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The Health Impacts of Artificial Reef Advancement (HIARA; in the Malagasy language, “together”) study cohort was set up in December 2022 to assess the economic and nutritional importance of seafood for the coastal Malagasy population living along the Bay of Ranobe in southwestern Madagascar. Over the course of the research, which will continue until at least 2026, the primary question we seek to answer is whether the creation of artificial coral reefs can rehabilitate fish biomass, increase fish catch, and positively influence fisher livelihoods, community nutrition, and mental health. Through prospective, longitudinal monitoring of the ecological and social systems of Bay of Ranobe, we aim to understand the influence of seasonal and long-term shifts in marine ecological resources and their benefits to human livelihoods and health. Fourteen communities (12 coastal and two inland) were enrolled into the study including 450 households across both the coastal (n = 360 households) and inland (n = 90 households) ecosystems. In the ecological component, we quantify the extent and health of coral reef ecosystems and collect data on the diversity and abundance of fisheries resources. In the social component, we collect data on the diets, resource acquisition strategies, fisheries and agricultural practices, and other social, demographic and economic indicators, repeated every 3 months. At these visits, clinical measures are collected including anthropometric measures, blood pressure, and mental health diagnostic screening. By analyzing changes in fish catch and consumption arising from varying distances to artificial reef construction and associated impacts on fish biomass, our cohort study could provide valuable insights into the public health impacts of artificial coral reef construction on local populations. Specifically, we aim to assess the impact of changes in fish catch (caused by artificial reefs) on various health outcomes, such as stunting, underweight, wasting, nutrient intake, hypertension, anxiety, and depression. 

Abstract Relationships between body shape and escape performance are well established for many species. However, organisms can face multiple selection pressures that might impose competing demands. Many fishes use fast starts for escaping predator attacks, whereas some species of gobiid fishes have evolved the ability to climb waterfalls out of predator-dense habitats. The ancestral ‘powerburst’ climbing mechanism uses lateral body undulations to move up waterfalls, whereas a derived ‘inching’ mechanism uses rectilinear locomotion. We examined whether fast-start performance is impacted by selection imposed from the new functional demands of climbing. We predicted that non-climbing species would show morphology and fast-start performance that facilitate predator evasion, because these fish live consistently with predators and are not constrained by the demands of climbing. We also predicted that, by using lateral undulations, powerburst climbers would show escape performance superior to that of inchers. We compared fast starts and body shape across six goby species. As predicted, non-climbing fish exhibited distinct morphology and responded more frequently to an attack stimulus than climbing species. Contrary to our predictions, we found no differences in escape performance among climbing styles. These results indicate that selection for a competing pressure need not limit the ability of prey to escape predator attacks. 

ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.