, drier, windier conditions were observed in the dead, P. australis section of the wetland, compared to an undisturbed section of live, native vegetation. Modeling results suggest that the elimination of transpiration in 2010 was partially offset by an increase in surface evaporation, thereby reducing the subsequent water savings by roughly 60%. Thus, the impact of vegetation removal depends on the local climate, depth to groundwater, and management decisions related to regrowth of vegetation.

International audience; Crop yield can be affected by crop water use and vice versa, so when trying to simulate one or the other, it can be important that both are simulated well. In a prior inter-comparison among maize growth models, evapotranspiration (ET) predictions varied widely, but no observations of actual ET were available for comparison. Therefore, this follow-up study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Observations of daily ET using the eddy covariance technique from an 8-year-long (2006-2013) experiment conducted at Ames, IA were used as the standard for comparison among models. Simulation results from 29 models are reported herein. In the first "blind" phase for which only weather, soils, phenology, and management information were provided to the modelers, estimates of seasonal ET varied from about 200 to about 700 mm. Subsequent three phases provided (1) leaf area indices for all years, (2) all daily ET and agronomic data for a typical year (2011), and (3) all data for all years, thus allowing the modelers to progressively calibrate their models as more information was provided, but the range among ET estimates still varied by a factor of two or more. Much of the variability among the models was due to differing estimates of potential evapotranspiration, which suggests an avenue for substantial model improvement. Nevertheless, the ensemble median values were generally close to the observations, and the medians were best (had the lowest mean squared deviations from observations, MSD) for several ET categories for inter-comparison, but not all. Further, the medians were best when considering both ET and agronomic parameters together. The best six models with the lowest MSDs were identified for several ET and agronomic categories, and they proved to vary widely in complexity in spite of having similar prediction accuracies. At the same time, other models with apparently similar approaches were not as accurate. The models that are widely used tended to perform better, leading us speculate that a larger number of users testing these models over a wider range of conditions likely has led to improvement. User experience and skill at calibration and dealing with missing input data likely were also a factor in determining the accuracy of model predictions. In several cases different versions of a model within the same family of models were run, and these within-family inter-comparisons identified particular approaches that were better while other factors were held constant. Thus, improvement is needed in many of the models with regard to their ability to simulate ET over a wide range of conditions, and several aspects for progress have been identified, especially in their simulation of potential ET.

The rapid expansion of irrigation since the 1950s has significantly depleted the Ogallala Aquifer. This study examines the warm-season climate impacts of irrigation over the Ogallala using high-resolution (6.33 km) simulations of a version of the Weather Research and Forecasting (WRF) Model that has been coupled to the Community Land Model with dynamic crop growth (WRF-CLM4crop). To examine how dynamic crops influence the simulated impact of irrigation, the authors compare simulations with dynamic crops to simulations with a fixed annual cycle of crop leaf area index (static crops). For each crop scheme, simulations were completed with and without irrigation for 9 years that represent the range of observed precipitation. Reduced temperature and precipitation biases occur with dynamic versus static crops. Fundamental differences in the precipitation response to irrigation occur with dynamic crops, as enhanced surface roughness weakens low-level winds, enabling more water from irrigation to remain over the region. Greater simulated rainfall increases (12.42 mm) occur with dynamic crops compared to static crops (9.08 mm), with the greatest differences during drought years (+20.1 vs +5.9 mm). Water use for irrigation significantly impacts precipitation with dynamic crops (R2 = 0.29), but no relationship exists with static crops. Dynamic crop growth has the largest effect on the simulated impact of irrigation on precipitation during drought years, with little impact during nondrought years, highlighting the need to simulate the dynamic response of crops to environmental variability within Earth system models to improve prediction of the agroecosystem response to variations in climate.

