ArticleFrontiers in plant science2023
Prediction of spatial distribution characteristics of ecosystem functions based on a minimum data set of functional traits of desert plants.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Using resurvey data to predict changes in ecosystem functioning across protected and unprotected coastal dunes.Conservation biology : the journal of the Society for Conservation Biology · 2026Article
- Intraspecific variation pattern and adaptation mechanism of ephemeral plants root functional traits in arid region.BMC plant biology · 2026Article
- The Gradient Heterogeneity of Deserts Alters the Interaction Relationships Between Xerophytic Plants and Soils.Biology · 2025Article
- Interaction between arbuscular mycorrhizal fungi and dark septate endophytes in the root systems ofFrontiers in plant science · 2024Article
- Study of Changes in the Ulan Buh Desert under the Dual Impacts of Desert Farmland Development and Climate Change.Plants (Basel, Switzerland) · 2023Article
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Authors and funding
7 authors.
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Abstract
The relationship between plant functional traits and ecosystem function is a hot topic in current ecological research, and community-level traits based on individual plant functional traits play important roles in ecosystem function. In temperate desert ecosystems, which functional trait to use to predict ecosystem function is an important scientific question. In this study, the minimum data sets of functional traits of woody (wMDS) and herbaceous (hMDS) plants were constructed and used to predict the spatial distribution of C, N, and P cycling in ecosystems. The results showed that the wMDS included plant height, specific leaf area, leaf dry weight, leaf water content, diameter at breast height (DBH), leaf width, and leaf thickness, and the hMDS included plant height, specific leaf area, leaf fresh weight, leaf length, and leaf width. The linear regression results based on the cross-validations (
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