ESR 34:323-337 (2017)  -  DOI: https://doi.org/10.3354/esr00855

ABSTRACT: Monitoring animal populations is essential to conservation, and complex monitoring goals require complex resources. Variable detection probabilities can create uncertainty in trends and abundances estimated from point count surveys (e.g. nest counts), as well as from more expensive monitoring methods such as line transect surveys (e.g. aerial surveys). Point count surveys in the form of nest counts are the most common form of sea turtle population monitoring, although in-water aerial surveys are also conducted. We used a loggerhead sea turtle Caretta caretta population model to generate stochastic ‘known’ populations from which we mimicked the information we would obtain from nest counts and from in-water aerial surveys. We subjected the populations to environmental or anthropogenic impacts and compared trends in each monitoring metric with the trend in simulated turtle population size in terms of adult equivalents. Over long time frames, either monitoring scheme performed equally well (mean population growth rates λ over 50 yr were within 1% of the growth rate estimated from simulated adult equivalents). Over shorter time frames, total adult females estimated from simulated nest counts generally tracked closer to adult equivalents than did abundance estimated from simulated aerial surveys; and λ for the nest count metric generally had a lower median absolute relative error. Aerial surveys added value if population impacts affected young turtles (which can take 20-30 yr to become nesters) or if impacts changed the population structure (e.g. changed the stable age distribution). For effective monitoring over short time frames, both monitoring schemes might be warranted.

KEY WORDS: Loggerhead · Caretta caretta · Nest counts · Line transect survey · Simulation · Abundance index · Adult equivalent

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Cite this article as: Warden ML, Haas HL, Richards PM, Rose KA, Hatch JM (2017) Monitoring trends in sea turtle populations: walk or fly? Endang Species Res 34:323-337. https://doi.org/10.3354/esr00855 Export citation Share:    Facebook - - linkedIn