Contemporary niche contraction affects climate change predictions for elephants and giraffes

• Published in: Diversity & distributions 2016-04, Vol.22 (4), p.432-444
• Main Authors: Martínez‐Freiría, Fernando, Tarroso, Pedro, Rebelo, Hugo, Brito, José C, Thuiller, Wilfried
• Format: Article
• Language: English
• Subjects: Africa; algorithms; BIODIVERSITY RESEARCH; Biogeography; Climate change; data collection; Elephantidae; Elephants; Giraffa camelopardalis; habitat loss; historical distributions; humans; Loxodonta africana; multivariate analysis; overhunting; prediction; range contraction; savannas; species distribution models; temporal variation; Wildlife management
• ISSN: 1366-9516; 1472-4642
• DOI: 10.1111/ddi.12406

AIM: Climate change assessments are largely based on correlative species distribution models (SDMs) that are sensible to spatial biases or incompleteness of input distribution data. We tested whether changes on the species' climatic niche resulting from recent human‐induced range contractions have a significant influence on SDM predictions of future species distributions. LOCATION: Africa. METHODS: For this study, we selected two highly detectable species with acknowledged human‐induced range contractions, namely the African savanna elephant (Loxodonta africana) and giraffe (Giraffa camelopardalis). We used presence data until the 1970s to describe each species' historical distribution, while more recent data characterized the contemporary distribution. We compared the temporal variation between these species distributions using multivariate analyses and the combination of four different SDM algorithms to predict historical, contemporary and future distributional ranges under climate change scenarios. RESULTS: We show how range contraction differentially reduces the climatic variability associated with the species niche and has an important influence on the predictions of suitable climatic space and species vulnerability trend under climate change scenarios. Future predictions of the distribution of the elephant were mainly affected by the loss of occupied area at the margins of the historical distributions, resulting in a lesser predicted extent when using the contemporary dataset. As for the giraffe models, there were more dramatic consequences with large areas of West Africa failing to be predicted as suitable in the contemporary models, probably as a result from the loss of climatic information due to the species almost complete disappearance from that region. MAIN CONCLUSIONS: Our findings support the importance of considering historical distributional ranges of species in climate change studies in order to account for their full climatic niche and to derive more reliable predictions of future distribution. This is particularly important in species for which distributional ranges have been strongly affected by human activities.