Data from a dense urban meteorological network (UMN) are analyzed, revealing the spatial heterogeneity and temporal variability of the Twin Cities (Minneapolis–St. Paul, Minnesota) canopy-layer urban heat island (UHI). Data from individual sensors represent surface air temperature (SAT) across a variety of local climate zones within a 5000-km2 area and span the 3-yr period from 1 August 2011 to 1 August 2014. Irregularly spaced data are interpolated to a uniform 1 km × 1 km grid using two statistical methods: 1) kriging and 2) cokriging with impervious surface area data. The cokriged SAT field exhibits lower bias and lower RMSE than does the kriged SAT field when evaluated against an independent set of observations. Maps, time series, and statistics that are based on the cokriged field are presented to describe the spatial structure and magnitude of the Twin Cities metropolitan area (TCMA) UHI on hourly, daily, and seasonal time scales. The average diurnal variation of the TCMA UHI exhibits distinct seasonal modulation wherein the daily maximum occurs by night during summer and by day during winter. Daily variations in the UHI magnitude are linked to changes in weather patterns. Seasonal variations in the UHI magnitude are discussed in terms of land–atmosphere interactions. To the extent that they more fully resolve the spatial structure of the UHI, dense UMNs are advantageous relative to limited collections of existing urban meteorological observations. Dense UMNs are thus capable of providing valuable information for UHI monitoring and for implementing and evaluating UHI mitigation efforts.

Downscaled climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were used to force a dynamic vegetation agricultural model (Agro-IBIS) and simulate yield responses to historical climate and two future emissions scenarios for maize in the U.S. Midwest and wheat in southeastern Australia. In addition to mean changes in yield, the frequency of high- and low-yield years was related to changing local hydroclimatic conditions. Particular emphasis was on the seasonal cycle of climatic variables during extreme-yield years and links to crop growth. While historically high (low) yields in Iowa tend to occur during years with anomalous wet (dry) growing season, this is exacerbated in the future. By the end of the twenty-first century, the multimodel mean (MMM) of growing season temperatures in Iowa is projected to increase by more than 5°C, and maize yield is projected to decrease by 18%. For southeastern Australia, the frequency of low-yield years rises dramatically in the twenty-first century because of significant projected drying during the growing season. By the late twenty-first century, MMM growing season precipitation in southeastern Australia is projected to decrease by 15%, temperatures are projected to increase by 2.8°–4.5°C, and wheat yields are projected to decline by 70%. Results highlight the sensitivity of yield projections to the nature of hydroclimatic changes. Where future changes are uncertain, the sign of the yield change simulated by Agro-IBIS is uncertain as well. In contrast, broad agreement in projected drying over southern Australia across models is reflected in consistent yield decreases for the twenty-first century. Climatic changes of the order projected can be expected to pose serious challenges for continued staple grain production in some current centers of production, especially in marginal areas.

The present study focuses on (i) evaluation of potato crop yield under present time slice (PTS) with recommended management of nitrogen (N) fertilizer and irrigation on sandy soils of Minnesota, USA (ii) simulation of potato productivity and nitrate leaching with the SUBSTOR DSSAT-potato model in a projected future climatic environment (2038–2067) and (iii) evaluation of alternative irrigation and N management strategies with the DSSAT model as adaptation measures to minimize climate change impacts. Ensemble global climate model output for each of three future mid-century (MC) 10-years time slices of crop growing season predicts increases in maximum temperature (Tmax) of 0.7, 1.2 and 2.1 °C; and in minimum temperature (Tmin) of 0.6, 1.3 and 2.0 °C in MC1 (2038–2047), MC2 (2048–2057) and MC3 (2058–2067), respectively, during the tuber bulking periods. Rainfall (RF) of 253.1 mm in PTS decreased by 29.7, 16.7 and 6.5 mm in MC1–MC3, respectively. Under the changed climate, simulations indicated decreases in potato yields of 19–29%, harvest index of 4–9% and water use efficiency of 22–32% compared with current irrigation and fertilizer rates (260 mm irrigation, 270 kg ha−1 N fertilizer). Potato yields could be sustained at present levels by increasing irrigation levels to 390 mm, with 450 kg ha−1 N in the years 2038–2047; and 326 and 390 mm irrigation with 450 kg N ha−1 in year 2048–2057. However, leaching losses in 2048–2057 would increase (relative to current losses) by 34–62%. In the years 2058–2067 yield in the region evaluated can no longer be sustained with increased N and irrigation levels and leaching losses would increase by 41–67%. Use of varieties tolerant to drought and heat or adapting alternative cultural practices will be required to maintain productivity.

