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Community composition and species traits and plot positions

Cite this dataset

Li, Yi et al. (2022). Community composition and species traits and plot positions [Dataset]. Dryad.


Biodiversity decline and its cascading effects through trophic interactions pose a severe threat to ecosystem service worldwide. Within a synthetic conceptual framework for beta-diversity, we proposed a series of hypotheses related to multi-trophic community assembly in subtropical forests. Our results suggested that, resulting from niche-based bottom-up dynamics, producer dissimilarities are predominant in structuring consumer dissimilarity, the degree of which highly depends on the trophic dependency, the diversity facet and the data quality. More importantly, we detected a significant dynamic between niche-based processes (e.g. environmental filtering and competitive exclusion) with the increasing producer dissimilarity. These findings enrich our mechanistic understanding of the ‘Diversity Begets Diversity’ rule and the complexity of multi-trophic community assembly, which is fundamental and critical for sustainable biodiversity conservation and ecosystem management.


Caterpillar sampling was conducted in April, June, and September in 2019; spider samples used in this work were collected in April, June, and September in 2017. The samplings of both caterpillars and spiders were carried out by beating and shaking 80 living trees in each plot. A white square sheet (1.5 m × 1.5 m) was used to collect all samples dislodged from the tree crown. This sampling regime covered all tree species and species richness levels. All samples were stored in separate tubes filled with 99.5% ethanol to reduce contamination and subsequently stored in a −20 ℃ freezer before DNA extractions.


Strategic Priority Research Program of the Chinese Academy of Science, Award: XDB310304

National Science Fund for Distinguished Young Scholars, Award: 31625024

Key Laboratory of the Zoological Systematics and Evolution of the Chinese Academy of Sciences, Award: Y229YX5105

National Natural Science Foundation of China, Award: 32100343