Madagascar is a marine biodiversity hotspot. A recent checklist recorded 1689 marine or transitional water fish species, 2.5% being endemic. To date, studies in this country were mostly focused on adult fishes using morphological-based identification. The early life stages of fishes remain largely understudied. The present work aimed to improve knowledge of fish biodiversity in Madagascar by focusing on post-larval reef fishes and settled juveniles in seagrass meadows of southwest Madagascar by using either species identification keys or DNA barcoding. Up to 119,500 individuals were collected, and 1096 individuals were successfully barcoded. We identified 387 species—85 through their morphology (with 58 unsuccessfully sequenced) and 302 by using CO1 barcoding corresponding to 302 barcode index numbers (BINs). This study added 27 new BINs for the BOLD database, 120 new for Madagascar, but only 159 were assigned a precise species name. By referring to the updated checklist of Madagascar fishes, 10 new species were detected for Madagascar. This number will probably increase when all the barcoded specimens become assigned to precise species names. These preliminary findings stress our poor knowledge of marine fish biodiversity in Madagascar and demonstrate the relevance of DNA barcoding in improving this knowledge.

Madagascar harbors a rich marine biodiversity, yet detailed knowledge of its fish species remains limited. Of the 1689 species listed in 2018, only 22% had accessible cytochrome oxidase I (COI) sequences in public databases. In response to growing pressure on fishery resources, this study aims to strengthen biodiversity monitoring tools. Its objectives were to enrich the COI database for Malagasy marine fishes, create the first 12S reference library, and evaluate the taxonomic resolution of different 12S metabarcodes for eDNA analysis, namely MiFish, Teleo1, AcMDB, Ac12S, and 12SF1/R1. An integrated approach combining morphological, molecular, and phylogenetic analyses was applied for specimen identification of fish captured using various types of fishing gear in Toliara and Ranobe Bays from 2018 to 2023. The Malagasy COI database now includes 2146 sequences grouped into 502 Barcode Index Numbers (BINs) from 82 families, with 14 BINs newly added to BOLD (The Barcode of Life Data Systems), and 133 cryptic species. The 12S library comprises 524 sequences representing 446 species from 78 families. Together, the genetic datasets cover 514 species from 84 families, with the most diverse being Labridae, Apogonidae, Gobiidae, Pomacentridae, and Carangidae. However, the two markers show variable taxonomic resolution: 67 species belonging to 35 families were represented solely in the COI dataset, while 10 species from nine families were identified exclusively in the 12S dataset. For 319 species with complete 12S gene sequences associated with COI BINs (Barcode Index Numbers), 12S primer sets were used to evaluate the taxonomic resolution of five 12S metabarcodes. The MiFish marker proved to be the most effective, with an optimal similarity threshold of 98.5%. This study represents a major step forward in documenting and monitoring Madagascar’s marine biodiversity and provides a valuable genetic reference for future environmental DNA (eDNA) applications.

Fishers’ spatial knowledge encompasses a diverse array of social, ecological, technical, experiential, and learning knowledge derived from local environmental and sociocultural contexts. In this study, we used a transdisciplinary framework to shed light on place names of fishing grounds in the context of small-scale fisheries through a case study in Madagascar. First, we jointly monitored fishing boat trajectories based on GPS tracking and recorded the vernacular names of fishing sites in a coral reef fishery from May 2018 to April 2019. This data was processed through spatial analysis to assess the dimensions of each named fishing site. A focus group discussion was conducted with fishers to determine the literal meanings of the toponyms (place names) in the local language. A total of 570 fishers (totaling 15,904 fishing trips) using five gear types were surveyed in eight communities. We identified 397 fishing sites over about 250 km², 304 of which (76.6%) were mapped. Overall, 371 toponyms (93.4%) were interpreted and categorized based on geographical features (n = 222), biodiversity (n = 86), and maritime uses (n = 63). The dimensions of the fishing sites varied significantly from 0.01 to 11.7 km², following spatially-explicit fishing distribution patterns and the level of precision of the delimitation method. Most fishing locations (63.3% of the total fishing grounds) were associated with multiple place names, particularly in heavily-targeted areas, indicating that individual fishers typically have their own names for their fishing sites. This study demonstrates that recording boat movements and vernacular toponyms simultaneously throughout an extensive monitoring survey in a coral reef fishery, effectively captured the rich and varied individual fishers’ conceptualizations of the coastal and nearshore marine environment. Our findings suggest that named fishing sites may be used as local spatial reference units with known precision and accuracy, which is relevant for addressing spatial data limitations in small-scale fisheries and incorporating fishers’ knowledge in collaborative fisheries science.

Understanding the interannual effect of various environmental factors on biodiversity distribution is fundamental for developing biological monitoring tools. The interannual variability of environmental factors on presettlement fish assemblages (PFAs) has been so far under investigated, especially in Madagascar. Numerous explanatory variables including local hydro-dynamic conditions recorded during the sampling night, characteristics of the benthic substrate and remotely sensed oceanic conditions (RSOC) were used to explain the spatio-temporal variability of PFAs in southwestern Madagascar. Gradient forest analyses were used to hierarchically classify the effect of these explanatory variables on the PFAs for two sites and during two different recruitment seasons. RSOC variables appeared to better explain the PFAs than the local variable and the characteristics of the benthic substrate. The PFAs caught in water masses with coastal characteristics were better explained than those with open water characteristics. This spatial variability is hypothesised to be linked to differences in feeding conditions among water masses. The gradient forest analyses also highlighted the complexity of predicting PFAs as the species for which abundances were better explained by RSOC variables varied between years. This interannual variability was mainly explained by the interannual variation of chlorophyll a (Chl a) concentration, wind and surface current, with better prediction obtained during the year with high Chl a values associated with high averaged sea surface temperature. These findings suggest the importance of forecasting Chl a concentrations, taking into account the impact of tropical storms and climate variability in order to predict PFAs in the future.

The blue economy agenda has generated tensions over marine space use, often marginalising small-scale fisheries in development policies. Boat tracking technology has only recently begun to be applied in these fisheries, but it offers a promising approach to accurately map fishing distribution. In this study, we explored how environmental, technological, and social factors influenced fishers’ spatial behaviour and catches at sea in one of the Madagascar's most heavily exploited coral reef fisheries. We recorded boat movements at 30 s intervals and reef fish catches simultaneously during a 12-month participatory survey. The spatial distribution of annual fishing effort (h·ha ⁻¹ ) and fish catch rates (kg·ha ⁻¹ ) was characterised by fishing community and gear type (beach seine, mosquito net trawl, gillnet, handline, and speargun) at 250−m resolution. A total of 75 reef fish families were recorded in catches (1,466 t·yr ⁻¹ ) across approximately 218 km ² . Annual catch rates of the seven dominant families (comprising 62% of total catches) were highly variable and heterogeneous (mostly 1–391 kg·ha ⁻¹ ) across marine habitats. A total of 7,359 tracks by 521 boats were recorded. Fishing pressure was highly variable spatially (mostly 1−150 h·ha ⁻¹ ) among communities and gear types. The results revealed preferential target areas, informal marine tenure, limited travel distance to fishing grounds, and overexploitation patterns within the fishery, offering critical insights for fishery management and inclusive marine spatial planning. This study showed the usefulness and opportunities of deploying combined boat tracking and catch surveys in small-scale fisheries through participatory research.