Trait‐dependent response of dung beetle populations to tropical forest conversion at local and regional scales. Issue 1 (1st January 2013)

• Record Type: Journal Article
• Authors: Nichols, Elizabeth; Uriarte, María; Bunker, Daniel E.; Favila, Mario E.; Slade, Eleanor M.; Vulinec, Kevina; Larsen, Trond; Vaz-de-Mello, Fernando Z.; Louzada, Julio; Naeem, Shahid; Spector, Sacha H.
• Is Part Of: Ecology. Volume 94:Issue 1(2013)
• Page Start: 180
• Page End: 189
• Publication Date: 2013-01-01
• Subjects: body size -- context-dependency -- extinction risk -- extrinsic factors -- fitness -- functional traits -- land use change -- population response -- Scarabaeinae -- trait-based approaches; Ecology -- Periodicals; Ecology -- Periodicals; Écologie -- Périodiques; Ecologie; Écologie; Écologie animale; Écologie végétale; Ecology; Periodicals; 577.05
• DOI: 10.1890/12-0251.1
• Languages: English
• ISSNs: 0012-9658

Abstract

Abstract : Comparative analyses that link information on species' traits, environmental change, and organism response have rarely identified unambiguous trait correlates of vulnerability. We tested if species' traits could predict local‐scale changes in dung beetle population response to three levels of forest conversion intensity within and across two biogeographic regions (the Neotropics and Afro‐Eurasian tropics). We combined biodiversity surveys, a global molecular phylogeny, and information on three species' traits hypothesized to influence vulnerability to forest conversion to examine (1) the consistency of beetle population response across regions, (2) if species' traits could predict this response, and (3) the cross‐regional consistency of trait–response relationships. Most beetle populations declined following any degree of forest conversion; these declines were strongest for Neotropical species. The relationship between traits and population trend was greatly influenced by local and biogeographic context. We discuss the ability of species' traits to explain population trends and suggest several ways to strengthen trait–response models.