A Standardized Protocol for Measuring Bioelectrical Impedance in Green Turtles (Chelonia mydas).

AbstractBioelectrical impedance analysis (BIA) is gaining popularity in wildlife studies as a portable technology for immediate and nondestructive predictions of body composition components, such as fat-free and fat masses. Successful application of BIA for field-based research requires the identification and control of potential sources of error, as well as the creation of and adherence to a standardized protocol for measurement. The aim of our study was to determine sources of error and to provide a standardization protocol to improve measurement precision of BIA on juvenile green turtles (Chelonia mydas; n=35). We assessed the effects of altered environmental temperature (20°C-30°C), postprandial state (2-72 h), and time out of the water (2 h) on five impedance parameters (resistance at infinite frequency [Rinf], resistance at zero frequency [R0], resistance at 50 kHz [R50], phase angle at 50 kHz [PhA50], and intracellular resistance [Ri]) using a bioimpedance spectroscopy device. Technical reproducibility of measurements and interanimal variability were also assessed. We found an inverse exponential relationship between change in environmental temperature and impedance parameters Rinf, R0, and R50. Postprandial state significantly increased Rinf and Ri 72 h after feeding. BIA measurements were reproducible within individual juvenile green turtles at temperatures from 20°C to 30°C. Significant variation in impedance values was found between animals at all temperatures, sampling times, and postprandial states, but the relative differences (%) were small in magnitude. Our study suggests that measurement precision is improved by measuring animals at consistent environmental temperatures close to their preferred thermal range. We propose a standardized protocol of measurement conditions to facilitate laboratory and field use of BIA for body composition assessment studies in turtles.

Field-based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning.

Loss of adipose tissue in vertebrate wildlife species is indicative of decreased nutritional and health status and is linked to environmental stress and diseases. Body condition indices (BCI) are commonly used in ecological studies to estimate adipose tissue mass across wildlife populations. However, these indices have poor predictive power, which poses the need for quantitative methods for improved population assessments. Here, we calibrate bioelectrical impedance spectroscopy (BIS) as an alternative approach for assessing the nutritional status of vertebrate wildlife in ecological studies. BIS is a portable technology that can estimate body composition from measurements of body impedance and is widely used in humans. BIS is a predictive technique that requires calibration using a reference body composition method. Using sea turtles as model organisms, we propose a calibration protocol using computed tomography (CT) scans, with the prediction equation being: adipose tissue mass (kg) = body mass - (-0.03 [intercept] - 0.29 * length2/resistance at 50 kHz + 1.07 * body mass - 0.11 * time after capture). CT imaging allows for the quantification of body fat. However, processing the images manually is prohibitive due to the extensive time requirement. Using a form of artificial intelligence (AI), we trained a computer model to identify and quantify nonadipose tissue from the CT images, and adipose tissue was determined by the difference in body mass. This process enabled estimating adipose tissue mass from bioelectrical impedance measurements. The predictive performance of the model was built on 2/3 samples and tested against 1/3 samples. Prediction of adipose tissue percentage had greater accuracy when including impedance parameters (mean bias = 0.11%-0.61%) as predictor variables, compared with using body mass alone (mean bias = 6.35%). Our standardized BIS protocol improves on conventional body composition assessment methods (e.g., BCI) by quantifying adipose tissue mass. The protocol can be applied to other species for the validation of BIS and to provide robust information on the nutritional and health status of wildlife, which, in turn, can be used to inform conservation decisions at the management level.

Importance of health assessments for conservation in noncaptive wildlife.

Wildlife health assessments help identify populations at risk of starvation, disease, and decline from anthropogenic impacts on natural habitats. We conducted an overview of available health assessment studies in noncaptive vertebrates and devised a framework to strategically integrate health assessments in population monitoring. Using a systematic approach, we performed a thorough assessment of studies examining multiple health parameters of noncaptive vertebrate species from 1982 to 2020 (n = 261 studies). We quantified trends in study design and diagnostic methods across taxa with generalized linear models, bibliometric analyses, and visual representations of study location versus biodiversity hotspots. Only 35% of studies involved international or cross-border collaboration. Countries with both high and threatened biodiversity were greatly underrepresented. Species that were not listed as threatened on the International Union for Conservation of Nature Red List represented 49% of assessed species, a trend likely associated with the regional focus of most studies. We strongly suggest following wildlife health assessment protocols when planning a study and using statistically adequate sample sizes for studies establishing reference ranges. Across all taxa blood analysis (89%), body composition assessments (81%), physical examination (72%), and fecal analyses (24% of studies) were the most common methods. A conceptual framework to improve design and standardize wildlife health assessments includes guidelines on the experimental design, data acquisition and analysis, and species conservation planning and management implications. Integrating a physiological and ecological understanding of species resilience toward threatening processes will enable informed decision making regarding the conservation of threatened species.

