利用空间激光雷达揭示动物种群的驱动因素。

IF 4.3 2区 环境科学与生态学 Q1 ECOLOGY
Brent R Barry,Joseph D Holbrook,Jody C Vogeler,Lisa H Elliott,Matthew J Weldy,Damon B Lesmeister,Clinton Epps,Todd Wilson,Kerri T Vierling
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引用次数: 0

摘要

遥感可提供连续的植被时空信息,为野生动物栖息地估算提供依据,但这些方法往往可用性有限,或缺乏足够的分辨率,无法捕捉对了解栖息地至关重要的三维植被细节。全球生态系统动态调查(GEDI)是一种空间光探测和测距系统(LiDAR),它彻底改变了地球温带和热带森林高质量三维植被测量的可用性。迄今为止,GEDI 数据或 GEDI 融合产品在野生动物方面的应用仅限于估计物种的栖息地使用、分布和多样性。在此,我们的目标是通过评估 GEDI 数据融合是否有助于描述野生动物的人口统计参数,将基于 GEDI 的应用扩展到野生动物的人口统计。我们利用最近发布的 GEDI 融合森林结构数据集和捕获-标记-再捕获数据,估算了两个小型哺乳动物物种--洪堡鼯鼠(Glaucomys oregonensis)和汤森花鼠(Neotamias townsendii)的密度和存活率,这两个物种来自俄勒冈州西部的三项研究,时间跨度为 2014-2021 年。我们在哈金斯稳健设计模型中使用捕获历史记录来估计表观年存活率,并将密度作为推导参数。我们发现,飞鼠和花栗鼠的密度与飞鼠5-10米层的叶高多样性和植物面积体积密度的GEDI-融合森林结构相关,而花栗鼠0-20米层的植物面积体积密度比例较高,同时还与海拔等其他时空因素相关。我们发现,对鼯鼠而言,表观年存活率与 GEDI-融合森林结构相关,但对花栗鼠而言却不相关,这一点得到了微弱的支持。通过绘制这两种物种的空间密度图,我们进一步证明了这些方法的实用性,这将有助于管理和保护政策的制定。我们的工作代表了一种将 GEDI 数据用于评估野生动物人口结构并为这些物种生成连续的空间明确密度预测的新方法。我们的结论是,通过 GEDI 数据融合所描述的森林结构可以解释小型哺乳动物种群分布的各个方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using spaceborne LiDAR to reveal drivers of animal demography.
Remote sensing can provide continuous spatiotemporal information about vegetation to inform wildlife habitat estimates, but these methods are often limited in availability or lack adequate resolution to capture the three-dimensional vegetative details critical for understanding habitat. The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne light detection and ranging system (LiDAR) that has revolutionized the availability of high-quality three-dimensional vegetation measurements of the Earth's temperate and tropical forests. To date, wildlife-related applications of GEDI data or GEDI-fusion products have been limited to estimate species habitat use, distribution, and diversity. Here, our goal was to expand the use of GEDI-based applications to wildlife demography by evaluating if GEDI data fusions could aid in characterizing demographic parameters of wildlife. We leveraged a recently published dataset of GEDI-fusion forest structures and capture-mark-recapture data to estimate the density and survival of two small mammal species, Humboldt's flying squirrel (Glaucomys oregonensis) and Townsend's chipmunk (Neotamias townsendii), from three studies in western Oregon spanning 2014-2021. We used capture histories in Huggins robust design models to estimate apparent annual survival and density as a derived parameter. We found strong support that both flying squirrel and chipmunk density were associated with GEDI-fusion forest structures of foliage height diversity and plant area volume density in the 5-10 m strata for flying squirrels and proportionately higher plant area volume density in the 0-20 m strata for chipmunks, as well as other spatiotemporal factors such as elevation. We found weak support that apparent annual survival was associated with GEDI-fusion forest structures for flying squirrels but not for chipmunks. We demonstrate further utility of these methods by creating spatially explicit density maps of both species that could aid management and conservation policies. Our work represents a novel application of GEDI data to evaluate wildlife demography and produce continuous spatially explicit density predictions for these species. We conclude that aspects of small mammal demography can be explained by forest structure as characterized via GEDI data fusions.
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来源期刊
Ecological Applications
Ecological Applications 环境科学-环境科学
CiteScore
9.50
自引率
2.00%
发文量
268
审稿时长
6 months
期刊介绍: The pages of Ecological Applications are open to research and discussion papers that integrate ecological science and concepts with their application and implications. Of special interest are papers that develop the basic scientific principles on which environmental decision-making should rest, and those that discuss the application of ecological concepts to environmental problem solving, policy, and management. Papers that deal explicitly with policy matters are welcome. Interdisciplinary approaches are encouraged, as are short communications on emerging environmental challenges.
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