Spatial modelling of large ungulate biomass in the gazetted protected areas and conservancies in Zimbabwe

Abstract

Understanding large ungulate quantities that can be sustained in protected areas (PAs) is key for implementing strategic management plans in PAs. Studies that have estimated LUB and the associated ecological carrying capacity in PAs using spatially-explicit rainfall data are few. Thus, this study aimed to assess LUB in the gazetted protected areas and conservancies in Zimbabwe using the biomass logarithmic models fed with satellite-based rainfall and soil nutrient availability (SNA). Pearson’s correlation was used to establish the spatial relationship between vegetation cover and LUB. Analysis of Covariance was applied to assess LUB model performance across different SNA levels with SNA, vegetation cover, and LUB as the explanatory, covariate, and response variable, respectively. Variation of LUB across different PA categories was assessed using One Way ANOVA. Results showed a significant positive association of vegetation cover with LUB on low SNA (r=0.4, p=0.03), medium SNA (r=0.53, p=0.002), and high SNA areas (r=0.69, p<0.001). Results revealed the significant relevance of rainfall and SNA in determining the spatial distribution of LUB(F(2,86)=51.76, p<0.01). Findings also indicated significant variation of LUB between different PA categories (F(4,145)=67.62, p<0.01). These Findings could guide conservation planning regarding wildlife translocation, stocking, destocking, rangeland monitoring, and ecological integrity maintenance within PAs.

Keywords

• Large ungulate biomass
• modelling
• logarithmic models
• Zimbabwe Protected Areas and Conservancies