Conservation Research Institute and Department of Plant Sciences, University of Cambridge, Cambridge, UK.
School of Biological Sciences, University of Bristol, Bristol, UK.
Glob Chang Biol. 2024 Sep;30(9):e17493. doi: 10.1111/gcb.17493.
The future of tropical forests hinges on the balance between disturbance rates, which are expected to increase with climate change, and tree growth. Whereas tree growth is a slow process, disturbance events occur sporadically and tend to be short-lived. This difference challenges forest monitoring to achieve sufficient resolution to capture tree growth, while covering the necessary scale to characterize disturbance rates. Airborne LiDAR time series can address this challenge by measuring landscape scale changes in canopy height at 1 m resolution. In this study, we present a robust framework for analysing disturbance and recovery processes in LiDAR time series data. We apply this framework to 8000 ha of old-growth tropical forests over a 4-5-year time frame, comparing growth and disturbance rates between Borneo, the eastern Amazon and the Guiana shield. Our findings reveal that disturbance was balanced by growth in eastern Amazonia and the Guiana shield, resulting in a relatively stable mean canopy height. In contrast, tall Bornean forests experienced a decrease in canopy height due to numerous small-scale (<0.1 ha) disturbance events outweighing the gains due to growth. Within sites, we found that disturbance rates were weakly related to topography, but significantly increased with maximum canopy height. This could be because taller trees were particularly vulnerable to disturbance agents such as drought, wind and lightning. Consequently, we anticipate that tall forests, which contain substantial carbon stocks, will be disproportionately affected by the increasing severity of extreme weather events driven by climate change.
热带森林的未来取决于干扰速率和树木生长之间的平衡,而干扰速率预计会随着气候变化而增加。虽然树木生长是一个缓慢的过程,但干扰事件是零星发生的,而且往往是短暂的。这种差异给森林监测带来了挑战,因为它需要足够的分辨率来捕捉树木生长,同时又需要足够的规模来描述干扰速率。机载激光雷达时间序列可以通过以 1 米的分辨率测量冠层高度的景观尺度变化来应对这一挑战。在本研究中,我们提出了一个稳健的框架,用于分析激光雷达时间序列数据中的干扰和恢复过程。我们将该框架应用于 4-5 年时间内的 8000 公顷的原始热带森林,比较了婆罗洲、东亚马孙和圭亚那地盾的生长和干扰速率。我们的研究结果表明,在东亚马孙和圭亚那地盾,干扰被生长所平衡,导致平均冠层高度相对稳定。相比之下,高大的婆罗洲森林由于大量小规模(<0.1 公顷)的干扰事件超过了生长带来的增益,导致冠层高度下降。在各个地点,我们发现干扰速率与地形的关系较弱,但与最大冠层高度呈显著正相关。这可能是因为高大的树木特别容易受到干旱、风和闪电等干扰因素的影响。因此,我们预计,含有大量碳储量的高大森林将受到气候变化驱动的极端天气事件日益严重的不成比例的影响。