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The influence of population growth and weather on the value of recreational angling trips within Utah (USA)
Fisheries Research ( IF 2.4 ) Pub Date : 2024-02-29 , DOI: 10.1016/j.fishres.2024.106976
Jordan W. Smith , Chase C. Lamborn

The decisions anglers make regarding where to fish involve trade-offs amongst the qualities of fishing sites. The types of sites available (e.g., streams, rivers, lakes, etc.), the costs associated with visiting potential sites, and other factors are all weighed in anglers’ site choice decisions. Economic models capable of quantifying the utility anglers derive from different site characteristics can inform policy and management decisions affecting those characteristics; they can also be used to evaluate the effects of demographic and environmental change on fishing. This research demonstrates one such model—a random utility travel cost model of Utah anglers’ site choice decisions—constructed with data on nearly 3,000 fishing trips made during 2021 and 2022 as well as geospatial data characterizing fishing opportunities within the state. The model suggests the site choice decisions of anglers in Utah are driven, in part, by the size of human populations surrounding fishing locations as well as the weather on the day of the trip. Knowing the human population and climate will change in the years ahead, managers can anticipate the likely impact these forces will have on the well-being derived from fishing. We pair the results of our model with projections of population growth and changes in climate-dependent characteristics of fishing sites to quantify potential losses to angler welfare over the next several decades. Fisheries and land managers can make strategic policy decisions to mitigate these losses and ultimately support the sustainability of fish, fish habitat, and fishing experiences.

中文翻译:

人口增长和天气对犹他州(美国)休闲钓鱼旅行价值的影响

垂钓者做出的关于在哪里钓鱼的决定涉及到钓鱼地点质量的权衡。可用地点的类型(例如溪流、河流、湖泊等)、与访问潜在地点相关的成本以及其他因素都在钓鱼者的地点选择决策中进行权衡。能够量化钓鱼者从不同地点特征中获得的效用的经济模型可以为影响这些特征的政策和管理决策提供信息;它们还可用于评估人口和环境变化对渔业的影响。这项研究展示了这样一个模型,即犹他州钓鱼者地点选择决策的随机实用旅行成本模型,该模型是根据 2021 年和 2022 年近 3,000 次钓鱼旅行的数据以及描述该州钓鱼机会的地理空间数据构建的。该模型表明,犹他州钓鱼者的地点选择决定部分取决于钓鱼地点周围的人口规模以及旅行当天的天气。了解人口和气候在未来几年将发生变化,管理人员可以预测这些力量对渔业福祉可能产生的影响。我们将模型的结果与人口增长的预测和捕鱼地点气候依赖性特征的变化相结合,以量化未来几十年钓鱼者福利的潜在损失。渔业和土地管理者可以制定战略政策决策,以减轻这些损失,并最终支持鱼类、鱼类栖息地和捕捞体验的可持续性。
更新日期:2024-02-29
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