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Local factors determine plant community structure on closely neighbored islands.

ABSTRACT: Despite the recent popularity of the metacommunity concept, ecologists have not evaluated the applicability of different metacommunity frameworks to insular organisms. We surveyed 50 closely spaced islands in the Thousand-Island Lake of China to examine the role of local (environmental) and regional (dispersal) factors in structuring woody plant assemblages (tree and shrub species) on these islands. By partitioning the variation in plant community structure into local and regional causes, we showed that local environmental conditions, specifically island morphometric characteristics, accounted for the majority of the variation in plant community structure among the studied islands. Spatial variables, representing the potential importance of species dispersal, explained little variation. We conclude that one metacommunity framework-species sorting-best characterizes these plant communities. This result reinforces the idea that the traditional approach of emphasizing the local perspective when studying ecological communities continues to hold its value.

SUBMITTER: Lu J

PROVIDER: S-EPMC3091879 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Local factors determine plant community structure on closely neighbored islands.

Lu Jianbo J Jiang Lin L Yu Lin L Sun Que Q

PloS one 20110510 5

Despite the recent popularity of the metacommunity concept, ecologists have not evaluated the applicability of different metacommunity frameworks to insular organisms. We surveyed 50 closely spaced islands in the Thousand-Island Lake of China to examine the role of local (environmental) and regional (dispersal) factors in structuring woody plant assemblages (tree and shrub species) on these islands. By partitioning the variation in plant community structure into local and regional causes, we sho ...[more]

PMID: 21572960

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Project description:Freshwater ecosystems are exposed to multiple stressors, but their individual and combined effects remain largely unexplored. Here, we investigated the response of stream biofilm bacterial communities to warming, hydrological stress, and pesticide exposure. We used 24 artificial streams on which epilithic (growing on coarse sediments) and epipsammic (growing on fine sediments) stream biofilms were maintained. Bacterial community composition and estimated function of biofilms exposed during 30 days to individual and combined stressors were assessed using 16S rRNA gene metabarcoding. Among the individual effects by stressors, hydrological stress (i.e., a simulated low-flow situation) was the most relevant, since it significantly altered 57% of the most abundant bacterial taxa (n = 28), followed by warming (21%) and pesticide exposure (11%). Regarding the combined effects, 16% of all stressor combinations resulted in significant interactions on bacterial community composition and estimated function. Antagonistic responses prevailed (57 to 89% of all significant interactions), followed by synergisms (11 to 43%), on specific bacterial taxa, indicating that multiple-stressor scenarios could lead to unexpected shifts in the community composition and associated functions of riverine bacterial communities.IMPORTANCE Freshwater ecosystems such as rivers are of crucial importance for human well-being. However, human activities result in many stressors (e.g., toxic chemicals, increased water temperatures, and hydrological alterations) cooccurring in rivers and streams worldwide. Among the many organisms inhabiting rivers and streams, bacteria are ecologically crucial; they are placed at the base of virtually all food webs and they recycle the organic matter needed for bigger organisms. Most of these bacteria are in close contact with river substratum, where they form the biofilms. There is an urgent need to evaluate the effects of these stressors on river biofilms, so we can anticipate future environmental problems. In this study, we experimentally exposed river biofilms to a pesticide mixture, an increase in water temperature and a simulated low-flow condition, in order to evaluate the individual and joint effects of these stressors on the bacterial community composition and estimated function.

Dataset Information

Local factors determine plant community structure on closely neighbored islands.

Publications

Local factors determine plant community structure on closely neighbored islands.

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