• Energy Research

Abstract Ecological resilience has become a conceptual cornerstone bridging ecological processes to conservation needs. Global change is increasingly associated with local changes in environmental conditions that can cause abrupt ecosystem reorganizations attending to system‐specific resilience fluctuations with time (i.e. resilience dynamics). Here we assess resilience dynamics associated with climate‐driven ecosystems transitions, expressed as changes in the relevant contribution of species with different life‐history strategies, in two benthopelagic systems. We analysed data from 1994 to 2019 coming from a scientific bottom trawl survey in two environmentally contrasting ecosystems in the Western Mediterranean Sea—Northern Spain and Alboran Sea. Benthopelagic species were categorized according to their life‐history strategies (opportunistic, periodic and equilibrium), ecosystem functions and habitats. We implemented an Integrated Resilience Assessment (IRA) to elucidate the response mechanism of the studied ecosystems to several candidate environmental stressors and quantify the ecosystems’ resilience. We demonstrate that both ecosystems responded discontinuously to changes in chlorophyll‐a concentration more than any other stressor. The response in Northern Spain indicated a more overarching regime shift than in the Alboran Sea. Opportunistic fish were unfavoured in both ecosystems in the recent periods, while invertebrate species of short life cycle were generally favoured, particularly benthic species in the Alboran Sea. The study illustrates that the resilience dynamics of the two ecosystems were mostly associated with fluctuating productivity, but subtle and long‐term effects from sea warming and fishing reduction were also discernible. Such dynamics are typical of systems with wide environmental gradient such as the Northern Spain, as well as systems with highly hydrodynamic and of biogeographical complexity such as the Alboran Sea. We stress that management should become more adaptive by utilizing the knowledge on the systems’ productivity thresholds and underlying shifts to help anticipate both short‐term/less predictable events and long‐term/expected effects of climate change.