Twenty-five years of change in southern African passerine diversity : nonclimatic factors of change

© 2015 John Wiley & Sons Ltd.

Bibliographische Detailangaben
Veröffentlicht in:Global change biology. - 1999. - 21(2015), 9 vom: 30. Sept., Seite 3347-55
1. Verfasser: Péron, Guillaume (VerfasserIn)
Weitere Verfasser: Altwegg, Res
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2015
Zugriff auf das übergeordnete Werk:Global change biology
Schlagworte:Journal Article Research Support, Non-U.S. Gov't South Africa biodiversity bush encroachment citizen science climate change conservation planning occupancy models pesticide accumulation species richness
Beschreibung
Zusammenfassung:© 2015 John Wiley & Sons Ltd.
We analysed more than 25 years of change in passerine bird distribution in South Africa, Swaziland and Lesotho, to show that species distributions can be influenced by processes that are at least in part independent of the local strength and direction of climate change: land use and ecological succession. We used occupancy models that separate species' detection from species' occupancy probability, fitted to citizen science data from both phases of the Southern African Bird Atlas Project (1987-1996 and 2007-2013). Temporal trends in species' occupancy probability were interpreted in terms of local extinction/colonization, and temporal trends in detection probability were interpreted in terms of change in abundance. We found for the first time at this scale that, as predicted in the context of bush encroachment, closed-savannah specialists increased where open-savannah specialists decreased. In addition, the trend in the abundance of species a priori thought to be favoured by agricultural conversion was negatively correlated with human population density, which is in line with hypotheses explaining the decline in farmland birds in the Northern Hemisphere. In addition to climate, vegetation cover and the intensity and time since agricultural conversion constitute important predictors of biodiversity changes in the region. Their inclusion will improve the reliability of predictive models of species distribution
Beschreibung:Date Completed 17.06.2016
Date Revised 10.12.2019
published: Print-Electronic
Citation Status MEDLINE
ISSN:1365-2486
DOI:10.1111/gcb.12909