Using a landscape ecological perspective to analyze regime shifts in social–ecological systems: a case study on grassland degradation of the Tibetan Plateau

Abstract
Context: Landscape ecology thinking and social–ecological system (SES) thinking investigate human–environment relationships from the perspective of ‘space’ and ‘system’, respectively. To date, empirical landscape ecology studies attempting to understand SES complexities are rare. Objectives: Using the Tibetan pastoral landscape as an empirical example, we conceptualize the black-soil formation as SES regime shifts. We seek to illustrate the spatial patterns of black-soil formation in the Tibetan SES, and to reveal their underlying ecological processes. Methods: We conducted interdisciplinary research in a Tibetan pastoral village. We obtained quantitative data on historical land-use intensity (LUI) and the associated management narratives. Landsat-based NDVI time series were used to derive a grassland productivity proxy and to reconstruct the process leading to the up-scaling of the regime shift of degradation. Results: Important SES features, such as LUI, productivity and degradation risk are heterogeneously distributed in space. Land-use intensification at farm-scales in the 1990s increased landscape-scale degradation risks. Eventually the regime shift of degradation scaled up from the plot level to the landscape level in the 2010s. The time lag was related to the gradual invasion of a native burrowing animal, the plateau pika, which inhabits low-vegetation height pastures. Conclusions: Our study shows that landscape ecology thinking provides an important spatial perspective to understanding SES complexities. The finding that unfavorable SES regime shifts are strongly linked across spatial scales implies that an ‘entry point’ into an adaptive management circle should be initiated when local-scale regime shifts are perceived and interpreted as early warning signals.
Funding Information
  • National Key Research and Development Program of China (2019YFC0507705)
  • Postdoctoral Research Foundation of China (2019M650322)