Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects.

Yunjun Bai,Xueping Wei,Xiaoqiang Li

doi:10.7717/peerj.4287

Abstract

BackgroundThe ongoing change in climate is predicted to exert unprecedented effects on Earth’s biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future.MethodsIn this study, we modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time.ResultsHistorical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas.DiscussionIn combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time.

Highlights

Of the four billion species that have evolved on Earth over the past 3.5 billion years, 99% are considered to have disappeared (Novacek, 2001), most notably in the ‘Big Five’ mass extinctions (Raup & Sepkoski, 1982; Jablonski & Chaloner, 1994; Bambach, 2006)
By the end of 2012, the closest emissions scenarios resulting from the Intergovernmental Panel on Climate Change (IPCC) process to the observed emission trends were the Special Report on Emissions Scenarios (SRES) A1B used in the IPCC Fourth Assessment Report and the Representative Concentration Pathways (RCPs) 8.5 used in the IPCC Fifth Assessment Report (Peters et al, 2012)
It is noteworthy that the predicted area based on the maximum training sensitivity plus specificity logistic (MTSS) threshold is very similar to that based on the 10 percentile training presence logistic (10% TP) threshold (Figs. 1A–1D)

Summary

Introduction

Of the four billion species that have evolved on Earth over the past 3.5 billion years, 99% are considered to have disappeared (Novacek, 2001), most notably in the ‘Big Five’ mass extinctions (Raup & Sepkoski, 1982; Jablonski & Chaloner, 1994; Bambach, 2006). Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. We modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. This work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time

Methods

Results

Discussion

Conclusion