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Most tropical small-scale fishing communities, like those of Zanzibar (Tanzania), strongly depend on fisheries resources for income and protein supply. Although imperative, the evaluation of fisheries performance indicators for adequate management is often challenging given the data-poor nature of most of these fisheries. This study reviews the current literature and integrates findings from annual fisheries statistics, the perceptions of fishers, and ecological surveys to provide a holistic understanding of the fisheries exploitation level in Zanzibar. Most reviewed studies focused on the perception of fishers and ecological surveys, and only a few conducted any form of fisheries assessment. While the perception of fishers suggests resource overexploitation, officially reported catch data rather suggest a state around full exploitation for most resources. Ecological surveys indicate overexploitation of several target fish stocks for the west coast of Unguja Island. This study indicates that the perception of fishers and aggregated catch statistics should not be used as the only source of information when assessing data-poor, multispecies fisheries. Furthermore, indicators from ecological surveys should be compared to reference points and related to fishing effort to inform fisheries managers better. The here used approach highlights that integrating local knowledge, fisheries-dependent and independent information helps to identify areas and taxonomic groups of highest concern and guides future research efforts toward contributing better information for the management of data-poor fisheries. [ABSTRACT FROM AUTHOR]

Knowledge of larval dispersal and connectivity in coral reef species is crucial for understanding population dynamics, resilience, and evolution of species. Here, we use ten microsatellites and one mitochondrial marker (cytochrome b) to investigate the genetic population structure, genetic diversity, and historical demography of the powder-blue tang Acanthurus leucosternon across more than 1000 km of the scarcely studied Eastern African region. The global AMOVA results based on microsatellites reveal a low but significant F value ( F = 0.00252 P < 0.001; D = 0.025 P = 0.0018) for the 336 specimens sampled at ten sample sites, while no significant differentiation could be found in the mitochondrial cytochrome b dataset. On the other hand, pairwise F , PCOA, and hierarchical analysis failed to identify any genetic breaks among the Eastern African populations, supporting the hypothesis of genetic homogeneity. The observed genetic homogeneity among Eastern African sample sites can be explained by the lengthy post-larval stage of A. leucosternon, which can potentiate long-distance dispersal. Tests of neutrality and mismatch distribution signal a population expansion during the mid-Pleistocene period. [ABSTRACT FROM AUTHOR]

Global climate change affects marine fish through drivers such as ocean warming, acidification and oxygen depletion, causing changes in marine ecosystems and socioeconomic impacts. While experimental and observational results can inform about anticipated effects of different drivers, linking between these results and ecosystem-level changes requires quantitative integration of physiological and ecological processes into models to advance research and inform management. We give an overview of important physiological and ecological processes affected by environmental drivers. We then provide a review of available modelling approaches for marine fish, analysing their capacities for process-based integration of environmental drivers. Building on this, we propose approaches to advance important research questions. Examples of integration of environmental drivers exist for each model class. Recent extensions of modelling frameworks increase the potential for including detailed mechanisms and improving model projections. Experimental results on energy allocation, behaviour and physiological limitations will advance the understanding of organism-level trade-offs and thresholds in response to multiple drivers. More explicit representation of life cycles and biological traits can improve description of population dynamics and adaptation, and data on food web topology and feeding interactions help to detail the conditions for possible regime shifts. Identification of relevant processes will also benefit the coupling of different models to investigate spatial-temporal changes in stock productivity and integrated responses of social-ecological systems. Thus, a more process-informed foundation for models will promote the integration of experimental and observational results and increase the potential for model-based extrapolations into a future under changing environmental conditions. [ABSTRACT FROM AUTHOR]