Kophamel Sara, Rudd Donna, Ward Leigh C, Shum Edith, Ariel Ellen, Mendez Diana, Starling Jemma, Mellers Renee, Burchell Richard K, Munns Suzanne L
College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, 4811, Australia.
School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, 4072, Australia.
Conserv Physiol. 2022 Jul 7;10(1):coac043. doi: 10.1093/conphys/coac043. eCollection 2022.
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 () across two foraging aggregations in North Queensland, Australia, using Bayesian generalized linear mixed-effects models ( = 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.
动物健康与种群生存能力直接相关,而种群生存能力可能受到人为干扰和疾病的影响。血液学和血液生化的参考区间(RIs)是评估动物健康的重要工具。然而,为濒危物种建立和解释可靠的参考区间常常受到样本量小的挑战。贝叶斯预测模型非常适合样本量限制,能够考虑个体差异以及影响变量之间的相互作用。我们旨在利用贝叶斯广义线性混合效应模型(n = 97),得出澳大利亚北昆士兰两个觅食聚集地绿海龟()的基线参考区间。预测的参考区间包含在先前公布的值范围内,且可信区间更窄。大多数分析物在觅食地(76%,22/29)、体重(86%,25/29)或曲甲壳长度(83%,24/29)方面没有显著差异。在嗜酸性粒细胞、嗜异性粒细胞:淋巴细胞比率、碱性磷酸酶、天冬氨酸转氨酶和尿素方面发现了长度和体重效应。在白蛋白、胆固醇、钾、总蛋白、甘油三酯、尿酸和钙:磷比率方面,发现觅食地之间存在显著差异。我们提供了觅食绿海龟的推导参考区间,这将有助于未来的种群健康评估和保护工作。未来对濒危物种的参考区间研究将受益于采用既定的兽医和生物医学标准。