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Combinación de la Relación de Especies‐Área‐Hábitat y el Análisis Clúster Ambiental para Definir Prioridades de Conservación: un Estudio en el Archipiélago Zhoushan, China
Author(s) -
CHEN YOUHUA
Publication year - 2009
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.2008.01084.x
Subject(s) - geography , spatial analysis , archipelago , diversity index , habitat , ecology , cluster analysis , environmental resource management , species richness , statistics , environmental science , mathematics , biology , remote sensing , archaeology
Identification of priority areas is a fundamental goal in conservation biology. Because of a lack of detailed information about species distributions, conservation targets in the Zhoushan Archipelago (China) were established on the basis of a species–area–habitat relationship (choros model) combined with an environmental cluster analysis (ECA). An environmental‐distinctness index was introduced to rank areas in the dendrogram obtained with the ECA. To reduce the effects of spatial autocorrelation, the ECA was performed considering spatial constraints. To test the validity of the proposed index, a principal component analysis–based environmental diversity approach was also performed. The priority set of islands obtained from the spatially constrained cluster analysis coupled with the environmental‐distinctness index had high congruence with that from the traditional environmental‐diversity approach. Nevertheless, the environmental‐distinctness index offered the advantage of giving hotspot rankings that could be readily integrated with those obtained from the choros model. Although the Wilcoxon matched‐pairs test showed no significant difference among the rankings from constrained and unconstrained clustering process, as indicated by cophenetic correlation, spatially constrained cluster analysis performed better than the unconstrained cluster analysis, which suggests the importance of incorporating spatial autocorrelation into ECA. Overall, the integration of the choros model and the ECA showed that the islands Liuheng, Mayi, Zhoushan, Fodu, and Huaniao may be good candidates on which to focus future efforts to conserve regional biodiversity. The 4 types of priority areas, generated from the combination of the 2 approaches, were explained in descending order on the basis of their conservation importance: hotspots with distinct environmental conditions, hotspots with general environmental conditions, areas that are not hotspots with distinct environmental conditions, and areas that are not hotspots with general environmental conditions.