Entity

Time filter

Source Type

Temple, TX, United States

Sorice M.G.,Virginia Polytechnic Institute and State University | Kreuter U.P.,Texas A&M University | Wilcox B.P.,Texas A&M University | Fox W.E.,Blackland Research and Extension Center
Journal of Environmental Management | Year: 2014

Motivations for owning rural land are shifting from an agricultural-production orientation to a preference for natural and cultural amenities. Resultant changes in land management have significant implications for the type and distribution of landscape-level disturbances that affect the delivery of ecosystem services. We examined the relationship between motivations for owning land and the implementation of conservation land management practices by landowners in the Southern Great Plains of the United States. Using a mail survey, we classified landowners into three groups: agricultural production, multiple-objective, and lifestyle-oriented. Cross tabulations of landowner group with past, current, and future use of 12 different land management practices (related to prescribed grazing, vegetation management, restoration, and water management) found that lifestyle-oriented landowners were overall less likely to adopt these practices. To the degree that the cultural landscape of rural lands transitions from production-oriented to lifestyle-oriented landowners, the ecological landscape and the associated flow of ecosystem services will likely change. This poses new challenges to natural resource managers regarding education, outreach, and policy; however, a better understanding about the net ecological consequences of lower rates of adoption of conservation management practices requires consideration of the ecological tradeoffs associated with the changing resource dependency of rural landowners. © 2013 Elsevier Ltd. Source


Folberth C.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Yang H.,Eawag - Swiss Federal Institute of Aquatic Science and Technology | Wang X.,Blackland Research and Extension Center | Abbaspour K.C.,Eawag - Swiss Federal Institute of Aquatic Science and Technology
Ecological Modelling | Year: 2012

Large-scale modeling applications are associated with various assumptions and spatial resolutions. In this study, the GIS-based Environmental Policy Integrated Climate (GEPIC) model was used to examine the effects of resampling input data from a resolution of 5. arcmin to 10 and 30. arcmin on simulated crop grain yields. Maize cultivation in the USA was used as a case study. The biggest impact was found to be the resampling of land use datasets. Rain-fed and irrigated areas are simulated separately and the yields are subsequently weighted according to irrigated and rain-fed fractions in each grid cell. The aggregation causes some grid cells to become rain-fed and irrigated at coarser resolutions after being only rain-fed or only irrigated at 5. arcmin. The estimated yield can increase or decrease largely in the affected grid cells due to the fact that irrigated areas generally have much higher yields than rain-fed agriculture in dry regions. The resampling of the climate data has a low impact on crop yields. However, changes in yield can still be large in regions with rain-fed agriculture and low precipitation. The aggregation of soil data by selecting the major soil type within neighboring grid cells has the lowest impact on crop yields. The impact of resampling input data from 5 to 10 and 30. arcmin is not significant when modeled maize yields were aggregated on the US national scale, and still quite comparable at the state level. Therefore, for estimating agricultural productivity over large areas, the coarser resolutions can be considered sufficient. Fine resolutions can be important when the goal is to make spatially detailed conclusions. Model performance shows that large deviations between simulated and reported yields can occur at all spatial resolutions in grid cells with harvested areas below 5% of the total cell area. This indicates that a sampling approach that uses representative pixels is preferable to a wall to wall approach using all grid cells. © 2012 Elsevier B.V. Source


Luo Y.,Xinjiang Institute of Ecology and Geography | Luo Y.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Arnold J.,Grassland Soil and Water Research Laboratory | Liu S.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | And 2 more authors.
Journal of Hydrology | Year: 2013

In this paper we proposed: (1) an algorithm of glacier melt, sublimation/evaporation, accumulation, mass balance and retreat; (2) a dynamic Hydrological Response Unit approach for incorporating the algorithm into the Soil and Water Assessment Tool (SWAT) model; and (3) simulated the transient glacier retreat and its impacts on streamflow at basin scale. Application of the enhanced SWAT model in the Manas River Basin (MRB) in the Tianshan Mountains in northwest China, shows that the approach is viable as evidenced by a Nash-Sutcliff efficiency of 0.65 and a percent bias of -3.7% for daily streamflow and water balance, respectively. The results indicate that the glacier area decreased by 11% during the simulation period from 1961 to 1999, which is within the range of records from other glaciers. On average, glacier melt contributed 25% to streamflow, although glacier area accounts for only 14% of the catchment drainage area in the MRB. Glacier melt was positively correlated to temperature change (R2=0.70, statistical significance P<0.001) and negatively correlated to precipitation (R2=0.20, statistical significance P<0.005). The results indicate that glacier melt was more sensitive to temperature change than to precipitation change, implying that modeling the effects of climate change with increasing temperatures and decreasing precipitation should be further studied. © 2012 Elsevier B.V. Source


