Disturbance of a Certain Intensity can Accelerate Spatial Shifts in Tree Species Composition and Biomass

Release Time:2023-01-12 Big Small

The migration of tree species in response to climate change can be reflected in spatial changes of tree species distribution, biomass and species composition. Disturbances such as logging, forest fires, pests and diseases can affect forest dynamics by affecting tree species growth, mortality and interspecies interactions. However, it is still unclear whether the increases in the frequency and intensity of these disturbances will further accelerate the spatio-temporal shifts in tree species composition and biomass under climate change .

In a recently published study led by Dr. LIANG Yu, a researcher of the Landscape Process Group of the Institute of Applied Ecology (IAE) of the Chinese Academy of Sciences (CAS), the researchers used LANDIS model (a forest landscape model) to simulate the migration dynamics of tree species under different disturbance scenarios, and quantify the changes in the velocity and direction of tree species abundance in response to these disturbance scenarios.

The researchers found that disturbance can accelerate the change in tree species biomass and composition, but only when the disturbance reaches a certain intensity. This study result challenged the traditional cognition that "disturbance will continue to accelerate changes in tree species distribution and migration". In addition, the researchers highlight the value of spatially explicit models for extrapolating forest dynamics in changing climate and disturbance scenarios.

This study, funded by the National Natural Science Foundation of China and the Major Program of IAE, CAS, has been published in Global Change Biology entitled "What is the role of disturbance in catalyzing spatial shifts in forest composition and tree species biomass under climate change."


YUE Qian

Institute of Applied Ecology, Chinese Academy of Sciences 

Tel: 86-24-83970317

E-mail: yueqian@iae.ac.cn  


Web: http://english.iae.cas.cn