Biophysical and economic models for assessing impacts of change on grazingland ecosystems

Abstract

PHYGROW, a hydrologic-based forage simulation model, was parameterized to represent a typical South Texas ranch engaged in the production of cattle and meat goats with an indigenous population of white-tailed deer. Forage production and associated stocking rates for two cattle:goat ratios were simulated with POPMIX for 20 years. Two ten-year weather scenarios, one representing normal conditions (30% drought years) and one representing dryer weather conditions (50% drought years) were analyzed. Management decision rules (ASPC) were developed for the region to produce estimates of annual animal production and operating costs for the enterprises on each of the four scenarios. These performance and cost data were then used as input into FLIPSIM, a firm level income and policy simulator, along with relevant product and input price data for the region. Integration of modeled results produced useful information showing the socioeconomic consequences for a typical South Texas firm impacted by alternative climatic conditions and management strategies.

Evaluación de la política pública para el sector pesquero en el noroeste mexicano: análisis económico y prospectivo

“…Desde los inicios de FLIPSIM, Richardson y Dixon (1986) desarrollaron dicho modelo y se caracteriza por ser dinámico, recursivo y estocástico, y, simula los impactos en las características financieras y económicas de una granja o rancho específico como alternativa institucional, técnica o gerencial del desarrollo de sus propios periodos específicos (Souza Neto, et al, 2001). Este modelo es oportuno para iniciar un modelo integrado que muestra la composición de especies (plantas y animales) que pueden ser integradas dentro de la evaluación de impactos socioeconómicos, ambientales o de otros cambios (Ibid).…”

Modeling Herbaceous Biomass for Grazing and Fire Risk Management

“…The Phygrow model is a hydrologically driven, daily time-step plant growth model [31] that has been used to study grazing management [32], hydrological policy and brush control investment [33,34], forecasting of forage availability [35], and drought early warning systems on arid grazinglands in East Africa [36][37][38][39][40], and Mongolia [41,42]. More recently, it has been evaluated to estimate herbaceous biomass for grazing management and fine fuels mitigation for the Department of Defense, and the US Forest Service (USFS) [9,43].…”