The use of marginal lands for biofuel production has been proposed as a promising solution for meeting biofuel demands while avoiding food–feed–fuel conflicts. However, uncertainty surrounds whether ...marginal lands can be reliably located, as well as their inherent biofuel potential and the possible environmental impacts. We developed a quantitative approach that integrates high‐resolution land cover and land productivity to classify productive croplands and nonarable marginal lands in a nine‐county region in southern Michigan. The classified lands were then examined with the spatially explicit modeling framework using the Environmental Policy Integrated Climate (EPIC) model to estimate net energy (NE) and soil organic carbon (SOC) changes associated with the cultivation of different annual and perennial production systems. Simulation results suggest that biofuel production systems underperform on marginal lands when compared to productive croplands. However, we found perennial grasses could perform better than annual crops. Hence, when growing perennial bioenergy crops on marginal lands instead of productive croplands, less additional land (about 0.09 ha per each hectare planted) would be needed to achieve the same NE than if growing annual bioenergy crops (additional 0.17 ha per hectare planted). Miscanthus (Miscanthus × giganteus) and switchgrass (Panicum virgatum L.) can produce 112.43 and 74.61 GJ ha−1 yr−1 NE, respectively, and have the potential to sequester, on average, 0.59 and 0.23 Mg C ha−1 yr−1 SOC, respectively. Notably, simulation results indicate substantial variability of the NE and SOC storage potential across the study region. Thus, although perennial energy crops are promising options for biofuel production on marginal lands, given the large spatial variability, regional‐ and site‐specific management strategies are required for sustainable biofuel production.
Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a ...32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.
Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1% points, representing a relative change of −8.6%.
As carbon dioxide and other greenhouse gasses accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and ...managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the General Circulation Model (GCM)-derived climate change projections, described in Part 1, to drive the crop production and water resource models EPIC (Erosion Productivity Impact Calculator) and HUMUS (Hydrologic Unit Model of the United States). These models are described and validated in this paper using historical crop yields and streamflow data in the conterminous United States in order to establish their ability to accurately simulate historical crop and water conditions and their capability to simulate crop and water response to the extreme climate conditions predicted by GCMs. EPIC simulated grain and forage crop yields are compared with historical crop yields from the US Department of Agriculture (USDA) and with yields from agricultural experiments. EPIC crop yields correspond more closely with USDA historical county yields than with the higher yields from intensively managed agricultural experiments. The HUMUS model was validated by comparing the simulated water yield from each hydrologic basin with estimates of natural streamflow made by the US Geological Survey. This comparison shows that the model is able to reproduce significant observed relationships and capture major trends in water resources timing and distribution across the country. PUBLICATION ABSTRACT
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether ...different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations CO2, we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha-1 per °C. Doubling CO2 from 360 to 720 µmol mol-1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to CO2 among models. Model responses to temperature and CO2 did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. ...Thomson et al use the PNNL Regional Climate Model which uses a sub-grid parameterization to resolve the complex topography of the US Pacific Northwest and simulate meteorology to drive the Erosion Productivity Impact Calculator crop model.
The contribution of agricultural soils to atmospheric N2O in the Boreal and Parkland regions of Alberta is largely unknown. Field data are required to quantify the flux of N2O from these regions, as ...are methodologies to scale up from site-specific measurements to large geographical areas. Climate-soil-management combinations (CSMCs) aggregated to an ecodistrict level have recently been proposed as a technique for scaling up greenhouse gas flux estimates for Canadian agriculture. Our objective was to calculate seasonal N2O losses and investigate large-scale spatial variability using field data from selected sites in the Boreal and Parkland regions. We used vented soil covers to measure N2O emissions during spring and summer of 1993 and 1994, and the spring of 1995, from six representative CSMCs in five ecodistricts in Alberta. Substantial and consistent differences in the magnitude of N2O-N loss among sites were observed, with annual estimated losses of N2O-N ranging from 0.4 to 2.6 kg ha-1. Up to 70% of the total annual N2O-N loss occurred during brief but intense bursts at spring thaw. Soil clay content was found to be strongly correlated with annual N2O-N loss. This relationship suggests that clay content, readily available from soil data bases, could be used as a N2O-loss predictor variable when applying scaling-up methodologies
Semiarid rangelands are very sensitive to global climatic change; studies of their biophysical attributes are crucial to understanding the dynamics of rangeland ecosystems under human disturbance. In ...the Santa Rita Experimental Range, AZ, the vegetation has changed considerably, and there have been many management activities applied. This study calculates seven surface variables: the enhanced vegetation index, the normalized difference vegetation index (NDVI), surface albedos (total shortwave, visible, and near-infrared), leaf area index (LAI), and the fraction of photosynthetically active radiation (FPAR) absorbed by green vegetation from the Enhanced Thematic Mapper (ETM+) data. Comparison with the Moderate Resolution Imaging Spectroradiometer vegetation index and albedo products indicates they agree well with our estimates from ETM+, while their LAI and FPAR are larger than from ETM+. Human disturbance has significantly changed the cover types and biophysical conditions. Statistical tests indicate that surface albedos increased and FPAR decreased following tree-cutting disturbances. The recovery will require more than 67 years and is about 50% complete within 40 years at the higher elevation. Grass cover, vegetation indexes, albedos, and LAI recovered from cutting faster at the higher elevation. Woody plants, vegetation indexes, and LAI have recovered to their original characteristics after 65 years at the lower elevation. More studies are needed to examine the spectral characteristics of different ground components.
The El Nino/Southern Oscillation (ENSO) phenomena alter global weather patterns with consequences for fresh water supply. ENSO events impact regions and their natural resource sectors around the ...globe. For example, in 1997 and 1998, a strong El Nino brought warm ocean temperatures, flooding, and record snowfall to the west coast of the United States. Research on ENSO events has improved long range climate predictions, affording the potential to reduce the damage and economic cost of these weather patterns. Here, using the Hydrologic Unit Model for the United States (HUMUS), we simulate the impacts of four types of ENSO states (Neutral, El Nino, La Nina, and strong El Nino) on water resources in the conterminous United States. The simulations show that La Nina conditions increase water yield across much of the country. We find that water yield increases during El Nino years across the south while declining in much of the rest of the country. However, under strong El Nino conditions, regional water yields are much higher than Neutral, especially along the West Coast. Strong El Nino is not simply an amplification of El Nino; it leads to strikingly different patterns of water resource response.
As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural ...and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO2 ldquofertilization effectrdquo on vegetation is examined by using two levels of atmospheric CO2 concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO2 fertilization effects. PUBLICATION ABSTRACT
PDF
