USDA-WS-National Wildlife Research Center, Fort Collins, Colorado, United States.
Center for Human-Carnivore Coexistence, Colorado State University, Fort Collins, Colorado, United States.
PeerJ. 2023 Jun 1;11:e15491. doi: 10.7717/peerj.15491. eCollection 2023.
Agricultural and pastoral landscapes can provide important habitat for wildlife conservation, but sharing these landscapes with wildlife can create conflict that is costly and requires managing. Livestock predation is a good example of the challenges involving coexistence with wildlife across shared landscapes. Integrating new technology into agricultural practices could help minimize human-wildlife conflict. In this study, we used concepts from the fields of robotics (., automated movement and adaptiveness) and agricultural practices (., managing livestock risk to predation) to explore how integration of these concepts could aid the development of more effective predator deterrents.
We used a colony of captive coyotes as a model system, and simulated predation events with meat baits inside and outside of protected zones. Inside the protected zones we used a remote-controlled vehicle with a state-of-the art, commercially available predator deterrent (., Foxlight) mounted on the top and used this to test three treatments: (1) light only (., without movement or adaptiveness), (2) predetermined movement (., with movement and without adaptiveness), and (3) adaptive movement (., with both movement and adaptiveness). We measured the time it took for coyotes to eat the baits and analyzed the data with a time-to-event survival strategy.
Survival of baits was consistently higher inside the protected zone, and the three movement treatments incrementally increased survival time over baseline except for the light only treatment in the nonprotected zone. Incorporating predetermined movement essentially doubled the efficacy of the light only treatment both inside and outside the protected zone. Incorporating adaptive movement exponentially increased survival time both inside and outside the protected zone. Our findings provide compelling evidence that incorporating existing robotics capabilities (predetermined and adaptive movement) could greatly enhance protection of agricultural resources and aid in the development of nonlethal tools for managing wildlife. Our findings also demonstrate the importance of marrying agricultural practices (., spatial management of livestock at night) with new technology to improve the efficacy of wildlife deterrents.
农业和畜牧业景观可为野生动物保护提供重要的栖息地,但与野生动物共享这些景观会产生代价高昂的冲突,需要加以管理。牲畜被捕食是涉及共享景观中与野生动物共存的挑战的一个很好的例子。将新技术整合到农业实践中可以帮助最大限度地减少人与野生动物的冲突。在这项研究中,我们将机器人技术(例如自动运动和适应性)和农业实践(例如管理牲畜免受捕食的风险)领域的概念结合起来,探索这些概念的整合如何有助于开发更有效的捕食者威慑手段。
我们使用圈养的郊狼群体作为模型系统,在保护区内外使用肉诱饵模拟捕食事件。在保护区内,我们使用了一辆配备最先进的商业可用捕食者威慑器(即 Foxlight)的遥控车,将其安装在顶部,并使用该车辆进行了三种处理:(1)仅灯光(即无运动或适应性),(2)预定运动(即有运动但无适应性),(3)自适应运动(即既有运动又有适应性)。我们测量了郊狼吃掉诱饵所需的时间,并使用时间事件生存策略分析了数据。
诱饵在保护区内的存活率始终较高,三种运动处理方法除非保护区内的仅灯光处理外,均逐渐延长了生存时间。预定运动的结合基本上使仅灯光处理的效果在保护区内外都增加了一倍。自适应运动的结合使保护区内外的生存时间呈指数级增加。我们的研究结果提供了令人信服的证据,表明整合现有的机器人技术能力(预定运动和自适应运动)可以极大地增强对农业资源的保护,并有助于开发用于管理野生动物的非致命工具。我们的研究结果还表明,将农业实践(例如夜间对牲畜的空间管理)与新技术相结合对于提高野生动物威慑手段的效果非常重要。