Lidar Prediction of Small Mammal Diversity in Wisconsin, USA
Lidar Prediction of Small Mammal Diversity in Wisconsin, USA
复制标题
美国威斯康星州小型哺乳动物多样性的激光雷达预测
DOI：
10.3390/rs11192222
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Harold S. J. Zald
中科院分区：
文献类型：
--
作者：
S. Schooler;Harold S. J. Zald
植被结构是许多类群栖息地选择的重要组成部分，机载激光雷达（LiDAR）技术越来越多地用于测量森林结构。许多研究已经研究了激光雷达衍生的结构特征与野生动物之间的关系，但很少研究这些特征与小型哺乳动物的关系，特别是小型哺乳动物的多样性。本研究的目的是确定激光雷达是否可以预测美国威斯康星州北部温带混交林群落的小型哺乳动物多样性，以及哪些激光雷达衍生的结构变量最能预测小型哺乳动物的多样性。我们利用激光雷达点云数据计算了3个不同管理地点的17个地块的网格指标，并将这些指标与基于5个月小型哺乳动物捕获数据计算的小型哺乳动物多样性相关联。我们建立了线性模型，然后使用模型选择和多模型推理以及模型拟合指标来确定激光雷达衍生的结构变量是否可以预测小型哺乳动物的多样性。我们发现，小型哺乳动物的多样性可以通过激光雷达衍生的变量来预测，包括结构多样性、覆盖度、冠层复杂性以及地点（作为管理的代理）。结构多样性和冠层复杂性与小哺乳动物多样性正相关，盖度与小哺乳动物多样性负相关。虽然该研究是在单一季节的单一栖息地类型中进行的，但它表明激光雷达可以用于预测该地点的小型哺乳动物多样性，并可能扩展到更大空间尺度上的小型哺乳动物多样性预测。
Vegetation structure is a crucial component of habitat selection for many taxa, and airborne LiDAR (Light Detection and Ranging) technology is increasingly used to measure forest structure. Many studies have examined the relationship between LiDAR-derived structural characteristics and wildlife, but few have examined those characteristics in relation to small mammals, specifically, small mammal diversity. The aim of this study was to determine if LiDAR could predict small mammal diversity in a temperate-mixed forest community in Northern Wisconsin, USA, and which LiDAR-derived structural variables best predict small mammal diversity. We calculated grid metrics from LiDAR point cloud data for 17 plots in three differently managed sites and related the metrics to small mammal diversity calculated from five months of small mammal trapping data. We created linear models, then used model selection and multi-model inference as well as model fit metrics to determine if LiDAR-derived structural variables could predict small mammal diversity. We found that small mammal diversity could be predicted by LiDAR-derived variables including structural diversity, cover, and canopy complexity as well as site (as a proxy for management). Structural diversity and canopy complexity were positively related with small mammal diversity, while cover was negatively related to small mammal diversity. Although this study was conducted in a single habitat type during a single season, it demonstrates that LiDAR can be used to predict small mammal diversity in this location and possibly can be expanded to predict small mammal diversity across larger spatial scales.
通过同时测试用户定义的多样性指数选择来评估生物多样性的群体差异
影响因子：
7.7
作者：
Pallmann;Schaarschmidt;Hothorn;Fischer;Priesnitz;Schork
通讯作者：
Schork