Theme 4: Wildlife--Oral Sessions

Description

Rangelands cover more than 80% of South Africa’s land area, providing critical ecosystem services, livelihoods and cultural values related to livestock. Communally owned rangelands are often overgrazed and subject to runaway fires but lack of data limits our understanding of how these threats impact production. In this transdisciplinary project, we use models to test hypotheses and predict future scenarios as a planning tool for resource-poor communal farmers. We think that moderate grazing and fire regimes will increase overall production and carbon sequestration with uncertain trade-offs for water and nutrient cycling. To test this, we trained two process-based biogeochemical models (DAYCENT and SPACSYS) with individual merits to simulate known fire returns and grazing pressures on a 40-year old long-term ecological research grassland site, and validated models with data from Mvenyane, a nearby communal livestock grazing area. DAYCENT and SPACSYS simulated observed soil organic carbon well, while accuracy for aboveground herbaceous biomass differed between models. DAYCENT projected that soil organic carbon could increase by ca. 1000 g C m-2 over ten years or 1 t C ha-1 yr-1 with moderate increases in biomass and no change in water fluxes when changing from continuous high pressure to moderate pressure grazing in a two-camp rotation, with or without fire. These and other scenarios, including future climate projections, will be used to evaluate biophysical and social trade-offs so that sustainable land use plans can be created in Mvenyane and the wider rangeland community.

Share

COinS
 

Modelling Grazing and Burning in Communal Rangelands to Help Understand Trade-offs between Production, Carbon, and Water

Rangelands cover more than 80% of South Africa’s land area, providing critical ecosystem services, livelihoods and cultural values related to livestock. Communally owned rangelands are often overgrazed and subject to runaway fires but lack of data limits our understanding of how these threats impact production. In this transdisciplinary project, we use models to test hypotheses and predict future scenarios as a planning tool for resource-poor communal farmers. We think that moderate grazing and fire regimes will increase overall production and carbon sequestration with uncertain trade-offs for water and nutrient cycling. To test this, we trained two process-based biogeochemical models (DAYCENT and SPACSYS) with individual merits to simulate known fire returns and grazing pressures on a 40-year old long-term ecological research grassland site, and validated models with data from Mvenyane, a nearby communal livestock grazing area. DAYCENT and SPACSYS simulated observed soil organic carbon well, while accuracy for aboveground herbaceous biomass differed between models. DAYCENT projected that soil organic carbon could increase by ca. 1000 g C m-2 over ten years or 1 t C ha-1 yr-1 with moderate increases in biomass and no change in water fluxes when changing from continuous high pressure to moderate pressure grazing in a two-camp rotation, with or without fire. These and other scenarios, including future climate projections, will be used to evaluate biophysical and social trade-offs so that sustainable land use plans can be created in Mvenyane and the wider rangeland community.