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Relation between rainfall intensity and savanna tree abundance explained by water use strategies.
Xu, Xiangtao; Medvigy, David; Rodriguez-Iturbe, Ignacio.
Afiliação
  • Xu X; Department of Geosciences, Princeton University, Princeton, NJ 08544; xiangtao@princeton.edu irodrigu@princeton.edu.
  • Medvigy D; Department of Geosciences, Princeton University, Princeton, NJ 08544;
  • Rodriguez-Iturbe I; Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 xiangtao@princeton.edu irodrigu@princeton.edu.
Proc Natl Acad Sci U S A ; 112(42): 12992-6, 2015 Oct 20.
Article em En | MEDLINE | ID: mdl-26438847
Tree abundance in tropical savannas exhibits large and unexplained spatial variability. Here, we propose that differentiated tree and grass water use strategies can explain the observed negative relation between maximum tree abundance and rainfall intensity (defined as the characteristic rainfall depth on rainy days), and we present a biophysical tree-grass competition model to test this idea. The model is founded on a premise that has been well established in empirical studies, namely, that the relative growth rate of grasses is much higher compared with trees in wet conditions but that grasses are more susceptible to water stress and lose biomass more quickly in dry conditions. The model is coupled with a stochastic rainfall generator and then calibrated and tested using field observations from several African savanna sites. We show that the observed negative relation between maximum tree abundance and rainfall intensity can be explained only when differentiated water use strategies are accounted for. Numerical experiments reveal that this effect is more significant than the effect of root niche separation. Our results emphasize the importance of vegetation physiology in determining the responses of tree abundance to climate variations in tropical savannas and suggest that projected increases in rainfall intensity may lead to an increase in grass in this biome.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Chuva / Árvores / Ecossistema Tipo de estudo: Prognostic_studies Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Chuva / Árvores / Ecossistema Tipo de estudo: Prognostic_studies Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2015 Tipo de documento: Article