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.

State-space models are important tools for quality control of error-prone
animal movement data. The near real-time (within 24 h) capability of the Argos
satellite system aids dynamic ocean management of human activities by informing
when animals enter intensive use zones. This capability also facilitates use of
ocean observations from animal-borne sensors in operational ocean forecasting
models. Such near real-time data provision requires rapid, reliable quality
control to deal with error-prone Argos locations. We formulate a
continuous-time state-space model for the three types of Argos location data
(Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular
timing of observations. Our model is deliberately simple to ensure speed and
reliability for automated, near real-time quality control of Argos data. We
validate the model by fitting to Argos data collected from 61 individuals
across 7 marine vertebrates and compare model-estimated locations to GPS
locations. Estimation accuracy varied among species with median Root Mean
Squared Errors usually < 5 km and decreased with increasing data sampling rate
and precision of Argos locations. Including a model parameter to inflate Argos
error ellipse sizes resulted in more accurate location estimates. In some
cases, the model appreciably improved the accuracy of the Argos Kalman smoother
locations, which should not be possible if the smoother uses all available
information. Our model provides quality-controlled locations from Argos
Least-Squares or Kalman filter data with slightly better accuracy than Argos
Kalman smoother data that are only available via reprocessing. Simplicity and
ease of use make the model suitable both for automated quality control of near
real-time Argos data and for manual use by researchers working with historical
Argos data.

AbstractMigratory movements in response to seasonal resources often influence population structure and dynamics. Yet in mobile marine predators, population genetic consequences of such repetitious behaviour remain inaccessible without comprehensive sampling strategies. Temporal genetic sampling of seasonally recurring aggregations of planktivorous basking sharks, Cetorhinus maximus, in the Northeast Atlantic (NEA) affords an opportunity to resolve individual re-encounters at key sites with population connectivity and patterns of relatedness. Genetic tagging (19 microsatellites) revealed 18% of re-sampled individuals in the NEA demonstrated inter/multi-annual site-specific re-encounters. High genetic connectivity and migration between aggregation sites indicate the Irish Sea as an important movement corridor, with a contemporary effective population estimate (Ne) of 382 (CI = 241–830). We contrast the prevailing view of high gene flow across oceanic regions with evidence of population structure within the NEA, with early-season sharks off southwest Ireland possibly representing genetically distinct migrants. Finally, we found basking sharks surfacing together in the NEA are on average more related than expected by chance, suggesting a genetic consequence of, or a potential mechanism maintaining, site-specific re-encounters. Long-term temporal genetic monitoring is paramount in determining future viability of cosmopolitan marine species, identifying genetic units for conservation management, and for understanding aggregation structure and dynamics.

AbstractGlobally, 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).

Shark take, driven by vast demand for meat and fins, is increasing. We set out to gain insights into the impact of small-scale longline fisheries in Peru. Onboard observers were used to document catch from 145 longline fishing trips (1668 fishing days) originating from Ilo, southern Peru. Fishing effort is divided into two seasons: targeting dolphinfish (Coryphaena hippurus; December to February) and sharks (March to November). A total of 16,610 sharks were observed caught, with 11,166 identified to species level. of these, 70.6% were blue sharks (Prionace glauca), 28.4% short-fin mako sharks (Isurus oxyrinchus), and 1% were other species (including thresher (Alopias vulpinus), hammerhead (Sphyrna zygaena), porbeagle (Lamnus nasus), and other Carcharhinidae species (Carcharhinus brachyurus, Carcharhinus falciformis, Galeorhinus galeus). Mean ± SD catch per unit effort of 33.6 ± 10.9 sharks per 1000 hooks was calculated for the shark season and 1.9 ± 3.1 sharks per 1000 hooks were caught in the dolphinfish season. An average of 83.7% of sharks caught (74.7% blue sharks; 93.3% mako sharks) were deemed sexually immature and under the legal minimum landing size, which for species exhibiting k-selected life history traits can result in susceptibility to over exploitation. As these growing fisheries operate along the entire Peruvian coast and may catch millions of sharks per annum, we conclude that their continued expansion, along with ineffective legislative approaches resulting in removal of immature individuals, has the potential to threaten the sustainability of the fishery, its target species, and ecosystem. There is a need for additional monitoring and research to inform novel management strategies for sharks while maintaining fisher livelihoods. © 2014 the Authors.