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.

Coastal small-scale fishers in the Asia-Pacific region (APR) face mounting challenges from climate change (CC), with vulnerability shaped by ecological exposure, socio-economic dependence, and limited adaptive capacity. This study reflects on two contrasting cases, Taiwan and Papua New Guinea (PNG), to explore fishers’ perceptions and perspectives on CC and practical adaptation strategies. In PNG, 209 respondents from Momase, the Islands, and Southern regions participated. In Taiwan, 45 respondents from the Yunlin and Chiayi coastal regions participated. Significant correlations in coastal communities’ vulnerabilities and perceptions towards CC were revealed. Small-scale fishers perceive rising sea temperatures, shifting fish stocks, and intensifying typhoons as disruptive shocks to livelihoods and eroding traditional fishing practices. In Taiwan, despite relatively stronger infrastructure, household income, and access to technology, adaptation remains constrained by market pressures, declining youth participation, and regulatory complexities. In PNG, fishers deeply rely on natural resources and coastal ecosystems for subsistence and income, yet face acute risks from sea-level rise, coral bleaching, and unpredictable weather. With limited financial resources, weak institutional support, and geographic isolation, fishers perceive CC as an amplifying factor to existing vulnerabilities, leaving communities dependent on traditional knowledge and communal coping strategies. Fishers’ perceptions of CC are shaped by lived experiences rather than scientific discourse, influencing adaptation choices ranging from livelihood diversification to migration. Perceptions of CC drivers, their distal and proximal impacts on coastal fishing community livelihoods are viewed as siloed; yet, remote sensing data revealed that the impacts are transboundary. The findings underscore the urgent need for context-sensitive policies that integrate local knowledge, science-based data (such as remote sensing CC maps) to strengthen institutional support, and enhance resilience among vulnerable and underserved coastal small-scale fishers.