Evaluation of three field monitoring-density estimation protocols and their relevance to Komodo dragon conservation

Finding practical ways to robustly estimate abundance or density trends in threatened species is a key facet for effective conservation management. Further identifying less expensive monitoring methods that provide adequate data for robust population density estimates can facilitate increased investment into other conservation initiatives needed for species recovery. Here we evaluated and compared inference-and cost-effectiveness criteria for three field monitoring-density estimation protocols to improve conservation activities for the threatened Komodo dragon (Varanus komodoensis). We undertook line-transect counts, cage trapping and camera monitoring surveys for Komodo dragons at 11 sites within protected areas in Eastern Indonesia to collect data to estimate density using distance sampling methods or the Royle-Nichols abundance induced heterogeneity model. Distance sampling estimates were considered poor due to large confidence intervals, a high coefficient of variation and that false absences were obtained in 45 % of sites where other monitoring methods detected lizards present. The Royle-Nichols model using presence/absence data obtained from cage trapping and camera monitoring produced highly correlated density estimates, obtained similar measures of precision and recorded no false absences in data collation. However because costs associated with camera monitoring were considerably less than cage trapping methods, albeit marginally more expensive than distance sampling, better inference from this method is advocated for ongoing population monitoring of Komodo dragons. Further the cost-savings achieved by adopting this field monitoring method could facilitate increased expenditure on alternative management strategies that could help address current declines in two Komodo dragon populations.

Comprehensive profiling and quantitation of amine group containing metabolites

Primary and secondary amines, including amino acids, biogenic amines, hormones, neurotransmitters, and plant siderophores, are readily derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate using easily performed experimental methodology. Complex mixtures of these amine derivatives can be fractionated and quantified using liquid chromatography–electrospray ionization-mass spectrometry (LC–ESI-MS). Upon collision induced dissociation (CID) in a quadrupole collision cell, all derivatized compounds lose the aminoquinoline tag. With the use of untargeted fragmentation scan functions, such as precursor ion scanning, the loss of the aminoquinoline tag (Amq) can be monitored to identify derivatized species; and the use of targeted fragmentation scans, such as multiple reaction monitoring, can be exploited to quantitate amine-containing molecules. Further, with the use of accurate mass, charge state, and retention time, identification of unknown amines is facilitated. The stability of derivatized amines was found to be variable with oxidatively labile derivatives rapidly degrading. With the inclusion of antioxidant and reducing agents, tris(2-carboxyethyl)-phosphine (TCEP) and ascorbic acid, into both extraction solvents and reaction buffers, degradation was significantly decreased, allowing reproducible identification and quantification of amine compounds in large sample sets.