Information regarding the oceanic environment is crucial for determining species distributions and their habitat preferences. However, in studies on crustaceans, especially swimming crabs, such information remains poorly utilized, and its effects on crab communities in the Taiwan Strait (TS) has not been well documented. The purpose of this study was to understand the relationship between the catch rates of three swimming crab species and environmental factors in the TS. We fitted generalized additive models (GAMs) to logbooks and voyage data recorder data from Taiwanese crab vessels (2011–2015), developed a species distribution model, and predicted catch rates for these three swimming crab species based on the GAM output. The chlorophyll-a (Chl-a) concentration was related to the high catch rates of Chrybdis feriatus and Portunus sanguinolentus, whereas bottom temperature (BT) was related to high catch rates of Portunus pelagicus. The variance percentages for each crab species indicated that high catch rates of C. feriatus and P. sanguinolentus occurred in a Chl-a concentration > 0.5 mg/m3, whereas P. pelagicus catch rates exhibited negative correlations with BTs > 25 °C. The model predicted high catch rates of C. feriatus in the north of the TS during autumn and winter, whereas P. pelagicus was observed to the south during summer and autumn. P. sanguinolentus was predicted to be widely distributed around the TS and distributed further to the northern area during autumn and winter. These findings revealed that each species responds to spatiotemporal environmental variations. Understanding the distributions and habitats of these three crabs is vital in fisheries resource management and conservation planning.
The environmental characteristics of the Taiwan Strait (TS) have been linked to variations in the abundance and distribution of greater amberjack (Seriola dumerili) populations. Greater amberjack is a commercially and ecologically valuable species in ecosystems, and its spatial distribution patterns are pivotal to fisheries management and conservation. However, the relationship between the catch rates of S. dumerili and the environmental changes and their impact on fish communities remains undetermined in the TS. The goal of this study was to determine the spatiotemporal distribution pattern of S. dumerili with environmental characteristics in the TS from south to north (20°N–29°N and 115°E–127°E), applying generalized additive models (GAMs) and spatiotemporal fisheries data from logbooks and voyage data recorders from Taiwanese fishing vessels (2014–2017) as well as satellite-derived remote sensing environmental data. We used the generalized linear model (GLM) and GAM to analyze the effect of environmental factors and catch rates. The predictive performance of the two statistical models was quantitatively assessed by using the root mean square difference. Results reveal that the GAM outperforms the GLM model in terms of the functional relationship of the GAM for generating a reliable predictive tool. The model selection process was based on the significance of model terms, increase in deviance explained, decrease in residual factor, and reduction in Akaike’s information criterion. We then developed a species distribution model based on the best GAMs. The deviance explained indicated that sea surface temperature, linked to high catch rates, was the key factor influencing S. dumerili distributions, whereas mixed layer depth was the least relevant factor. The model predicted a relatively high S. dumerili catch rate in the northwestern region of the TS in summer, with the area extending to the East China Sea. The target species is strongly influenced by biophysical environmental conditions, and potential fishing areas are located throughout the waters of the TS. The findings of this study showed how S. dumerili populations respond to environmental variables and predict species distributions. Data on the habitat preferences and distribution patterns of S. dumerili are essential for understanding the environmental conditions of the TS, which can inform future priorities for conservation planning and management.
How top predators behave and are distributed depend on the conditions in their marine ecosystem through bottom−up forcing; this is because where and when these predators can feed and spawn are limited and change often. This study investigated how the catch rates of immature and mature cohorts of bigeye tuna (BET) varied across space and time; this was achieved by analyzing data on the Taiwanese longline fishery in the western and central Pacific Ocean (WCPO). We also conducted a case study on the time series patterns of BET cohorts to explore the processes that underlie the bottom-up control of the pelagic ecosystem that are influenced by decadal climate events. Wavelet analysis results revealed crucial synchronous shifts in the connection between the pelagic ecosystems at low trophic levels in relation to the immature BET cohort. Many variables exhibited decreasing trends after 2004–2005, and we followed the Pacific Decadal Oscillation (PDO) as a bottom-up control regulator. The results indicated that low recruitment into the mature cohort occurs 3 years after a decrease in the immature cohort’s food stocks, as indicated by a 3-year lag in our results. This finding demonstrated that, by exploring the connection between low-trophic-level species and top predators at various life stages, we can better understand how climate change affects the distribution and abundance of predator fish.
The swimming crabs is a crucial predator species in benthic habitats and a high value in commercial fishery industries in subtropical and tropical Asia. The climate variability caused by El Niño–Southern Oscillation (ENSO) events has substantial impacts on the catch and habitat of this species. In this study, a weighted habitat suitability index (HSI) model was constructed using logbooks and voyage data records from Taiwanese crab vessels (2013–2019) with the addition of environmental variables to examine the influence of ENSO events on catch rates (CRs) and habitat suitability for Charybdis feriatus, Portunus pelagicus, and Portunus sanguinolentus in the Taiwan Strait (TS). The autumn (September–October) is the major fishing season for catching these three swimming crab species in the TS. A high CR of P. sanguinolentus was observed across the TS, whereas high CRs of P. pelagicus and C. feriatus were recorded in areas in the southern and northern TS, respectively, during autumn. Moreover, the CRs for C. feriatus and P. pelagicus were higher (>7.0 and >8.0 kg/h) during La Niña events, with the increase being more than 40.0% compared with the CRs under normal and El Niño events in autumn. For P. sanguinolentus, the CRs were higher during both La Niña and El Niño events (>8.0 kg/h) compared with normal years. The high CRs for C. feriatus and P. sanguinolentus during autumn in La Niña years co-occurred with high sea temperature and low salinity, whereas the high CR of P. pelagicus co-occurred with high sea temperature and high salinity. Furthermore, the high CRs for C. feriatus and P. pelagicus were observed in areas with high HSI in the La Niña years but were distributed more widely with a lower HSI during normal and El Niño years. The low CRs for C. feriatus and P. pelagicus during normal and El Niño years and the low CR for P. sanguinolentus in normal years during autumn were highly consistent with substantial shrinkage of suitable habitats. Our findings suggest that ENSO events strongly affected the catch and habitat suitability of C. feriatus, P. pelagicus, and P. sanguinolentus during autumn in the TS.
This study investigated the relationship of the catch rates (CRs) of Spanish mackerel (Scomberomorus commerson) with oceanographic factors in the waters around Taiwan by using high-resolution fishery and environmental data for the period 2011–2016. The investigation results revealed that trammel nets accounted for 69.79% of the total catch of S. commerson and were operated mostly in the Taiwan Strait (TS). We noted seasonal variations in the distribution of high CRs. These CRs were observed in the southwestern TS, including the waters along the southwestern coast of Taiwan and around the Penghu Islands, and extended to the Taiwan Bank during autumn; they increased in winter. To predict the spatial and temporal patterns of Spanish mackerel density and their relationship with oceanographic and spatiotemporal variables, generalized additive models were used. These models explained 48.4% of the total deviance, which was consistent with the assumed Gaussian distribution. Moreover, all variables examined were significant CR predictors (p < 0.05). Latitude and longitude were the key factors influencing the spatiotemporal distribution of S. commerson, and sea surface chlorophyll a concentration was a key oceanographic factor. Observing projected changes in El Niño/Southern Oscillation events for S. commerson revealed that CRs were higher and distributed further southward during La Niña events than during other events. We inferred that the S. commerson distribution gradually moved toward the southwest with the northeast monsoon, which was enhanced during La Niña in winter.
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