Critically examining the knowledge base required to mechanistically project climate impacts: A case study of Europe's fish and shellfish

An amalgam of empirical data from laboratory and field studies is needed to build robust, theoretical models of climate impacts that can provide science-based advice for sustainable management of fish and shellfish resources. Using a semi-systematic literature review, Gap Analysis and multilevel meta-analysis,we assessed the status of empirical knowledge on the direct effects of climate change on 37 high-value species targeted by European fisheries and aquaculture sectors operating in marine and freshwater regions. Knowledge on potential climate change-related drivers (single or combined) on several responses (vital rates) across four categories (exploitation sector, region, life stage, species), was considerably unbalanced as well as biased, including a low number of studies (a) examining the interaction of abiotic factors, (b) offering opportunities to assess local adaptation, (c) targeting lower-value species. The meta-analysisrevealed that projected warming would increase mean growth rates in fishand mollusks and significantly elevate metabolic rates in fish. Decreased levels ofdissolved oxygen depressed rates of growth and metabolism across coherent species groups (e.g., small pelagics, etc.) while expected declines in pH reduced growth in most species groups and increased mortality in bivalves. The meta-analytical results were influenced by the study design and moderators (e.g., life stage, season). Although meta-analytic tools have become increasingly popular, when performed on the limited available data, these analyses cannot grasp relevant population effects, even in species with a long history of study. We recommend actions to overcome these shortcomings and improve mechanistic (cause-and-effect) projections of climate impacts on fish and shellfish