Spatial patterns of tree and shrub biomass in a deciduous forest using leaf-off and leaf-on lidar

Spatial patterns of tree and shrub biomass in a deciduous forest using leaf-off and leaf-on lidar
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DOI:
10.1139/cjfr-2018-0033
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发表时间:
2018-06
影响因子:
2.2
通讯作者:
K. Brubaker;Quincey K. Johnson;Margot W. Kaye
K. Brubaker;Quincey K. Johnson;Margot W. Kaye
中科院分区:
农林科学3区
文献类型:
--
作者:
K. Brubaker;Quincey K. Johnson;Margot W. Kaye

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随着管理人员适应全球变化的威胁,了解各类森林地上碳储存的模式越来越重要。我们结合实地测量的地上生物量与激光雷达模型的细尺度生物量位于两个流域的落叶林,一个流域是由砂岩和页岩。我们测量了树木和灌木生物量在三个地形位置的流域和生物量分析使用混合模型。页岩下的流域有60%以上的地上生物量比砂岩流域。虽然生物量的空间格局是不同的流域,都有较高的(约40%和55%之间)的生物量值在趾坡的位置比在脊顶的位置。为了模拟生物量的精细尺度空间格局,我们测试了叶上和叶关闭激光雷达与地形指标相结合的有效性,以开发一个空间上明确的随机森林模型的树木和灌木生物量在两个流域。叶上变量更重要的建模灌木生物量,而叶关闭变量更有效地建模树木生物量。我们的树木和灌木生物量模型反映了两个流域的生物量分布在一个很好的尺度,并突出了非生物因素,如地形和基岩影响碳储量的潜力。
Understanding patterns of aboveground carbon storage across forest types is increasingly important as managers adapt to threats of global change. We combined field measures of aboveground biomass with lidar to model fine-scale biomass in deciduous forests located in two watersheds; one watershed was underlain by sandstone and the other by shale. We measured tree and shrub biomass across three topographic positions for both watersheds and analyzed biomass using mixed models. The watershed underlain by shale had 60% more aboveground biomass than the sandstone watershed. Although spatial patterns of biomass were different across watersheds, both had higher (between about 40% and 55%) biomass values at the toe-slope position than at the ridge-top position. To model fine-scale spatial patterns of biomass, we tested the effectiveness of leaf-on and leaf-off lidar combined with topographic metrics to develop a spatially explicit random forest model of tree and shrub biomass across both watersheds. Leaf-on variables were more important for modeling shrub biomass, while leaf-off variables were more effective at modeling tree biomass. Our model of tree and shrub biomass reflects the distribution of biomass across both watersheds at a fine scale and highlights the potential of abiotic factors such as topography and bedrock to affect carbon storage.