Atmospheric aerosols scatter and potentially absorb incoming solar radiation, thereby reducing the total amount of radiation reaching the surface and increasing the fraction that is diffuse. The partitioning of incoming energy at the surface into sensible heat flux and latent heat flux is postulated to change with increasing aerosol concentrations, as an increase in diffuse light can reach greater portions of vegetated canopies. This can increase photosynthesis and transpiration rates in the lower canopy and potentially decrease the ratio of sensible to latent heat for the entire canopy. Here, half-hourly and hourly surface fluxes from six Flux Network (FLUXNET) sites in the coterminous United States are evaluated over the past decade (2000–08) in conjunction with satellite-derived aerosol optical depth (AOD) to determine if atmospheric aerosols systematically influence sensible and latent heat fluxes. Satellite-derived AOD is used to classify days as high or low AOD and establish the relationship between aerosol concentrations and the surface energy fluxes. High AOD reduces midday net radiation by 6%–65% coupled with a 9%–30% decrease in sensible and latent heat fluxes, although not all sites exhibit statistically significant changes. The partitioning between sensible and latent heat varies between ecosystems, with two sites showing a greater decrease in latent heat than sensible heat (Duke Forest and Walker Branch), two sites showing equivalent reductions (Harvard Forest and Bondville), and one site showing a greater decrease in sensible heat than latent heat (Morgan–Monroe). These results suggest that aerosols trigger an ecosystem-dependent response to surface flux partitioning, yet the environmental drivers for this response require further exploration.

Conference: International Crop Modelling Symposium on Crop Modelling for Agriculture and Food Security under Global Change (iCropM) - Proceedings Paper Berlin, GERMANY 2016; This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO2]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thünen Institute in Braunschweig, Germany (Manderscheid et al., 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50% of models within a range of +/−1 Mg ha−1 around the mean. The bias of the median of the 21 models was less than 1 Mg ha−1. However under water deficit in one of the two years, the models captured only 30% of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

a b s t r a c t The production of cellulosic feedstocks for renewable fuels will increase over the coming decades. How- ever, it is uncertain which feedstocks will be best suited for bioenergy production. A key factor dictating feedstock selection for a given region is water use efficiency (WUE), the trade-off between evapotranspira- tion (ET) and carbon uptake or productivity. Using an ecosystem model, two of the top candidate cellulosic feedstocks, Miscanthus × giganteus (miscanthus) and Panicum virgatum (switchgrass) were compared to Zea mays L. (maize), the existing dominant bioenergy feedstock, with 0 and 25% residue removal for the Midwest US. We determined productivity in three ways: harvested yield (HY), net ecosystem productiv- ity (NEP) and net biome productivity (NBP). Evapotranspiration was compared against each of the three productivity metrics, respectively, to yield Harvest Water Use Efficiency (HWUE), Ecosystem Water Use Efficiency (EWUE) and Biome Water Use Efficiency (BWUE). Simulations indicated that, over the study domain, miscanthus had a significantly higher HWUE compared to switchgrass and maize, while maize and switchgrass were similar. When EWUE was compared miscanthus was higher than both maize and switchgrass, which were similar for most of the region. Biome WUE was similar for both of the perenni- als and higher compared to maize for most of the study domain with the exception of the driest regions where maize showed the highest BWUE. Removing 25% of maize residue slightly increased HWUE and greatly decreased BWUE throughout the domain, however only HWUE changes were statistically signif- icant. These results indicate that the feedstock with the highest WUE varied based on the productivity metric, but BWUE for maize was consistently lower than the perennials. Published by Elsevier B.V.

