Habitat structural complexity is an emergent property of ecosystems that directly shapes their biodiversity, functioning and resilience to disturbance. Yet despite its importance, we continue to lack consensus on how best to define structural complexity, nor do we have a generalised approach to measure habitat complexity across ecosystems. To bridge this gap, here we adapt a geometric framework developed to quantify the surface complexity of coral reefs and apply it to the canopies of tropical rainforests. Using high-resolution, repeat-acquisition airborne laser scanning data collected over 450 km² of human-modified tropical landscapes in Borneo, we generated 3D canopy height models of forests at varying stages of recovery from logging. We then tested whether the geometric framework of habitat complexity – which characterises 3D surfaces according to their height range, rugosity and fractal dimension – was able to detect how both human and natural disturbances drive variation in canopy structure through space and time across these landscapes. We found that together, these three metrics of surface complexity captured major differences in canopy 3D structure between highly degraded, selectively logged and old-growth forests. Moreover, the three metrics were able to track distinct temporal patterns of structural recovery following logging and wind disturbance. However, in the process we also uncovered several important conceptual and methodological limitations with the geometric framework of habitat complexity. We found that fractal dimension was highly sensitive to small variations in data inputs and was ecologically counteractive (e.g. higher fractal dimension in oil palm plantations than old-growth forests), while rugosity and height range were tightly correlated (r = 0.75) due to their strong dependency on maximum tree height. Our results suggest that forest structural complexity cannot be summarised using these three descriptors alone, as they overlook key features of canopy vertical and horizontal structure that arise from the way trees fill 3D space.

中文翻译：

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跟踪人类改造的热带景观中森林结构复杂性随空间和时间的变化


栖息地结构的复杂性是生态系统的一个新兴属性，直接影响其生物多样性、功能和抗干扰能力。然而，尽管它很重要，但我们在如何最好地定义结构复杂性方面仍然缺乏共识，也没有通用的方法来衡量整个生态系统的栖息地复杂性。为了弥补这一差距，我们采用了一个几何框架来量化珊瑚礁的表面复杂性，并将其应用于热带雨林的树冠。利用在婆罗洲超过 450 公里 ² 人类改造的热带景观中收集的高分辨率、重复采集机载激光扫描数据，我们生成了处于不同采伐恢复阶段的森林的 3D 树冠高度模型。然后，我们测试了栖息地复杂性的几何框架（根据高度范围、粗糙度和分形维数来表征 3D 表面）是否能够检测人类和自然干扰如何通过这些景观的空间和时间驱动冠层结构的变化。我们发现，这三个表面复杂性指标共同捕捉了高度退化、选择性砍伐和古老森林之间冠层 3D 结构的主要差异。此外，这三个指标能够跟踪伐木和风扰动后结构恢复的不同时间模式。然而，在此过程中，我们还发现了栖息地复杂性几何框架的几个重要的概念和方法学局限性。我们发现分形维数对数据输入的微小变化高度敏感，并且在生态上具有反作用（例如， 油棕种植园的分形维数高于原始森林），而粗糙度和高度范围紧密相关（r = 0.75），因为它们对最大树高的强烈依赖性。我们的结果表明，森林结构的复杂性不能单独使用这三个描述符来概括，因为它们忽略了树冠垂直和水平结构的关键特征，而这些特征是由树木填充 3D 空间的方式产生的。