Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

Xiang Xu,Huayong Zhang,Yao Xu,Ting Xie,Wang Tian,Lei Zhao

doi:10.3390/f8100399

Xiang Xu, Huayong Zhang + Show 4 more

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https://doi.org/10.3390/f8100399

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Abstract

Identifying the potentially suitable climatic geographical range for Liriodendron chinense (L. chinense) and predicting its responses to climate change is urgently necessary, as L. chinense is an important tertiary relict tree species. In this study, we simulated the potentially suitable climatic habitat of L. chinense in China using maximum entropy (MaxEnt) modeling. We found that the MaxEnt model was highly accurate with an average training Area Under the Curve (AUC) value of 0.912. Annual precipitation and mean temperature of the driest quarter are the main factors controlling the geographical distribution of L. chinense. Currently, the suitable climatic habitat of L. chinense is mainly located in Southeastern China. Forecasted patterns of predicted suitable climatic habitat show a significant change by the 2050s and 2070s, suggesting that the suitable climatic habitat of L. chinense would shift north with future climate change, based on four Representative Concentrations Pathways for carbon dioxide (CO2) emissions. The southern extent of the current distribution would become unsuitable for L. chinense, pointing to a threat of extinction and highlighting the urgent need for conservation within the next half century. The potentially suitable climatic habitat of L. chinense was predicted to move further north, but those habitat gains may be inaccessible because of dispersal limitations. Our unique findings offer a climatic suitability map for L. chinense in China, which can help to identify locations where L. chinense may already exist, but has not yet been detected; to recognize locations where L. chinense is likely to spread in the future given forecasted climate change; and to select priority areas for its introduction, cultivation, and conservation.

Highlights

Biodiversity is generally accepted to be decreasing at an unprecedented rate [1,2]
The Intergovernmental Panel on Climate Change estimated that the average global temperature, which has increased by 0.85 ◦ C during the 20th century, will continue to increase by at least 0.3–1.7 ◦ C and at most by 2.6–4.8 ◦ C by 2100 [6]
We found that the four topographical variables were not highly correlated with each other, and were all included in the maximum entropy (MaxEnt) modeling

Summary

Introduction

Biodiversity is generally accepted to be decreasing at an unprecedented rate [1,2]. Among the many reasons for this, climate change is often regarded as one of the most significant drivers of the loss in biodiversity as it influences the growth and reproduction of species, thereby determining the natural distribution of species [3,4,5]. The Intergovernmental Panel on Climate Change estimated that the average global temperature, which has increased by 0.85 ◦ C during the 20th century, will continue to increase by at least 0.3–1.7 ◦ C and at most by 2.6–4.8 ◦ C by 2100 [6] This increase in temperature is often considered to negatively affect ecosystems, through habitat fragmentation, increases in disease outbreak frequencies, and increases in the extinction rate of endangered species [7,8,9], some studies have found positive impacts on some species [10]. The inputting of parameters into the mechanistic model requires scientific expertise and essential resources, which are unavailable for many species [19]. Correlative models use readily available presence/absence or presence-only species occurrence data as well as spatial environmental data

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