Species distribution models have been widely used in both terrestrial and marine systems, and applications have included invasive species management, evaluating potential effects of climate change, and conservation. Generally, only a single type of data can be accommodated within the model structures used, which may lead to higher uncertainty in the predictions when the data are sparse. In this case, it can be beneficial to pool data from multiple sources and data types, such as fishery observations and telemetry data. An integrated species distribution model (ISDM) utilizes data integration methods that address the challenges of harnessing multiple data types to estimate species distribution. In this study, an ISDM approach was developed to link turtle locations gathered as part of fishery observations with those derived from satellite telemetry in the East Pacific Ocean to enhance our understanding of a highly migratory and endangered marine species, the leatherback turtle (Dermochelys coriacea). These models were developed to support a dynamic management tool, South Pacific TurtleWatch, to identify high-risk areas of management concern and help inform bycatch reduction efforts for this critically endangered species. This data fusion approach could be applied to other populations and species for which telemetry and other point source data are available.

This study presents a comprehensive genetic analysis of stock structure for leatherback turtles (Dermochelys coriacea), combining 17 microsatellite loci and 763 bp of the mtDNA control region. Recently discovered eastern Atlantic nesting populations of this critically endangered species were absent in a previous survey that found little ocean-wide mtDNA variation. We added rookeries in West Africa and Brazil and generated longer sequences for previously analyzed samples. A total of 1,417 individuals were sampled from nine nesting sites in the Atlantic and SW Indian Ocean. We detected additional mtDNA variation with the longer sequences, identifying ten polymorphic sites that resolved a total of ten haplotypes, including three new variants of haplotypes previously described by shorter sequences. Population differentiation was substantial between all but two adjacent rookery pairs, and F (ST) values ranged from 0.034 to 0.676 and 0.004 to 0.205 for mtDNA and microsatellite data respectively, suggesting that male-mediated gene flow is not as widespread as previously assumed. We detected weak (F (ST) = 0.008 and 0.006) but significant differentiation with microsatellites between the two population pairs that were indistinguishable with mtDNA data. POWSIM analysis showed that our mtDNA marker had very low statistical power to detect weak structure (F (ST) < 0.005), while our microsatellite marker array had high power. We conclude that the weak differentiation detected with microsatellites reflects a fine scale level of demographic independence that warrants recognition, and that all nine of the nesting colonies should be considered as demographically independent populations for conservation. Our findings illustrate the importance of evaluating the power of specific genetic markers to detect structure in order to correctly identify the appropriate population units to conserve.

There is growing evidence that small-scale, coastal, passive net fisheries may be the largest single threat to some sea turtle populations. We review assessments of turtle interactions in these fisheries, and experiments on gear-technology approaches (modifying gear designs, materials and fishing methods) to mitigate turtle by-catch, available from a small number of studies and fisheries. Additional assessments are needed to improve the limited understanding of the relative degree of risk coastal net fisheries pose to turtle populations, to prioritize limited conservation resources and identify suitable mitigation opportunities. Whether gear technology provides effective and commercially viable solutions, alone or in combination with other approaches, is not well-understood. Fishery-specific assessments and trials are needed, as differences between fisheries, including in gear designs; turtle and target species, sizes and abundance; socioeconomic context; and practicality affect efficacy and suitability of by-catch mitigation methods. Promising gear-technology approaches for gillnets and trammel nets include: increasing gear visibility to turtles but not target species, through illumination and line materials; reducing net vertical height; increasing tiedown length or eliminating tiedowns; incorporating shark-shaped silhouettes; and modifying float characteristics, the number of floats or eliminating floats. Promising gear-technology approaches for pound nets and other trap gear include: replacing mesh with ropes in the upper portion of leaders; incorporating a turtle releasing device into traps; modifying the shape of the trap roof to direct turtles towards the location of an escapement device; using an open trap; and incorporating a device to prevent sea turtle entrance into traps.

The single largest threat to the critically endangered leatherback turtle (Dermochelys coriacea) in Trinidad, is the accidental capture in coastal gillnet fisheries. The entanglement problem also places a severe strain on the ability of fishers to operate. It is estimated that as many as 3,000 entanglements occur each year in Trinidad and that as much as 35% of those entanglements result in mortalities (Fournillier and Eckert 1999; Eckert and Lien 1999; Lee Lum 2003; Gass 2005). Traditional surface drift gillnets used along the Northern and Eastern coasts of Trinidad have the highest bycatch rates. These nets are used to target King mackerel (Scomberomorous cavalla) and Serra Spanish mackerel (Scomberomorus brasiliensis). In 2007, a cooperative study between the National Marine Fisheries Service (NMFS) and the Wider Caribbean Sea Turtle Conservation Network (WIDECAST) determined that reducing the fishing depth or "profile" of the nets used in this fishery to a level that targets the most productive portion of the water column, the upper 3 to 5 meters, maximizes target catch, while reducing unwanted bycatch of sea turtles. However, results of the study differed between ports with the experimental net reducing turtle bycatch by 5.5% in one port and 37% in another. These differences may have been attributed to the use of net marking lights used in one port, which may have attracted turtles to a specific portion of the gear thereby biasing results. To examine the net marking light effect on both sea turtle bycatch and target catch, two studies were conducted during the 2008 fishing season comparing white and red marking lights and no light vs. white marking lights. Results indicate that there was no significant difference in leatherback bycatch between treatments for each study. However, target catch was reduced by experimental red light and white light treatments in each study.