Abstract

The marine coastal ecosystems are being significantly altered under climate change which amplifies the occurrence and severity of ecosystem shifts, endangering the productivity and biodiversity of fisheries as well as the long-term sustainability of the ecosystem. Stock-based fisheries assessment models are not typically well-equipped to predict such sudden shifts as many do not include biological adaptability, ecosystem complexity and early warning. The proposed study suggests an integrative research structure that integrates both fish functional trait analysis and molecular ecology to enhance predictability of climate-induced regime shifts in fisheries in the coastal areas. Major functional characteristics, such as thermal tolerance, trophic position, body size, growth rate, and reproductive strategy, are combined with molecular signals, i.e. genetic diversity, population structure, adaptive potential and community signals based on eDNA. The ecological vulnerability and resilience are also measured using these biological measures in combination with key climate stressors such as sea surface temperature variations, ocean acidification, and hypoxia. The predictive modeling techniques are used to find the non-linear thresholds and early warning signals to regime shifts. Findings have shown that the integrated trait-genomic framework is more sensitive to ecosystem shifts, which is earlier and more reliable than conventional stock-based models, not only in terms of ecological but also evolutionary adaptation to climate stress. The suggested solution offers a transferable and scalable methodology of early warning of shifts in regimes to help manage climate-resilient fisheries and implement ecosystem-based governance. This research has international implications in addressing the challenges of sustaining coastal fisheries in the face of increasing global environmental change where functional ecology is bridged with molecular biology to offer predictive abilities.