J Insect Conserv (2009) 13:429–447 DOI 10.1007/s10841-008-9192-z ORIGINAL PAPER Meta-analysis of survey data to assess trends of prairie butterflies in Minnesota, USA during 1979–2005 Dennis Schlicht Æ Ann Swengel Æ Scott Swengel Received: 6 May 2008 / Accepted: 20 October 2008 / Published online: 25 November 2008 Ó The Author(s) 2008. This article is published with open access at Springerlink.com Abstract During 1993–1996, two teams (Schlicht, recorded non-specialist) species had an even distribution of Swengels) surveyed the same Minnesota prairies, but negative and positive trends. While adjacent sites had sim- without any coordination of sites, routes, methods, dates, ilarly timed decline thresholds (last year when a higher rate and results between teams. In 27 instances, both teams or any individual was recorded vs. first year when all sub- surveyed the same site in the same year between 30 June and sequent indices were lower or zero) within species, these 18 July. For the 18 most frequently recorded species, thresholds were not synchronized among sites in different abundance indices (individuals/h per site) significantly counties. All sites analyzed in this study were preserves covaried between teams for 11 (61%) species, including 2/3 managed primarily with fire. While the ecosystem (or veg- prairie specialists tested. No species significantly correlated etative) approach to reserve selection has been validated in negatively, 17/18 species had positive correlations, and the other studies to be effective at capturing populations of preponderance of positive correlations was significant. associated specialist butterflies, butterfly declines after Swengel indices per hour (two surveyors; unlimited-width reserve designation will likely continue unless the ecosys- transect) averaged 2.42 times Schlicht indices (one sur- tem approach to reserve management includes specific veyor; fixed-width transect). These results demonstrate that consideration of individual butterfly species’ required transect surveys by different teams at the same sites but not resources and management tolerances. the same routes produce similar rankings of species abun- dance among sites. This approach to population monitoring Keywords Atrytone arogos iowa Á Hesperia dacotae Á (transect surveys during the season that covers the most Hesperia ottoe Á Oarisma poweshiek Á Speyeria idalia Á specialist species at once, not necessarily with fixed routes Specialist butterflies Á Prairie management but recording all species seen) might also be appropriate in other regions with high habitat loss and low human popu- lation density. Abundance indices from surveys by seven Introduction teams spanning 1979–2005 were calculated for evaluating population trends. For the five analyzable specialist species, Surveying and monitoring are necessary components of 25/30 population trend tests of a species at a site had a conservation programs, both to identify those species (of negative direction, a highly significant skewing (P \ the ones effectively sampled) that do and do not require 0.0001). By contrast, five ‘‘common’’ (most frequently conservation action, and to assess the efficacy of conser- vation actions (Dennis 1993; Pollard and Yates 1993). Butterfly abundance varies greatly among broods attribut- D. Schlicht able to fluctuations in abundance due to climate and other Iowa Lepidoptera Project, 1108 First Avenue, Center Point, factors (Dennis 1993; Pollard and Yates 1993). As a result, IA 52213, USA long-term monitoring is necessary to assess a butterfly species’ status and trend (Thomas et al. 2002). In England, A. Swengel (&) Á S. Swengel 909 Birch Street, Baraboo, WI 53913, USA weekly counts have occurred long-term on fixed routes, e-mail: [email protected] with results among trained observers validated to be 123 430 J Insect Conserv (2009) 13:429–447 functionally similar (Pollard and Yates 1993). Many isolation, degradation, and unfavorable land use/manage- European countries have similar programs (van Swaay and ment of remaining conserved and unconserved tracts van Strien 2005). These are rigorous monitoring programs, (McCabe 1981; Dana 1991; Schlicht 2001). As a compar- but such data are not available for Minnesota, USA due to ison, long-term monitoring indices were also calculated for limitations of resources and personnel. To obtain long-term the five most abundant butterflies in these surveys. The data, survey results from different teams using different goals of the individual teams’ studies were to assess the methods must be evaluated. An underlying premise of most status of these prairie-specialist species and to document butterfly status/trend assessments is that data from different their habitat and management preferences. The goals of or informal (variable) methodologies can be pooled in this meta-analysis were to assess the comparability of data some manner (Saarinen et al. 2003; Shuey 2005; van among teams, so as to determine whether and how the Swaay and van Strien 2005; van Swaay et al. 2006; teams’ data could be aggregated to analyze status and trend Kuussaari et al. 2007). of key species in major reserves. At the more informal end of the spectrum are collector/ observer records. Such presence/absence records are a function of effort just as abundance indices are (Dennis Methods et al. 1999; Dennis and Thomas 2000), but it is difficult to assess what locations were visited and when, if only Surveys positive data are available. Studies may correct for this bias (Dennis et al. 1999), not correct for this after determining it Two teams conducted transect butterfly surveys in summer to be a minor error in the analyzed dataset (Saarinen et al. in Minnesota: Schlicht during 1993–1997 and 2000 2003), not correct or test for this bias (Parmesan 1996; (Schlicht 1997a, b; Schlicht and Saunders 1993, 1995; Komonen 2007), or conclude that the data can’t be inter- Schlicht 2001, 2003) and Swengels during 1988–1997 preted (Swengel and Swengel 2001a). The datasets in this (Swengel 1996, 1998; Swengel and Swengel 1999a). meta-analysis are more rigorous than collector/observer Numbers of all butterfly species and diurnal Schinia moths records, in that date, effort (hour or km of surveying, or were recorded (see Tables 1 and 2 for scientific names). both), number of surveyor(s), and surveyed species (found Special effort was made to identify and survey habitat of or not) are known for the available datasets, and often target species: for Schlicht, primarily Dakota skipper but weather conditions, time of day, and route location. also regal fritillary, Poweshiek skipperling, and Arogos and Nonetheless, unquantified sources of variation (e.g., dif- Ottoe skippers (‘‘midsummer specialists’’); for Swengels, ferences in exact survey route, although location at the those same species plus ‘‘late-summer specialists’’ scale of site is controlled) are potential sources of error in (Leonard’s and common branded skippers). ‘‘Specialist’’ is this study, requiring more care in interpreting the results. defined as restricted, or nearly so, to native prairie vege- During 1993–1996, two teams—Schlicht (one surveyor) tation, being sensitive to vegetative degradation (Swengel and Swengels (two surveyors)—happened to survey the 1998; Schlicht et al. 2007). The target species were same Minnesota prairies at much the same time in the same selected because these specialists were particularly years, but without any coordination of survey sites, transect restricted in their requirements and/or range, and were of routes, survey methods, survey dates, and results between particular conservation concern, e.g., having a legal status the teams. In this paper, butterfly abundance indices were in the study region (Table 1, Coffin and Pfannmuller 1988). tested for correlation between the two teams at the scale of Methods were similar between the two teams (e.g., both the site and the subsite. Since strong covariance occurred, teams used binoculars for identification), with these dif- thus establishing a validation of data pooling, a calibration ferences. Schlicht included within survey time the of the indices between the two teams was then conducted. collection of voucher specimens, net-and-release identifi- Abundance indices of prairie-specialist butterfly species in cation, and recording of wing wear of target species, while western Minnesota prairies were then calculated for long- Swengels did not use nets, vouchered with photography but term monitoring during 1979–2005 (‘‘monitoring’’ defined deducted that from survey time, and recorded nectar visits here as a time series of population indices used to calculate and behavior of targets. Schlicht used a transect 10 m wide; trend), using not only Schlicht and Swengel surveys but Swengels an unlimited width. Where routes were marked also publicly available data from five other teams. State- on a topographic map in the Schlicht survey reports, dis- listed butterfly and day-flying moths occurring in western tance surveyed was measured from the map for analysis Minnesota prairie (Table 1) are a conservation concern here. Swengels estimated distance surveyed at the time of primarily because of vast prairie destruction (99.6% in each survey, based on site maps and landmarks of known Minnesota) due to conversion to intensive agriculture and distance apart. Schlicht surveys conducted by 1–3 survey- urbanization (Samson and Knopf 1994), as well as ors; when one, occasionally the surveyor wasn’t Schlicht. 123 J Insect Conserv (2009) 13:429–447 431 Table 1 Butterfly and day- Statusa Species