Planning precision aquaculture activities in a changing and crowded sea

Extreme climate events are increasingly challenging the growth of the marine aquaculture sector, causing local influences on species performance and affecting production and yield - impacting where to locate cage aquaculture facilities. Here we produced scenario-based quantitative maps using modelled species-specific performance combined with predicted high-resolution future IPCC temperature scenarios. We ran a species-specific Dynamic Energy Budget mechanistic model for four model species, up to 2050, and mapped functional trait-based outcomes as: i) time to reach the commercial size, ii) feces produced and iii) uneaten food. A high spatial resolution suitability index allowed the sustainability of farming strategies for single- and multi-species to be identified across a 159.696 km2 surface extension (Italian Exclusive Economic Zone; 6% of the Mediterranean basin surface). Providing a good case study to shed light on difficult questions facing aquaculture planning around the world. Good future performance under both representative concentration pathway (RCP) scenarios were modelled for Sea bream and European seabass in inshore waters. Performance of Mediterranean mussels and Japanese oysters was found to decrease slightly when compared to the 2007–2010 time interval. Scenario-based quantitative maps represent a heterogeneous species-specific knowledge layer that is critical to better inform aquaculture management and development strategies. Yet this knowledge layer is missing from the process to develop climate-resilient risk maps and associated adaptation measures, as well as when informing stakeholders on potential site expansion and/or the establishment of nascent aquaculture industry sites

Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept

Realistic predictions of climate change effects on natural resources are central to adaptation policies that try to reduce these impacts. However, most current forecasting approaches do not incorporate species-specific, process-based biological information, which limits their ability to inform actionable strategies. Mechanistic approaches, incorporating quantitative information on functional traits, can potentially predict species- and population-specific responses that result from the cumulative impacts of small-scale processes acting at the organismal level, and can be used to infer population-level dynamics and inform natural resources management. Here we present a proof-of-concept study using the European anchovy as a model species that shows how a trait-based, mechanistic species distribution model can be used to explore the vulnerability of marine species to environmental changes, producing quantitative outputs useful for informing fisheries management. We crossed scenarios of temperature and food to generate quantitative maps of selected mechanistic model outcomes (e.g., Maximum Length and Total Reproductive Output). These results highlight changing patterns of source and sink spawning areas as well as the incidence of reproductive failure. This study demonstrates that model predictions based on functional traits can reduce the degree of uncertainty when forecasting future trends of fish stocks. However, to be effective they must be based on high spatial- and temporal resolution environmental data. Such a sensitive and spatially explicit predictive approach may be used to inform more effective adaptive management strategies of resources in novel climatic conditions