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Effects of distance on detectability of Arctic waterfowl using double‐observer sampling during helicopter surveys

机译:直升机调查期间距离对北极水禽可探测性的影响

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摘要

Aerial survey is an important, widely employed approach for estimating free‐ranging wildlife over large or inaccessible study areas. We studied how a distance covariate influenced probability of double‐observer detections for birds counted during a helicopter survey in Canada’s central Arctic. Two observers, one behind the other but visually obscured from each other, counted birds in an incompletely shared field of view to a distance of 200 m. Each observer assigned detections to one of five 40‐m distance bins, guided by semi‐transparent marks on aircraft windows. Detections were recorded with distance bin, taxonomic group, wing‐flapping behavior, and group size. We compared two general model‐based estimation approaches pertinent to sampling wildlife under such situations. One was based on double‐observer methods without distance information, that provide sampling analogous to that required for mark–recapture (MR) estimation of detection probability, p^, and group abundance, G^, along a fixed‐width strip transect. The other method incorporated double‐observer MR with a categorical distance covariate (MRD). A priori, we were concerned that estimators from MR models were compromised by heterogeneity in p^ due to un‐modeled distance information; that is, more distant birds are less likely to be detected by both observers, with the predicted effect that p^ would be biased high, and G^ biased low. We found that, despite increased complexity, MRD models (ΔAICc range: 0–16) fit data far better than MR models (ΔAICc range: 204–258). However, contrary to expectation, the more naïve MR estimators of p^ were biased low in all cases, but only by 2%–5% in most cases. We suspect that this apparently anomalous finding was the result of specific limitations to, and trade‐offs in, visibility by observers on the survey platform used. While MR models provided acceptable point estimates of group abundance, their far higher stranded errors (0%–40%) compared to MRD estimates would compromise ability to detect temporal or spatial differences in abundance. Given improved precision of MRD models relative to MR models, and the possibility of bias when using MR methods from other survey platforms, we recommend avian ecologists use MRD protocols and estimation procedures when surveying Arctic bird populations.
机译:航空测量是一种重要的,广泛采用的方法,用于估算在较大或无法进入的研究区域内自由放养的野生动植物。我们研究了距离协变量如何影响在加拿大中部北极地区进行的直升机调查中对双鸟发现次数的概率。两名观察员彼此落后,但在视觉上却相互遮挡,他们在不完全共享的视野中数到200 m时对鸟类进行计数。每个观察员在飞机窗上的半透明标记的引导下,将探测分配给五个40 m的距离箱之一。检测记录了距离箱,分类组,机翼拍打行为和组大小。我们比较了两种与这种情况下的野生动植物采样有关的基于模型的通用估计方法。一种基于无距离信息的双观测器方法,该方法提供类似于检测概率的标记捕获(MR)估计所需的采样, <移动器重音=” true“> p ^ 和组丰度, <移动器accent =“ true”> G ^ ,沿着固定宽度的条形样带。另一种方法是将双观测器MR与分类距离协变量(MRD)结合在一起。先验地,我们担心来自MR模型的估计值会因 p ^ ;也就是说,两个观察者都不太可能检测到更远的鸟类,其预测效果是 p ^ 会偏高和 <移动器重音=“ true”> G ^ 偏低。我们发现,尽管复杂性增加,MRD模型(ΔAICc范围:0–16)比MR模型(ΔAICc范围:204–258)拟合的数据好得多。但是,与预期相反,在所有情况下, p ^ 偏低,但只有2%–在大多数情况下为5%。我们怀疑这种明显的异常发现是观察者在所使用的调查平台上对可见性进行特定限制和权衡的结果。尽管MR模型提供了群体丰度的可接受点估计,但与MRD估计相比,它们的更高的搁浅误差(0%–40%)将损害检测丰度的时间或空间差异的能力。鉴于MRD模型相对于MR模型的精度有所提高,并且在使用来自其他调查平台的MR方法时可能会产生偏差,因此我们建议鸟类生态学家在调查北极鸟类种群时使用MRD协议和估算程序。

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