Hydrological Networks and Associated Topographic Variation as Templates for the Spatial Organization of Tropical Forest Vegetation

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10–1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30–600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20–300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.

深入理解热带森林结构与生物量的空间变异特征及其背后的驱动机制，对于区域碳清查相关野外研究的设计、解读与尺度上推至关重要。本研究以巴拿马中部4930公顷热带林区的高分辨率激光雷达（LiDAR）反演平均冠层剖面高度（mean canopy profile height, MCH）与海拔地图为数据基础，探究了10~1000米空间尺度下热带森林植被的空间结构，及其与水文网络及相关地形结构的关联。MCH与水文网络存在显著关联：在临近汇水面积≥1公顷河道的正凸区域（即山谷、洼地）中，冠层高度最高；平均MCH则随凸度降低（即向山脊、山顶过渡）以及距最近河道距离增加而显著下降。通过小波分解开展的频谱分析显示，MCH的方差在约30~600米尺度上呈现分形相似性，且与海拔变化显著相关，在约250米尺度处达到相关峰值。此前针对热带森林结构的地形关联研究多仅在单一或少数空间粒度下开展分析，而本研究发现此类关联具有显著的尺度依赖性。对MCH与坡度、坡向、曲率及拉普拉斯凸度（Laplacian convexity）的关联开展多尺度分析后发现，MCH与20~300米尺度下测得的凸度关联最为紧密——该地形变量可较好地指示区域相对于水文网络的空间位置。总体而言，本研究结果支持如下观点：即便在这类中生森林中，水文网络与相关地形变异依然构成了植被在特定尺度范围内有序分布的基础模板。本研究结果为从机制层面理解此类格局迈出了重要一步，同时可为尺度上推与尺度下推工作提供指导。