Seasonal resilience of temperate estuarine fish in response to climate change

Abstract

To date, the intricacies and efficacy of how periodic seasonal environmental fluctuations affect fish populations in biogeography in the context of profound climate change remain to be elucidated. Collected monitoring data on fish resources in the temperate estuary provide an excellent opportunity to assess the effects of seasonal environmental fluctuations on populations and functional assemblages under climate change. We first developed a framework for predicting habitat suitability under different climate change scenarios (SSP1-2.6 and SSP5-8.5) for 12 fish populations in the Yangtze estuary by examining the seasonal environmental affinities of temperate estuarine fishes. We then summarized the multidimensional habitat suitability responses (HSRs) of populations and functional assemblages and discussed the possible drivers and mechanisms underlying these changes. The results suggest that the acidity of the Yangtze estuary may decline in the future as the climate warms, endangering the ecosystem that many fish species depend on. Prospective climate change may have an impact on fish population HSRs through redistribution, area changes, and centroid migration of suitable habitats; nevertheless, affinity for environmental factors may be limited to distinguishing patterns of population response in the spring. Fish (5 populations) and functional assemblages (11 assemblages) may exhibit robust adaptations or non-adaptations to climate change when seasons change, given their suitable habitat area. Furthermore, projections indicate that the majority of fish habitat centroids exhibit seasonal responses, migrating northeast in the spring and southeast in the autumn. By decentralizing climate risk to seasonal scales, seasonal resilience in the multidimensional HSRs of several fish populations (5/12) and their functional assemblages (11/16) is revealed for the first time. Efforts to mitigate climate risks and safeguard resources should take these seasonal forecasts and indicative information into account.