This study combines previous work on quantifying the greenhouse gas value of ecosystems with models of the effects of biophysical processes to produce an integrated metric of climate-regulation services. The approach is used to quantify climate-regulation values of natural and managed ecosystems across the Western Hemisphere.

Accurately quantifying changes in soil carbon (C) stocks with land-use change is important for estimating the anthropogenic fluxes of greenhouse gases to the atmosphere and for implementing policies such as REDD (Reducing Emissions from Deforestation and Degradation) that provide financial incentives to reduce carbon dioxide fluxes from deforestation and land degradation. Despite hundreds of field studies and at least a dozen literature reviews, there is still considerable disagreement on the direction and magnitude of changes in soil C stocks with land-use change. We conducted a meta-analysis of studies that quantified changes in soil C stocks with land use in the tropics. Conversion from one land use to another caused significant increases or decreases in soil C stocks for 8 of the 14 transitions examined. For the three land-use transitions with sufficient observations, both the direction and magnitude of the change in soil C pools depended strongly on biophysical factors of mean annual precipitation and dominant soil clay mineralogy. When we compared the distribution of biophysical conditions of the field observations to the area-weighted distribution of those factors in the tropics as a whole or the tropical lands that have undergone conversion, we found that field observations are highly unrepresentative of most tropical landscapes. Because of this geographic bias we strongly caution against extrapolating average values of land-cover change effects on soil C stocks, such as those generated through meta-analysis and literature reviews, to regions that differ in biophysical conditions.

The central and eastern United States is an important food and timber production region and could potentially be a large-scale carbon sink. These characteristics are functions of the human management of the landscape and favorable soil and climate conditions. Large-scale assessments of carbon uptake and trends in net primary productivity (NPP) have been previously reported for this region using satellite observations, but they cannot quantify the contributions from changes in management and technology independently from climate effects. To address this shortcoming, we used the Agro-IBIS dynamic ecosystem model to examine the relationship of temperature and precipitation trends to NPP changes from 1950 to 2002 and 1982 to 2002 over both natural and managed ecosystems. In order to isolate the vegetation growth response to climate trends, we minimized the representation of management for agroecosystems and forested ecosystems by removing nitrogen stress and irrigation from the model. Simulated NPP trends were larger during 1982–2002 than during 1950–2002 and were positive across most of the domain. For the 1982–2002 period, corn had the largest NPP trend of 6.43 g C m−2 year−2 (p = 0.22), followed by soybean, spring wheat, deciduous forest, and grassland with 4.06 (p = 0.30), 4.05 (p = 0.42), 1.98 (p = 0.17), and 0.84 g C m−2 year−2 (p = 0.73), respectively. Winter wheat had a trend of −0.64 g C m−2 year−2 (p = 0.55) and evergreen needleleaf forest had a negligible NPP trend. Trends in NPP in grasslands, deciduous forest, spring wheat, and winter wheat were associated with trends in precipitation, while trends in corn and soybean were attributed to a combination of longer growing periods, decreased summer average temperatures, and increased precipitation. We found that 19% of corn and 11% of soybean NPP trends could be explained by temperature trends while 23% of corn and 44% of soybean trends could be explained by precipitation trends. Our results provide further evidence supporting observational results that suggest 20–25% of recent crop yield trends can be explained by changing climate, and suggest that over the past several decades climate changes have favored increased crop productivity in most agroecosystems of the central United States with the exception of winter wheat.

