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Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield
Global Change Biology ( IF 10.8 ) Pub Date : 2024-09-06 , DOI: 10.1111/gcb.17493 Toby D Jackson 1, 2 , Fabian J Fischer 2 , Grégoire Vincent 3 , Eric B Gorgens 4 , Michael Keller 5, 6 , Jérôme Chave 7 , Tommaso Jucker 2 , David A Coomes 1
Global Change Biology ( IF 10.8 ) Pub Date : 2024-09-06 , DOI: 10.1111/gcb.17493 Toby D Jackson 1, 2 , Fabian J Fischer 2 , Grégoire Vincent 3 , Eric B Gorgens 4 , Michael Keller 5, 6 , Jérôme Chave 7 , Tommaso Jucker 2 , David A Coomes 1
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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.
中文翻译：
高大的婆罗洲森林的树冠干扰率高于亚马逊东部或圭亚那地盾的树冠干扰率
热带森林的未来取决于干扰率与树木生长之间的平衡，干扰率预计会随着气候变化而增加。尽管树木生长是一个缓慢的过程，但干扰事件却是零星发生且往往是短暂的。这种差异对森林监测提出了挑战，即要实现足够的分辨率来捕获树木的生长情况，同时覆盖必要的规模来表征干扰率。机载 LiDAR 时间序列可以通过以 1 m 分辨率测量冠层高度的景观尺度变化来应对这一挑战。在这项研究中，我们提出了一个强大的框架来分析激光雷达时间序列数据中的干扰和恢复过程。我们在 4 至 5 年的时间内将该框架应用于 8000 公顷的古老热带森林，比较了婆罗洲、亚马逊东部和圭亚那地盾之间的生长和干扰率。我们的研究结果表明，亚马逊流域东部和圭亚那地盾的生长平衡了干扰，导致平均树冠高度相对稳定。相比之下，高大的婆罗洲森林由于大量小规模（<0.1 ha）干扰事件超过了生长带来的收益，导致树冠高度下降。在站点内，我们发现干扰率与地形关系较弱，但随着树冠高度的增加而显着增加。这可能是因为较高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导致的日益严重的极端天气事件的严重影响。
更新日期：2024-09-06
中文翻译：
高大的婆罗洲森林的树冠干扰率高于亚马逊东部或圭亚那地盾的树冠干扰率
热带森林的未来取决于干扰率与树木生长之间的平衡，干扰率预计会随着气候变化而增加。尽管树木生长是一个缓慢的过程，但干扰事件却是零星发生且往往是短暂的。这种差异对森林监测提出了挑战，即要实现足够的分辨率来捕获树木的生长情况，同时覆盖必要的规模来表征干扰率。机载 LiDAR 时间序列可以通过以 1 m 分辨率测量冠层高度的景观尺度变化来应对这一挑战。在这项研究中，我们提出了一个强大的框架来分析激光雷达时间序列数据中的干扰和恢复过程。我们在 4 至 5 年的时间内将该框架应用于 8000 公顷的古老热带森林，比较了婆罗洲、亚马逊东部和圭亚那地盾之间的生长和干扰率。我们的研究结果表明，亚马逊流域东部和圭亚那地盾的生长平衡了干扰，导致平均树冠高度相对稳定。相比之下，高大的婆罗洲森林由于大量小规模（<0.1 ha）干扰事件超过了生长带来的收益，导致树冠高度下降。在站点内，我们发现干扰率与地形关系较弱，但随着树冠高度的增加而显着增加。这可能是因为较高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导致的日益严重的极端天气事件的严重影响。
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