ArticleCommunications biology2023
Integrating multiple plant functional traits to predict ecosystem productivity.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Divergent mechanisms governing aboveground biomass in desert plants across a drought gradient.iScience · 2026Article
- Using leaf and stomatal traits to predict biomass production and water use efficiency in Populus.The Plant journal : for cell and molecular biology · 2025Article
- Climatic Adaptability Changes in Leaf Functional Traits of OldPlants (Basel, Switzerland) · 2025Article
- Contrasting Roles of Intraspecific Trait Variability and Species Turnover in Shaping Functional Composition During Vegetation Restoration on the Loess Plateau.Ecology and evolution · 2025Article
- Article
- Plant Acquisitive Strategies Promote Resistance and Temporal Stability of Semiarid Grasslands.Ecology letters · 2025Article
- Plant traits shape global spatiotemporal variations in photosynthetic efficiency.Nature plants · 2025Article
- Comparative analysis of morphological traits and photosynthetic parameters as well as carbon accumulation characteristics of six typical shrub species in the Qilian Mountains.Frontiers in plant science · 2025Article
- Nitrogen Addition and Heterotroph Exclusion Affected Plant Species Diversity-Biomass Relationship by Affecting Plant Functional Traits.Plants (Basel, Switzerland) · 2024Article
- Water-limited environments affect the association between functional diversity and forest productivity.Ecology and evolution · 2023Article
- Integrating multiple plant functional traits to predict ecosystem productivity.Communications biology · 2023Article
- Response of grassland ecosystem function to plant functional traits under different vegetation restoration models in areas of karst desertification.Frontiers in plant science · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R
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