Multivariate grazing pressure indices improve prediction of semi-arid rangeland dynamics

Forage provision of semi-arid rangelands is severely impacted by droughts and overgrazing, threatening the livelihoods of many people, particularly in the Global South. In these rangelands, grazing pressure is an important predictor of rangeland functionality. However, quantifying grazing pressure at fine spatial resolution and comparing it across management systems remains challenging, due to its complex spatial, temporal and behavioural dimensions. In this study, we assessed whether composite grazing indices offer greater explanatory power than the widely used indicator ‘distance from water source’ and whether these indices can be applied across tenure systems. To this end, we developed three composite grazing indices of increasing complexity using Principal Component Regression. These indices incorporated cattle-grazing related variables such as distance measures, grazing offtake, moribund plant material and signs of cattle activity. The variables reflected both long- and short-term grazing pressure and were derived from communal and freehold rangelands in Namibia. To evaluate our indices, we fitted quantile regression models using bare soil, perennial grass cover, plant species richness and plant species diversity as response variables. We found notable improvements in model fit with increasing model complexity. This was particularly the case for plant species diversity, which displayed a unimodal relationship with grazing pressure but none with distance from water. Despite high data variability and generally low model fit, our results demonstrate that composite grazing pressure indices offer great potential to capture and compare semi-arid rangeland dynamics at finer spatial resolution than a single distance-based metric.