Evaluating differences in density estimation for central Iowa butterflies using two methodologies
- PMID: 37842044
- PMCID: PMC10569161
- DOI: 10.7717/peerj.16165
Evaluating differences in density estimation for central Iowa butterflies using two methodologies
Abstract
The Pollard-Yates transect is a widely used method for sampling butterflies. Data from these traditional transects are analyzed to produce density estimates, which are then used to make inferences about population status or trends. A key assumption of the Pollard-Yates transect is that detection probability is 1.0, or constant but unknown, out to a fixed distance (generally 2.5 m on either side of a transect line). However, species-specific estimates of detection probability would allow for sampling at farther distances, resulting in more detections of individuals. Our objectives were to (1) evaluate butterfly density estimates derived from Pollard-Yates line transects and distance sampling, (2) estimate how detection probabilities for butterflies vary across sampling distances and butterfly wing lengths, and (3) offer advice on future butterfly sampling techniques to estimate population density. We conducted Pollard-Yates transects and distance-sampling transects in central Iowa in 2014. For comparison to densities derived from Pollard-Yates transects, we used Program DISTANCE to model detection probability (p) and estimate density (D) for eight butterfly species representing a range of morphological characteristics. We found that detection probability among species varied beyond 2.5 m, with variation apparent even within 5 m of the line. Such variation correlated with wing size, where species with larger wing size generally had higher detection probabilities. Distance sampling estimated higher densities at the 5-m truncation for five of the eight species tested. At this truncation, detection probability was <0.8 for all species, and ranged from 0.53 to 0.79. With the exception of the little yellow (Pyrisitia lisa), species with median wing length <5.0 mm had the lowest detection probabilities. We recommend that researchers integrate distance sampling into butterfly sampling and monitoring, particularly for studies utilizing survey transects >5 m wide and when smaller species are targeted.
Keywords: Butterfly; Detection probability; Distance sampling; Pollard-Yates; Program Distance; Wing length.
©2023 Patterson et al.
Conflict of interest statement
The authors declare there are no competing interests.
Figures


Similar articles
-
Determining optimal population monitoring for rare butterflies.Conserv Biol. 2008 Aug;22(4):929-40. doi: 10.1111/j.1523-1739.2008.00932.x. Epub 2008 May 9. Conserv Biol. 2008. PMID: 18477025
-
Road-based line distance surveys overestimate densities of olive baboons.PLoS One. 2022 Feb 2;17(2):e0263314. doi: 10.1371/journal.pone.0263314. eCollection 2022. PLoS One. 2022. PMID: 35108346 Free PMC article.
-
Monitoring butterfly abundance: beyond Pollard walks.PLoS One. 2012;7(7):e41396. doi: 10.1371/journal.pone.0041396. Epub 2012 Jul 30. PLoS One. 2012. PMID: 22859980 Free PMC article.
-
Mimicry in butterflies: co-option and a bag of magnificent developmental genetic tricks.Wiley Interdiscip Rev Dev Biol. 2018 Jan;7(1). doi: 10.1002/wdev.291. Epub 2017 Sep 14. Wiley Interdiscip Rev Dev Biol. 2018. PMID: 28913870 Review.
-
Adaptive evolution of butterfly wing shape: from morphology to behaviour.Biol Rev Camb Philos Soc. 2019 Aug;94(4):1261-1281. doi: 10.1111/brv.12500. Epub 2019 Feb 21. Biol Rev Camb Philos Soc. 2019. PMID: 30793489 Review.
References
-
- Brown JA, Boyce MS. Line transect sampling of Karner blue butterflies (Lycaeides Melissa samuelis) Environmental and Ecological Statistics. 1998;5:81–91. doi: 10.1023/A:1009620105039. - DOI
-
- Brown JA, Boyce MS. A survey design for monitoring butterflies. Statistica. 2001;61:291–299.
-
- Buckland ST. Point-transect surveys for songbirds: robust methodologies. The Auk. 2006;123:345–357. doi: 10.1093/auk/123.2.345. - DOI
-
- Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L. Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press; Oxford: 2001.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources