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Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta

机译:利用空间标记捕获技术监测阿尔伯塔省的灰熊种群

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摘要

One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.
机译:保护方面的挑战之一是确定人口密度和分布的模式和对策,因为它与生境和人为活动的变化有关。我们应用了空间显式捕获再捕获(SECR)方法,并结合了加拿大艾伯塔省五个灰熊(Ursus arctos)管理区(BMA)的密度表面建模,以评估SECR方法并探讨影响熊分布的因素。在这里,我们使用灰熊栖息地和死亡风险模型,使用密度表面模型来测试局部密度关联。结果表明BMA特定因素会影响密度,以及栖息地和地形对熊的发现和运动的影响。 SECR的估计值与封闭人口模型和遥测数据的估计值相似,但精度相似或更高。生境与北部熊密度较高的地区最相关,而死亡风险与南部熊密度最大(负)相关。死亡风险和栖息地分布的比较显示,BMA的差异反过来又影响了当地熊的数量。通过直接推断空间因素对调节动物局部密度的影响,将SECR方法与密度表面建模相结合可以提高标记捕获方法的分辨率。

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