Literature DB >> 18477025

Determining optimal population monitoring for rare butterflies.

Nick M Haddad1, Brian Hudgens, Chris Damiani, Kevin Gross, Daniel Kuefler, Ken Pollock.   

Abstract

Determining population viability of rare insects depends on precise, unbiased estimates of population size and other demographic parameters. We used data on the endangered St. Francis' satyr butterfly (Neonympha mitchellii francisci) to evaluate 2 approaches (mark-recapture and transect counts) for population analysis of rare butterflies. Mark-recapture analysis provided by far the greatest amount of demographic information, including estimates (and standard errors) of population size, detection, survival, and recruitment probabilities. Mark-recapture analysis can also be used to estimate dispersal and temporal variation in rates, although we did not do this here. Models of seasonal flight phenologies derived from transect counts (Insect Count Analyzer) provided an index of population size and estimates of survival and statistical uncertainty. Pollard-Yates population indices derived from transect counts did not provide estimates of demographic parameters. This index may be highly biased if detection and survival probabilities vary spatially and temporally. In terms of statistical performance, mark-recapture and Pollard-Yates indices were least variable. Mark-recapture estimates were less likely to fail than Insect Count Analyzer, but mark-recapture estimates became less precise as sampling intensity decreased. In general, count-based approaches are less costly and less likely to cause harm to rare insects than mark-recapture. The optimal monitoring approach must reconcile these trade-offs. Thus, mark-recapture should be favored when demographic estimates are needed, when financial resources enable frequent sampling, and when marking does not harm the insect populations. The optimal sampling strategy may use 2 sampling methods together in 1 overall sampling plan: limited mark-recapture sampling to estimate survival and detection probabilities and frequent but less expensive transect counts.

Mesh:

Year:  2008        PMID: 18477025     DOI: 10.1111/j.1523-1739.2008.00932.x

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


  4 in total

1.  Reconstructing eight decades of genetic variation in an isolated Danish population of the large blue butterfly Maculinea arion.

Authors:  Line V Ugelvig; Per S Nielsen; Jacobus J Boomsma; David R Nash
Journal:  BMC Evol Biol       Date:  2011-07-11       Impact factor: 3.260

2.  Density estimates of monarch butterflies overwintering in central Mexico.

Authors:  Wayne E Thogmartin; Jay E Diffendorfer; Laura López-Hoffman; Karen Oberhauser; John Pleasants; Brice X Semmens; Darius Semmens; Orley R Taylor; Ruscena Wiederholt
Journal:  PeerJ       Date:  2017-04-26       Impact factor: 2.984

3.  Multi-surveyor capture-mark-recapture as a powerful tool for butterfly population monitoring in the pre-imaginal stage.

Authors:  Heiko Hinneberg; Jörg Döring; Gabriel Hermann; Gregor Markl; Jennifer Theobald; Ines Aust; Thomas Bamann; Ralf Bertscheit; Daniela Budach; Jana Niedermayer; Alicia Rissi; Thomas K Gottschalk
Journal:  Ecol Evol       Date:  2022-07-31       Impact factor: 3.167

4.  Monitoring butterfly abundance: beyond Pollard walks.

Authors:  Jérôme Pellet; Jason T Bried; David Parietti; Antoine Gander; Patrick O Heer; Daniel Cherix; Raphaël Arlettaz
Journal:  PLoS One       Date:  2012-07-30       Impact factor: 3.240

  4 in total

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