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Change in Phylogenetic Community Structure during Succession of Traditionally Managed Tropical Rainforest in Southwest China

Overview of attention for article published in PLOS ONE, July 2013
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Title
Change in Phylogenetic Community Structure during Succession of Traditionally Managed Tropical Rainforest in Southwest China
Published in
PLOS ONE, July 2013
DOI 10.1371/journal.pone.0071464
Pubmed ID
Authors

Xiao-Xue Mo, Ling-Ling Shi, Yong-Jiang Zhang, Hua Zhu, J. W. Ferry Slik

Abstract

Tropical rainforests in Southeast Asia are facing increasing and ever more intense human disturbance that often negatively affects biodiversity. The aim of this study was to determine how tree species phylogenetic diversity is affected by traditional forest management types and to understand the change in community phylogenetic structure during succession. Four types of forests with different management histories were selected for this purpose: old growth forests, understorey planted old growth forests, old secondary forests (∼200-years after slash and burn), and young secondary forests (15-50-years after slash and burn). We found that tree phylogenetic community structure changed from clustering to over-dispersion from early to late successional forests and finally became random in old-growth forest. We also found that the phylogenetic structure of the tree overstorey and understorey responded differentially to change in environmental conditions during succession. In addition, we show that slash and burn agriculture (swidden cultivation) can increase landscape level plant community evolutionary information content.

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The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
Germany 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Philippines 1 <1%
Unknown 110 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 19%
Researcher 17 15%
Student > Master 13 11%
Student > Bachelor 7 6%
Other 6 5%
Other 26 22%
Unknown 25 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 45%
Environmental Science 23 20%
Medicine and Dentistry 2 2%
Engineering 2 2%
Earth and Planetary Sciences 1 <1%
Other 3 3%
Unknown 33 28%