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Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability

机译:绘制障碍物和林下灌木,以基于LiDAR的野生动植物栖息地适宜性评估

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The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for mapping the presence/absence of understory shrub species and different snag diameter classes important for birds (i.e. >= 15 cm, >= 25 cm and >= 30 cm) in a 30.000 ha mixed-conifer forest in Northern Idaho (USA). We used forest inventory plots, LiDAR-derived metrics, and the Random Forest algorithm to achieve classification accuracies of 83% for the understory shrubs and 86% to 88% for the different snag diameter classes. Second, we evaluated the use of LiDAR data for mapping wildlife habitat suitability using four avian species (one flycatcher and three woodpeckers) as case studies. For this, we integrated LiDAR-derived products of forest structure with available models of habitat suitability to derive a variety of species-habitat associations (and therefore habitat suitability patterns) across the study area. We found that the value of LiDAR resided in the ability to quantify 1) ecological variables that are known to influence the distribution of understory vegetation and snags, such as canopy cover, topography, and forest succession, and 2) direct structural metrics that indicate or suggest the presence of shrubs and snags, such as the percent of vegetation returns in the lower strata of the canopy (for the shrubs) and the vertical heterogeneity of the forest canopy (for the snags). When applied to wildlife habitat assessment, these new LiDAR-based maps refined habitat predictions in ways not previously attainable using other remote sensing technologies. This study highlights new value of LiDAR in characterizing key forest structure components important for wildlife, and warrants further applications to other forested environments and wildlife species.
机译:缺乏描绘森林三维结构的地图,尤其是与断枝和林下灌木物种分布有关的地图,这是管理森林中野生动植物栖息地的主要限制。因此,开发新技术来远程绘制障碍物和林下灌木丛是一个重要的需求。为了解决这个问题,我们首先评估了使用LiDAR数据绘制30.000英亩以下灌木丛物种的存在/不存在以及对鸟类重要的不同粗细直径类别(即> = 15 cm,> = 25 cm和> = 30 cm)的情况。美国爱达荷州北部的混合针叶林。我们使用森林清单图,LiDAR得出的度量标准和随机森林算法来获得林下灌木的分类准确度为83%,不同断枝直径类别的分类准确度为86%至88%。其次,我们使用LiDAR数据评估了使用四种鸟类(一种捕蝇器和三种啄木鸟)绘制野生动植物栖息地适宜性的案例研究。为此,我们将源自森林结构的LiDAR衍生产品与可用的生境适应性模型进行了集成,以得出研究区域内各种物种-生境关联(并因此得出了生境适应性模式)。我们发现,LiDAR的价值在于量化以下能力:1)已知会影响地下植被和断枝分布的生态变量,例如冠层覆盖,地形和森林演替,以及2)指示或这表明灌木和障碍物的存在,例如在冠层下部地层的植被回报百分比(对于灌木)和森林冠层的垂直异质性(对于障碍物)。这些新的基于LiDAR的地图应用于野生动植物栖息地评估时,以以前使用其他遥感技术无法实现的方式完善了栖息地预测。这项研究突出了激光雷达在表征对野生生物重要的关键森林结构成分方面的新价值,并保证了其在其他森林环境和野生生物物种中的进一步应用。

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