Russo Tommaso, Parisi Antonio, Garofalo Germana, Gristina Michele, Cataudella Stefano, Fiorentino Fabio
Laboratory of Experimental Ecology and Aquaculture, Department of Biology, "Tor Vergata" University of Rome, via della Ricerca Scientifica s.n.c., Rome, Italy.
Department of Economics and Finance, Faculty of Economics, "Tor Vergata" University of Rome, Rome, Italy.
PLoS One. 2014 Jan 23;9(1):e86222. doi: 10.1371/journal.pone.0086222. eCollection 2014.
Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species.
渔获量、捕捞努力量和开发模式的管理被认为是控制捕捞死亡率并最终确保渔业生产力和可持续性的最有效措施。尽管人们越来越关注渔业的空间维度,但在评估和管理过程中很少考虑资源在空间上的分布和捕捞努力量。在此,我们提出了SMART(拖网渔业底层资源空间管理),这是一种用于评估不同管理情景下生物经济反馈的工具。SMART整合了欧洲渔业数据收集框架内不同任务收集的信息,由以下部分组成:1)捕捞努力量、环境特征和底层资源分布的空间模型;2)一个人工神经网络,它以空间明确的方式捕捉这些方面之间的关系,并利用它们预测资源丰度;3)一个确定性模块,根据不同的基于空间的管理情景分析渔获量的大小结构和相关收入。SMART应用于西西里海峡的底层渔业,该海峡是地中海最具生产力的渔业之一。三种主要目标物种被用作拖网渔船所开发的整个范围的代表。经过训练后,SMART用于评估不同的管理情景,包括空间封闭,采用模拟近期开发模式的模拟方法。结果表明模型性能良好,不同组成部分的输出具有显著的一致性和可靠性。其中,主要发现是,即使该地区的总体捕捞努力量保持稳定,通过设立幼鱼保护区也可以部分改善资源状况。因此,一系列经过战略设计的拖网禁渔区可以显著改善西西里海峡底层渔业的资源状况,如果不同物种不同时实施禁渔,也能为渔民提供可持续的经济回报。