Scholarly record
NON-PARAMETRIC ASSESSMENT OF LONG-TERM TRENDS IN MUGILIDAE LANDINGS ALONG THE BULGARIAN BLACK SEA COAST (2006 - 2025)
Abstract
Long-term changes in fishery landings are important indicators of stock status and ecosystem condition, particularly in semi-enclosed and data-limited marine systems such as the Black Sea. These trends are also relevant to the broader international debate on sustainable fisheries management, as they can provide early warning of persistent declines where full analytical stock assessments are limited. This study assesses temporal trends in the annual landings of three Mugilidae species (Mugil cephalus, Chelon auratus and Chelon saliens), along the Bulgarian Black Sea coast during 2006–2025, using officially reported fisheries statistics. The aim was to determine the direction, consistency and magnitude of long-term changes and to evaluate the applicability of non-parametric trend analyses for coastal fisheries monitoring. Spearman’s rank correlation, the Mann–Kendall trend test and Sen’s slope estimator were applied because they are robust to non-normal distributions, interannual variability and outliers. All three species showed consistent negative trends. Spearman coefficients were -0.732 for M. cephalus, -0.541 for Ch. auratus and -0.604 for Ch. saliens, while Sen’s slope estimates indicated average annual declines of -0.622 tonnes per year, -0.069 tonnes per year and -0.451 tonnes per year, respectively. The largest decrease was observed in M. cephalus. These patterns are consistent with declines reported for mullet fisheries in other coastal regions, including Mediterranean lagoon systems, and likely reflect the combined effects of fishing pressure and environmental stressors such as eutrophication, hypoxia and climate-driven ecosystem change. The observed declines have direct implications for fisheries management and policy in the Black Sea region, supporting the need for improved species-specific monitoring, precautionary management and reassessment of exploitation levels. The results also demonstrate that non-parametric analyses provide a practical and transferable approach for detecting long-term change in exploited coastal fish populations and for supporting adaptive management in data-limited fisheries.
Publication details
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