Climate & Environmentarticle2026-08-26

Species-resolved baselines reveal limited diagnostic resolution of aggregate river-fish indicators: evidence from a 16-year lower Yangtze survey

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Abstract

Aggregate catch and biomass are widely used to evaluate river restoration and fishery closures, but their management value depends on whether they resolve changes in the species of concern. We evaluated this diagnostic resolution using a 16-year fixed-station survey (2002–2017; 519 valid surveys) of 28 migratory and estuarine-associated fishes at a lower Yangtze nearshore habitat. Annual abundance and biomass catch per unit effort (CPUE) were compared with species trends, dominance, effort-standardised turnover and dynamic factor analysis (DFA). A common annual rank-based rule found no directional aggregate-abundance trend. A month-adjusted survey-level model estimated +5.7% yr −1 , but support weakened under CR2/Satterthwaite correction for 16 clusters defined by year ( p = 0.062). The 2002–2004 to 2015–2017 abundance contrast was +132% for all species but only +2.3% after removing the three most abundant species; an equal-weight index of the same 15 adequately detected species increased. The annual species rule identified four increases and one decline, although temporal checks weakened three increases. Survey-level CR2 inference corroborated all five directions and retained one additional upward signal after BH correction. Thirteen species were detection-limited. Top-three dominance was 86.6% for abundance and 72.6% for biomass. A one-axis DFA remained strongly concordant after excluding detection-limited taxa, and all 16 one-axis leave-one-year-out refits converged. Aggregate CPUE is therefore a repeatable descriptor of gear-indexed use of one habitat, but inference at both aggregate and species levels remained model-dependent. Pairing a common classification rule with species-resolved and model-sensitivity evidence provides a more defensible pre-moratorium baseline.

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View paper (DOI)Open access versionOpenAlexEcological IndicatorsPublished 2026-08-26

Authors: hongyi Guo, Zhang Ya, Wenqiao Tang, Kai Liu

Institutions: Shanghai Ocean University, Ministry of Agriculture and Rural Affairs, Chinese Academy of Fishery Sciences, Freshwater Fisheries Research Center