Data · dataset · 2026
Non-random defaunation: Multidimensional dark diversity demonstrates pervasive mammal community incompleteness in China’s protected area network
Listed in ScienceDB
Protected areas are central to global biodiversity conservation, yet assessments of their effectiveness focus largely on observed species richness.
Description
This approach overlooks dark diversity—the species absent from biogeographically suitable habitats and their associated evolutionary and ecological roles. We used a dataset comprising 7.4 million camera-trap days across 199 nature reserves in China to assess the taxonomic, phylogenetic, and functional dark diversity of medium- and large-sized mammals.
Biogeographic null models and Bayesian hierarchical models showed that mammal communities in these reserves were, on average, 56% incomplete. Dark diversity across all three dimensions was highest in southern and east-central China, despite these regions having the highest observed species richness. Null-model analyses indicated that mammal losses in southern China were non-random, with disproportionate losses of evolutionary lineages and functional trait space.
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By contrast, northern and high-altitude reserves retained more complete mammal assemblages than expected by chance. Although the three dimensions of dark diversity were positively correlated, they had distinct drivers. Reserve area was the main constraint on taxonomic dark diversity, whereas topography, precipitation, and net primary productivity shaped phylogenetic and functional dark diversity.
These findings show that conventional richness-based metrics can mask conservation deficits in biodiverse regions. We recommend integrating multidimensional dark diversity into routine protected-area evaluations to inform ecological restoration, habitat-connectivity planning, and species recovery.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.44656 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Forestry sciences 74%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.44656 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3007 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |