Alldredge Mathew W, Simons Theodore R, Pollock Kenneth H
North Carolina Cooperative Fish and Wildlife Research Unit, Department of Zoology, Campus Box 7617, North Carolina State University, Raleigh, North Carolina 27695, USA.
Ecol Appl. 2007 Apr;17(3):948-55. doi: 10.1890/06-0685.
Many factors affect the number of birds detected on point count surveys of breeding songbirds. The magnitude and importance of these factors are not well understood. We used a bird song simulation system to quantify the effects of detection distance, singing rate, species differences, and observer differences on detection probabilities of birds detected by ear. We simulated 40 point counts consisting of 10 birds per count for five primary species (Black-and-white Warbler Mniotilta varia, Black-throated Blue Warbler Dendroica caerulescens, Black-throated Green Warbler Dendroica virens, Hooded Warbler Wilsonia citrina, and Ovenbird Seiurus aurocapillus) over a range of 15 distances (34-143 m). Songs were played at low (two songs per count) and high (13-21 songs per count) singing rates. Detection probabilities averaged across observers ranged from 0.60 (Black-and-white Warbler) to 0.83 (Hooded Warbler) at the high singing rate and 0.41 (Black-and-white Warbler) to 0.67 (Hooded Warbler) at the low singing rate. Logistic regression analyses indicated that species, singing rate, distance, and observer were all significant factors affecting detection probabilities. Singing rate x species and singing rate X distance interactions were also significant. Simulations of expected counts, based on the best logistic model, indicated that observers detected between 19% (for the worst observer, lowest singing rate, and least detectable species) and 65% (for the best observer, highest singing rate, and most detectable species) of the true population. Detection probabilities on actual point count surveys are likely to vary even more because many sources of variability were controlled in our experiments. These findings strongly support the importance of adjusting measures of avian diversity or abundance from auditory point counts with direct estimates of detection probability.
许多因素会影响在繁殖鸣禽的定点计数调查中检测到的鸟类数量。这些因素的大小和重要性尚未得到很好的理解。我们使用了一个鸟鸣模拟系统来量化检测距离、鸣叫率、物种差异和观察者差异对通过听觉检测到的鸟类检测概率的影响。我们模拟了40次定点计数,每次计数由10只鸟组成,涉及5种主要物种(黑白森莺Mniotilta varia、黑喉蓝林莺Dendroica caerulescens、黑喉绿林莺Dendroica virens、 hooded林莺Wilsonia citrina和灶鸟Seiurus aurocapillus),距离范围为15种(34 - 143米)。鸟鸣以低鸣叫率(每次计数两首鸟鸣)和高鸣叫率(每次计数13 - 21首鸟鸣)播放。观察者平均检测概率在高鸣叫率时从0.60(黑白森莺)到0.83(hooded林莺),在低鸣叫率时从0.41(黑白森莺)到0.67(hooded林莺)。逻辑回归分析表明,物种、鸣叫率、距离和观察者都是影响检测概率的重要因素。鸣叫率×物种和鸣叫率×距离的相互作用也很显著。基于最佳逻辑模型的预期计数模拟表明,观察者检测到的真实种群数量在19%(对于最差的观察者、最低的鸣叫率和最难检测的物种)到65%(对于最佳的观察者、最高的鸣叫率和最易检测的物种)之间。实际定点计数调查中的检测概率可能会有更大差异,因为我们的实验控制了许多变异性来源。这些发现有力地支持了通过直接估计检测概率来调整听觉定点计数中鸟类多样性或丰度测量的重要性。