Conservation of a flagship species: Health assessment of the pink land iguana, Conolophus marthae.
Giuliano ColosimoGabriele GentileCarlos A VeraChristian SevillaGlenn P GerberHans D WestermeyerGregory A LewbartPublished in: PloS one (2022)
The pink land iguana, Conolophus marthae, is one of four species of iguanas (three terrestrial and one marine) in the Galápagos Islands, and the only one listed as critically endangered by the IUCN. The species can only be found on the north-west slopes of the highest volcano on Isabela Island and was first described to science in 2009. As part of a population telemetry study, a health assessment was authorized by the Galápagos National Park. Wild adult iguanas were captured on Wolf Volcano in September 2019 and April 2021 to record morphological and physiological parameters including body temperature, heart rate, intraocular pressures, tear formation, and infrared iris images. Blood samples were also collected and analyzed. An i-STAT portable blood analyzer was used to obtain values for base excess in the extracellular fluid compartment (BEecf), glucose (Glu), hematocrit (HctPCV), hemoglobin (Hb), ionized calcium (iCa), partial pressure of carbon dioxide (pCO2), partial pressure of oxygen (pO2), percent oxygen saturation (sO2%), pH, potassium (K), and sodium (Na). When possible, data were compared to previously published and available data for the other Galápagos iguanas. The results reported here provide baseline values that will be useful in detecting changes in health status among pink land iguanas affected by climate change, invasive species, anthropogenic threats, or natural disturbances. The collected data also provide an invaluable resource for conservation scientists planning to implement conservation strategies, like translocations, that may temporarily alter these baseline values.
Keyphrases
- climate change
- heart rate
- public health
- carbon dioxide
- electronic health record
- healthcare
- human health
- genetic diversity
- big data
- heart rate variability
- blood pressure
- mental health
- deep learning
- cell proliferation
- machine learning
- optical coherence tomography
- metabolic syndrome
- young adults
- blood glucose
- type diabetes
- adipose tissue
- risk assessment
- weight loss