Using the dynamics of productivity and precipitation-use efficiency to detect state transitions in Eurasian grasslands - Zhang, Tianyou; Chen, Zhi; Jiao, Cuicui; Zhang, Weikang; Han, Lang; Fu, Zheng; Sun, Zhongyi; Liu, Zhaogang; Wen, Zhongming; Yu, Guirui (Frontiers in Ecology and Evolution, 2023)
In the face of accelerated global dryland expansion and grassland degradation, signaling grassland ecosystem state transitions are ongoing challenges in ecology. However, there is yet lack of effective indicators and mechanisms understanding for grassland ecosystem state transitions at the continental-scale. Here, we proposed a framework that links ecosystem function-based indicators and critical slowing down (CSD) theory to reveal grassland state transitions. Across precipitation gradient, we quantified statistical characteristics and spatial patterns in ANPP and PUE dynamics (variability, asymmetry, sensitivity to precipitation and temperature) in Eurasian grasslands. We show that the CVANPP, CVPUE, AANPP, APUE, SPUE-P, and SANPP-P of temperate steppe was significantly higher than those of alpine steppe, while the SPUE-T and SANPP-T was inverse. In temperate grasslands, AANPP, APUE and SANPP-P indicated the transition of typical steppe, CVANPP, APUE, and SPUE-T indicated the transition from meadow to typical steppe. In alpine grassland, APUE indicated the transition between alpine desert and alpine steppe, AANPP and SANPP-P indicated the transition between alpine steppe and meadow steppe. Interannual variability of precipitation strongly affected xerophyte proportion and demographic processes, which controlled state transition in low-resilience grasslands. Community structure and limiting factors (nutrient, light and/or temperature) regulated state transition in high-resilience grasslands. Our results demonstrated that function-based indicators were predictive of impending state transitions of temperate and alpine grasslands, highlighting the complementation of ANPP and PUE dynamics that have the potential for predicting grassland ecosystems regime shift and the underlying mechanisms.