Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, P.O. Box 110430, Gainesville, Florida 32611, USA.
Ecology. 2011 Apr;92(4):821-8. doi: 10.1890/10-0137.1.
Many populations of animals are fluid in both space and time, making estimation of numbers difficult. Much attention has been devoted to estimation of bias in detection of animals that are present at the time of survey. However, an equally important problem is estimation of population size when all animals are not present on all survey occasions. Here, we showcase use of the superpopulation approach to capture-recapture modeling for estimating populations where group membership is asynchronous, and where considerable overlap in group membership among sampling occasions may occur. We estimate total population size of long-legged wading bird (Great Egret and White Ibis) breeding colonies from aerial observations of individually identifiable nests at various times in the nesting season. Initiation and termination of nests were analogous to entry and departure from a population. Estimates using the superpopulation approach were 47-382% larger than peak aerial counts of the same colonies. Our results indicate that the use of the superpopulation approach to model nesting asynchrony provides a considerably less biased and more efficient estimate of nesting activity than traditional methods. We suggest that this approach may also be used to derive population estimates in a variety of situations where group membership is fluid.
许多动物种群在空间和时间上都是流动的，这使得数量估计变得困难。人们已经非常关注在调查时存在的动物的检测偏差的估计。然而，同样重要的问题是当所有动物不在所有调查时刻都存在时，如何估计种群数量。在这里，我们展示了超级群体方法在捕获-再捕获建模中的应用，以估计群体成员身份不同步的种群数量，并且在采样时刻之间可能会发生相当大的群体成员身份重叠。我们通过在筑巢季节的不同时间对可识别个体巢的航空观测来估计长腿涉禽（大白鹭和白琵鹭）繁殖群体的总种群数量。巢的开始和结束类似于进入和离开一个种群。使用超级群体方法的估计值比同一繁殖群体的高峰航空计数大 47-382%。我们的结果表明，使用超级群体方法来模拟筑巢的异步性，比传统方法提供了一个偏差更小、效率更高的筑巢活动估计值。我们建议，这种方法也可以用于在群体成员身份不稳定的各种情况下得出种群估计值。
