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From the Cover: The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape

机译:从封面开始:在古老的亚马逊中部森林景观上扰动和演替的稳态镶嵌

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摘要

Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomass⋅ha−1⋅y−1 were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1–16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.
机译:老龄森林生态系统由不同演替阶段的斑块马赛克组成,在任何特定状态下,大片景观在较大的时空范围内都相对恒定。扰动事件的大小分布和返回频率,以及随后的恢复过程,在很大程度上决定了这种旧增长稳态发展的空间尺度。在这里,我们通过整合现场图数据,遥感干扰概率分布函数和基于个体的仿真模型来描述亚马逊中部森林的马赛克。结果表明,不同年龄的斑块处于稳定状态,发生在相对较大的空间范围内,这对于检测对一小部分景观采样的地块上的时间趋势具有重要意义。长期突发的平均随机活动平均生物量为1.0 Mg·ha −1 ⋅y −1 ,通常会受到突发干扰事件的干扰,从而形成公顷规模树的锯齿时间序列生物质。为了最大程度地检测该中央亚马逊站点的时间趋势(例如,受CO2施肥驱动),大于10公顷的地块将提供最大的灵敏度。基于模型的跨所有间隙大小的死亡率的分析表明,基于地块的方法缺少树木死亡率的9.1–16.9%,强调了需要结合地块和遥感方法来估算净景观碳平衡。古老的热带森林可以表现出受干扰和恢复周期驱动的复杂的大规模结构,公顷规模样地的生态系统和社区属性呈现出与稳态状态连续不断的动态偏离。

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