Vierling Lee A, Vierling Kerri T, Adam Patrick, Hudak Andrew T
Department of Forest, Rangeland, and Fire Sciences, McCall Outdoor Science School, University of Idaho, Moscow, Idaho, United States of America.
PLoS One. 2013 Dec 6;8(12):e80988. doi: 10.1371/journal.pone.0080988. eCollection 2013.
Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.
将垂直植被结构纳入动物分布模型可以增进对支配栖息地选择的模式和过程的理解。激光雷达可以提供此类结构信息，但这些数据通常是通过飞机收集的，因此空间范围有限。我们的目标是探索来自地球科学激光高度计系统（GLAS）的基于卫星的激光雷达数据相对于基于航空的激光雷达在模拟爱达荷州北部一种依赖森林的生态系统工程师——红颈吸汁啄木鸟（Sphyrapicus nuchalis）繁殖分布方面的效用。GLAS数据出现在直径约64米的椭圆内，这些椭圆彼此间隔至少172米，所有占有率分析都局限于这个粒度尺度。我们采用分层方法，将红颈吸汁啄木鸟的占有率建模为源自两个平台的激光雷达指标的函数。基于卫星数据的占有率模型效果不佳，可能是因为GLAS椭圆内的数据没有完全代表对该物种重要的栖息地特征。基于航空激光雷达数据，影响红颈吸汁啄木鸟繁殖地点选择的最重要结构变量包括树叶高度多样性、树冠垂直剖面中主要层次之间的距离以及地面附近的植被密度。这些特征与该物种表现出的觅食活动多样性一致。据我们所知，这项研究是首次考察基于卫星的激光雷达在模拟动物分布方面的效用。每个GLAS椭圆的面积较大以及GLAS数据的不连续性可能给野生动物分布建模带来重大挑战；尽管如此，这些数据可以提供有关生态系统垂直结构的有用信息，特别是在地形平缓的地区。因此，有必要开展更多工作，利用从航空以及过去和未来的卫星平台（如GLAS和计划中的冰卫星2任务）收集的激光雷达数据集，目标是改进全球更多地点的野生动物建模。
