Land degradation in Central Asia : identifying dynamics of pasture resources in heterogeneous landscapes using remote sensing

• Main Author: Eddy, Ian
• Language: English
• Published: University of British Columbia 2016
• Online Access: http://hdl.handle.net/2429/58813

Rangeland degradation is an issue of global concern yet it can be challenging to accurately assess. In Kyrgyzstan, the post-Soviet transition led to wide-ranging environmental changes in pasturelands, though comprehensive and spatially explicit data remains scarce. Remote sensing vegetation indices (VI) are often used to assess pasture condition where higher VI are assumed to indicate greater productivity. However, pasture productivity may be degraded owing to declining vegetation productivity or changes in plant species composition, both of which can differentially affect vegetation indices. Here, we examined these two aspects using satellite-derived vegetation indices. In Chapter 1, we compared temporal trends (2000-2015) and seasonal maximums of Moderate-Resolution Imaging Spectroradiometer (MODIS) VI in field sites with varying cover of plant species unpalatable to livestock. Relative to other pastures, we found pastures with unpalatable plant cover were associated with higher seasonal maximums of VI (r² = 0.23-0.31) and increases in VI over time (r² = 0.08-0.16). These findings were problematic for pasture monitoring using remote sensing, as detrimental changes in species composition may be conflated with desirable increases in plant cover. In Chapter 2, we examined pixel-based temporal trends in the Normalized Difference Vegetation Index (NDVI) in Naryn oblast, Kyrgyzstan from 2000-2015. We then examined trends in the residuals after applying a regression relationship linking NDVI as a function of precipitation and temperature metrics in order to differentiate anthropogenic from climate-induced impacts to pasture resources. Trend maps were validated against areas of overgrazing identified from interviews with local pasture managers. Temporal trends in NDVI and the regression residuals were overwhelmingly negative (24.0 and 15.2% of the landscape, respectively) outside of row crop agricultural fields, particularly in the lower elevation spring/fall and winter pastures, and were consistent with local managers’ perceptions of pasture degradation. While our approach was limited by the topographic complexity of the study region, it was most successful in the semi-arid steppe region where pasture degradation is believed to be worst. === Forestry, Faculty of === Graduate