Climatic and hydrologic observations and results from a terrestrial ecosystem model coupled to a regional-scale river-routing algorithm are used to document the associations between the El Niño–Southern Oscillation (ENSO) phenomenon and anomalies in climate, surface water balance, and river hydrology within the Mississippi River basin. While no ENSO signal is found in streamflow at the outlet of the basin in Vicksburg, Mississippi, significant anomalies in all water balance components are found in certain regions within the basin. ENSO is mainly associated with positive winter temperature anomalies, but hydrologic patterns vary with season, location, and ENSO phase. El Niño precipitation anomalies tend to affect evapotranspiration (ET) in the western half of the basin and runoff in the eastern half. La Niña events are associated with ET anomalies in the central portion of the basin and runoff anomalies in the southern and eastern portions of the basin. Both ENSO phases are associated with decreased snow depth. Anomalous soil moisture patterns occur at seasonal time scales and filter noisier spatial patterns of precipitation anomalies into coherent patterns with larger field significance; however, for all water budget components, there is a large amount of variability in response within a particular ENSO phase. With anomalies that are up to 4 times those of a typical event, it is clear that improved predictability of the onset and strength of an upcoming ENSO event is important for both water resource management and disaster mitigation.

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 increase...

Independent measurements of the major energy balance flux components are not often consistent with the principle of conservation of energy. This is referred to as a lack of closure of the surface energy balance. Most results in the literature have shown the sum of sensible and latent heat fluxes measured by eddy covariance to be less than the difference between net radiation and soil heat fluxes. This under-measurement of sensible and latent heat fluxes by eddy-covariance instruments has occurred in numerous field experiments and among many different manufacturers of instruments. Four eddy-covariance systems consisting of the same models of instruments were set up side-by-side during the Southern Great Plains 1997 Hydrology Experiment and all systems under-measured fluxes by similar amounts. One of these eddy-covariance systems was collocated with three other types of eddy-covariance systems at different sites; all of these systems under-measured the sensible and latent-heat fluxes. The net radiometers and soil heat flux plates used in conjunction with the eddy-covariance systems were calibrated independently and measurements of net radiation and soil heat flux showed little scatter for various sites. The 10% absolute uncertainty in available energy measurements was considerably smaller than the systematic closure problem in the surface energy budget, which varied from 10 to 30%. When available-energy measurement errors are known and modest, eddy-covariance measurements of sensible and latent heat fluxes should be adjusted for closure. Although the preferred method of energy balance closure is to maintain the Bowen‐ratio, the method for obtaining closure appears to be less important than assuring that eddy-covariance measurements are consistent with conservation of energy. Based on numerous measurements over a sorghum canopy, carbon dioxide fluxes, which are measured by eddy covariance, are underestimated by the same factor as eddy covariance evaporation measurements when energy balance closure is not achieved. Published by Elsevier Science B.V.

Increasing demand for food and bioenergy has altered the global landscape dramatically in recent years. Land use and land cover change affects the environmental system in many ways through biophysical and biogeochemical mechanisms. In this study, we evaluate the impacts of land use and land cover change driven by recent crop expansion and conversion on the water budget, carbon exchange, and carbon storage in the Midwest USA. A dynamic global vegetation model was used to simulate and examine the impacts of landscape change in a historical case based on crop distribution data from the United States Department of Agriculture National Agricultural Statistics Services. The simulation results indicate that recent crop expansion not only decreased soil carbon sequestration (60 Tg less of soil organic carbon) and net carbon flux into ecosystems (3.7 Tg·year−1 less of net biome productivity), but also lessened water consumption through evapotranspiration (1.04 × 1010 m3·year−1 less) over 12 states in the Midwest. More water yield at the land surface does not necessarily make more water available for vegetation. Crop residue removal might also exacerbate the soil carbon loss.

