Ward Eric J, English Philina A, Rooper Christopher N, Ferriss Bridget E, Whitmire Curt E, Wetzel Chantel R, Barnett Lewis A K, Anderson Sean C, Thorson James T, Johnson Kelli F, Indivero Julia, Markowitz Emily H
Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States.
Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, BC, Canada.
PeerJ. 2025 Sep 3;13:e19964. doi: 10.7717/peerj.19964. eCollection 2025.
Fisheries management faces challenges due to political, spatial, and ecological complexities, which are further exacerbated by variation or shifts in species distributions. Effective management depends on the ability to integrate fisheries data across political and geographic boundaries. However, such efforts may be hindered by inconsistent data formats, limited data sharing, methodological differences in sampling, and regional governance differences. To address these issues, we introduce the R package, which combines and provides public access to bottom trawl survey data collected in the Northeast Pacific Ocean by NOAA Fisheries and Fisheries and Oceans Canada. This initial database integrates over 3.3 million observations from 14 bottom trawl surveys spanning Alaska, British Columbia, Washington, Oregon, and California from the 1980s to present. This database standardizes variables such as catch-per-unit-effort (CPUE), haul data, and measurements of bottom temperature. We demonstrate the utility of this database through three case studies. Our first case study develops a coastwide biomass index for Pacific hake () using geostatistical index standardization, comparing results to independent acoustic survey estimates. The second case study examines spatial patterns in groundfish community structure, highlighting breakpoints between assemblages in their mixture of life histories and trophic compositions. Our third example applies spatially varying coefficient models to assess sablefish () biomass trends, identifying regional variability in increases in occurrence and biomass. Together, these case studies demonstrate how the R package and database may improve species and ecosystem assessments by providing insights into population trends across geopolitical boundaries. This database and package represent an important step toward offering a scalable framework that can be extended to include additional data types, surveys, and species. By fostering collaboration, transparency, and data-driven decision making, supports international efforts to sustainably manage shared marine resources under dynamic environmental conditions.
由于政治、空间和生态的复杂性，渔业管理面临诸多挑战，而物种分布的变化或转移进一步加剧了这些挑战。有效的管理取决于跨越政治和地理边界整合渔业数据的能力。然而，这些努力可能会受到数据格式不一致、数据共享有限、采样方法差异以及区域治理差异的阻碍。为解决这些问题，我们引入了R包，该包整合了美国国家海洋和大气管理局渔业局以及加拿大渔业和海洋部在东北太平洋收集的底拖网调查数据，并提供公开访问。这个初始数据库整合了从20世纪80年代至今在阿拉斯加、不列颠哥伦比亚省、华盛顿州、俄勒冈州和加利福尼亚州进行的14次底拖网调查中的330多万条观测数据。该数据库对单位捕捞努力量（CPUE）、捕捞数据和底层温度测量等变量进行了标准化。我们通过三个案例研究展示了这个数据库的实用性。我们的第一个案例研究使用地理统计指数标准化方法为太平洋无须鳕（）开发了一个全海岸生物量指数，并将结果与独立的声学调查估计值进行比较。第二个案例研究考察了底层鱼类群落结构的空间模式，突出了不同组合在生活史和营养组成混合方面的断点。我们的第三个例子应用空间可变系数模型来评估黑鳕（）的生物量趋势，确定其出现率和生物量增加的区域变异性。这些案例研究共同展示了R包和数据库如何通过提供跨地缘政治边界的种群趋势洞察来改善物种和生态系统评估。这个数据库和包代表了朝着提供一个可扩展框架迈出的重要一步，该框架可扩展以纳入更多数据类型、调查和物种。通过促进合作、透明度和数据驱动的决策制定，支持在动态环境条件下可持续管理共享海洋资源的国际努力。
