New historical data for long-term swordfish ecological studies in the Mediterranean Sea

Abstract

Abstract. Management of marine fisheries and ecosystems is constrained by knowledge based on datasets with limited temporal coverage. Many populations and ecosystems were perturbed long before scientific investigations began. This situation is particularly acute for the largest and commercially most valuable species. We hypothesized that historical trap fishery records for bluefin tuna (Thunnus thynnus Linnaeus, 1758) could contain catch data and information for other, bycatch species, such as swordfish (Xiphias gladius Linnaeus, 1758). This species has a long history of exploitation and is presently overexploited, yet indicators of its status (biomass) used in fishery management only start in 1950. Here we examine historical fishery records and logbooks from some of these traps and recovered ca. 110 years of bycatch data (1896–2010). These previously neglected, but now recovered, data include catch dates and amounts in numbers and/or weights (including individual weights) for the time period before and after major expansion of swordfish fisheries in the Mediterranean Sea. New historical datasets such as these could help understand how human activities and natural variability interact to affect the long-term dynamics of this species. The datasets are online and available with open access via three DOIs, as described in the “Data availability” section of the article.

Top predator status and trends: ecological implications, monitoring and mitigation strategies to promote ecosystem-based management

“…Population models are frequently used in stock assessments to inform Regional Fisheries Management Organizations, such as the International Commission for the Conservation of Atlantic Tunas (ICCAT), the International Council for the Exploration of the Sea (ICES), and the General Fisheries Commission for the Mediterranean (GFCM). The age-structured stochastic modeling approach, used to assess Atlantic bluefin tuna dynamics and to predict the future development of fish populations (over 10-20 years) under different fishing mortality and population biology scenarios (e.g., growth rates, maturity schedules, reproduction rate; MacKenzie et al, 2009MacKenzie et al, , 2021, informed the recovery plan for this species. Population models integrate empirically derived estimates of the uncertainty of input variables to estimate probabilistic outputs of population variables (e.g., biomasses) and information on biological and fishing mortality rates from assessments.…”