Bled Florent, Belant Jerrold L, Van Daele Lawrence J, Svoboda Nathan, Gustine David, Hilderbrand Grant, Barnes Victor G
Carnivore Ecology Laboratory Mississippi State University Mississippi State MS USA.
Kodiak Wildlife Services Kodiak AK USA.
Ecol Evol. 2017 Oct 11;7(22):9531-9543. doi: 10.1002/ece3.3469. eCollection 2017 Nov.
Current management of large carnivores is informed using a variety of parameters, methods, and metrics; however, these data are typically considered independently. Sharing information among data types based on the underlying ecological, and recognizing observation biases, can improve estimation of individual and global parameters. We present a general integrated population model (IPM), specifically designed for brown bears (), using three common data types for bear (. spp.) populations: repeated counts, capture-mark-recapture, and litter size. We considered factors affecting ecological and observation processes for these data. We assessed the practicality of this approach on a simulated population and compared estimates from our model to values used for simulation and results from count data only. We then present a practical application of this general approach adapted to the constraints of a case study using historical data available for brown bears on Kodiak Island, Alaska, USA. The IPM provided more accurate and precise estimates than models accounting for repeated count data only, with credible intervals including the true population 94% and 5% of the time, respectively. For the Kodiak population, we estimated annual average litter size (within one year after birth) to vary between 0.45 [95% credible interval: 0.43; 0.55] and 1.59 [1.55; 1.82]. We detected a positive relationship between salmon availability and adult survival, with survival probabilities greater for females than males. Survival probabilities increased from cubs to yearlings to dependent young ≥2 years old and decreased with litter size. Linking multiple information sources based on ecological and observation mechanisms can provide more accurate and precise estimates, to better inform management. IPMs can also reduce data collection efforts by sharing information among agencies and management units. Our approach responds to an increasing need in bear populations' management and can be readily adapted to other large carnivores.
目前对大型食肉动物的管理是依据多种参数、方法和指标进行的；然而，这些数据通常是被独立看待的。基于潜在的生态学原理在不同数据类型间共享信息，并认识到观测偏差，能够改进对个体参数和全局参数的估计。我们提出了一种通用的综合种群模型（IPM），它是专门为棕熊设计的，使用了棕熊种群的三种常见数据类型：重复计数、捕获-标记-重捕和窝仔数。我们考虑了影响这些数据的生态和观测过程的因素。我们在一个模拟种群上评估了这种方法的实用性，并将我们模型的估计值与用于模拟的值以及仅来自计数数据的结果进行了比较。然后，我们给出了这种通用方法的一个实际应用，该应用针对美国阿拉斯加科迪亚克岛棕熊的案例研究的限制条件进行了调整，利用了可获取的历史数据。与仅考虑重复计数数据的模型相比，综合种群模型提供了更准确和精确的估计，其可信区间分别在94%和5%的时间内包含真实种群数量。对于科迪亚克岛的种群，我们估计每年的平均窝仔数（出生后一年内）在0.45 [95%可信区间：0.43；0.55] 到1.59 [1.55；1.82] 之间变化。我们发现鲑鱼可获得量与成年个体存活率之间存在正相关关系，雌性的存活概率高于雄性。存活概率从幼崽到一岁幼熊再到≥2岁的依赖幼熊逐渐增加，并随着窝仔数的增加而降低。基于生态和观测机制链接多个信息源能够提供更准确和精确的估计，以便更好地为管理提供依据。综合种群模型还可以通过在各机构和管理单位之间共享信息来减少数据收集工作。我们的方法回应了棕熊种群管理中日益增长的需求，并且可以很容易地应用于其他大型食肉动物。
