Managing conflicts between economic activities and threatened migratory marine species toward creating a multiobjective blue economy.

Harnessing the economic potential of the oceans is key to combating poverty, enhancing food security, and strengthening economies. But the concomitant risk of intensified resource extraction to migratory species is worrying given these species contribute to important ecological processes, often underpin alternative livelihoods, and are mostly already threatened. We thus sought to quantify the potential conflict between key economic activities (5 fisheries and hydrocarbon exploitation) and sea turtle migration corridors in a region with rapid economic development: southern and eastern Africa. We satellite tracked the movement of 20 loggerhead (Caretta caretta) and 14 leatherback (Dermochelys coriacea) turtles during their postnesting migrations. We used movement-based kernel density estimation to identify migration corridors for each species. We overlaid these corridors on maps of the distribution and intensity of economic activities, quantified the extent of overlap and threat posed by each activity on each species, and compared the effects of activities. These results were compared with annual bycatch rates in the respective fisheries. Both species' 3 corridors overlapped most with longline fishing, but the effect was worse for leatherbacks: their bycatch rates of approximately 1500/year were substantial relative to the regional population size of <100 nesting females/annum. This bycatch rate is likely slowing population growth. Artisanal fisheries may be of greater concern for loggerheads than for leatherbacks, but the population appears to be withstanding the high bycatch rates because it is increasing exponentially. The hydrocarbon industry currently has a moderately low impact on both species, but mining in key areas (e.g., Southern Mozambique) may undermine >50 years of conservation, potentially affecting >80% of loggerheads, 33% of the (critically endangered) leatherbacks, and their nesting beaches. We support establishing blue economies (i.e., generating wealth from the ocean), but oceans need to be carefully zoned and responsibly managed in both space and time to achieve economic (resource extraction), ecological (conservation, maintenance of processes), and social (maintenance of alternative livelihood opportunities, alleviate poverty) objectives.

Accuracy of ARGOS locations of Pinnipeds at-sea estimated using Fastloc GPS.

BACKGROUND: ARGOS satellite telemetry is one of the most widely used methods to track the movements of free-ranging marine and terrestrial animals and is fundamental to studies of foraging ecology, migratory behavior and habitat-use. ARGOS location estimates do not include complete error estimations, and for many marine organisms, the most commonly acquired locations (Location Class 0, A, B, or Z) are provided with no declared error estimate. METHODOLOGY/PRINCIPAL FINDINGS: We compared the accuracy of ARGOS Locations to those obtained using Fastloc GPS from the same electronic tags on five species of pinnipeds: 9 California sea lions (Zalophus californianus), 4 Galapagos sea lions (Zalophus wollebaeki), 6 Cape fur seals (Arctocephalus pusillus pusillus), 3 Australian fur seals (A. p. doriferus) and 5 northern elephant seals (Mirounga angustirostris). These species encompass a range of marine habitats (highly pelagic vs coastal), diving behaviors (mean dive durations 2-21 min) and range of latitudes (equator to temperate). A total of 7,318 ARGOS positions and 27,046 GPS positions were collected. Of these, 1,105 ARGOS positions were obtained within five minutes of a GPS position and were used for comparison. The 68(th) percentile ARGOS location errors as measured in this study were LC-3 0.49 km, LC-2 1.01 km, LC-1 1.20 km, LC-0 4.18 km, LC-A 6.19 km, LC-B 10.28 km. CONCLUSIONS/SIGNIFICANCE: The ARGOS errors measured here are greater than those provided by ARGOS, but within the range of other studies. The error was non-normally distributed with each LC highly right-skewed. Locations of species that make short duration dives and spend extended periods on the surface (sea lions and fur seals) had less error than species like elephant seals that spend more time underwater and have shorter surface intervals. Supplemental data (S1) are provided allowing the creation of density distributions that can be used in a variety of filtering algorithms to improve the quality of ARGOS tracking data.

Transoceanic migration, spatial dynamics, and population linkages of white sharks.

The large-scale spatial dynamics and population structure of marine top predators are poorly known. We present electronic tag and photographic identification data showing a complex suite of behavioral patterns in white sharks. These include coastal return migrations and the fastest known transoceanic return migration among swimming fauna, which provide direct evidence of a link between widely separated populations in South Africa and Australia. Transoceanic return migration involved a return to the original capture location, dives to depths of 980 meters, and the tolerance of water temperatures as low as 3.4 degrees C. These findings contradict previous ideas that female white sharks do not make transoceanic migrations, and they suggest natal homing behavior.