This study sought to investigate the feasibility of using field data and remote sensing structural and functional indices in the evaluation and monitoring of semi-steppe rangelands of Isfahan Province, Iran. The study area was first divided into 40 sub-catchments, and rangeland conditions in each sub-catchment were classified into three classes using the four-factor method (FFM). Landsat TM and OLI images for 1987 and 2015 were obtained, and the normalized difference vegetation index (NDVI) was calculated. The structure of the area was evaluated using landscape function analysis (LFA) and rangeland landscape metrics. Rangeland function was also assessed and statistically compared using LFA and the leakiness index (LI). In order to clarify the effects of climate and management on rangeland function, changes in the standardized precipitation index (SPI) were computed and monitored at different intervals. The results indicated the reduction of structural indices, rangeland conditions, and patch sizes over time. Structural metrics suggested the fragmentation of the rangelands with 40–60% canopy cover and the development of rangelands with 0–20%. The structural changes affected rangeland function, and thus reduced the functions of the studied sub-catchments over the 28-year period (p < 0.05). The trend of SPI revealed several periods of drought with different intensities and durations. Reduced precipitation caused structural changes and further decreased function in 2015. According to the obtained results, the combined field-based and remotely sensed approach applied in this research can be used to assess and monitor the functionality and structure of semi-steppe rangeland ecosystems at sub-catchment scale.
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Safaei, M., Jafari, R., Bashari, H. et al. Mapping and monitoring of the structure and function of rangeland ecosystems in central Zagros, Iran. Environ Monit Assess 190, 662 (2018). https://doi.org/10.1007/s10661-018-7005-8
- Leakiness index
- Rangelands condition
- Standard precipitation index
- Structural and functional analysis
- Semi-steppe ecosystems