Burskiî O V
Zh Obshch Biol. 2011 May-Jun;72(3):163-82.
The stochastic modeling technique serves as a way to correctly separate "return rate" of marked animals into survival rate (phi) and capture probability (p). The method can readily be used with the program MARK freely distributed through Internet (Cooch, White, 2009). Input data for the program consist of "capture histories" of marked animals--strings of units and zeros indicating presence or absence of the individual among captures (or sightings) along the set of consequent recapture occasions (e.g., years). Probability of any history is a product of binomial probabilities phi, p or their complements (1 - phi) and (1 - p) for each year of observation over the individual. Assigning certain values to parameters phi and p, one can predict the composition of all individual histories in the sample and assess the likelihood of the prediction. The survival parameters for different occasions and cohorts of individuals can be set either equal or different, as well as recapture parameters can be set in different ways. There is a possibility to constraint the parameters, according to the hypothesis being tested, in the form of a specific model. Within the specified constraints, the program searches for parameter values that describe the observed composition of histories with the maximum likelihood. It computes the parameter estimates along with confidence limits and the overall model likelihood. There is a set of tools for testing the model goodness-of-fit under assumption of equality of survival rates among individuals and independence of their fates. Other tools offer a proper selection among a possible variety of models, providing the best parity between details and precision in describing reality. The method was applied to 20-yr recapture and resighting data series on 4 thrush species (genera Turdus, Zoothera) breeding in the Yenisei River floodplain within the middle taiga subzone. The capture probabilities were quite independent of observational efforts fluctuations while differing significantly between the species and sexes. The estimates of adult survival rate, obtained for the Siberian migratory populations, were lower than those for sedentary populations from both the tropics and intermediate latitudes with marine climate (data by Ricklefs, 1997). Two factors, the average temperature influencing birds during their annual movements, and climatic seasonality (temperature difference between summer and winter) in the breeding area, fit the latitudinal pattern of survival most closely (R2 = 0.90). Final survival of migrants reflects an adaptive life history compromise for use of superabundant resources in breeding area at the cost of avoidance of severe winter conditions.
随机建模技术是一种将标记动物的“回报率”正确分解为存活率(φ)和捕获概率(p)的方法。该方法可以很容易地与通过互联网免费分发的MARK程序一起使用(库奇、怀特,2009年)。该程序的输入数据由标记动物的“捕获历史”组成——由0和1组成的字符串,表示个体在一系列连续的重捕场合(如年份)的捕获(或观察)中是否出现。任何历史的概率是个体每年观察的二项式概率φ、p或它们的补数(1 - φ)和(1 - p)的乘积。给参数φ和p赋予特定值,可以预测样本中所有个体历史的组成,并评估预测的可能性。不同场合和个体群组的存活参数可以设置为相等或不同,重捕参数也可以以不同方式设置。根据所检验的假设,可以以特定模型的形式对参数进行约束。在指定的约束范围内,程序搜索以最大似然描述观察到的历史组成的参数值。它计算参数估计值以及置信限和总体模型似然性。有一组工具用于在个体存活率相等且命运独立的假设下检验模型拟合优度。其他工具在可能的各种模型中提供适当的选择,在描述现实的细节和精度之间提供最佳平衡。该方法应用于在中泰加亚区叶尼塞河泛滥平原繁殖的4种鸫属(鸫属、地鸫属)鸟类的20年重捕和再观察数据系列。捕获概率与观察努力的波动相当独立,而在物种和性别之间有显著差异。从西伯利亚迁徙种群获得的成年存活率估计值低于来自热带地区和具有海洋性气候的中纬度地区的定居种群(数据来自里克尔斯,1997年)。两个因素,即鸟类年度迁徙期间影响它们的平均温度和繁殖区的气候季节性(夏季和冬季之间的温差),与存活的纬度模式拟合得最紧密(R2 = 0.90)。候鸟的最终存活率反映了一种适应性的生活史权衡,即以避免严冬条件为代价,在繁殖区利用丰富的资源。