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Corn Production (corn + production)
Selected AbstractsUsing species distribution models to identify suitable areas for biofuel feedstock productionGCB BIOENERGY, Issue 2 2010JASON M. EVANS Abstract The 2007 Energy Independence and Security Act mandates a five-fold increase in US biofuel production by 2022. Given this ambitious policy target, there is a need for spatially explicit estimates of landscape suitability for growing biofuel feedstocks. We developed a suitability modeling approach for two major US biofuel crops, corn (Zea mays) and switchgrass (Panicum virgatum), based upon the use of two presence-only species distribution models (SDMs): maximum entropy (Maxent) and support vector machines (SVM). SDMs are commonly used for modeling animal and plant distributions in natural environments, but have rarely been used to develop landscape models for cultivated crops. AUC, Kappa, and correlation measures derived from test data indicate that SVM slightly outperformed Maxent in modeling US corn production, although both models produced significantly accurate results. When compared with results from a mechanistic switchgrass model recently developed by Oak Ridge National Laboratory (ORNL), SVM results showed higher correlation than Maxent results with models fit using county-scale point inputs of switchgrass production derived from expert opinion estimates. However, Maxent results for an alternative switchgrass model developed with point inputs from research trial sites showed higher correlation to the ORNL model than the corresponding results obtained from SVM. Further analysis indicates that both modeling approaches were effective in predicting county-scale increases in corn production from 2006 to 2007, a time period in which US corn production increased by 24%. We conclude that presence-only methods are a powerful first-cut tool for estimating relative land suitability across geographic regions in which candidate biofuel feedstocks can be grown, and may also provide important insight into potential land-use change patterns likely to be associated with increased biofuel demand. [source] Interactions between land use, habitat use, and population increase in greater snow geese: what are the consequences for natural wetlands?GLOBAL CHANGE BIOLOGY, Issue 6 2005Gilles Gauthier Abstract The North American greater snow goose population has increased dramatically during the last 40 years. We evaluated whether refuge creation, changes in land use on the wintering and staging grounds, and climate warming have contributed to this expansion by affecting the distribution, habitat use, body condition, and migration phenology of birds. We also reviewed the effects of the increasing population on marshes on the wintering grounds, along the migratory routes and on the tundra in summer. Refuges established before 1970 may have contributed to the initial demographic increase. The most important change, however, was the switch from a diet entirely based on marsh plants in spring and winter (rhizomes of Scirpus/Spartina) to one dominated by crops (corn/young grass shoots) during the 1970s and 1980s. Geese now winter further north along the US Atlantic coast, leading to reduced hunting mortality. Their migratory routes now include portions of southwestern Québec where corn production has increased exponentially. Since the mid-1960s, average temperatures have increased by 1,2.4°C throughout the geographic range of geese, which may have contributed to the northward shift in wintering range and an earlier migration in spring. Access to spilled corn in spring improved fat reserves upon departure for the Arctic and may have contributed to a high fecundity. The population increase has led to intense grazing of natural wetlands used by geese although these habitats are still largely undamaged. The foraging in fields allowed the population to exceed limits imposed by natural marshes in winter and spring, but also prevented permanent damage because of their overgrazing. [source] Will photosynthesis of maize (Zea mays) in the US Corn Belt increase in future [CO2] rich atmospheres?GLOBAL CHANGE BIOLOGY, Issue 6 2004An analysis of diurnal courses of CO2 uptake under free-air concentration enrichment (FACE) Abstract The C4 grass Zea mays (maize or corn) is the third most important food crop globally in terms of production and demand is predicted to increase 45% from 1997 to 2020. However, the effects of rising [CO2] upon C4 plants, and Z. mays specifically, are not sufficiently understood to allow accurate predictions of future crop production. A rainfed, field experiment utilizing free-air concentration enrichment (FACE) technology in the primary area of global corn production (US Corn Belt) was undertaken to determine the effects of elevated [CO2] on corn. FACE technology allows experimental treatments to be imposed upon a complete soil,plant,atmosphere continuum with none of the effects of experimental enclosures on plant microclimate. Crop performance was compared at ambient [CO2] (354 , mol mol,1) and the elevated [CO2] (549 ,mol mol,1) predicted for 2050. Previous laboratory studies suggest that under favorable growing conditions C4 photosynthesis is not typically enhanced by elevated [CO2]. However, stomatal conductance and transpiration are decreased, which can indirectly increase photosynthesis in dry climates. Given the deep soils and relatively high rainfall of the US Corn Belt, it was predicted that photosynthesis would not be enhanced by elevated [CO2]. The diurnal course of gas exchange of upper canopy leaves was measured in situ across the growing season of 2002. Contrary to the prediction, growth at elevated [CO2] significantly increased leaf photosynthetic CO2 uptake rate (A) by up to 41%, and 10% on average. Greater A was associated with greater intercellular [CO2], lower stomatal conductance and lower transpiration. Summer rainfall during 2002 was very close to the 50-year average for this site, indicating that the year was not atypical or a drought year. The results call for a reassessment of the established view that C4 photosynthesis is insensitive to elevated [CO2] under favorable growing conditions and that the production potential of corn in the US Corn Belt will not be affected by the global rise in [CO2]. [source] Integrated modeling environment for statewide assessment of groundwater vulnerability from pesticide use in agriculture,PEST MANAGEMENT SCIENCE (FORMERLY: PESTICIDE SCIENCE), Issue 8 2004Audra Eason Abstract Atrazine, a herbicide widely used for corn production in the Midwest, has been detected in groundwater of several states, and has been identified as a possible human carcinogen. With the widespread use of pesticides in crop production, and the frequent detection of these chemicals in groundwater, large-scale risk assessments would help water resource managers to identify areas that are more susceptible to contamination and implement practices to ameliorate the problem. This paper presents an integrated, visual and interactive system for predicting potential environmental risks associated with pesticide contamination at spatial scales ranging from fields to landscapes and regions. The interactive system extends the predictive ability of the Pesticide Root Zone Model Release 2.0 (PRZM-2) to a landscape and statewide scale through integration with a geographic information system (GIS), graphical user interface and environmental databases. Predictions of statewide (Iowa) vulnerability of groundwater from atrazine leaching below the unsaturated zone were made to demonstrate the utility of the system, and the results were used in risk assessment. In the example application, atrazine fate and transport were evaluated using long-term climatic data (1980,1989) in combination with several environmental databases (eg STATSGO soils database) and exposure risks were expressed in terms of the probability of the predicted pesticide concentrations exceeding the maximum contaminant level (MCL) for drinking water. The results indicate that the predicted pesticide concentrations were significantly lower than the EPA-established MCL. In addition to providing an interactive environment for landscape-level assessment of potential risks from pesticide leaching, the system significantly reduces the time and resources needed to organize and manipulate data for use with PRZM-2, and provides an analytical framework for evaluating groundwater-leaching impacts of pesticide management practices. Copyright © 2004 Society of Chemical Industry [source] | ||||||||||