Of detectability and camouflage: evaluating Pollard Walk rules using a common, cryptic butterfly

Federico Riva,Scott E Nielsen,Giorgio Gentile,Simona Bonelli,Francisco V Denes,John H Acorn,Andrew D Crosby

doi:10.1002/ecs2.3101

Abstract

AbstractEstimating distribution and abundance of species depends on the probability at which individuals are detected. Butterflies are of conservation interest worldwide, but data collected with Pollard walks—the standard for national monitoring schemes—are often analyzed assuming that changes in detectability are negligible within recommended sampling criteria. The implications of this practice remain poorly understood. Here, we evaluated the effects of sampling conditions on butterfly counts from Pollard walks using the Arctic fritillary, a common but cryptic butterfly in boreal forests of Alberta, Canada. We used an open population binomial N‐mixture model to disentangle the effects of habitat suitability and phenology on abundance of Arctic fritillaries, and its detectability by sampling different conditions of temperature, wind, cloud cover, and hour of the day. Detectability varied by one order of magnitude within the criteria recommended for Pollard walks (P varying between 0.04 and 0.45), and simulations show how sampling in suboptimal conditions increases substantially the risk of false‐absence records (e.g., false‐absences are twice as likely than true‐presences when sampling 10 Arctic fritillaries at P = 0.04). Our results suggest that the risk of false‐absences is highest for species that are poorly detectable, low in abundance, and with short flight periods. Analysis with open population binomial N‐mixture models could improve estimates of abundance and distribution for rare species of conservation interest, while providing a powerful method for assessing butterfly phenology, abundance, and behavior using counts from Pollard walks, but require more intensive sampling than conventional monitoring schemes.

Highlights

Species’ distribution and abundance are the two most common state variables in ecology (Krebs 1972, Kery and Schaub 2012)
Evaluating the recommended sampling conditions for Pollard walks (PW), we found that P varies between a minimum of
Results are especially important in relation to initiatives such as the European Butterfly Monitoring scheme, a continental effort that includes more than 6200 PW transects that have been sampled for decades, recording more than 400 species and used to inform the protection and management of habitats and species in Europe

Summary

Introduction

Species’ distribution and abundance are the two most common state variables in ecology (Krebs 1972, Kery and Schaub 2012). To estimate distribution and abundance, ecologists have historically drawn upon counts of organisms, treating them either as indices of abundance or censuses (Krebs 1972, Kery and Schaub 2012). Ability to understand the ecology, abundance, and distribution of organisms (Brown and Boyce 1998, MacKenzie et al 2002, Ancona et al 2017). Because ignoring imperfect detection can result in biased estimates of diversity, occupancy, and abundance (Kery and Plattner 2007, Jarzyna and Jetz 2016, Ancona et al 2017), ecologists have developed techniques to account for detectability (MacKenzie et al 2002, Nowicki et al 2008). Methods designed to incorporate the observation process are often not used, especially for insects (Nowicki et al 2008, Kellner and Swihart 2014)

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Discussion

Conclusion