Naumburg Elke, Ellsworth David S
Nicholas School of the Environment, Duke University, Durham, NC 27708-0328, USA.
Tree Physiol. 2002 Apr;22(6):393-401. doi: 10.1093/treephys/22.6.393.
Instantaneous measurements of photosynthesis are often implicitly or explicitly scaled to longer time frames to provide an understanding of plant performance in a given environment. For plants growing in a forest understory, results from photosynthetic light response curves in conjunction with diurnal light data are frequently extrapolated to daily photosynthesis (A(day)), ignoring dynamic photosynthetic responses to light. In this study, we evaluated the importance of two factors on A(day) estimates: dynamic physiological responses to photosynthetic photon flux density (PPFD); and time-resolution of the PPFD data used for modeling. We used a dynamic photosynthesis model to investigate how these factors interact with species-specific photosynthetic traits, forest type, and sky conditions to affect the accuracy of A(day) predictions. Increasing time-averaging of PPFD significantly increased the relative overestimation of A(day) similarly for all study species because of the nonlinear response of photosynthesis to PPFD (15% with 5-min PPFD means). Depending on the light environment characteristics and species-specific dynamic responses to PPFD, understory tree A(day) can be overestimated by 6-42% for the study species by ignoring these dynamics. Although these overestimates decrease under cloudy conditions where direct sunlight and consequently understory sunfleck radiation is reduced, they are still significant. Within a species, overestimation of A(day) as a result of ignoring dynamic responses was highly dependent on daily sunfleck PPFD and the frequency and irradiance of sunflecks. Overall, large overestimates of A(day) in understory trees may cause misleading inferences concerning species growth and competition in forest understories with < 2% full sunlight. We conclude that comparisons of A(day) among co-occurring understory species in deep shade will be enhanced by consideration of sunflecks by using high-resolution PPFD data and understanding the physiological responses to sunfleck variation.
光合作用的瞬时测量结果通常会被隐式或显式地扩展到更长的时间尺度，以了解植物在特定环境中的表现。对于生长在森林下层的植物，结合昼夜光照数据的光合光响应曲线结果常常被外推到每日光合作用（A(day)），而忽略了光合作用对光照的动态响应。在本研究中，我们评估了两个因素对A(day)估计值的重要性：对光合光子通量密度（PPFD）的动态生理响应；以及用于建模的PPFD数据的时间分辨率。我们使用一个动态光合作用模型来研究这些因素如何与物种特异性光合特性、森林类型和天空条件相互作用，从而影响A(day)预测的准确性。由于光合作用对PPFD的非线性响应，PPFD时间平均的增加显著增加了所有研究物种对A(day)的相对高估（5分钟PPFD平均值时高估15%）。根据光照环境特征和物种对PPFD的特定动态响应，对于研究物种，忽略这些动态会使下层树木的A(day)高估6 - 42%。尽管在多云条件下，直接阳光以及因此下层光斑辐射减少时，这些高估会降低，但仍然很显著。在一个物种内，由于忽略动态响应导致的A(day)高估高度依赖于每日光斑PPFD以及光斑的频率和辐照度。总体而言，下层树木中A(day)的大量高估可能会导致关于阳光不足2%的森林下层物种生长和竞争的误导性推断。我们得出结论，通过使用高分辨率PPFD数据并了解对光斑变化的生理响应来考虑光斑，将增强对深荫下共存下层物种之间A(day)的比较。
