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首页> 外文期刊>Remote Sensing >Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?
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Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?

机译:从卫星图像得出的机载激光扫描(ALS)和森林估计值能否用于预测北方森林鸟类和甲虫的丰度和物种丰富度?

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In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS) and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand) had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands). Bird abundance and species richness were best explained by the ALS variables “maximum vegetation height” and “vegetation cover between 0.5 and 3 m” (both positive). Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living) beetle richness were best explained by a model including the ALS variable “maximum vegetation height” (positive) and the satellite-derived variable “proportion of pine” (negative). Epigaeic beetle abundance was best explained by “maximum vegetation height” at 50 m (positive) and “stem volume” at 200 m (positive). Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.
机译:在受管理的景观中,保护区规划需要有效的方法来识别高生物多样性地区。这项研究的目的是评估机载激光扫描(ALS)和从在两个空间尺度上提取的卫星图像得出的森林估计值的潜力,以预测在受管理的北方森林景观中鸟类和甲虫的尺度规模丰度和物种丰富度。与基于200米半径(即还包括部分相邻林分)的模型相比,基于50米半径(即对应于同质林分)的森林数据的多元回归模型具有更好的解释力。用ALS变量“最大植被高度”和“ 0.5至3 m之间的植被覆盖”(均为正值)可以最好地解释鸟类的丰度和物种丰富度。飞行甲虫的丰度和物种丰富度以及表甲(即地面生活)甲虫的丰富度可以通过一个模型得到最好的解释,该模型包括ALS变量“最大植被高度”(正)和卫星衍生变量“松树比例”(负)。甲虫的丰度最好用50 m(正)的“最大植被高度”和200 m(正)的“茎体积”来最好地解释。我们的结果表明,从卫星图像和ALS数据得出的森林估计值可提供补充信息,以解释森林生物多样性模式。我们得出的结论是,这些类型的遥感数据可能为受管理的北方景观的保护规划提供有效的工具。

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