Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA.
Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA.
Glob Chang Biol. 2017 Mar;23(3):1240-1257. doi: 10.1111/gcb.13509. Epub 2016 Oct 11.
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R = 0.77) to interannual (R = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.
热带森林的总生态系统生产力 (GEP) 既随环境变化而变化，也随光合作用基础设施的生物变化而变化，但我们对这些因素在不同时间尺度上的相对影响的理解是有限的。在这里，我们使用统计模型将亚马逊中部常绿森林七年的涡度相关衍生 GEP 变化分为两个主要原因：环境驱动因素（太阳辐射、漫射光分数和蒸气压亏缺）的变化与控制光合作用的模型参数相互作用，以及与参数本身变化相关的冠层光合光利用效率的生物变化。我们拟合的模型能够解释 GEP 在小时（R = 0.77）到年际（R = 0.80）时间尺度上的大部分变化。在小时时间尺度上，我们发现 75%的观测到的 GEP 变化可以归因于环境变化。然而，当将 GEP 聚合到更长的时间尺度（每日、每月和每年）时，环境变化解释的 GEP 变化越来越少：在每月的时间尺度上，它仅解释了 3%，远低于冠层光合光利用效率的生物变化，后者占 63%。这些结果挑战了在短时间和长时间内都假设 GEP 主要受环境控制的建模方法。我们区分生物和环境变化的方法可以帮助解决关于热带森林光合作用的环境限制的争论。例如，我们发现，与叶片物候相关的生物调节的冠层光合光利用效率在旱季随着阳光的增加而增加（与冠层发育的光限制而不是水限制一致），但与旱季相比，实际 GEP 仍然相对较低湿季（与特定叶片组合中光合作用的水分限制一致）。这项工作强调了在不同时间尺度上考虑 GEP 差异化调节以及确定潜在反馈和适应机制的重要性。
