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Browsing by Author "Stuth, Jerry"

Now showing 1 - 9 of 9
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    Agricultural climate change impact: General concerns and findings from Mali, Kenya, Uganda, and Senegal
    Butt, T.; Angerer, Jay; Dyke, P.; Kim, M.; Kaitho, R.; Stuth, Jerry (2004)
    This paper discusses concerns about the impact of climate change on agriculture. Methods for assessing the impacts of climate change and the results from impact assessments in Mali, Kenya, Uganda, and Senegal are presented.
  • Biophysical and economic models for assessing impacts of change on grazingland ecosystems
    Souza, N.; Conner, J.; Stuth, Jerry (Campina Grande, Brazil: Asociación Latinoamericana del Caribe de Ingeniería Agrícola, 2001)
    This paper integrates three models to derive information on socioeconomic impacts of climatic conditions and management approaches for a typical South Texas ranch. The authors apply PHYGROW to simulate conditions on a South Texas cattle and goat ranch. POPMIX was used to simulate forage production with two cattle : goat ratios (to represent different management strategies). Simulation results, as well as two ten-year weather scenarios (30% and 50% drought years to simulate normal and dryer conditions), and estimated animal production and operating costs, were incorporated into a firm level income and policy simulator (FLIPSIM), to yield integrated predictions of socioeconomic impacts.
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    Common modeling environment (CME): A framework for integrated decision support systems
    Stuth, Jerry; Schmitt, Dan; Zander, Kristen; Heath, Clint; Angerer, Jay; Vitale, Jeff (2001)
    Assessing impact of technologies and policies requires the use of a suite of decision support models that address the complexity of economic systems at the sector level, farm level economics and human welfare, crop production, grazing land production, livestock performance and resulting environmental processes. Typically "integration" of these processes involved manual transfer of data files between applications or limited digital integration in a subset of modules. Further, there was limited ability to modify models in a manner that allowed tighter "digital" integration. There is growing need within SANREM and with other partners, including FAO, to package a number of different research simulations together to develop a more detailed and holistic view of non-homogeneous activities and environments. This need to package integrated suites of models so that they can be run on a single computer or internet/intranet, led to the pursuit of the Common Assessing impact of technologies and policies requires the use of a suite of decision support models that address the complexity of economic systems at the sector level, farm level economics and human welfare, crop production, grazing land production, livestock performance and resulting environmental processes. Typically "integration" of these processes involved manual transfer of data files between applications or limited digital integration in a subset of modules. Further, there was limited ability to modify models in a manner that allowed tighter "digital" integration. There is growing need within SANREM and with other partners, including FAO, to package a number of different research simulations together to develop a more detailed and holistic view of non-homogeneous activities and environments. This need to package integrated suites of models so that they can be run on a single computer or internet/intranet, led to the pursuit of the Common Modeling Environment (CME) concept. CME is an evolving set of information technology that is modular and designed to grow in sophistication as needs are identified within organizations. This system brings cross-platform delivery, a scalable distributed computing model, and shared common input data to many research models with minimal model modification. A model server process can be run on any platform that has a JAVA virtual machine installed and quickly allows incorporation of stand alone models without undue stress on research model developers.
  • The economic and food security implications of climate change in Mali
    Butt, T.; McCarl, Bruce A.; Angerer, Jay; Dyke, P.; Stuth, Jerry (Dordrecht-Holland ; Boston: Reidel Publishing Company, 2003)
    This study uses climate change projections from two global circulation models to address the impact of climate change on Mali's agriculture sector and the consequences for the sector economy and food security. The authors focus on crops, forage, and livestock as indicators of climate change effects. The analysis projected a change in national crop yields between a 17% decrease and a 6% increase, a 5 to 36% decrease in forage yields, and a 14 to 16% decrease in livestock weights. These changes correspond to economic losses of $70 to $142 million, which are primarily absorbed by the consumers; the percentage of the population at risk for hunger is projected to increase to 64 to 72%, which is a potentially doubling the current estimate of 34%. The authors suggest that developing heat resistant cultivars, using improved cultivars already developed, adapting cropping patterns to climate changes, and expanding cropland can prevent these dramatic consequences of climate change and lower the percentage facing a hunger risk to as low as 28%.
