Characterizing spatio-temporal variation in survival and recruitment with integrated population models
Characterizing spatio-temporal variation in survival and recruitment with integrated population models
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DOI：
10.1642/auk-17-181.1
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发表时间：
2018-07-01
期刊：
影响因子：
2.8
通讯作者：
Cooper, Robert J.
中科院分区：
文献类型：
--
作者：
Chandler, Richard B.;Hepinstall-Cymerman, Jeff;Cooper, Robert J.
了解种群动态和确定高质量栖息地的努力需要有关人口参数的空间变化的信息。然而，估计人口统计参数通常需要劳动密集型的捕获-再捕获方法，这些方法很难在大空间范围内实施。空间显式综合人口模型(IPMS)通过将在少数地点收集的空间捕获-再捕获(SCR)数据与可能在更大范围内收集的调查数据相适应，提供了一种解决方案。我们扩展了空间IPM框架以包括一个时空点过程模型用于补充，并将该模型应用于美国北卡罗来纳州靠近物种繁育范围南部范围的加拿大林莺(Cardellina Canensis)的4年SCR和距离采样数据，那里的气候变化预计将导致种群数量下降和分布向高海拔转移。为了描述我们研究区域内人口统计参数随气候梯度的空间变化，我们模拟了密度、存活率和人均招募作为海拔的函数。我们使用仅限男性的模型，因为男性占我们点数检测的90%。表观存活率很低，但随着海拔的升高而增加，从900m的0.040(95%可信区间：0.0032-0.12)增加到1500米的0.29(95%可信区间：0.16-0.42)。补充与海拔没有很强的相关性，但密度变化很大，从1400米以上的0.2ha-1。
Efforts to understand population dynamics and identify high-quality habitat require information about spatial variation in demographic parameters. However, estimating demographic parameters typically requires labor-intensive capture-recapture methods that are difficult to implement over large spatial extents. Spatially explicit integrated population models (IPMs) provide a solution by accommodating spatial capture-recapture (SCR) data collected at a small number of sites with survey data that may be collected over a much larger extent. We extended the spatial IPM framework to include a spatio-temporal point process model for recruitment, and we applied the model to 4 yr of SCR and distance-sampling data on Canada Warblers (Cardellina canadensis) near the southern extent of the species' breeding range in North Carolina, USA, where climate change is predicted to cause population declines and distributional shifts toward higher elevations. To characterize spatial variation in demographic parameters over the climate gradient in our study area, we modeled density, survival, and per capita recruitment as functions of elevation. We used a male-only model because males comprised >90% of our point-count detections. Apparent survival was low but increased with elevation, from 0.040 (95% credible interval [Cl]: 0.0032-0.12) at 900 m to 0.29 (95% CI: 0.16-0.42) at 1,500 m. Recruitment was not strongly associated with elevation, yet density varied greatly, from 0.2 males ha -1 above 1,400 m. Point estimates of population growth rate were