Climate change hastens the conservation urgency of an endangered ungulate.

• Main Authors: Junhua Hu, Zhigang Jiang
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2011-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC3149626?pdf=render

Global climate change appears to be one of the main threats to biodiversity in the near future and is already affecting the distribution of many species. Currently threatened species are a special concern while the extent to which they are sensitive to climate change remains uncertain. Przewalski's gazelle (Procapra przewalskii) is classified as endangered and a conservation focus on the Qinghai-Tibetan Plateau. Using measures of species range shift, we explored how the distribution of Przewalski's gazelle may be impacted by projected climate change based on a maximum entropy approach. We also evaluated the uncertainty in the projections of the risks arising from climate change. Modeling predicted the Przewalski's gazelle would be sensitive to future climate change. As the time horizon increased, the strength of effects from climate change increased. Even assuming unlimited dispersal capacity of gazelles, a moderate decrease to complete loss of range was projected by 2080 under different thresholds for transforming the probability prediction to presence/absence data. Current localities of gazelles will undergo a decrease in their occurrence probability. Projections of the impacts of climate change were significantly affected by thresholds and general circulation models. This study suggests climate change clearly poses a severe threat and increases the extinction risk to Przewalski's gazelle. Our findings 1) confirm that endangered endemic species is highly vulnerable to climate change and 2) highlight the fact that forecasting impacts of climate change needs an assessment of the uncertainty. It is extremely important that conservation strategies consider the predicted geographical shifts and be planned with full knowledge of the reliability of projected impacts of climate change.