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    Impacts of reforestation policy and agro-forestry technology on the environment and food security in the Upper Tana river basin of Kenya
    Srinivasan, R.; Jacobs, J.; Stuth, Jerry; Angerer, Jay; Kaitho, R.; Clarke, N. (2004)
    This presentation is on a study to explore the hydrologic impacts on the Masinga reservoir in response to land use interventions in the Upper Tana River catchment with a focus on varying levels of reforestation.
  • An interdisciplinary approach to valuing water from brush control
    Lemberg, B.; Mjelde, J.; Conner, J.; Griffin, R.; Rosenthal, W.; Stuth, Jerry (Herndon, Va.: Water Resources Association, 2002)
    This paper develops an integrated model to assess the viability of increasing water yields in the Frio River basin of Texas through brush control. The presented method accounts for the effect of brush control on forage productivity and water supply by incorporating ecological, hydrologic, and economic models. The simulation of water yields suggests that brush control would increase water yields on 35% of the land area, but the costs usually would exceed the financial benefits. The authors conclude that subsidizing brush control in the Frio basin is not a cost-effective policy at this time.
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    Policy and technology options for dairy systems in East Africa: Economic and environmental assessment
    Kaitho, R.; Eddleman, B.; Chen, Chi Chung; McCarl, Bruce A.; Angerer, Jay; Stuth, Jerry (2001)
    Assessment of smallholder dairy technology was used as a case study to develop models in the SANREM decision support system. Scenarios depicting the industry before current improvements, the current situation, and forecasted improvements resulting from further adoption of technology were evaluated. GIS methods were used to establish appropriate sampling frames for field studies and analysis. Forage and livestock models supplemented reported data as input to economic and environmental models. Assessment of the impact of alternative smallholder dairy technology packages was evaluated in the Sondu river basin using watershed models driven by economic and environmental models. With demand growth from projected population increases, full adoption of the improved dairy technology package would generate total economic welfare of KS 4,206 million. Full adoption of the technology package in the Sondu river basin would increase sediment loads in the basin by 5% over a 21-year period and stream flow would increase slightly. The general models developed from initial smallholder dairy studies predict annual increases in productivity of between 0.3 and 0.5% per year would be required to sustain food prices at current levels with 2015 demand. Intensification and extensification strategies were evaluated to achieve these levels of productivity. Combinations of strategies were predicted to be the most rational in meeting future food security demands with sustainable use of natural resources.
  • Regional cost share necessary for rancher participation in brush control
    Lee, Andrew C.; Conner, J. Richard; Mjelde, James W.; Richardson, James W.; Stuth, Jerry (Bozeman, MT: Western Agricultural Economics Association, 2001)
    This paper uses biophysical and economic simulation models to assess the proposed large-scale brush-control programs in four regions of the Edwards Plateau area in Texas. The objective of the brush control is to increase off-site water yields. For representative ranches in three of the four regions, brush control decreases the net present value. For these three regions to break even on brush control costs, there would need to be cost sharing of 7 to 31% of the total costs. Consequently, the state of Texas would have to supply a significant investment for large-scale brush-control programs to be feasible.
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    Use of satellite-derived data to improve biophysical model output: An example from Southern Kenya
    Angerer, Jay; Stuth, Jerry; Wandera, F.; Kaitho, R. (Watkinsville, GA: SANREM CRSP, 2001)
    The use of satellite data products produced by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) was explored to determine if these products could be used to provide plant growth model output for large landscapes. The use of satellite-derived data is generally advantageous because it is spatially dense (i.e., many measurements for a large landscape). Gridded daily temperature (0.1 x 0.1 degree) and rainfall (8x8 km), derived from the METEOSAT satellite, were used as inputs into the PHYGROW plant growth model for 30 pastoral households in southern Kenya. After model runs were completed, cokriging was used to determine if model output, coupled with NASAï'½s Normalized Difference Vegetation Index (NDVI) product (a greenness index), could be used to create forage production maps for a large landscape. Cokriging is a geostatistical technique that allows one to take advantage of spatial autocorrelation (i.e., things closer together in space are usually similar than those farther apart), and the similarity between a small number of data points (model output in our case) and a one that is spatially dense (NDVI). Using cokriging, the majority of ten-day averages for year 2000 had moderate to high similarity between model output and NDVI. A comparison of model output and estimates from cokriging indicated that cokriging generally did a good job of estimating forage available for the 30 pastoral households. Mapped surfaces of the cokriging output successfully identified areas of drought in year 2000. Institutions at all levels could use these mapped surfaces as part of their GIS, which can then be linked to economic models, natural resource management assessments, or used for drought early warning systems.