The present study provides the length-weight relationships (LWRs) for 10 marine fish species collected from the coastal waters of the East China Sea by bottom trawl surveys. The open width of the sampling net was 40 m and the mesh size of the codend was 20 mm. Specimens were collected from November 2015 to November 2019 at seasonal intervals. The measurement accuracy of weight and length were 0.1 grams and 0.1 centimeters, respectively. This study provides new information of LWRs for nine species which have not yet been reported in FishBase. Also, this study updates the information of maximum length for two species.
It is important in fisheries management to evaluate the effects of environmental factors on changes in the abundance of species, particularly those inhabiting estuaries. The Yangtze River estuary is the largest in the western Pacific Ocean and serves as a spawning, feeding and nursery ground to species of economic and ecological importance, such as Collichthys lucidus and Lophiogobius ocellicauda. By using 3 years of environmental variables and data on the abundance of C. lucidus and L. ocellicauda gathered seasonally through trawl surveys, we compared four generalised additive models (GAMs), each comprising different spline terms, to analyse the influence of the measured variables on the abundance of both species. Deviance explained, Akaike information criterion and generalised cross-validation were used to select the optimal GAM after evaluating the fit and predictive performance of the models. Generalised additive model (GAM) with spline ‘te’ was the optimal model, and predicted that the abundance of both species was influenced by season and by variables temperature, salinity and chlorophyll-a concentration. For C. lucidus, abundance increased during spring and summer, and, for L. ocellicauda, it was higher during winter. Given the socioeconomic importance of both species, we contend that determining the drivers causing abundance fluctuations of estuarine species can support the putting in place of robust monitoring and assessment plans for such fisheries.
An estuary region is a complex environment with a transition from fresh to brackish to salt water, and in which some environmental factors change dramatically over small ranges. Therefore, it is important to understand the impact of the selection of spatial scale on the prediction of the distribution of estuarine species. As the largest estuary in China, the Changjiang River estuary is the spawning ground, feeding ground, and migration channel for many species. Based on Coilia nasus, an important economic fish species in the Changjiang River estuary, this study uses the two-stage generalized additive model (GAM) to investigate the potential differences in the response of species’ spatial distribution when environmental factors are assessed at different spatial scales (1′ × 1′, 2′ × 2′, 3′ × 3′, 4′ × 4′, 5′ × 5′). The results showed the following: (1) according to the analysis of the variance inflation factor (VIF), the values of all environmental factors were less than three and we found no correlation among the environmental variables selected. (2) The first stage GAM retained six variables, including year, month, latitude (Lat), water depth (Depth, m), bottom salinity (Sal, mg/L), and chemical oxygen demand (COD, mg/L). The second stage GAM retained four variables, including Year, Lat, pH, and chlorophyll a (Chl-a, μg/L). (3) The mean value of the Chla for the 3′ × 3′ spatial scale was significantly lower than that of the other spatial scales, and the mean value of Sal for the 5′ × 5′ spatial scale was higher than that of the other spatial scales. (4) In terms of the spatial distribution of abundance, the distribution patterns of C. nasus predicted by all scales were not very similar, and the distribution patterns predicted by the 5′ × 5′ scale, in the autumn of 2012, were significantly different from those at other scales. Therefore, the selection of spatiotemporal scales may affect predictions of the spatial distributions of species. We suggest that potential spatiotemporal scale effects should be evaluated in future studies.
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