Decoupling species richness variation and spatial turnover in beta diversity across a fragmented landscape

Guang Hu, Maxwell C. Wilson, Jianguo Wu, Jingjing Yu, Mingjian Yu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: How habitat fragmentation affects the relationship between local richness and the variation in community composition across space is important to both ecology and conservation biology, but this effect remains poorly understood. Methods: Here, we present an empirical study to address this topic in a fragmented landscape, the Thousand Island Lake (TIL), an artificial land-bridge island system with more than 1,000 islands, which provides an "experimental" fragmented landscape with a homogeneous matrix and similar successional history. We measured species composition and plant functional type (PFT) on 29 islands, and tested the effects of island area and isolation on the relationship between a- A nd β-diversity. General Linear Models were applied to test the impact of habitat fragmentation. In addition, variation partitioning was used to decouple a-diversity dependent and a-diversity independent spatial turnover in β-diversity of the plant community and across different PFTs. Results: We found habitat fragmentation influences β-diversity of plants primarily by modifying local a-diversity, not spatial turnover in the TIL system. We also found area-dependent environmental filtering and differential plant responses across functional types were the most likely underlying driving mechanisms. Discussion: These results highlight the importance of hierarchical linkages between components of biodiversity across scales in fragmented landscapes, and have practical conservation implications.

Original languageEnglish (US)
Article number6714
JournalPeerJ
Volume2019
Issue number4
DOIs
StatePublished - 2019

Keywords

  • Area effect
  • Environmental filtering
  • Isolation
  • Land-bridge islands
  • Plant functional type
  • Thousand island lake

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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