Climate and plant species richness shape productivity allocation under extreme drought across Eurasian steppes

Abstract Extreme drought events are becoming more frequent under climate warming, imposing deleterious effects on plant diversity and ecosystem functioning. Yet how such events influence the allocation of net primary productivity (NPP)—a key indicator of plant adaptation and carbon cycling—remains poorly understood. Using a coordinated extreme drought experiment across six grassland sites spanning Northern China’s Eurasian steppes, we investigated how extreme drought, implemented as control, chronic drought (66% precipitation reduction, May–August), or intense drought (complete rainfall exclusion, June–July), affects NPP partitioning along broad climatic gradients. We found that both drought treatments disproportionately reduced aboveground NPP (ANPP) compared to belowground NPP (BNPP), increasing the fraction of BNPP to NPP (fBNPP). The magnitude of this shift was modulated by aridity, interannual precipitation variability, and soil moisture changes, with the largest increases in fBNPP occurring in regions of intermediate aridity and low precipitation variability. Additionally, drought reduced plant species richness, which in turn exacerbated ANPP declines and further contributed to the shift in fBNPP. These findings highlight the joint regulatory roles of climatic context and biodiversity in mediating NPP allocation under extreme drought. Therefore, our study provides ecological insights into how extreme drought reshapes productivity allocation in grassland ecosystems.

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Publication Details

Journal
Journal of Plant Ecology
Published
2026-03-26
DOI
https://doi.org/10.1093/jpe/rtag058
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Climate and plant species richness shape productivity allocation under extreme drought across Eurasian steppes

Yingjie Yan, Changjin Cheng, Yuguang Ke, Jinsong Wang et al.
Journal of Plant Ecology
Remote Sensing in Agriculture
article

Climate and plant species richness shape productivity allocation under extreme drought across Eurasian steppes

Yingjie Yan, Changjin Cheng, Yuguang Ke, Jinsong Wang, C L Xu, Xiaoan Zuo, Wentao Luo, Honghui Wu, Hongqiang Wang, Yann Hautier, Qiang Yu
article en

Abstract

Abstract Extreme drought events are becoming more frequent under climate warming, imposing deleterious effects on plant diversity and ecosystem functioning. Yet how such events influence the allocation of net primary productivity (NPP)—a key indicator of plant adaptation and carbon cycling—remains poorly understood. Using a coordinated extreme drought experiment across six grassland sites spanning Northern China’s Eurasian steppes, we investigated how extreme drought, implemented as control, chronic drought (66% precipitation reduction, May–August), or intense drought (complete rainfall exclusion, June–July), affects NPP partitioning along broad climatic gradients. We found that both drought treatments disproportionately reduced aboveground NPP (ANPP) compared to belowground NPP (BNPP), increasing the fraction of BNPP to NPP (fBNPP). The magnitude of this shift was modulated by aridity, interannual precipitation variability, and soil moisture changes, with the largest increases in fBNPP occurring in regions of intermediate aridity and low precipitation variability. Additionally, drought reduced plant species richness, which in turn exacerbated ANPP declines and further contributed to the shift in fBNPP. These findings highlight the joint regulatory roles of climatic context and biodiversity in mediating NPP allocation under extreme drought. Therefore, our study provides ecological insights into how extreme drought reshapes productivity allocation in grassland ecosystems.

Journal of Plant Ecology
Utrecht University (NL), Beijing Forestry University (CN), Northwest Institute of Eco-Environment and Resources (CN), Institute of Agricultural Resources and Regional Planning (CN), Institute of Applied Ecology (CN), South China Botanical Garden (CN), Chinese Academy of Agricultural Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN)
Climate action
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
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