Gowan Timothy A, Crum Nathan J, Roberts Jason J
Fish and Wildlife Research Institute Florida Fish and Wildlife Conservation Commission St. Petersburg FL USA.
Department of Wildlife Ecology and Conservation University of Florida Gainesville FL USA.
Ecol Evol. 2021 May 3;11(12):7354-7365. doi: 10.1002/ece3.7566. eCollection 2021 Jun.
The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line-transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture-recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture-recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture-recapture model that can be applied to line-transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line-transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line-transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.
许多野生动物种群研究的目的是估计密度、迁移情况或种群统计学参数。将这些参数与诸如栖息地特征等协变量联系起来，能提供更多的生态学见解，并可用于为管理目的进行预测。线截距调查结合距离抽样方法，常被用于估计离散时间点的密度，而标记重捕法用于估计迁移情况和其他种群统计学参数。最近，已开发出开放种群空间标记重捕模型，该模型能同时估计密度和种群统计学参数，但仅适用于从固定探测器阵列收集的数据，且未纳入栖息地协变量的影响。我们开发了一种空间标记重捕模型，通过以类似于距离抽样的方式对探测概率进行建模，可将其应用于线截距调查数据。我们将此模型扩展为：a）使用开放种群框架估计种群统计学参数；b）将密度和空间利用的变化建模为栖息地协变量的函数。使用模拟数据和美国东南部北大西洋露脊鲸的航空线截距调查数据对该模型进行了说明，这也展示了整合来自多个调查平台的数据以及适应不同层次或种群群体之间差异的能力。当从线截距调查中检测到的个体能够被唯一识别时，我们的模型可用于同时推断影响密度、迁移以及种群动态的空间和时间变化的因素。
