Abstract

AbstractAimClimate change is expected to have important effects on plant phenology and carbon storage, with further shifts predicted in the future. Therefore, we proposed the community carbon accumulation rate (CAR) from the start of the growing season (SOS) to the peak of the growing season (POS) to fill the gap that the dynamic interactions between plant phenology and plant carbon research.LocationTibetan Plateau.Major taxaAlpine grassland plants.Time period2015.MethodsWe conducted a transect survey across grasslands to measure community aboveground net primary production and carbon concentration. Additionally, phenology indicator data (SOS and POS) were extracted from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index version 3 database. Next, we used ‘changepoint’ analysis to detect the patterns of CARs, and performed linear regression and one‐way ANOVA to explore the variability of CARs in response to the environmental factors. Ultimately, the total effects of environmental factors on CARs were illustrated by a structural equation model.ResultsOur results indicated that three CAR patterns were detected, which are low‐CAR (0.15 g/m2/day), medium‐CAR (0.31 g/m2/day) and high‐CAR (0.84 g/m2/day) patterns. We found that the availabilities of water and heat mediated CARs by regulating soil nutrition variability, and that drought climate and insufficient soil resources co‐constrained the community CAR at long time‐scales. In contrast, high CAR could be explained by more water and heat availability via either direct or indirect effects on soil moisture and soil nutrients.Main conclusionsOur findings highlight that water and heat availability are critical driving factors in ecological carbon accumulation processes undergoing climate change. Meanwhile, the vegetative phenology also has important effect on carbon accumulation. Consequently, we propose incorporating the dynamic interactions between plant phenology and plant carbon into the ecological carbon cycle model to improve our understanding of resource utilization and survival strategies of plants under environmental change.

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