SEIB-DGVM: A new dynamic global vegetation model using a spatially explicit individual-based approach

被引:280
作者
Sato, Hisashi
Itoh, Akihiko
Kohyama, Takashi
机构
[1] Japan Agcy Marine Earth Sci & Technol, FRCGC, Kanazawa Ku, Yokohama, Kanagawa 2360001, Japan
[2] Natl Inst Environm Studies, Tsukuba, Ibaraki 3058506, Japan
[3] Hokkaido Univ, Grad Sch Environm Earth Sci, Kita Ku, Sapporo, Hokkaido 0600810, Japan
关键词
Dynamic Global Vegetation Model; biogeochemical model; individual-base model; plant community-dynamics; size structure; vegetation dynamics;
D O I
10.1016/j.ecolmodel.2006.09.006
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
We report the development of a new spatially explicit individual-based Dynamic Global Vegetation Model (SEIB-DGVM), the first DGVM that can simulate the local interactions among individual trees within a spatially explicit virtual forest. In the model, a sample plot is placed at each grid box, and then the growth, competition, and decay of each individual tree within each plot is calculated by considering the environmental conditions for that tree as it relates to the trees that surround it. Based on these parameters only, the model simulated time lags between climate change and vegetation change. This time lags elongated when original biome was forest, because existing trees prevent newly establish trees from receiving enough sunlight and space to quickly replace the original vegetation. This time lags also elongated when horizontal heterogeneity of sunlight distribution was ignored, indicating the potential importance of horizontal heterogeneity for predicting transitional behavior of vegetation under changing climate. on a local scale, the model reproduced climate zone-specific patterns of succession, carbon dynamics, and water flux, although on a global scale, simulations were not always in agreement with observations. Because the SEIB-DGVM was formulated to the scale at which field biologists work, the measurements of relevant parameters and data comparisons are relatively straightforward, and the model should enable more robust modeling of terrestrial ecosystems. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:279 / 307
页数:29
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