From species to pixels : monitoring rangeland quality & productivity by leveraging the NDVI-RCI relationship

Abstract

Grasslands are highly vulnerable to climate and changes in grazing management, yet little is known about the national rangeland response to long-term (>18 years) grazing management that may confound climate effects. This study assessed the correlation between Normalized Difference Vegetation Index (NDVI), i.e., productivity and Rangeland Condition Index (RCI) i.e., quality and predicted historical grazing management (26 years) using Ecological Index Method (EIM) analysis of 72 relevés in the Highland Sourveld (HSV). Relationships between 150 NDVI and 72 RCI samples showed a rate of 0.125 change in NDVI for every 12.5% change in RCI. In 1983, the HSV’s rangeland carrying capacity (RCC) ranged from 2.0 - 2.2 ha/AU/yr (land required to support one mature bovine for 1 year), with an NDVI of 0.43, like the benchmark. site. By 2009, the RCC decreased to 3.2 ha/AU/yr, with NDVI <0.30. Selective overgrazing, reduced RCC by increasing Increaser II species and reducing Decreaser species presence. Findings suggest combining NDVI and RCI is more effective than using either alone. Integrating remote sensing with traditional ecological data (Ecological Remote Sensing - eRS) improves our understanding of rangeland vulnarability, thus, ideal for permanent monitoring of public rangelands in South Africa.