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Illegal, unregulated, and unreported (IUU) fishing poses a major threat to effective management of marine resources, affecting biodiversity and communities dependent on these coastal resources. Spatiotemporal patterns of industrial fisheries in developing countries are often poorly understood, and global efforts to describe spatial patterns of fishing vessel activity are currently based on automatic identification system (AIS) data. However, AIS is often not a legal requirement on fishing vessels, likely resulting in underestimates of the scale and distribution of legal and illegal fishing activity, which could have significant ramifications for targeted enforcement efforts and the management of fisheries resources. To help address this knowledge gap, we analyzed 3 years of vessel monitoring system (VMS) data in partnership with the national fisheries department in the Republic of the Congo to describe the behavior of national and distant-water industrial fleets operating in these waters. We found that the spatial footprint of the industrial fisheries fleet encompassed over one-quarter of the Exclusive Economic Zone. On average, 73% of fishing activity took place on the continental shelf (waters shallower than 200 m). Our findings highlight that VMS is not acting as a deterrent or being effectively used as a proactive management tool. As much as 33% (13% on average) of fishing effort occurred in prohibited areas set aside to protect biodiversity, including artisanal fisheries resources, and the distant-water fleet responsible for as much as 84% of this illegal activity. Given the growth in industrial and distant-water fleets across the region, as well as low levels of management and enforcement, these findings highlight that there is an urgent need for the global community to help strengthen regional and national capacity to analyze national scale data sets if efforts to combat IUU fishing are to be effective.Amenazas de la Pesca Ilegal, No Regulada y No Reportada para la Biodiversidad y la Seguridad Alimentaria en la República del Congo Resumen La pesca ilegal, no regulada y no reportada (INN) representa una amenaza importante para el manejo efectivo de los recursos marinos, lo que afecta a la biodiversidad y a las comunidades que dependen de estos recursos costeros. Los patrones espaciotemporales de las pesquerías industriales en los países en desarrollo a menudo están poco comprendidas, y los esfuerzos globales para describir los patrones espaciales de la actividad de los navíos pesqueros actualmente están basados en los datos del sistema automático de identificación (SAI). Sin embargo, el SAI no es siempre un requerimiento legal en los navíos pesqueros, lo que probablemente resulta en valores subestimados de la escala y la distribución de la actividad pesquera legal e ilegal, lo que podría tener ramificaciones significativas para los esfuerzos enfocados de aplicación de la ley y para el manejo de los recursos de las pesquerías. Para ayudar a completar este vacío en el conocimiento, analizamos tres años de datos del sistema de monitoreo de navíos (SMN) en asociación con el departamento nacional de pesquerías de la República del Congo para describir el comportamiento de las flotas industriales nacionales y de altura que operan en estas aguas. Descubrimos que la huella espacial de la flota de pesquerías industriales abarcó más de un cuarto de la Zona Económica Exclusiva. En promedio, el 73% de la actividad pesquera se realizó en el talud continental (aguas con una profundidad menor a 200 m). Nuestros descubrimientos resaltan que el SMN no está actuando como un disuasivo o no se está usando efectivamente como una herramienta proactiva de manejo. Un máximo del 33% (13% en promedio) de los esfuerzos de pesca ocurrieron en áreas prohibidas apartadas para proteger a la biodiversidad, incluyendo los recursos para la pesca artesanal, con el 84% de la responsabilidad de esta actividad ilegal cayendo sobre las flotas de altura. Dado el crecimiento de flotas industriales y de altura en la región, así como los bajos niveles de manejo y aplicación de la ley, estos resultados resaltan la necesidad urgente que existe para que la comunidad global ayude a fortalecer la capacidad regional y nacional para analizar los conjuntos de datos de escala nacional si se espera que los esfuerzos para combatir la pesca INN sean efectivos.

Monitoring how populations respond to sustained conservation measures is essential to detect changes in their population status and determine the effectiveness of any interventions. In the case of sea turtles, their populations are difficult to assess because of their complicated life histories. Ground-derived clutch counts are most often used as an index of population size for sea turtles; however, data are often incomplete with varying sampling intensity within and among sites and seasons. To address these issues, we: (1) develop a Bayesian statistical modelling framework that can be used to account for sampling uncertainties in a robust probabilistic manner within a given site and season; and (2) apply this to a previously unpublished long-term sea turtle dataset (n = 17 years) collated for the Republic of the Congo, which hosts two sympatrically nesting species of sea turtle (leatherback turtle [Dermochelys coriacea] and olive ridley turtle [Lepidochelys olivacea]). The results of this analysis suggest that leatherback turtle nesting levels dropped initially and then settled into quasi-cyclical levels of interannual variability, with an average of 573 (mean, 95% prediction interval: 554–626) clutches laid annually between 2012 and 2017. In contrast, nesting abundance for olive ridley turtles has increased more recently, with an average of 1,087 (mean, 95% prediction interval: 1,057–1,153) clutches laid annually between 2012 and 2017. These findings highlight the regional and global importance of this rookery with the Republic of the Congo, hosting the second largest documented populations of olive ridley and the third largest for leatherback turtles in Central Africa; and the fourth largest non-arribada olive ridley rookery globally. Furthermore, whilst the results show that Congo’s single marine and coastal national park provides protection for over half of sea turtle clutches laid in the country, there is scope for further protection along the coast. Although large parts of the African coastline remain to be adequately monitored, the modelling approach used here will be invaluable to inform future status assessments for sea turtles given that most datasets are temporally and spatially fragmented.

Globally, marine turtles are considered threatened throughout their range, and therefore conservation practitioners are increasingly investing resources in marine protected areas to protect key life history stages and critical habitats, including foraging grounds, nesting beaches and inter-nesting areas. Empirical data on the distribution of these habitats and/or the spatial ecology and behaviour of individuals of many marine turtle populations are often lacking, undermining conservation efforts, particularly along the Atlantic coast of Africa. Here we contribute to the knowledge base in this region by describing patterns of habitat use for nine green turtles Chelonia mydas tagged with satellite platform transmitter terminals at a foraging ground in Loango Bay, Republic of the Congo, one of only a few documented mainland foraging grounds for marine turtles in Central Africa. Analyses of these data revealed that core areas of habitat use and occupancy for a wide range of size/age classes were restricted to shallow waters adjacent to Pointe Indienne in Loango Bay, with most individuals showing periods of high fidelity to this area. These data are timely given the Congolese government recently announced its intention to create a marine conservation zone to protect marine turtles in Loango Bay. Despite the small sample size of this study, these data exemplify the need for comprehensive strategies that span national jurisdictions, as we provide the first documented evidence of linkages between green turtle foraging sites in Central Africa (Loango Bay, Republic of the Congo) and Southern Africa (Mussulo Bay, Angola).