Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology

Di Marco, Moreno, Buchanan, Graeme M., Szantoi, Zoltan, Holmgren, Milena, Marasini, Gabriele Grottolo, Gross, Dorit, Tranquilli, Sandra, Boitani, Luigi and Rondinini, Carlo (2014) Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 369 1643: 1-12. doi:10.1098/rstb.2013.0198


Author Di Marco, Moreno
Buchanan, Graeme M.
Szantoi, Zoltan
Holmgren, Milena
Marasini, Gabriele Grottolo
Gross, Dorit
Tranquilli, Sandra
Boitani, Luigi
Rondinini, Carlo
Title Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology
Journal name Philosophical transactions of the Royal Society of London. Series B, Biological sciences   Check publisher's open access policy
ISSN 1471-2970
0962-8436
Publication date 2014-05-26
Sub-type Article (original research)
DOI 10.1098/rstb.2013.0198
Open Access Status Not yet assessed
Volume 369
Issue 1643
Start page 1
End page 12
Total pages 12
Place of publication London, United Kingdom
Publisher The Royal Society Publishing
Language eng
Abstract Although conservation intervention has reversed the decline of some species, our success is outweighed by a much larger number of species moving towards extinction. Extinction risk modelling can identify correlates of risk and species not yet recognized to be threatened. Here, we use machine learning models to identify correlates of extinction risk in African terrestrial mammals using a set of variables belonging to four classes: species distribution state, human pressures, conservation response and species biology. We derived information on distribution state and human pressure from satellite-borne imagery. Variables in all four classes were identified as important predictors of extinction risk, and interactions were observed among variables in different classes (e.g. level of protection, human threats, species distribution ranges). Species biology had a key role in mediating the effect of external variables. The model was 90% accurate in classifying extinction risk status of species, but in a few cases the observed and modelled extinction risk mismatched. Species in this condition might suffer from an incorrect classification of extinction risk (hence require reassessment). An increased availability of satellite imagery combined with improved resolution and classification accuracy of the resulting maps will play a progressively greater role in conservation monitoring.
Keyword Biodiversity
onservation actions
Habitat loss
Life history
Random forest model
Threats
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Biological Sciences Publications
 
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