How plant diversity varies across an archipelago with highly heterogeneous human activities
Global Ecology and Conservation, ISSN: 2351-9894, Vol: 43, Page: e02446
2023
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Article Description
Identifying and quantifying the impacts of human activity on island plant diversity can help inform their management. Here, we examined the spatial pattern of plant diversity across 11 inhabited islands near to, but outside, the Yangtze River Estuary in the Shengsi Archipelago, China, that represent a diverse range of environmental conditions and human activity levels. We quantified six factors (island morphology, landscape, proximity, ecology, terrain, and soil) and 30 environmental indicators, with different levels of human influence. Regression and canonical correction analyses were used to determine the effects of various factors on the spatial distribution of trees, shrubs, and herbs at four regional scales: sample, island, sub-archipelago, and archipelago. We recorded 287 vascular species belonging to 201 genera at 93 sampling sites in Shengsi, of which 10 invasive alien species at 60 sampling sites were recorded. The plants showed a diverse spatial distribution pattern at the sampling site scale because of the synergistic influence of multiple environmental factors. From the sub-archipelago and island scales, area and isolation are the most critical factors affecting the richness and diversity of shrubs and herbs. The diversity and distribution of trees is highly dependent on human residents, and herbs show strong adaptability on barren landscapes. At the site scale, when collinearity among environmental factors was eliminated, we found that soil bulk density and salinity were critical factors driving the distribution of shrubs and herbs, respectively.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2351989423000811; http://dx.doi.org/10.1016/j.gecco.2023.e02446; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85151316650&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2351989423000811; https://dx.doi.org/10.1016/j.gecco.2023.e02446
Elsevier BV
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