An expert-based system to predict population survival rate from health data.

Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach, but we propose that monitoring population health could prove more effective. We collated data from 7 bottlenose dolphin (Tursiops truncatus) populations in the southeastern United States to develop a method for estimating survival probability based on a suite of health measures identified by experts as indices for inflammatory, metabolic, pulmonary, and neuroendocrine systems. We used logistic regression to implement the veterinary expert system for outcome prediction (VESOP) within a Bayesian analysis framework. We fitted parameters with records from 5 of the sites that had a robust network of responders to marine mammal strandings and frequent photographic identification surveys that documented definitive survival outcomes. We also conducted capture-mark-recapture (CMR) analyses of photographic identification data to obtain separate estimates of population survival rates for comparison with VESOP survival estimates. The VESOP analyses showed that multiple measures of health, particularly markers of inflammation, were predictive of 1- and 2-year individual survival. The highest mortality risk 1 year following health assessment related to low alkaline phosphatase (odds ratio [OR] = 10.2 [95% CI: 3.41-26.8]), whereas 2-year mortality was most influenced by elevated globulin (OR = 9.60 [95% CI: 3.88-22.4]); both are markers of inflammation. The VESOP model predicted population-level survival rates that correlated with estimated survival rates from CMR analyses for the same populations (1-year Pearson's r = 0.99, p = 1.52 × 10-5 ; 2-year r = 0.94, p = 0.001). Although our proposed approach will not detect acute mortality threats that are largely independent of animal health, such as harmful algal blooms, it can be used to detect chronic health conditions that increase mortality risk. Random sampling of the population is important and advancement in remote sampling methods could facilitate more random selection of subjects, obtainment of larger sample sizes, and extension of the approach to other wildlife species.

Un sistema basado en conocimiento experto para predecir la tasa de supervivencia a partir de datos de salud Resumen La detección y el entendimiento oportunos de la declinación poblacional son esenciales para que el manejo y la conservación de fauna tengan efectividad. La evaluación de las tendencias en el tamaño poblacional ha sido la estrategia estándar, pero proponemos que el monitoreo de la salud poblacional podría ser más efectivo. Recopilamos datos de siete poblaciones de delfines (Tursiops truncatus) en el sureste de Estados Unidos para desarrollar un método de estimación de la probabilidad de supervivencia con base en un conjunto de medidas sanitarias identificadas por expertos como índices para los sistemas inflamatorio, metabólico, pulmonar y neuroendocrino. Usamos la regresión logística para implementar el sistema de expertos veterinarios para la predicción de resultados (SEVPR) en un análisis bayesiano. Ajustamos los parámetros con los registros de cinco sitios que contaban con una buena red de respondientes a los varamientos de mamíferos marinos y censos de identificación fotográfica (foto-ID) que documentaron los resultados de supervivencia definitivos. También realizamos análisis de marcaje-recaptura (MR) en los datos de identificación fotográfica para obtener estimados separados de las tasas de supervivencia poblacional para compararlos con los estimados del SEVPR. Los análisis del SEVPR mostraron que varias medidas sanitarias, particularmente los marcadores de inflamación son buenos predictores de la supervivencia individual para uno y dos años. El riesgo de mortalidad más alto un año después de la valoración sanitaria se relacionó con una fosfatasa alcalina baja (cociente de probabilidades de 10.2 [95% CI 3.41-26.8]), mientras que la mortalidad a los dos años estuvo más influenciada por una globulina elevada (9.60 [95% CI 3.88-22.4]); ambas son marcadores de la inflamación. El modelo del SEVPR predijo las tasas de supervivencia a nivel poblacional en correlación con las tasas estimadas de supervivencia de los análisis de MR para las mismas poblaciones (Pearson de un año r = 0.99, p = 1.52e-05; dos años r = 0.94, p = 0.001). Aunque nuestra propuesta no detecta las amenazas agudas de mortalidad que en su mayoría son independientes de la salud animal, como la proliferación de algas nocivas, puede usarse para detectar las condiciones crónicas de salud que incrementan el riesgo de mortalidad. Es importante el muestreo aleatorio de la población y los avances en los métodos de muestreo remoto podrían facilitar una selección más aleatoria de los sujetos, la obtención de muestras de mayor tamaño y la expansión de la estrategia a otras especies de fauna.

Modeling population effects of the Deepwater Horizon oil spill on a long-lived species.

The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14-74) relative to baseline and will take 35 years (95% CI 18-67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607-94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins' survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.

