Department of Fish Wildlife and Conservation Biology, Colorado State University Fort Collins, CO 805325.
Ecol Evol. 2013 Oct;3(12):4215-20. doi: 10.1002/ece3.791. Epub 2013 Sep 30.
In capture-recapture studies, the estimation accuracy of demographic parameters is essential to the efficacy of management of hunted animal populations. Dead recovery models based upon the reporting of rings or bands are often used for estimating survival of waterfowl and other harvested species. However, distance from the ringing site or condition of the bird may introduce substantial individual heterogeneity in the conditional band reporting rates (r), which could cause bias in estimated survival rates (S) or suggest nonexistent individual heterogeneity in S. To explore these hypotheses, we ran two sets of simulations (n = 1000) in MARK using Seber's dead recovery model, allowing time variation on both S and r. This included a series of heterogeneity models, allowing substantial variation on logit(r), and control models with no heterogeneity. We conducted simulations using two different values of S: S = 0.60, which would be typical of dabbling ducks such as mallards (Anas platyrhynchos), and S = 0.80, which would be more typical of sea ducks or geese. We chose a mean reporting rate on the logit scale of -1.9459 with SD = 1.5 for the heterogeneity models (producing a back-transformed mean of 0.196 with SD = 0.196, median = 0.125) and a constant reporting rate for the control models of 0.196. Within these sets of simulations, estimation models where σS = 0 and σS > 0 (σS is SD of individual survival rates on the logit scale) were incorporated to investigate whether real heterogeneity in r would induce apparent individual heterogeneity in S. Models where σS = 0 were selected approximately 91% of the time over models where σS > 0. Simulation results showed < 0.05% relative bias in estimating survival rates except for models estimating σS > 0 when true S = 0.8, where relative bias was a modest 0.5%. These results indicate that considerable variation in reporting rates does not cause major bias in estimated survival rates of waterfowl, further highlighting the robust nature of dead recovery models that are being used for the management of harvested species.
在捕获-再捕获研究中，对人口统计学参数的估计准确性对于被猎动物种群管理的效果至关重要。基于环或带报告的死亡恢复模型通常用于估计水禽和其他收获物种的存活率。然而，距环站的距离或鸟类的状况可能会导致条件带报告率（r）个体间存在显著的异质性，这可能导致估计的存活率（S）存在偏差，或者表明 S 中不存在个体异质性。为了探讨这些假设，我们使用 MARK 中的 Seber 死亡恢复模型运行了两组模拟（n = 1000），允许 S 和 r 随时间变化。这包括一系列异质性模型，允许对数几率（r）有很大的变化，以及没有异质性的对照模型。我们使用两种不同的 S 值进行了模拟：S = 0.60，这是普通鸭类（如绿头鸭（Anas platyrhynchos））的典型值，S = 0.80，这是海鸭或鹅的典型值。我们选择了对数刻度上的平均报告率为-1.9459，标准差（SD）为 1.5，用于异质性模型（产生反变换后的平均值为 0.196，标准差为 0.196，中位数为 0.125），而对照模型的报告率为常数 0.196。在这些模拟组中，纳入了 σS = 0 和 σS > 0（σS 是个体存活率在对数刻度上的标准差）的估计模型，以研究 r 中的真实异质性是否会导致 S 中的明显个体异质性。当真实 S = 0.8 时，大约 91%的时间选择了 σS = 0 的模型，而不是 σS > 0 的模型，除了估计 σS > 0 的模型外，这些模型的估计存活率的相对偏差<0.05%。这些结果表明，报告率的较大变化不会导致水禽估计存活率的主要偏差，进一步突出了用于收获物种管理的死亡恢复模型的稳健性。
