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Clusters of high abundance of plants detected from local indicators of spatial association (LISA) in a semi-deciduous tropical forest

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  • José Ramón Martínez Batlle
  • Yntze van der Hoek

Abstract

Plants are rarely randomly distributed across communities, and patchiness is a common spatial pattern in most tropical forests. Clusters of high density of plant individuals are related to internal and external forces, as well as to historical events. The detection of aggregated patterns of plant individuals allows for a better understanding of the internal and external factors that guide the distribution of species. The aim of this research was to detect and characterize clusters of high abundance of plants and species richness in semi-deciduous forests in the Dominican Republic. For this, we collected vegetation data from 575 quadrats in 23 transects (2300 m2 in total) within the Ocoa river basin. Using local Moran’s I statistics, we isolated 18 quadrats of high density of individuals. We show that density of individuals can be 2.5 times larger on average than in non-aggregated quadrats, and can reach higher values for shrubs species as well as for palms and vines species. In addition, we found that shrub species are the most abundant group in aggregated quadrats, and density of tree species is significantly smaller than that of shrub species. High density quadrats are predominantly occupied by shrubs, palms and vines, following patterns of species composition and lithology. Detecting clusters of high density of individuals could help in the efficient assessment of richness in semi-deciduous tropical forests, and may support new conservation practices for this valuable but threatened ecosystem.

Suggested Citation

  • José Ramón Martínez Batlle & Yntze van der Hoek, 2018. "Clusters of high abundance of plants detected from local indicators of spatial association (LISA) in a semi-deciduous tropical forest," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-16, December.
    • Handle: RePEc:plo:pone00:0208780
    DOI: 10.1371/journal.pone.0208780
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    1. Min Li & Peng Zheng & Wenbin Pan, 2022. "Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian," Sustainability, MDPI, vol. 14(5), pages 1-25, March.
    2. Yaqi Cheng & Wei Song & Hao Yu & Xi Wei & Shuangqing Sheng & Bo Liu & He Gao & Junfang Li & Congjie Cao & Dazhi Yang, 2023. "Assessment and Prediction of Landscape Ecological Risk from Land Use Change in Xinjiang, China," Land, MDPI, vol. 12(4), pages 1-21, April.

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