Marine fisheries represent a social-ecological system driven by both complex ecological processes and human interactions. Ecosystem-based fisheries management requires an understanding of both the biological and social components, and management failure can occur when either are excluded. Despite the significance of both, most research has focused on characterizing biological uncertainty rather than on better understanding the impacts of human behavior because of the difficulty of incorporating human behavior into simulation models. In this study, we use the fisheries in Narragansett Bay (Rhode Island, USA) as a case study to demonstrate how coupled modeling can be used to represent interactions between the food web and fishers in a social-ecological system. Narragansett Bay holds both a commercial fishery for forage fish, i.e., Atlantic menhaden (Brevoortia tyrannus) and a recreational fishery for their predators, i.e. striped bass (Morone saxatilis) and bluefish (Pomatomus saltatrix). To explore trade-offs between these two fisheries, we created a food web model and then coupled it to a recreational fishers’ behavior model, creating a dynamic social-ecological representation of the ecosystem. Fish biomass was projected until 2030 in both the stand-alone food web model and the coupled social-ecological model, with results highlighting how the incorporation of fisher behavior in modeling can lead to changes in the ecosystem. We examined how model outputs varied in response to three attributes: (1) the forage fish commercial harvest scenario, (2) the predatory (piscivorous) fish abundance-catch relationship in the recreational fishery, and (3) the rate at which recreational fishers become discouraged (termed “satisfaction loss”). Higher commercial harvest of forage fish led to lower piscivorous fish biomass but had minimal effects on the number of piscivorous fish caught recreationally or recreational fisher satisfaction. Both the abundance-catch relationship and satisfaction loss rate had notable effects on the fish biomass, the number of fish caught recreationally, and recreational fisher satisfaction. Currently, the lack of spatial and location-specific fisher behavior data limits the predictive use of our model. However, our modeling framework shows that fisher behavior can be successfully incorporated into a coupled social-ecological model through the use of agent-based modeling, and our results highlight that its inclusion can influence ecosystem dynamics. Because fisher decision making and the ecosystem can influence one another, social responses to changing ecosystems should be explicitly integrated into ecosystem modeling to improve ecosystem-based fisheries management efforts.

中文翻译：

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使用耦合食物网和人类行为模型探索渔业中的社会生态权衡

海洋渔业代表了一个由复杂生态过程和人类相互作用驱动的社会生态系统。基于生态系统的渔业管理需要了解生物和社会组成部分，如果将​​其中任何一个排除在外，就会导致管理失败。尽管两者都很重要，但大多数研究都集中在表征生物不确定性上，而不是更好地理解人类行为的影响，因为将人类行为纳入模拟模型很困难。在本研究中，我们以纳拉甘西特湾（美国罗德岛州）的渔业为例，展示如何使用耦合建模来表示社会生态系统中食物网与渔民之间的相互作用。纳拉甘西特湾拥有饲料鱼的商业渔业，即，大西洋鲱鱼 (Brevoortia tyrannus) 及其捕食者的休闲渔业，即条纹鲈鱼 (Morone saxatilis) 和蓝鱼 (Pomatomus saltatrix)。为了探索这两种渔业之间的权衡，我们创建了一个食物网模型，然后将其与休闲渔民的行为模型相结合，创建了生态系统的动态社会生态表征。在独立的食物网模型和耦合的社会-生态模型中，鱼类生物量预计到 2030 年，结果强调了将渔民行为纳入建模如何导致生态系统发生变化。我们研究了模型输出如何响应三个属性而变化：（1）饲料鱼商业捕捞场景，（2）休闲渔业中的掠食性（鱼食性）鱼类丰度 - 捕获量关系，(3) 休闲渔民变得灰心的比率（称为“满意度损失”）。较高的饲料鱼商业收获导致较低的食鱼鱼生物量，但对休闲捕获的食鱼鱼数量或休闲渔民满意度的影响很小。丰度-渔获量关系和满意度损失率对鱼类生物量、休闲捕捞数量和休闲渔民满意度都有显着影响。目前，缺乏空间和位置特定的渔民行为数据限制了我们模型的预测使用。然而，我们的建模框架表明，通过使用基于代理的建模，可以将渔民行为成功地纳入耦合的社会-生态模型中，我们的结果强调其包含可以影响生态系统动态。