Evidence map›Paper›PMID 42368523›Full record

ArticleFrontiers in plant science2026

Divergent environmental constraints shape the spatial patterns of annual gross primary productivity in China's terrestrial ecosystems.

Sha Lei, Ping Zhou, Hui Chen, Ping Yan, Jiaying Lin, Zhaowei Tan, Junxiang Huang, Jiahui Xue

Abstract read
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Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Sha LeiGuangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China.
Ping ZhouGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Hui ChenGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Ping YanGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Jiaying LinGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Zhaowei TanGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Junxiang HuangGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Jiahui XueGuangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Annual Gross Primary Productivity (AGPP) is a key indicator of terrestrial ecosystem carbon sequestration. However, its spatial variability and biome-specific controls remain poorly understood. Methods: Here, we analyzed AGPP across forests, grasslands, croplands, and wetlands in China using data from 166 eddy covariance flux sites. We applied SHapley Additive exPlanations (SHAP) and structural equation modeling (SEM) to quantify the relative importance of environmental variables and to disentangle their direct and indirect effects on AGPP. Results: Our results revealed clear productivity patterns: forests exhibited the highest AGPP, followed by wetlands, croplands, and grasslands. In forests, AGPP was positively associated with temperature and precipitation but negatively related to high vapor pressure deficit (VPD). In grasslands, precipitation enhanced AGPP both directly and indirectly via vegetation structure (leaf area index), whereas excessive radiation constrained productivity. High soil organic carbon (SOC) was associated with lower AGPP in wetlands and croplands, likely reflecting nutrient immobilization under waterlogged conditions and the impacts of intensive agricultural management. Discussion: These findings highlight biome-specific responses of AGPP to climatic conditions, soil properties, and vegetation structure, and provide insights for improving carbon cycle models and guiding targeted ecosystem management.

Indexed as

annual gross primary productivity (AGPP)ecosystem typeseddy covariance (EC)machine learningstructure equation modeling (SEM)

Identifiers

PMID42368523
PMCPMC13293895

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