An adaptive cycle resilience perspective to understand the regime shifts of social-ecological system interactions over the past two millennia in the Tarim River Basin

Abstract

Socio-ecological systems (SESs) in arid regions have experienced multiple transformations throughout history due to human activities and natural forces. However, few studies have used the resilience cycle model to explain the resilience status and determinants of SESs over the past two millennia. This study proposes the adaptive cycle resilience (ACR) perspective to investigate regime shifts of socio-ecological system interactions in the Tarim River Basin (TRB) over the past two millennia. An ACR framework combining a piecewise linear regression model (PLR), ACR theory, and physical resilience models has been built to assess and quantify socio-ecological system resilience. Key indicators such as climate variability, settlement numbers, war frequency, glacier accumulation, and oasis area changes are identified and quantified to evaluate SESs adaptability and transformability. Glacier accumulation serves as a proxy for long-term climate change, while oasis area changes reflect the direct impact of human activities and environmental feedback on ecosystem productivity. Population and war indicators provide insights into social system stability and the impact of conflicts on SESs dynamics. The findings reveal that the 7th century and 1850s are critical points of regime shifts in the ACR. 200s BC-350s AD and 700s AD-900s AD are in the forward loop (r-K) period of the ACR. 350s AD-700s AD and 900s AD-1850s AD are the adaptive resilience backward loop (Ω-α) phase. Assessing the historical socio-ecological system resilience and identifying key transition points can inform proactive measures to mitigate potential regime shifts. Combining historical data with resilience theory provides a deep understanding of the ACR of SESs and their driving factors. This enriches the theoretical understanding of SESs and offers a robust case study for future resilience assessments and scenario analyses in arid regions.