El derrame de petróleo Deepwater Horizon (DWH) en 2010 expuso gravemente a este hidrocarburo a los delfines (Tursiops truncatus) de la Bahía Barataria, Luisiana, causando un incremento en la mortalidad y en las enfermedades crónicas, y deteriorando la reproducción de los delfines sobrevivientes. Realizamos censos fotográficos y evaluaciones veterinarias durante la década posterior al derrame. Asignamos un puntaje pronóstico (bueno, favorable, moderado, malo, o grave) a cada delfín para proporcionar un indicador integrado único de la salud en general. También examinamos las tendencias temporales de estos puntajes. Usamos información de expertos para cuantificar las implicaciones de las tendencias para la proporción de delfines que se recuperaría dentro de su periodo de vida. Integramos esta información, junto con información nueva, a un modelo de dinámica poblacional para predecir los efectos sobre la demografía de las tendencias observadas en la salud. Comparamos la trayectoria poblacional resultante con aquella pronosticada bajo condiciones de línea base (sin derrame). Las condiciones de enfermedad persistieron y recientemente han empeorado en los delfines que supuestamente estuvieron expuestos al petróleo de DWH: 78% de aquellos evaluados en 2018 tuvieron un pronóstico moderado, malo o grave. Los delfines que nacieron después del derrame contaron con mejor salud. Estimamos que la población declinó en un 45% (95% CI 14-74) relativo a la línea base y tardará 35 años (95% CI 18-67) en recuperar el 95% de los números de línea base. La suma de las diferencias anuales entre el tamaño poblacional de línea base y el dañado (es decir, los años cetáceos perdidos) fue de 30,993 (95% CI 6,607-94,148). La población actualmente está en un punto mínimo de su trayectoria de recuperación y es vulnerable a las amenazas emergentes, incluyendo los esfuerzos de restauración ambiental planeada que probablemente sean nocivos para la supervivencia de los delfines. Nuestro marco de modelado demuestra una estrategia para la integración de diferentes fuentes y tipos de datos, resalta la utilidad de la información de expertos para los parámetros de aportación indeterminable, y enfatiza la importancia de la consideración y el monitoreo de la salud a largo plazo de las especies longevas sujetas a los desastres ambientales. Modelado de los Efectos Poblacionales del Derrame de Petróleo Deepwater Horizon sobre Especies Longevas.

Skin Transcriptomes of common bottlenose dolphins (Tursiops truncatus) from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts.

Common bottlenose dolphins serve as sentinels for the health of their coastal environments as they are susceptible to health impacts from anthropogenic inputs through both direct exposure and food web magnification. Remote biopsy samples have been widely used to reveal contaminant burdens in free-ranging bottlenose dolphins, but do not address the health consequences of this exposure. To gain insight into whether remote biopsies can also identify health impacts associated with contaminant burdens, we employed RNA sequencing (RNA-seq) to interrogate the transcriptomes of remote skin biopsies from 116 bottlenose dolphins from the northern Gulf of Mexico and southeastern U.S. Atlantic coasts. Gene expression was analyzed using principal component analysis, differential expression testing, and gene co-expression networks, and the results correlated to season, location, and contaminant burden. Season had a significant impact, with over 60% of genes differentially expressed between spring/summer and winter months. Geographic location exhibited lesser effects on the transcriptome, with 23.5% of genes differentially expressed between the northern Gulf of Mexico and the southeastern U.S. Atlantic locations. Despite a large overlap between the seasonal and geographical gene sets, the pathways altered in the observed gene expression profiles were somewhat distinct. Co-regulated gene modules and differential expression analysis both identified epidermal development and cellular architecture pathways to be expressed at lower levels in animals from the northern Gulf of Mexico. Although contaminant burdens measured were not significantly different between regions, some correlation with contaminant loads in individuals was observed among co-expressed gene modules, but these did not include classical detoxification pathways. Instead, this study identified other, possibly downstream pathways, including those involved in cellular architecture, immune response, and oxidative stress, that may prove to be contaminant responsive markers in bottlenose dolphin skin.

Reproductive outcome and survival of common bottlenose dolphins sampled in Barataria Bay, Louisiana, USA, following the Deepwater Horizon oil spill.

Common bottlenose dolphins (Tursiops truncatus) inhabit bays, sounds and estuaries across the Gulf of Mexico. Following the Deepwater Horizon oil spill, studies were initiated to assess potential effects on these ecologically important apex predators. A previous study reported disease conditions, including lung disease and impaired stress response, for 32 dolphins that were temporarily captured and given health assessments in Barataria Bay, Louisiana, USA. Ten of the sampled dolphins were determined to be pregnant, with expected due dates the following spring or summer. Here, we report findings after 47 months of follow-up monitoring of those sampled dolphins. Only 20% (95% CI: 2.50-55.6%) of the pregnant dolphins produced viable calves, as compared with a previously reported pregnancy success rate of 83% in a reference population. Fifty-seven per cent of pregnant females that did not successfully produce a calf had been previously diagnosed with moderate-severe lung disease. In addition, the estimated annual survival rate of the sampled cohort was low (86.8%, 95% CI: 80.0-92.7%) as compared with survival rates of 95.1% and 96.2% from two other previously studied bottlenose dolphin populations. Our findings confirm low reproductive success and high mortality in dolphins from a heavily oiled estuary when compared with other populations. Follow-up studies are needed to better understand the potential recovery of dolphins in Barataria Bay and, by extension, other Gulf coastal regions impacted by the spill.