Environmental and Biological Variability Across Spring Trawl Surveys in the Yun–Chang Rise, Taiwan Strait

This study examined environmental and biological variability across three spring trawl surveys conducted at seven fixed stations in the Yun–Chang Rise (YCR), Taiwan Strait, in May 2019, April 2020, and May 2021. Catch per unit effort (CPUE), taxon richness, biodiversity indices, assemblage composition, and major taxon-specific responses were compared among survey periods, accounting for repeated sampling at fixed stations. Environmental variability was characterized using near-bottom temperature and salinity, surface current velocity, and satellite-derived surface chlorophyll-a concentration. No significant differences among survey periods were detected in CPUE, taxon richness, or biodiversity indices. Similarly, PERMANOVA based on 12 observations from four stations with non-zero catches in all three surveys did not detect a significant survey-period effect on assemblage composition (pseudo-F = 1.35, R2 = 0.231, p = 0.22). The nMDS ordination showed substantial overlap among survey periods, while SIMPER revealed high average between-survey dissimilarities. However, none of the five leading SIMPER contributors exhibited significant differences in abundance or species-specific CPUE. In contrast, multivariate environmental conditions differed significantly among survey periods after accounting for repeated sampling at fixed stations (pseudo-F = 4.689, R2 = 0.510, p = 0.010). The station-restricted canonical correspondence analysis (CCA) did not detect a significant overall relationship between the selected-taxon assemblage and the measured environmental variables (pseudo-F = 0.9, p = 0.304; adjusted explained variation = 0%). These findings indicate that statistically detectable environmental differences among spring surveys were not accompanied by a consistent, statistically detectable survey-period effect on assemblage composition or aggregate community metrics within the analyzed stations. Integrating environmental, assemblage-level, and taxon-specific assessments is therefore important for interpreting ecological variability while recognizing the spatial and temporal limitations of the sampling design.