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A right whale pootree: classification trees of faecal hormones identify reproductive states in North Atlantic right whales (Eubalaena glacialis)
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2017
Source: Conserv Physiol. 2017 Mar 9;5(1):cox006.
[PDF-363.27 KB]
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Journal Title:Conservation Physiology
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NOAA Program & Office:
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Description:Immunoassay of hormone metabolites extracted from faecal samples of free-ranging large whales can provide biologically relevant information on reproductive state and stress responses. North Atlantic right whales (Eubalaena glacialis Müller 1776) are an ideal model for testing the conservation value of faecal metabolites. Almost all North Atlantic right whales are individually identified, most of the population is sighted each year, and systematic survey effort extends back to 1986. North Atlantic right whales number <500 individuals and are subject to anthropogenic mortality, morbidity and other stressors, and scientific data to inform conservation planning are recognized as important. Here, we describe the use of classification trees as an alternative method of analysing multiple-hormone data sets, building on univariate models that have previously been used to describe hormone profiles of individual North Atlantic right whales of known reproductive state. Our tree correctly classified the age class, sex and reproductive state of 83% of 112 faecal samples from known individual whales. Pregnant females, lactating females and both mature and immature males were classified reliably using our model. Non-reproductive [i.e. 'resting' (not pregnant and not lactating) and immature] females proved the most unreliable to distinguish. There were three individual males that, given their age, would traditionally be considered immature but that our tree classed as mature males, possibly calling for a re-evaluation of their reproductive status. Our analysis reiterates the importance of considering the reproductive state of whales when assessing the relationship between cortisol concentrations and stress. Overall, these results confirm findings from previous univariate statistical analyses, but with a more robust multivariate approach that may prove useful for the multiple-analyte data sets that are increasingly used by conservation physiologists.
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Source:Conserv Physiol. 2017 Mar 9;5(1):cox006.
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Pubmed Central ID:PMC5570057
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Rights Information:Public Domain
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Compliance:PMC
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Main Document Checksum:urn:sha256:09f6bb05049e3e878cd9899b49c80608a597c6b432b24a1990d60a2e1f6d017b
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