Shifts of the Mean Centers of Potential Vegetation Ecosystems under future climate change in Eurasia

Author:

Fan ,Fan

Abstract

Climate change dominantly controls the spatial distributions of potential vegetation ecosystems; the shift trends in the mean centers of potential vegetation ecosystems could be used to explain their responses to climate change. In terms of the climate observation data of Eurasia for the period from 1981 to 2010 and the climate scenario data for the period from 2011 to 2100 under the three Representative Concentration Pathways (RCPs) scenarios of RCP2.6, RCP4.5 and, RCP8.5, which were released by the Coupled Model Intercomparison Project Phase 5 (CMIP5), the Holdridge Life Zone (HLZ) ecosystem model was improved to quantitatively classify the potential vegetation types, and the shift model of mean center was adopted to compute the trends in the spatiotemporal shifts of potential vegetation types in Eurasia. The results showed that the mean centers of the major potential vegetation ecosystems would be distributed in the central and southern parts of Eurasia. Under the RCP2.6, RCP4.5, and RCP8.5 scenarios, the potential shift distances of the mean centers of the vegetation types under the RCP8.5 scenario would be the largest, and those of the polar/nival area, subpolar/alpine moist tundra, warm temperate dry forest, subtropical moist forest, cool temperate moist forest, cool temperate wet forest, subtropical wet forest, subtropical thorn woodland, warm temperate moist forest and subtropical dry forest would be larger than those in the other potential vegetation types in Eurasia. Moreover, the shift directions of the mean centers of the major potential vegetation types would generally shift northward, and subtropical dry forest, warm temperate moist forest and subpolar/alpine moist tundra would be the most sensitive to change among all vegetation types under the three scenarios for the period from 2011 to 2100.

Funder

the National Natural Science Foundation

Publisher

MDPI AG

Subject

Forestry

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