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Using abundance and habitat variables to identify high conservation value areas for threatened mammals

Tijdschriftbijdrage - Tijdschriftartikel

The present study used abundance and habitat variables to design High Conservation Value Forests for wildlife protection. We considered great apes (Gorilla gorilla gorilla and Pan troglodytes troglodytes) as model species, and we used nest surveys, dietary analysis and botanical inventories to evaluate whether the traditional methods that use abundance data alone were consistent with the survival of the species. We assumed that setting a local priority area for animal conservation can be made possible if at least one variable (abundance or habitat variables) is spatially clustered and that the final decision for a species may depend on the pattern of spatial association between abundance, nesting
habitat and feeding habitat. We used Kernel Density Estimation to evaluate the spatial pattern of each biological variable. The results indicate that all three variables were spatially clustered for both gorillas and chimpanzees. The abundance variables of both animal species were spatially correlated to their preferred nesting habitat variables. But while the chimpanzee feeding habitat variable was spatially correlated to the abundance and nesting
habitat variables, the same pattern was not observed for gorillas. We then proposed different methods to be considered to design local priority areas for the conservation of each great ape species. Alone, the abundance variable does not successfully represent the spatial distribution of major biological requirements for the survival of wildlife species; we, therefore, recommend the integration of the spatial distribution of their food resources to overcome the mismatch caused by the existence of a biological interaction between congeneric
species.
Tijdschrift: Biodiversity and Conservation
ISSN: 0960-3115
Aantal pagina's: 23
Jaar van publicatie:2017
Trefwoorden:Omgevingswetenschappen en technologie, Ecologie en toegepaste ecologie
  • Scopus Id: 85035792549