The physiological response of vegetation to increasing atmospheric carbon dioxide concentration ([CO2 ]) modifies productivity and surface energy and water fluxes. Quantifying this response is required for assessments of future climate change. Many global climate models account for this response; however, significant uncertainty remains in model simulations of this vegetation response and its impacts. Data from in situ field experiments provide evidence that previous modeling studies may have overestimated the increase in productivity at elevated [CO2 ], and the impact on large-scale water cycling is largely unknown. We parameterized the Agro-IBIS dynamic global vegetation model with observations from the SoyFACE experiment to simulate the response of soybean and maize to an increase in [CO2 ] from 375 ppm to 550 ppm. The two key model parameters that were found to vary with [CO2 ] were the maximum carboxylation rate of photosynthesis and specific leaf area. Tests of the model that used SoyFACE parameter values showed a good fit to site-level data for all variables except latent heat flux over soybean and sensible heat flux over both crops. Simulations driven with historic climate data over the central USA showed that increased [CO2 ] resulted in decreased latent heat flux and increased sensible heat flux from both crops when averaged over 30 years. Thirty-year average soybean yield increased everywhere (ca. 10%); however, there was no increase in maize yield except during dry years. Without accounting for CO2 effects on the maximum carboxylation rate of photosynthesis and specific leaf area, soybean simulations at 550 ppm overestimated leaf area and yield. Our results highlight important model parameter values that, if not modified in other models, could result in biases when projecting future crop-climate-water relationships.

[1] Dynamic global vegetation models (DGVMs) simulate ecosystem responses to multiple environmental factors. Traditionally, these models were evaluated with sparse ground measurements, but satellite observations now allow evaluation at model grid cell scales with near-global coverage. Agro-IBIS is the first DGVM to explicitly simulate the major crop types of the United States. We evaluate these simulated agroecosystems using satellite information of greenness for the first time at the regional scale. We compare Agro-IBIS-simulated leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) of crops, forests, and grasses with AVHRR (1982–2000) and MODIS (2000–2002) LAI and FPAR data sets across the central and eastern United States. Compared with MODIS data, Agro-IBIS overestimates growing season LAI over broadleaf crops and simulates reasonable but lower growing season LAI over deciduous forest, with an early onset bias in the southern region. Agro-IBIS underestimates needleleaf forest LAI and substantially overestimates the magnitude of grassland growing season LAI, with an early onset bias of one month. Similar bias patterns in FPAR occur in all biomes. While we do not trust the LAI/FPAR magnitudes from AVHRR data, we do suggest that AVHRR data may be used to evaluate the timing of onset and offset of the growing season of broadleaf crops and grasses. Evaluation of broadleaf crop peak LAI from Agro-IBIS and MODIS with ground measurements shows significant discrepancies. Continuing improvements in DGVMs (especially grass algorithms in Agro-IBIS) and validation of satellite data sets (especially over crops in MODIS) are needed to understand regional-scale terrestrial ecosystem processes.

The Mississippi Basin is the third largest drainage basin in the world and is home to one of the most productive agricultural regions on Earth. Here we discuss how land use/land cover change and climatic variability may be affecting some key environmental processes across the Mississippi and how these, in turn, affect the flow of selected ecosystem goods and services in the region. Specifically, we consider the recent history of land use/land cover change, crop yields, basin river flow and hydrology, and large-scale water quality in the Mississippi Basin. We find that agricultural activities may have had a profound influence on the basin and may have shifted the flow of many ecosystem goods and services into agricultural commodities, at the expense of altering many of the important biogeochemical linkages between atmosphere, land, and water.

A new vegetation trend is emerging in northeastern forests of the United States, characterized by an expansion of red maple at the expense of oak. This has changed emissions of biogenic volatile organic compounds (BVOCs), primarily isoprene and monoterpenes. Oaks strongly emit isoprene while red maple emits a negligible amount. This species shift may impact nearby urban centers because the interaction of isoprene with anthropogenic nitrogen oxides can lead to tropospheric ozone formation and monoterpenes can lead to the formation of particulate matter. In this study the Global Biosphere Emissions and Interactions System was used to estimate the spatial changes in BVOC emission fluxes resulting from a shift in forest composition between oak and maple. A 70% reduction in isoprene emissions occurred when oak was replaced with maple. Ozone simulations with a chemical box model at two rural and two urban sites showed modest reductions in ozone concentrations of up to 5–6 ppb resulting from a transition from oak to red maple, thus suggesting that the observed change in forest composition may benefit urban air quality. This study illustrates the importance of monitoring and representing changes in forest composition and the impacts to human health indirectly through changes in BVOCs.

[1] 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.