Simulating the efficacy of wolf-dog hybridization management with individual-based modeling.

Introgressive hybridization between wolves and dogs is a conservation concern due to its potentially deleterious long-term evolutionary consequences. European legislation requires that wolf-dog hybridization be mitigated through effective management. We developed an individual-based model (IBM) to simulate the life cycle of gray wolves that incorporates aspects of wolf sociality that affect hybridization rates (e.g., the dissolution of packs after the death of one/both breeders) with the goal of informing decision-making on management of wolf-dog hybridization. We applied our model by projecting hybridization dynamics in a local wolf population under different mate choice and immigration scenarios and contrasted results of removal of admixed individuals with their sterilization and release. In several scenarios, lack of management led to complete admixture, whereas reactive management interventions effectively reduced admixture in wolf populations. Management effectiveness, however, strongly depended on mate choice and number and admixture level of individuals immigrating into the wolf population. The inclusion of anthropogenic mortality affecting parental and admixed individuals (e.g., poaching) increased the probability of pack dissolution and thus increased the probability of interbreeding with dogs or admixed individuals and boosted hybridization and introgression rates in all simulation scenarios. Recognizing the necessity of additional model refinements (appropriate parameterization, thorough sensitivity analyses, and robust model validation) to generate management recommendations applicable in real-world scenarios, we maintain confidence in our model's potential as a valuable conservation tool that can be applied to diverse situations and species facing similar threats.

Simulación de la eficiencia de la gestión de híbridos de perro y lobo con modelos basados en individuos Resumen La hibridación introgresiva entre perros y lobos es un tema de conservación por las posibles consecuencias evolutivas deletéreas a largo plazo. Las leyes europeas requieren que estos híbridos se mitiguen mediante una gestión efectiva. Desarrollamos un modelo basado en individuos (MBI) para simular el ciclo de vida del lobo gris que además incorpora los aspectos sociales de los lobos que afectan las tasas de hibridación (p. ej.: la disolución de las manadas después de la muerte de uno o ambos reproductores) con el objetivo de guiar las decisiones de gestión de estos híbridos. Aplicamos nuestro modelo con la proyección de las dinámicas de hibridación en una población local de lobos bajo diferentes selecciones de pareja y escenarios de inmigración y contrastamos los resultados de la extirpación de individuos mezclados con su esterilización y liberación. En varios escenarios, la falta de gestión llevó a una mezcla completa, mientras que las intervenciones de gestión reactiva redujeron de forma efectiva la mezcla en las poblaciones de lobos. Sin embargo, la eficiencia de la gestión dependió en su mayoría de la selección de pareja y el número y nivel de mezcla de los individuos inmigrantes a la población de lobos. La inclusión de la mortalidad antropogénica que afecta a los individuos parentales y mezclados (p. ej.: la cacería) incrementó la probabilidad de que se disolviera la manada y por lo tanto incrementara la probabilidad del entrecruzamiento con perros o individuos mezclados, además de que aumentó la hibridación y las tasas de introgresión en todos los escenarios de simulación. Reconocemos la necesidad de refinar el modelo (parametrización adecuada, análisis detallados de sensibilidad y validación del modelo robusto) para generar recomendaciones de gestión aplicables en escenarios reales y mantenemos la confianza en el potencial de nuestro modelo como una herramienta valiosa de conservación que podría aplicarse a diferentes situaciones y especies que enfrentan amenazas similares.

Use of hidden Markov capture-recapture models to estimate abundance in the presence of uncertainty: Application to the estimation of prevalence of hybrids in animal populations.

Estimating the relative abundance (prevalence) of different population segments is a key step in addressing fundamental research questions in ecology, evolution, and conservation. The raw percentage of individuals in the sample (naive prevalence) is generally used for this purpose, but it is likely to be subject to two main sources of bias. First, the detectability of individuals is ignored; second, classification errors may occur due to some inherent limits of the diagnostic methods. We developed a hidden Markov (also known as multievent) capture-recapture model to estimate prevalence in free-ranging populations accounting for imperfect detectability and uncertainty in individual's classification. We carried out a simulation study to compare naive and model-based estimates of prevalence and assess the performance of our model under different sampling scenarios. We then illustrate our method with a real-world case study of estimating the prevalence of wolf (Canis lupus) and dog (Canis lupus familiaris) hybrids in a wolf population in northern Italy. We showed that the prevalence of hybrids could be estimated while accounting for both detectability and classification uncertainty. Model-based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. We also showed that ignoring detectability and uncertainty in the wolf case study would lead to underestimating the prevalence of hybrids. Our results underline the importance of a model-based approach to obtain unbiased estimates of prevalence of different population segments. Our model can be adapted to any taxa, and it can be used to estimate absolute abundance and prevalence in a variety of cases involving imperfect detection and uncertainty in classification of individuals (e.g., sex ratio, proportion of breeders, and prevalence of infected individuals).

A Robust Design Capture-Recapture Analysis of Abundance, Survival and Temporary Emigration of Three Odontocete Species in the Gulf of Corinth, Greece.

While the Mediterranean Sea has been designated as a Global Biodiversity Hotspot, assessments of cetacean population abundance are lacking for large portions of the region, particularly in the southern and eastern basins. The challenges and costs of obtaining the necessary data often result in absent or poor abundance information. We applied capture-recapture models to estimate abundance, survival and temporary emigration of odontocete populations within a 2,400 km2 semi-enclosed Mediterranean bay, the Gulf of Corinth. Boat surveys were conducted in 2011-2015 to collect photo-identification data on striped dolphins Stenella coeruleoalba, short-beaked common dolphins Delphinus delphis (always found together with striped dolphins in mixed groups) and common bottlenose dolphins Tursiops truncatus, totaling 1,873 h of tracking. After grading images for quality and marking distinctiveness, 23,995 high-quality photos were included in a striped and common dolphin catalog, and 2,472 in a bottlenose dolphin catalog. The proportions of striped and common dolphins were calculated from the photographic sample and used to scale capture-recapture estimates. Best-fitting robust design capture-recapture models denoted no temporary emigration between years for striped and common dolphins, and random temporary emigration for bottlenose dolphins, suggesting different residency patterns in agreement with previous studies. Average estimated abundance over the five years was 1,331 (95% CI 1,122-1,578) striped dolphins, 22 (16-32) common dolphins, 55 (36-84) "intermediate" animals (potential striped x common dolphin hybrids) and 38 (32-46) bottlenose dolphins. Apparent survival was constant for striped, common and intermediate dolphins (0.94, 95% CI 0.92-0.96) and year-dependent for bottlenose dolphins (an average of 0.85, 95% CI 0.76-0.95). Our work underlines the importance of long-term monitoring to contribute reliable baseline information that can help assess the conservation status of wildlife populations.