Wagner Fabien, Rossi Vivien, Aubry-Kientz Mélaine, Bonal Damien, Dalitz Helmut, Gliniars Robert, Stahl Clément, Trabucco Antonio, Hérault Bruno
Remote Sensing Division, National Institute for Space Research - INPE, São José dos Campos, SP, Brazil; Cirad, UMR 93 "Ecologie des Forêts de Guyane," Kourou, France.
Cirad, UR 105 "Biens et services des écosystèmes forestiers tropicaux," Montpellier, France; Université de Yaoundé 1, UMI 209 "Modélisation Mathématique et Informatique de Systèmes Complexes," Yaoundé, Cameroun.
PLoS One. 2014 Mar 26;9(3):e92337. doi: 10.1371/journal.pone.0092337. eCollection 2014.
Climate models predict a range of changes in tropical forest regions, including increased average temperatures, decreased total precipitation, reduced soil moisture and alterations in seasonal climate variations. These changes are directly related to the increase in anthropogenic greenhouse gas concentrations, primarily CO2. Assessing seasonal forest growth responses to climate is of utmost importance because woody tissues, produced by photosynthesis from atmospheric CO2, water and light, constitute the main component of carbon sequestration in the forest ecosystem. In this paper, we combine intra-annual tree growth measurements from published tree growth data and the corresponding monthly climate data for 25 pan-tropical forest sites. This meta-analysis is designed to find the shared climate drivers of tree growth and their relative importance across pan-tropical forests in order to improve carbon uptake models in a global change context. Tree growth reveals significant intra-annual seasonality at seasonally dry sites or in wet tropical forests. Of the overall variation in tree growth, 28.7% was explained by the site effect, i.e. the tree growth average per site. The best predictive model included four climate variables: precipitation, solar radiation (estimated with extrasolar radiation reaching the atmosphere), temperature amplitude and relative soil water content. This model explained more than 50% of the tree growth variations across tropical forests. Precipitation and solar radiation are the main seasonal drivers of tree growth, causing 19.8% and 16.3% of the tree growth variations. Both have a significant positive association with tree growth. These findings suggest that forest productivity due to tropical tree growth will be reduced in the future if climate extremes, such as droughts, become more frequent.
气候模型预测热带森林地区会出现一系列变化,包括平均气温升高、总降水量减少、土壤湿度降低以及季节性气候变化的改变。这些变化与人为温室气体浓度的增加直接相关,主要是二氧化碳。评估森林季节性生长对气候的响应至关重要,因为由大气中的二氧化碳、水和光通过光合作用产生的木质组织构成了森林生态系统中碳固存的主要成分。在本文中,我们将已发表的树木生长数据中的年内树木生长测量值与25个泛热带森林站点相应的月度气候数据相结合。这项荟萃分析旨在找出树木生长的共同气候驱动因素及其在泛热带森林中的相对重要性,以便在全球变化背景下改进碳吸收模型。树木生长在季节性干燥的站点或湿润的热带森林中呈现出显著的年内季节性。在树木生长的总体变化中,28.7%可由站点效应解释,即每个站点的树木生长平均值。最佳预测模型包括四个气候变量:降水量、太阳辐射(用到达大气的日地外辐射估算)、温度振幅和相对土壤含水量。该模型解释了热带森林中超过50%的树木生长变化。降水量和太阳辐射是树木生长的主要季节性驱动因素,分别导致19.8%和16.3%的树木生长变化。两者均与树木生长呈显著正相关。这些发现表明,如果干旱等极端气候变得更加频繁,未来热带树木生长导致的森林生产力将会降低。