Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models

被引:85
作者
Baudena, M. [1 ]
Dekker, S. C. [1 ]
van Bodegom, P. M. [2 ,3 ]
Cuesta, B. [4 ]
Higgins, S. I. [5 ]
Lehsten, V. [6 ]
Reick, C. H. [7 ]
Rietkerk, M. [1 ]
Scheiter, S. [8 ]
Yin, Z. [9 ]
Zavala, M. A. [4 ]
Brovkin, V. [7 ]
机构
[1] Univ Utrecht, Environm Sci Grp, Copernicus Inst Sustainable Dev, NL-3508 TC Utrecht, Netherlands
[2] Vrije Univ Amsterdam, Dept Ecol Sci, NL-1081 HV Amsterdam, Netherlands
[3] Leiden Univ, Inst Environm Sci, NL-2333 CC Leiden, Netherlands
[4] Univ Alcala, Dept Life Sci, Forest Ecol & Restorat Grp, Madrid 28805, Spain
[5] Univ Otago, Dept Bot, Dunedin 9054, New Zealand
[6] Lund Univ, Dept Phys Geog & Ecosyst Sci, S-22362 Lund, Sweden
[7] Max Planck Inst Meteorol, D-20146 Hamburg, Germany
[8] Senckenberg Gesell Naturforsch, Biodivers & Climate Res Ctr LOEWE BiK F, D-60325 Frankfurt, Germany
[9] Univ Utrecht, Inst Marine & Atmospher Res Utrecht, NL-3508 TC Utrecht, Netherlands
关键词
ATMOSPHERIC CO2; AFRICAN SAVANNA; WOODY COVER; TREE COVER; ECOSYSTEM PRODUCTIVITY; GROWTH-RESPONSES; PLANT GEOGRAPHY; TROPICAL FOREST; CARBON-CYCLE; FIRE;
D O I
10.5194/bg-12-1833-2015
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
引用
收藏
页码:1833 / 1848
页数:16
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