Franzluebbers A.J.,U.S. Department of Agriculture | Causarano H.J.,National University of Asuncion | Norfleet M.L.,Blackland Research and Extension Center
Journal of Soil and Water Conservation | Year: 2011

Calibration of the soil conditioning index (SCI) to a diversity of field studies with known changes in soil organic carbon (SOC) would improve the usefulness of the SCI by the USDA Natural Resources Conservation Service to assess the environmental services provided by agricultural land stewardship. Our objectives were to (1) calibrate SCI scores against SOC from published field studies in the Midwest and (2) compare the calibration with a recently derived calibration from the southeastern United States. We found that SOC sequestration (at 25 ± 6 cm [10 ± 2 in] depth) could be reliably related to SCI across a diversity of studies in the region using the regression slope: 4.52 Mg C ha-1 SCI-1 (2.02 tn ac-1 SCI-1), which translated into a rate of 0.35 ± 0.06 Mg C ha-1 y-1 SCI-11 (314 ± 57 lb ac-1 yr-1 SCI -1), which is the mean ± standard error of 18 slope estimates. Calibration slopes did not vary significantly between the Midwest and southeastern United States, resulting in a combined calibration of 0.29 ± 0.03 Mg C ha-1 y-1 SCI-1 (255 ± 30 lb ac-1 yr-1 SCI-1), which is the mean ± standard error of 49 slope estimates. The calibration of SCI scores to SOC will allow SCI to become a quantitative tool for natural resource professionals to predict SOC sequestration for farmers wanting to adopt conservation practices. © 2011 Soil and Water Conservation Society . Source


Strauss F.,University of Natural Resources and Life Sciences, Vienna | Schmid E.,University of Natural Resources and Life Sciences, Vienna | Moltchanova E.,University of Canterbury | Formayer H.,University of Natural Resources and Life Sciences, Vienna | Wang X.,Blackland Research and Extension Center
Climatic Change | Year: 2012

Climate change affects major biophysical processes in agricultural crop production (e. g. evaporation of plants and soils, nutrient cycles, and growth of plants). This analysis aims to assess some of these effects by simulating regional climate projections that are integrated in the biophysical process model EPIC (Environmental Policy Integrated Climate). Statistical climate models have been developed for six weather parameters based on daily weather records of a weather station in the Austrian Marchfeld region from 1975 to 2006. These models have been used to estimate daily weather parameters for the period 2007-2038. The resulting projections have been compared to climate scenarios provided from the TYNDALL Centre for Climate Change Research, which are based on General Circulation Models (GCMs). The comparison indicates some differences, namely a smaller temperature increase and a higher precipitation amount in the TYNDALL data. Both climate datasets have been used to simulate impacts of climate change on crop yields, topsoil organic carbon content, and nitrate leaching with EPIC and thus to perform a sensitivity analysis of EPIC. Yield impacts have been assessed for four simulated crops, i. e. 6.2 t/ha for winter wheat for statistical climate projections compared to 5.7 t/ha for TYNDALL scenarios, 10.6 t/ha for corn compared to 10.5 t/ha, 3.9 t/ha for sunflower compared to 3.7 t/ha, and 4.5 t/ha for spring barley compared to 4.3 t/ha-all values as an average over the period 2007-2038. Smaller differences have been simulated for topsoil organic carbon content i. e. 55. 1 t/ha for the statistical climate projections compared to 55.3 t/ha for the TYNDALL scenarios and nitrate leaching i. e. 7.1 kg/ha compared to 11.1 kg/ha. All crop yields as well as topsoil organic carbon content and nitrate leaching show highest sensitivity to temperature and solar radiation. © 2011 Springer Science+Business Media B.V. Source

Discover hidden collaborations