51. Long-term dynamics of a semiarid grass steppe under stochastic climate and different grazing regimes: A simulation analysis
- Author
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José M. Paruelo, Thorsten Wiegand, Sandro Pütz, Martín R. Aguiar, G. E. Weber, Rodolfo A. Golluscio, and Mónica B. Bertiller
- Subjects
geography ,Herbivore ,geography.geographical_feature_category ,ECOSYSTEM DYNAMICS ,Ecology ,Steppe ,Stochastic modelling ,Tussock ,Primary production ,ARID SYSTEMS ,Atmospheric sciences ,INDIVIDUAL-BASED MODEL ,Rangeland management ,CIENCIAS AGRÍCOLAS ,Grazing ,Environmental science ,Ecosystem ,Otras Ciencias Agrícolas ,SPATIAL EXPLICIT MODELS ,HERBIVORY ,GRASS STEPPES ,Ecology, Evolution, Behavior and Systematics ,Earth-Surface Processes - Abstract
We built a grid-based spatial explicit stochastic model that simulates grazing events and basic processes like seedling establishment, growth or mortality of the dominant species in the grass steppes of Patagonia. After evaluating the model with field data, we performed simulation experiments aimed to explore the interaction of precipitation and grazing regimes on vegetation dynamics. Grazing generated a reduction in tussock density which results in a decline in aboveground net primary production (ANPP). Both response variables presented a non-linear behavior including high temporal variability and delay effects, which may prolong for decades. There was a clear threshold in the response of the variables to stock density, though changes become evident only when a highly selective grazing scenario was used. Under high stock density conditions, precipitation use efficiency (PUE) was 82% lower than the values for non-grazed runs. The inter-annual variability of precipitation was more important than the grazing regime in explaining differences in tussock density. Simulation results highlight important issues regarding rangeland management: grazing regime might be as important as stocking density as a degradation agent, temporal lags might obscure degradation processes for decades, the definition of monitoring variables need to consider their response time constants. Fil: Paruelo, José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Pütz, S.. UFZ Centre for Environmental Research Leipzig-Halle; Alemania Fil: Weber, G.. UFZ Centre for Environmental Research Leipzig-Halle; Alemania Fil: Bertiller, Monica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; Argentina Fil: Golluscio, Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Aguiar, Martin Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Wiegand, T.. UFZ Centre for Environmental Research Leipzig-Halle; Alemania
- Published
- 2008
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