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气流模型预测各岛屿上的海鸟繁殖栖息地。

Airflow modelling predicts seabird breeding habitat across islands.

作者信息

Lempidakis Emmanouil, Ross Andrew N, Börger Luca, Shepard Emily L C

机构信息

Dept of Biosciences, Swansea Univ., Swansea, UK.

School of Earth and Environment, Univ. of Leeds, Leeds, UK.

出版信息

Ecography. 2021 Nov 21;2022(1):05733. doi: 10.1111/ecog.05733. eCollection 2022 Jan.

DOI:10.1111/ecog.05733
PMID:34987352
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7612159/
Abstract

Wind is fundamentally related to shelter and flight performance: two factors that are critical for birds at their nest sites. Despite this, airflows have never been fully integrated into models of breeding habitat selection, even for well-studied seabirds. Here, we use computational fluid dynamics to provide the first assessment of whether flow characteristics (including wind speed and turbulence) predict the distribution of seabird colonies, taking common guillemots breeding on Skomer Island as our study system. This demonstrates that occupancy is driven by the need to shelter from both wind and rain/wave action, rather than airflow characteristics alone. Models of airflows and cliff orientation both performed well in predicting high-quality habitat in our study site, identifying 80% of colonies and 93% of avoided sites, as well as 73% of the largest colonies on a neighbouring island. This suggests generality in the mechanisms driving breeding distributions and provides an approach for identifying habitat for seabird reintroductions considering current and projected wind speeds and directions.

摘要

风与庇护所和飞行性能有着根本联系

这两个因素对鸟类在其筑巢地点至关重要。尽管如此,气流从未被完全纳入繁殖栖息地选择模型,即使是对于研究充分的海鸟也是如此。在此,我们使用计算流体动力学,以在斯科默岛繁殖的普通海鸠作为我们的研究系统,首次评估气流特征(包括风速和湍流)是否能预测海鸟栖息地的分布。这表明栖息地的选择是出于躲避风雨/海浪作用的需要,而非仅仅由气流特征驱动。气流模型和悬崖方向模型在预测我们研究地点的优质栖息地方面都表现良好,识别出了80%的栖息地和93%的避开地点,以及邻近岛屿上73%的最大栖息地。这表明驱动繁殖分布的机制具有普遍性,并提供了一种考虑当前和预计风速及风向来识别海鸟重新引入栖息地的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/a1a103e5ee56/EMS140358-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/3c1ce6a1065c/EMS140358-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/b4714a82d0a4/EMS140358-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/1709fbc10cf9/EMS140358-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/a1a103e5ee56/EMS140358-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/3c1ce6a1065c/EMS140358-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/b4714a82d0a4/EMS140358-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/1709fbc10cf9/EMS140358-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b335/7612159/a1a103e5ee56/EMS140358-f004.jpg

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