Resource selection by a megaomnivore in a marine foraging habitat

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-11-03 DOI:10.1002/ece3.70132
Andrew S. Maurer, Tomo Eguchi, Garrett E. Lemons, Robin A. LeRoux, Erin L. LaCasella, Calandra N. Turner Tomaszewicz, Megan E. Hanna, Jessica Curran, Bryant Chesney, Sheila V. Madrak, Jeffrey A. Seminoff
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Abstract

Habitat-based approaches to animal conservation are bolstered by an understanding of resource selection, that is, use of resources (i.e., habitat features) relative to their availability in the environment. Quantifying resource selection is especially valuable when data characterizing animal space use are limited, as is often the case with mobile and/or cryptic species. Documenting associations with habitat features can better inform management in space in time, while also revealing key insight into movement ecology and behavior. Here, we evaluate resource selection by a megaomnivore whose highly mobile nature within marine habitats has resulted in an incomplete understanding of drivers of space use. We used satellite telemetry to track 29 green turtles (Chelonia mydas) from an eastern Pacific foraging aggregation in San Diego Bay, California, USA during 2013–2023. Tracking produced 5023 Fastloc-GPS points which we used to model selection for local environmental resources relative to their availability. We employed logistic models to evaluate associations with seagrass, bathymetry, and water temperatures, implementing a framework that additionally allowed us to explore the roles of season, diel period, and turtle body size. Our methods demonstrate an approach for down-weighting observations according to assumed telemetry error and autocorrelation. Results from fine-scale resource selection models provide evidence that green turtles in San Diego Bay select for eelgrass meadows (Zostera marina), particularly during the warmest months of the year, but the strength of this selection changes from day to night. We additionally found day–night shifts in depth and temperature selection that changed with turtle body size and season. We discuss these findings in the context of diel patterns in resting and foraging behavior in addition to seasonal changes in thermally sensitive metabolic rates. Our study documents resource associations and provides quantitative information for the management of sea turtle foraging populations and their habitats. We offer key insight into habitat use by green turtles in the eastern Pacific at a pivotal time when multiple indicators point to population growth and expansion within the region.

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巨型食肉动物在海洋觅食栖息地的资源选择
基于栖息地的动物保护方法可以通过对资源选择的理解得到支持,即相对于环境中的可用性对资源(即栖息地特征)的利用。当描述动物空间利用特征的数据有限时,量化资源选择就显得尤为重要,移动和/或隐蔽物种通常就是这种情况。记录与栖息地特征的关联可以更好地为空间和时间管理提供信息,同时还能揭示运动生态学和行为学的关键信息。在这里,我们对一种巨型食肉动物的资源选择进行了评估,这种食肉动物在海洋栖息地内的高度流动性导致我们对空间利用驱动因素的了解不够全面。2013-2023 年间,我们使用卫星遥测技术追踪了 29 只绿海龟(Chelonia mydas),它们来自美国加利福尼亚州圣地亚哥湾的一个东太平洋觅食聚集地。追踪产生了 5023 个 Fastloc-GPS 点,我们利用这些点建立了当地环境资源选择模型。我们采用逻辑模型来评估与海草、水深和水温之间的关联,并实施了一个框架,使我们能够探索季节、昼夜周期和海龟体型的作用。我们的方法展示了一种根据假定的遥测误差和自相关性对观测结果进行降权的方法。细尺度资源选择模型的结果证明,圣地亚哥湾的绿海龟选择鳗草草甸(Zostera marina),尤其是在一年中最温暖的月份,但这种选择的强度从白天到夜晚会发生变化。我们还发现,深度和温度选择的昼夜变化随海龟体型和季节而变化。除了热敏代谢率的季节性变化之外,我们还结合休息和觅食行为的昼夜模式讨论了这些发现。我们的研究记录了资源关联,为海龟觅食种群及其栖息地的管理提供了定量信息。我们对东太平洋绿海龟栖息地的利用提供了重要的洞察力,而此时正值多个指标显示该地区绿海龟种群增长和扩张的关键时期。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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