Zellweger Florian, Baltensweiler Andri, Schleppi Patrick, Huber Markus, Küchler Meinrad, Ginzler Christian, Jonas Tobias
Swiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf Switzerland.
Forest Ecology and Conservation Group, Department of Plant Sciences University of Cambridge Cambridge UK.
Ecol Evol. 2019 Jul 26;9(16):9149-9159. doi: 10.1002/ece3.5462. eCollection 2019 Aug.
Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three-dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especially across large areas. Remotely sensed canopy structure data from airborne laser scanning (ALS) provide outstanding opportunities for advancement in this respect. We used ALS point clouds and a digital terrain model to produce hemispherical photographs from which we derived indices of nondirectional diffuse skylight and direct sunlight reaching the understory. We validated our approach by comparing the performance of these indices, as well as canopy closure (CCl) and canopy cover (CCo), for explaining the light conditions experienced by forest plant communities, as indicated by the Landolt indicator values for light ( ) from 43 vegetation surveys along an elevational gradient. We applied variation partitioning to analyze how the independent and joint statistical effects of light, macroclimate, and soil on the spatial variation in plant species composition (i.e., turnover, Simpson dissimilarity, ) depend on light approximation methodology. Diffuse light explained best, followed by direct light, CCl and CCo ( = .31, .23, .22, and .22, respectively). The combination of diffuse and direct light improved the model performance for compared with CCl and CCo ( = .30, .27 and .24, respectively). The independent effect of macroclimate on dropped from an of .15 to .10 when diffuse light and direct light were included. The ALS methods presented here outperform conventional approximations of below-canopy light conditions, which can now efficiently be quantified along entire horizontal and vertical forest gradients, even in topographically complex environments such as mountains. The effect of macroclimate on forest plant communities is prone to be overestimated if local light regimes and associated microclimates are not accurately accounted for.
光照是森林生物多样性和功能的关键驱动因素。树冠层下方的光照状况主要受太阳角度、地形和植被结构的驱动，其三维复杂性创造了异质的光照条件，难以进行量化，尤其是在大面积区域。来自机载激光扫描（ALS）的遥感树冠结构数据为这方面的进展提供了绝佳机会。我们使用ALS点云和数字地形模型生成半球形照片，从中得出到达林下的无方向性漫射天光和直射阳光的指数。我们通过比较这些指数以及树冠郁闭度（CCl）和树冠覆盖率（CCo）的表现来验证我们的方法，以解释森林植物群落所经历的光照条件，这由沿海拔梯度的43次植被调查中的光照兰多尔特指标值表示。我们应用变异分解来分析光照、大气候和土壤对植物物种组成空间变异（即周转率、辛普森差异度）的独立和联合统计效应如何取决于光照近似方法。漫射光解释效果最佳，其次是直射光、CCl和CCo（分别为0.31、0.23、0.22和0.22）。与CCl和CCo相比，漫射光和直射光的组合提高了模型对的表现（分别为0.30、0.27和0.24）。当纳入漫射光和直射光时，大气候对的独立效应从0.15降至0.10。这里介绍的ALS方法优于树冠层以下光照条件的传统近似方法，现在即使在诸如山区等地形复杂的环境中，也能沿着整个水平和垂直森林梯度有效地进行量化。如果没有准确考虑当地光照状况和相关微气候，大气候对森林植物群落的影响可能会被高估。
