The Institute of Bird Populations, P.O. Box 1346, Point Reyes, California, 94956, USA.
Foundation for Ecological Research, Advocacy and Learning, Pondicherry, 605012, India.
Ecol Appl. 2017 Apr;27(3):916-924. doi: 10.1002/eap.1493. Epub 2017 Mar 21.
Integrated population models (IPMs) provide a unified framework for simultaneously analyzing data sets of different types to estimate vital rates, population size, and dynamics; assess contributions of demographic parameters to population changes; and assess population viability. Strengths of an IPM include the ability to estimate latent parameters and improve the precision of parameter estimates. We present a hierarchical IPM that combines two broad-scale avian monitoring data sets: count data from the North American Breeding Bird Survey (BBS) and capture-recapture data from the Monitoring Avian Productivity and Survivorship (MAPS) program. These data sets are characterized by large numbers of sample sites and observers, factors capable of inducing error in the sampling and observation processes. The IPM integrates the data sets by modeling the population abundance as a first-order autoregressive function of the previous year's population abundance and vital rates. BBS counts were modeled as a log-linear function of the annual index of population abundance, observation effects (observer identity and first survey year), and overdispersion. Vital rates modeled included adult apparent survival, estimated from a transient Cormack-Jolly-Seber model using MAPS data, and recruitment (surviving hatched birds from the previous season + dispersing adults) estimated as a latent parameter. An assessment of the IPM demonstrated it could recover true parameter values from 200 simulated data sets. The IPM was applied to data sets (1992-2008) of two bird species, Gray Catbird (Dumetella carolinensis) and Wood Thrush (Hylocichla mustelina) in the New England/Mid-Atlantic coastal Bird Conservation Region of the United States. The Gray Catbird population was relatively stable (trend +0.4% per yr), while the Wood Thrush population nearly halved (trend -4.5% per yr) over the 17-yr study period. IPM estimates of population growth rates, adult survival, and detection and residency probabilities were similar and as precise as estimates from the stand-alone BBS and CJS models. A benefit of using the IPM was its ability to estimate the latent recruitment parameter. Annual growth rates for both species correlated more with recruitment than survival, and the relationship for Wood Thrush was stronger than for Gray Catbird. The IPM's unified modeling framework facilitates integration of these important data sets.
综合种群模型（IPM）为同时分析不同类型的数据组以估计重要的生命参数、种群规模和动态提供了一个统一的框架；评估人口变化中人口参数的贡献；评估人口的生存能力。IPM 的优势包括估计潜在参数和提高参数估计精度的能力。我们提出了一种层次综合种群模型，该模型结合了两个广泛的鸟类监测数据集：来自北美的繁殖鸟类调查（BBS）的计数数据和监测鸟类生产力和生存能力（MAPS）计划的捕获-再捕获数据。这些数据集的特点是样本点和观察者的数量众多，这些因素会导致采样和观察过程中的误差。该模型通过将种群丰度建模为前一年种群丰度的一阶自回归函数来整合这些数据集。BBS 的计数被建模为年度种群丰度指数的对数线性函数，观测效果（观测者身份和第一次调查年份）和过离散。模型中包括成年个体的表观存活率，这是使用 MAPS 数据从瞬态 Cormack-Jolly-Seber 模型中估计的，以及招募率（上一季存活的孵化雏鸟+扩散成年个体），这是一个潜在的参数。对 IPM 的评估表明，它可以从 200 个模拟数据集中恢复真实的参数值。该模型应用于两个鸟类物种的数据（1992-2008 年），即美国新英格兰/大西洋中部沿海鸟类保护区的灰猫鸟（Dumetella carolinensis）和林地鸟（Hylocichla mustelina）。在 17 年的研究期间，灰猫鸟的种群相对稳定（趋势为每年增长 0.4%），而林地鸟的种群数量几乎减半（趋势为每年下降 4.5%）。IPM 对种群增长率、成年个体存活率以及检测和居留概率的估计与单独使用 BBS 和 CJS 模型的估计相似，并且同样精确。使用 IPM 的一个好处是它能够估计潜在的招募参数。这两个物种的年增长率与招募率的相关性都高于存活率，林地鸟的相关性强于灰猫鸟。IPM 的统一建模框架促进了这些重要数据集的整合。