Importancia de los exámenes diagnósticos para la conservación de fauna silvestre Resumen Los exámenes diagnósticos de fauna silvestre ayudan a identificar poblaciones en riesgo por desnutrición, enfermedades infecciosas y disminución poblacional, causadas por impactos antropogénicos. Revisamos los estudios disponibles que llevaron a cabo exámenes diagnósticos en fauna silvestre y diseñamos un marco de trabajo para integrar dichos exámenes en monitoreos poblacionales. Empleando un enfoque sistemático, evaluamos aquellos estudios que examinaban múltiples indicadores de salud en vertebrados no cautivos entre 1982 y 2020 (n = 261 estudios). Cuantificamos las tendencias estadísticas, clasificadas por taxones, del diseño del estudio y de los métodos diagnósticos usando modelos lineales generalizados, análisis bibliométricos y representaciones visuales del lugar de estudio versus los hotspots (puntos calientes) de biodiversidad. Sólo el 35% de los estudios incluían colaboraciones internacionales o transfronterizas, y los países ricos en biodiversidad y especies amenazadas estaban gravemente subrepresentados. Las especies no clasificadas como amenazadas en la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza representaban el 49% de las especies examinadas; una tendencia posiblemente asociada al enfoque regional de la mayoría de los estudios. Recomendamos encarecidamente seguir protocolos diagnósticos y manuales de técnicas del estudio de la fauna silvestre, además de usar tamaños muestrales estadísticamente adecuados al establecer rangos de referencia. Los métodos diagnósticos más comunes para todos los taxones fueronanálisis sanguíneos (89%), evaluaciones de composición corporal (81%), exámenes físicos (72%) y análisis fecales (24% de los estudios). Presentamos un marco conceptual para mejorar y estandarizar los exámenes diagnósticos en estudios de fauna silvestre; dicho marco incluye guías para el diseño experimental, para la obtención y el análisis de datos, y para elaborar planes de acción para especies amenazadas. La combinación de conocimientos fisiológicos y ecológicos, relacionados con la resiliencia biológica de especies amenazadas, facilitará una toma de decisiones eficiente para el manejo y para la conservación de la biodiversidad.

Haematological and biochemical reference intervals for wild green turtles (Chelonia mydas): a Bayesian approach for small sample sizes.

Animal health is directly linked to population viability, which may be impacted by anthropogenic disturbances and diseases. Reference intervals (RIs) for haematology and blood biochemistry are essential tools for the assessment of animal health. However, establishing and interpreting robust RIs for threatened species is often challenged by small sample sizes. Bayesian predictive modelling is well suited to sample size limitations, accounting for individual variation and interactions between influencing variables. We aimed to derive baseline RIs for green turtles (Chelonia mydas) across two foraging aggregations in North Queensland, Australia, using Bayesian generalized linear mixed-effects models (n = 97). The predicted RIs were contained within previously published values and had narrower credible intervals. Most analytes did not vary significantly with foraging ground (76%, 22/29), body mass (86%, 25/29) or curved carapace length (83%, 24/29). Length and body mass effects were found for eosinophils, heterophil:lymphocyte ratio, alkaline phosphatase, aspartate transaminase and urea. Significant differences between foraging grounds were found for albumin, cholesterol, potassium, total protein, triglycerides, uric acid and calcium:phosphorus ratio. We provide derived RIs for foraging green turtles, which will be helpful in future population health assessments and conservation efforts. Future RI studies on threatened species would benefit from adapting established veterinary and biomedical standards.

Disease risk analysis in sea turtles: A baseline study to inform conservation efforts.

The impact of a range of different threats has resulted in the listing of six out of seven sea turtle species on the IUCN Red List of endangered species. Disease risk analysis (DRA) tools are designed to provide objective, repeatable and documented assessment of the disease risks for a population and measures to reduce these risks through management options. To the best of our knowledge, DRAs have not previously been published for sea turtles, although disease is reported to contribute to sea turtle population decline. Here, a comprehensive list of health hazards is provided for all seven species of sea turtles. The possible risk these hazards pose to the health of sea turtles were assessed and "One Health" aspects of interacting with sea turtles were also investigated. The risk assessment was undertaken in collaboration with more than 30 experts in the field including veterinarians, microbiologists, social scientists, epidemiologists and stakeholders, in the form of two international workshops and one local workshop. The general finding of the DRA was the distinct lack of knowledge regarding a link between the presence of pathogens and diseases manifestation in sea turtles. A higher rate of disease in immunocompromised individuals was repeatedly reported and a possible link between immunosuppression and environmental contaminants as a result of anthropogenic influences was suggested. Society based conservation initiatives and as a result the cultural and social aspect of interacting with sea turtles appeared to need more attention and research. A risk management workshop was carried out to acquire the insights of local policy makers about management options for the risks relevant to Queensland and the options were evaluated considering their feasibility and effectiveness. The sea turtle DRA presented here, is a structured guide for future risk assessments to be used in specific scenarios such as translocation and head-starting programs.