Quantifying the causes and consequences of variation in satellite‐derived population indices: a case study of emperor penguins
Quantifying the causes and consequences of variation in satellite‐derived population indices: a case study of emperor penguins
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量化卫星得出的种群指数变化的原因和后果：帝企鹅的案例研究
DOI：
10.1002/rse2.233
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发表时间：
2021
影响因子：
5.5
通讯作者：
LaRue, Michelle
中科院分区：
文献类型：
--
作者：
Labrousse, Sara;Iles, David;Viollat, Lise;Fretwell, Peter;Trathan, Philip N.;Zitterbart, Daniel P.;Jenouvrier, Stephanie;LaRue, Michelle
非常高分辨率卫星（VHR）图像是估算野生动物种群丰度的一种很有前途的工具，特别是在传统调查受到后勤挑战限制的偏远地区。帝企鹅是第一个通过VHR图像估算出环极种群的物种。在这里，我们解决了Fretwell等人（2012）的一个未经检验的假设，即帝企鹅群体的单张图像可以合理地代表该图像拍摄年份的群体。我们评估了可能影响企鹅像素计算面积的卫星相关变量和环境变量，以减少未来基于卫星估算帝企鹅种群的不确定性。我们重点分析了2011年9月至12月期间来自三个代表性群落的多幅VHR图像：Atka湾、Stancomb‐Wills（威德尔海区）和Coulman岛（罗斯海区）。我们复制了Fretwell等人（2012）的方法，包括使用ArcGIS 10.7软件中的监督分类工具计算每张图像中企鹅占据的面积（以下称为“种群指数”）。我们发现种群指数的变化范围从2倍到近6倍，这表明从单个图像计算的企鹅像素面积可能无法完全了解当年的种群规模。因此，我们进一步强调：(i)通过图像分辨率的太阳方位角和高程以及（ii）企鹅斑块（聚集与分布）在计算区域上的重要作用。我们发现了风和温度对企鹅斑块的影响。尽管种群指数存在季节内变化，但模拟表明，通过包括与卫星相关的协变量和环境协变量以及跨越时间和空间的汇总指数，可以获得可靠、稳健的种群趋势。我们的工作提供了额外的参数，这些参数应该包括在未来的帝企鹅种群规模模型中。
Very high‐resolution satellite (VHR) imagery is a promising tool for estimating the abundance of wildlife populations, especially in remote regions where traditional surveys are limited by logistical challenges. Emperor penguinsAptenodytes forsteriwere the first species to have a circumpolar population estimate derived via VHR imagery. Here we address an untested assumption from Fretwell et al. (2012) that a single image of an emperor penguin colony is a reasonable representation of the colony for the year the image was taken. We evaluated satellite‐related and environmental variables that might influence the calculated area of penguin pixels to reduce uncertainties in satellite‐based estimates of emperor penguin populations in the future. We focused our analysis on multiple VHR images from three representative colonies: Atka Bay, Stancomb‐Wills (Weddell Sea sector) and Coulman Island (Ross Sea sector) between September and December during 2011. We replicated methods in Fretwell et al. (2012), which included using supervised classification tools in ArcGIS 10.7 software to calculate area occupied by penguins (hereafter referred to as ‘population indices’) in each image. We found that population indices varied from 2 to nearly 6‐fold, suggesting that penguin pixel areas calculated from a single image may not provide a complete understanding of colony size for that year. Thus, we further highlight the important roles of: (i) sun azimuth and elevation through image resolution and (ii) penguin patchiness (aggregated vs. distributed) on the calculated areas. We found an effect of wind and temperature on penguin patchiness. Despite intra‐seasonal variability in population indices, simulations indicate that reliable, robust population trends are possible by including satellite‐related and environmental covariates and aggregating indices across time and space. Our work provides additional parameters that should be included in future models of population size for emperor penguins.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
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发表时间：
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期刊：
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影响因子：
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作者：
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影响因子：
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作者：
Trathan, Philip N.;Wienecke, Barbara;Barbraud, Christophe;Jenouvrier, Stéphanie;Kooyman, Gerald;Le Bohec, Céline;Ainley, David G.;Ancel, André;Zitterbart, Daniel P.;Chown, Steven L.
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影响因子：
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作者：
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通讯作者：
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