Combining high temporal resolution whale distribution and vessel tracking data improves estimates of ship strike risk
Combining high temporal resolution whale distribution and vessel tracking data improves estimates of ship strike risk
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DOI：
10.1016/j.biocon.2020.108757
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发表时间：
2020-10-01
影响因子：
5.9
通讯作者：
Hazen, Elliott L.
中科院分区：
文献类型：
--
作者：
Blondin, Hannah;Abrahms, Briana;Hazen, Elliott L.
在评估有害的人类与野生动物相互作用时，研究人员经常试图计算相互作用发生的风险。然而，这些分析往往基于物种分布和人类活动的时间静态或空间粗糙测量来量化风险。因此，风险估计往往不能反映动物运动和人为利用环境的动态性质。为了说明各种时间分辨率数据的影响，我们结合预测的每日鲸鱼分布和连续的船只运动数据，对美国南加州海域的蓝鲸（Balaenoptera musculus）船只罢工风险进行了案例研究。这是第一次通过包括对东太平洋蓝鲸分布的最新高分辨率估计来描述蓝鲸船只撞击风险的努力。我们使用这些数据来比较不同时间分辨率下的船舶撞击风险模型，以解决使用粗分辨率输入数据的影响。我们的研究结果表明，在评估人类与野生动物冲突的风险时，考虑人类活动的动态模式和物种的发生是至关重要的。基于更高分辨率的潜在相互作用的分析显示风险的变异性更大。较粗的分辨率数据掩盖了蓝鲸栖息地的不均匀条件和/或船只交通的变化可能导致的风险变化。我们还证明，较粗的时间分辨率会导致对风险的高估。对于蓝鲸等受人类与野生动物相互作用影响的高流动性物种，长期的环境解决方案取决于将生态数据与人类活动数据在最适当的规模上进行匹配。
When assessing harmful human-wildlife interactions, researchers often attempt to calculate the risk that an interaction will occur. However, these analyses often quantify risk based on temporally static or spatially coarse measures of species distributions and human activity. As a result, risk estimates often do not reflect the dynamic nature of animal movement and anthropogenic uses of the environment. To illustrate the impacts of various temporal resolutions of data, we present a case study of blue whale (Balaenoptera musculus) ship strike risk in the U.S. Southern California Bight by combining predicted daily whale distributions with continuous vessel movement data. This represents the first effort to characterize blue whale ship strike risk by including the most recent high-resolution estimates of eastern Pacific blue whale distribution. We used these data to compare the ship strike risk models at varying temporal resolutions to address the effect of using coarser resolution input data. Our results show that it is critical to account for both dynamic patterns of human activity and species occurrences when assessing the risk of human-wildlife conflict. Analysis based on higher resolutions of potential interactions show greater variability in risk. Coarser resolution data mask variability in risk that may result from patchy conditions of blue whale habitat and/or variations in vessel traffic. We also demonstrate that coarser temporal resolutions lead to overestimations of risk. For highly mobile species subject to human-wildlife interactions such as blue whales, long-term environmental solutions depend on matching ecological data to human activity data at the most appropriate scale.