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Landslide age, elevation and residual vegetation determine tropical montane forest canopy recovery and biomass accumulation after landslide disturbances in the Peruvian Andes
Journal of Ecology ( IF 5.5 ) Pub Date : 2021-06-25 , DOI: 10.1111/1365-2745.13737
Cathryn A. Freund 1, 2 , Kasey E. Clark 3 , James F. Curran 1 , Gregory P. Asner 2 , Miles R. Silman 1
Affiliation  

  1. Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post-landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood.
  2. Here we use a LiDAR-derived canopy height map coupled with a 25-year landslide time-series map to examine how landslide, topographic and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate above-ground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels.
  3. We find that age and elevation are the biggest determinants of forest recovery, and that the jump-start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6–37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest above-ground biomass in frequently disturbed landscapes.
  4. Synthesis. Using a high-resolution LiDAR dataset and a time-series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post-landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on above-ground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on above-ground biomass, wherein high-wood density species gradually replace light-wooded pioneer species, it overestimates above-ground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that above-ground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR-derived structure alone.


中文翻译:

滑坡年龄、海拔和残留植被决定了秘鲁安第斯山脉滑坡扰动后热带山地森林冠层恢复和生物量积累

  1. 山体滑坡是热带山地森林中常见的自然干扰。虽然已经研究了安第斯山脉滑坡的地貌驱动因素,但对控制热带山脉特征的陡峭气候和地形梯度滑坡后森林恢复的因素知之甚少。
  2. 在这里,我们使用 LiDAR 衍生的冠层高度图和 25 年滑坡时间序列图来检查滑坡、地形和生物物理因素以及残余植被如何影响再生滑坡中的冠层高度和异质性。我们还计算地上生物量积累率并估计滑坡恢复到成熟森林生物量水平的时间。
  3. 我们发现年龄和海拔是森林恢复的最大决定因素,残余植被提供的再生启动至少持续 18 年。我们对生物量恢复时间(31.6-37.1 年)的估计出奇地快,因此我们建议未来的研究将 LiDAR 与高光谱图像配对,以估计经常受到干扰的景观中的森林地上生物量。
  4. 合成. 使用高分辨率 LiDAR 数据集和分布在安第斯山地森林中广泛海拔梯度的 608 个滑坡的时间序列清单,我们表明年龄和海拔是森林冠层高度和冠层变化的最有影响力的预测因子。滑坡的其他特征,特别是残留植被的存在,塑造了滑坡后的再生轨迹。LiDAR 允许对大型景观和干扰数量的森林结构恢复进行详细分析,并提供地上生物量积累率的合理上限。然而,由于该方法没有通过演替来捕捉组成变化对地上生物量的影响,其中高木材密度物种逐渐取代轻木先锋物种,它高估了地上生物量。
更新日期:2021-06-25
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