Abstract
Effective conservation and utilization strategies for natural biological resources require a clear understanding of the geographic distribution of the target species. Tricholoma matsutake is an ectomycorrhizal (ECM) mushroom with high ecological and economic value. In this study, the potential geographic distribution of T. matsutake under current conditions in China was simulated using MaxEnt software based on species presence data and 24 environmental variables. The future distributions of T. matsutake in the 2050s and 2070s were also projected under the RCP 8.5, RCP 6, RCP 4.5 and RCP 2.6 climate change emission scenarios described in the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Climate Change (IPCC). The areas of marginally suitable, suitable and highly suitable habitats for T. matsutake in China were approximately 0.22 × 106 km2, 0.14 × 106 km2, and 0.11 × 106 km2, respectively. The model simulations indicated that the area of marginally suitable habitats would undergo a relatively small change under all four climate change scenarios; however, suitable habitats would significantly decrease, and highly suitable habitat would nearly disappear. Our results will be influential in the future ecological conservation and management of T. matsutake and can be used as a reference for studies on other ectomycorrhizal mushroom species.
Highlights
In Asia, in China[17,19]
maximum entropy (MaxEnt) was used to simulate the potential habitat of T. matsutake under four climate warming scenarios (RCP 8.5, representative concentration pathways (RCP) 6, RCP 4.5 and RCP 2.6, given by the Intergovernmental Panel on Climate Change (IPCC))[34]
species distribution models (SDMs) provide a possible solution to this problem
Summary
In Asia, in China[17,19]. Modern pharmacology has confirmed that the polysaccharides and terpenoids extracted from the fruiting body of T. matsutake have antitumor and antioxidant properties[20,21]. Determining the potential geographic distribution of this species and predicting how climate change would affect its geographic range are necessary and meaningful. Species presence data at 91 locations and 24 climatic and environmental variables were analyzed using MaxEnt to predict the distribution of T. matsutake in China. The objective was to select key environmental variables that are highly correlated with T. matsutake distribution and to predict the impact of climate change on the potential habitat of T. matsutake. Our results will supply advice for the protection and sustainable utilization of T. matsutake resources and establishing measures and proposals for the prediction of the distribution of ectomycorrhizal mushrooms under different climate change conditions
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