Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future...

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Published inGlobal change biology Vol. 22; no. 11; pp. 3642 - 3661
Main Authors Dai, Erfu, Wu, Zhuo, Ge, Quansheng, Xi, Weimin, Wang, Xiaofan
Format Journal Article
LanguageEnglish
Published England Blackwell Publishing Ltd 01.11.2016
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Summary:In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS‐II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET‐II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010–2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad‐leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad‐leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types.
Bibliography:National Key Technology R&D Program - No. 2013BAC03B04
istex:A8FE5687C27656C5EE7B3850270FC10AE04330C1
National Natural Science Foundation of China - No. 41571098; No. 41371196
Figure S1. The distribution of the points for model validation. Figure S2. The variation trend of aboveground net primary production (ANPP) and species' establishment probability (SEP) simulated by PnET-II under RCP2.6, RCP4.5, RCP8.5 and control scenarios across the four active ecoregions. Figure S3. The rate of inter-annual variation of area for the five forest types under four climate scenarios. Figure S4. The spatial distribution of five forest types under four climate scenarios. Table S1. Species life-history attributes in the Taihe County, Jiangxi Province, China.
ark:/67375/WNG-FN1S608L-8
ArticleID:GCB13307
National Basic Research Program of China (973 Program) - No. 2015CB452702; No. 2012CB416906
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1354-1013
1365-2486
DOI:10.1111/gcb.13307