English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/142479
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


Living in risky landscapes: delineating management units in multithreat environments for effective species conservation

AuthorsOlea, Pedro P.; Mateo-Tomás, Patricia
KeywordsNeophron percnopterus
Threatened species
Multivariate analysis
Wildlife management
Biodiversity conservation
Egyptian vulture
Evidence-based conservation
Habitat heterogeneity
Issue Date2014
PublisherJohn Wiley & Sons
CitationJournal of Applied Ecology 51(1): 42-52 (2014)
AbstractManaging threatened species to reduce their extinction risk is a widely used, yet challenging, means of halting biodiversity loss. Species show complex spatial patterns of extinction risk, due to spatial variation in both threats and vulnerability across their ranges. Conservation practitioners, however, rarely consider this spatial variation and routinely apply uniform conservation schemes, either throughout the species' ranges, or following administrative borders that do not match ecological boundaries. Most of these schemes are experience-based (e.g. expert opinion) and thus difficult to replicate. We accounted for spatial variation in species' threats by using multivariate techniques [i.e. cluster analyses and multidimensional scaling (MDS)] to delineate management units for more effective conservation. We grouped breeding territories of the endangered Egyptian vulture, according to interterritory similarity in presence and intensity of their threats. The first three MDS axes explained 62% of the data variation. The first axis separated territories in protected areas, with low human presence, but high risk of illegal poisoning from areas highly dominated by humans. The second axis classified territories regarding the density of sheep/goats and griffon vultures and the presence of wind farms. The third axis confronted territories in protected areas with those in unprotected areas with wind farms. We obtained 18 statistically supported groups (i.e. management units) including 86% of the territories. Territories within the same group were geographically close, agreeing with the underlying spatial autocorrelation of threats. However, six groups (33%) were distributed over more than one administrative region, which will require inter-regional coordination for cost-effective conservation. Synthesis and applications. Our results show wide spatial variation for species' threats and suggest incorporation of this heterogeneity into conservation schemes. We demonstrate how multivariate statistics, coupled with uncertainty analysis, can be employed in a systematic and repeatable way to deal with the heterogeneous landscapes of risk that species face across their ranges. Our approach allows researchers and managers to delineate management units according to similarity in species' threats for any targeted organization level (e.g. individuals, territories, populations). The results can be visualized in Euclidean and geographical spaces for better interpretation, allowing managers to design more effective conservation actions.
Identifiersdoi: 10.1111/1365-2664.12176
issn: 0021-8901
e-issn: 1365-2664
Appears in Collections:(IREC) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.