Fortin Jennifer K, Rode Karyn D, Hilderbrand Grant V, Wilder James, Farley Sean, Jorgensen Carole, Marcot Bruce G
US Geological Survey, Alaska Science Center Anchorage, Alaska, United States of America.
College of Forestry and Conservation, University of Montana, Missoula, MT, United States of America.
PLoS One. 2016 Jan 5;11(1):e0141983. doi: 10.1371/journal.pone.0141983. eCollection 2016.
Increased popularity of recreational activities in natural areas has led to the need to better understand their impacts on wildlife. The majority of research conducted to date has focused on behavioral effects from individual recreations, thus there is a limited understanding of the potential for population-level or cumulative effects. Brown bears (Ursus arctos) are the focus of a growing wildlife viewing industry and are found in habitats frequented by recreationists. Managers face difficult decisions in balancing recreational opportunities with habitat protection for wildlife. Here, we integrate results from empirical studies with expert knowledge to better understand the potential population-level effects of recreational activities on brown bears. We conducted a literature review and Delphi survey of brown bear experts to better understand the frequencies and types of recreations occurring in bear habitats and their potential effects, and to identify management solutions and research needs. We then developed a Bayesian network model that allows managers to estimate the potential effects of recreational management decisions in bear habitats. A higher proportion of individual brown bears in coastal habitats were exposed to recreation, including photography and bear-viewing than bears in interior habitats where camping and hiking were more common. Our results suggest that the primary mechanism by which recreation may impact brown bears is through temporal and spatial displacement with associated increases in energetic costs and declines in nutritional intake. Killings in defense of life and property were found to be minimally associated with recreation in Alaska, but are important considerations in population management. Regulating recreation to occur predictably in space and time and limiting recreation in habitats with concentrated food resources reduces impacts on food intake and may thereby, reduce impacts on reproduction and survival. Our results suggest that decisions managers make about regulating recreational activities in time and space have important consequences for bear populations. The Bayesian network model developed here provides a new tool for managers to balance demands of multiple recreational activities while supporting healthy bear populations.
自然区域内娱乐活动日益普及,这使得人们需要更好地了解其对野生动物的影响。迄今为止开展的大多数研究都集中在个体娱乐活动的行为影响上,因此对于种群水平或累积影响的潜力了解有限。棕熊(Ursus arctos)是日益壮大的野生动物观赏产业的焦点,且在娱乐爱好者常去的栖息地中被发现。管理者在平衡娱乐机会与野生动物栖息地保护方面面临艰难决策。在此,我们将实证研究结果与专家知识相结合,以更好地理解娱乐活动对棕熊潜在的种群水平影响。我们对棕熊专家进行了文献综述和德尔菲调查,以更好地了解熊栖息地中娱乐活动的频率和类型及其潜在影响,并确定管理解决方案和研究需求。然后,我们开发了一个贝叶斯网络模型,使管理者能够估计熊栖息地娱乐管理决策的潜在影响。与内陆栖息地相比,沿海栖息地有更高比例的个体棕熊接触到娱乐活动,包括摄影和观赏熊,而在内陆栖息地露营和徒步旅行更为常见。我们的研究结果表明,娱乐活动可能影响棕熊的主要机制是通过时间和空间上的位移,伴随着能量消耗增加和营养摄入减少。在阿拉斯加,为保护生命和财产而导致的棕熊死亡与娱乐活动的关联极小,但在种群管理中是重要的考虑因素。规范娱乐活动在空间和时间上可预测地进行,并限制在食物资源集中的栖息地进行娱乐活动,可减少对食物摄入的影响,从而可能减少对繁殖和生存的影响。我们的研究结果表明,管理者在时间和空间上对娱乐活动进行监管的决策对熊种群具有重要影响。这里开发的贝叶斯网络模型为管理者提供了一种新工具,可在支持健康熊种群的同时平衡多种娱乐活动的需求。