Ecological generalism and physiology mediate fish biogeographic ranges under ocean warming

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning

Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquatic ecosystems. A new ESHIPPOClim model was developed by integrating climate change assessment into the ESHIPPO model. The model identifies spirlin as a potential early indicator of environmental changes, highlighting the interactive effects of climate change and anthropogenic stressors on fish populations and freshwater ecosystems. The ESHIPPOClim model reveals that 28.57 % of the spirlin's data indicates high resilience and ecological responsiveness, with 34.92 % showing medium-high adaptability, suggesting its substantial ability to withstand environmental stressors. With 36.51 % of the data in medium level and no data in the low category, spirlin may serve as a sentinel species, providing early warnings of environmental stressors before they severely impact other species or ecosystems. The results of uniform manifold approximation and projection (UMAP) and a decision tree show that pollution has the highest impact on the population dynamics of spirlin, followed by annual water temperature, overexploitation, and invasive species. Despite the obtained key drivers, higher abundance, dominance, and frequency values were detected in habitats with higher HIPPO stressors and climate change effects. Integrating state-of-the-art machine learning models has enhanced the predictive power of the ESHIPPOClim model, achieving approximately 90 % accuracy in identifying spirlin as an early indicator of climate change and anthropogenic stressors. The ESHIPPOClim model offers a holistic approach with broad practical applications using a simplified three-point scale, adaptable to various fish species, communities, and regions. The ecological modeling supported with advanced machine learning could serve as a foundation for rapid and cost-effective management of aquatic ecosystems, revealing the adaptability potential of fish species, which is crucial in rapidly changing environments.

Warming, stochastic diel thermal fluctuations affect physiological performance and gill plasticity in an amphibious mangrove fish

Natural temperature variation in many marine ecosystems is stochastic and unpredictable, and climate change models indicate that this thermal irregularity is likely to increase. Temperature acclimation may be more challenging when conditions are highly variable and stochastic, and there is a need for empirical physiological data in these thermal environments. Using the hermaphroditic, amphibious mangrove rivulus (Kryptolebias marmoratus), we hypothesized that compared with regular, warming diel thermal fluctuations, stochastic warm fluctuations would negatively affect physiological performance. To test this, we acclimated fish to: (1) non-stochastic and (2) stochastic thermal fluctuations with a similar thermal load (27-35°C), and (3) a stable/consistent control temperature at the low end of the cycle (27°C). We determined that fecundity was reduced in both cycles, with reproduction ceasing in stochastic thermal environments. Fish acclimated to non-stochastic thermal cycles had growth rates lower than those of control fish. Exposure to warm, fluctuating cycles did not affect emersion temperature, and only regular diel cycles modestly increased critical thermal tolerance. We predicted that warm diel cycling temperatures would increase gill surface area. Notably, fish acclimated to either thermal cycle had a reduced gill surface area and increased intralamellar cell mass when compared with control fish. This decreased gill surface area with warming contrasts with what is observed for exclusively aquatic fish and suggests a preparatory gill response for emersion in these amphibious fish. Collectively, our data reveal the importance of considering stochastic thermal variability when studying the effects of temperature on fishes.

Ecological generalism and physiology mediate fish biogeographic ranges under ocean warming

Climate-driven species redistributions are facilitated by niche modifications that increase a species's chances of establishment in novel communities. It is well understood how range-extending species adjust individual niche traits when entering novel environments, yet whether modification of ecological niche traits collectively alters the pace of range extensions or contractions remains unknown. We quantified habitat niche, abundance, physiological performance and cellular defence/damage of range-extending coral reef fishes and coexisting local temperate fishes along a 2000 km latitudinal gradient. We also assessed their dietary and behavioural niches, and establishment potential, to understand whether ecological generalism facilitates successful range extension of coral reef fishes. The coral reef fish that increased all ecological niches, showed stronger establishment, increased physiological performance and cellular damage, but decreased cellular defence at their cold-range edge, whereas tropical species that showed unmodified ecological niches showed lower establishment. One temperate species showed decreased abundance, habitat niche width and body condition, but increased cellular defence, cellular damage and energy reserves at their warm-trailing range, while other temperate species showed contrasting responses. Therefore, ecological generalists might be more successful than ecological specialists during the initial stages of climate change, with increasing future warming strengthening this pattern by physiologically benefitting tropical generalists but disadvantaging temperate specialists.