Modeling the Effect of Climate Change on the Potential Distribution of Qinghai Spruce (Picea crassifolia Kom.) in Qilian Mountains

Zhanlei Rong,Junjie Liu,Chuanyan Zhao,Zhaoxia Guo,Fei Zang,Ling Wang,Yunfei Gao,Yahua Mao

doi:10.3390/f10010062

Zhanlei Rong, Junjie Liu + Show 6 more

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https://doi.org/10.3390/f10010062

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Abstract

Qinghai spruce forests play a key role in water conservation in the dry region of northwest China. So, it is necessary to understand the impacts of climate change on the species to implement adaptation strategies. Based on the four-emission scenario (i.e., RCP2.6 (Representative Concentration Pathway), RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report, in the study, we predicted the potential distribution of Qinghai spruce (Picea crassifolia Kom.) under current and future scenarios using a maximum entropy (Maxent) model. Seven variables, selected from 22 variables according to correlation analysis combining with their contribution rates to the distribution, are used to simulate the potential distribution of the species under current and future scenarios. Simulated results are validated by area under the operating characteristic curve (AUC). Results demonstrate that elevation, mean temperature of wettest quarter, annual mean temperature, and mean diurnal range are more important in dominating the potential distribution of Qinghai spruce. Ratios of the suitable area to the total study area are 34.3% in current climate condition, 34% in RCP2.6, 33.9% in RCP4.5, 33.8% in RCP6.0, and 30.5% in RCP8.5, respectively. The warmer the climate condition is, the more area of higher suitable classification is changed to that of lower suitable classification. The ratios of real distribution area in simulated unsuitable class to the real distribution area change from 4.3% (60.7 km2) in the current climate to 13% (185 km2) in RCP8.5, suggesting that the real distribution area may decrease in the future. We conclude that there is a negative effect of climate change on the distribution of Qinghai spruce forest. The result can help decision-makers to draft adaptation countermeasures based on climate change.

Highlights

Global warming is an indisputable fact, and the global annual temperature has increased 0.85 ◦ C between 1880 and 2012 and will continuously rise in the future [1]
Many Species distribution model (SDM) have been developed for predicting the potential distribution of species under climate change, such as the Genetic Algorithm for Rule-set Prediction (GARP) [20,21], Surface Range Envelope (SRE; usually called BIOCLIM) [22], Random Forests (RFs) [23], Ecological Niche Factor Analysis (ENFA) [24], and Maximum Entropy (Maxent) [25]
Overlapping the real distribution with potential distributions of current and future scenarios, we found that the area of real distribution in unsuitable class increased from 60.7 km2 (4.3%) in the current climate to

Summary

Introduction

Global warming is an indisputable fact, and the global annual temperature has increased 0.85 ◦ C between 1880 and 2012 and will continuously rise in the future [1]. Many SDMs have been developed for predicting the potential distribution of species under climate change, such as the Genetic Algorithm for Rule-set Prediction (GARP) [20,21], Surface Range Envelope (SRE; usually called BIOCLIM) [22], Random Forests (RFs) [23], Ecological Niche Factor Analysis (ENFA) [24], and Maximum Entropy (Maxent) [25]. They have been applied to predict the potential distribution of the selected species under current as well as the future scenarios in many places [18,26,27]

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