Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient
Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient
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DOI：
10.1111/ele.12771
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发表时间：
2017-06-01
期刊：
影响因子：
8.8
通讯作者：
Malhi, Yadvinder
中科院分区：
文献类型：
--
作者：
Fyllas, Nikolaos M.;Bentley, Lisa Patrick;Malhi, Yadvinder
生态学的主要挑战之一是了解生态系统如何对环境条件的变化做出反应，以及分类和功能多样性如何介导这些变化。在这项研究中，我们使用一个性状谱和个人为基础的模型，分析森林初级生产力的变化沿着3.3公里的海拔梯度在亚马逊-安第斯山脉。该模型准确地预测了森林生产力与海拔的幅度和趋势，太阳辐射和植物功能性状（单位面积叶干质量，叶氮和磷浓度，木材密度）共同占生产力的变化。值得注意的是，明确表示温度随海拔的变化是不需要实现准确的预测森林生产力，作为性状变化驱动的物种周转似乎捕捉温度的影响。我们的半机械模型表明，性状的空间变异可能被用来估计在景观尺度上的生产力的空间变异。
One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale.