An agent-based model to evaluate recovery times and monitoring strategies to increase accuracy of sea turtle population assessments

Modeling juvenile sea turtle bycatch risk in commercial and recreational fisheries

Understanding the drivers of fisheries bycatch is essential for limiting its impacts on vulnerable species. Here we present a model to estimate the relative magnitude of sea turtle bycatch in major coastal fisheries across the southeastern US based on spatiotemporal variation in fishing effort and the simulated distributions of juvenile Kemp's ridley (Lepidochelys kempii) and green (Chelonia mydas) sea turtles recruiting from oceanic to nearshore habitats. Over the period modeled (1996-2017), bycatch in recreational fisheries was estimated to be greater than the sum of bycatch that occurred in commercial fisheries that have historically been considered high risks to turtles (e.g., those using trawls, gillnets, and bottom longlines). Prioritizing engagement with recreational anglers to reduce bycatch could be especially beneficial to sea turtle populations. Applying lessons learned from efforts to protect turtles in commercial fisheries may help meet the challenges that arise from the large, diffuse recreational fishing sector.

Matrix and agent-based modeling of threats to a diamond-backed terrapin population

Population models are important tools for evaluating human impacts and potential management approaches on declining species. However, often studies are limited by constraints of the specific modeling approach. In this study we considered the persistence of a diamond-backed terrapin (Malaclemys terrapin) population using two distinct modeling approaches. Two of the models were deterministic matrix models. Analysis of the discrete non-spatial models showed that female adult survival rate had the largest positive impact on population growth while delaying sexual maturity decreased population growth. The matrix models also demonstrated that an increase in crab traps skewed the sex ratio of the population in favor of females. The third model was a stochastic agent-based formulation that evaluated how increases in the number of crab traps and frequency of nest disturbances affected the long-term viability of diamond-backed terrapins. The spatial agent-based model revealed how terrapin mortality was highly sensitive to the proximity of traps to the primary terrapin habitat. Results from this project improve our understanding of threats to diamond-backed terrapins and can be used to guide conservation efforts.

Managing fisheries in a world with more sea turtles

For decades, fisheries have been managed to limit the accidental capture of vulnerable species and many of these populations are now rebounding. While encouraging from a conservation perspective, as populations of protected species increase so will bycatch, triggering management actions that limit fishing. Here, we show that despite extensive regulations to limit sea turtle bycatch in a coastal gillnet fishery on the eastern United States, the catch per trip of Kemp's ridley has increased by more than 300% and green turtles by more than 650% (2001-2016). These bycatch rates closely track regional indices of turtle abundance, which are a function of increased reproductive output at distant nesting sites and the oceanic dispersal of juveniles to near shore habitats. The regulations imposed to help protect turtles have decreased fishing effort and harvest by more than 50%. Given uncertainty in the population status of sea turtles, however, simply removing protections is unwarranted. Stock-assessment models for sea turtles must be developed to determine what level of mortality can be sustained while balancing continued turtle population growth and fishing opportunity. Implementation of management targets should involve federal and state managers partnering with specific fisheries to develop bycatch reduction plans that are proportional to their impact on turtles.

Modeling the emergence of migratory corridors and foraging hot spots of the green sea turtle

Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade-offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual-based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open-source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.

Fathoming sea turtles: monitoring strategy evaluation to improve conservation status assessments

Population monitoring must be accurate and reliable to correctly classify population status. For sea turtles, nesting beach surveys are often the only population-level surveys that are accessible. However, process and observation errors, compounded by delayed maturity, obscure the relationship between trends on the nesting beach and the population. We present a simulation-based tool, monitoring strategy evaluation (MoSE), to test the relationships between monitoring data and assessment accuracy, using green sea turtles, Chelonia mydas, as a case study. To explore this first application of MoSE, we apply different treatments of population impacts to virtual true populations, and sample the nests or nesters, with observation error, to test if the observation data can be used to diagnose population status accurately. Based on the observed data, we examine population trend and compare it to the known values from the operating model. We ran a series of scenarios including harvest impacts, cyclical breeding probability, and sampling biases, to see how these factors impact accuracy in estimating population trend. We explored the necessary duration of monitoring for accurate trend estimation and the probability of a false trend diagnosis. Our results suggest that disturbance type and severity can have important and persistent effects on the accuracy of population assessments drawn from monitoring nesting beaches. The underlying population phase, age classes disturbed, and impact severity influenced the accuracy of estimating population trend. At least 10 yr of monitoring data is necessary to estimate population trend accurately, and >20 yr if juvenile age classes were disturbed and the population is recovering. In general, there is a greater probability of making a false positive trend diagnosis than a false negative, but this depends on impact type and severity, population phase, and sampling duration. Improving detection rates to 90% does little to lower probability of a false trend diagnosis with shorter monitoring spans. Altogether, monitoring strategies for specific populations may be tailored based on the impact history, population phase, and environmental drivers. The MoSE is an important framework for analysis through simulation that can comprehensively test population assessments for accuracy and inform policy recommendations regarding the best monitoring strategies.