DOI: 10.5061/dryad.wdbrv15sr
title: Data for: Positive impact of postfire environment on bumble bees not explained by habitat variables in a remote forested ecosystem

description: Bumble bees are important pollinators in temperate forested regions where
 fire is a driving force for habitat change, and thus understanding how
 these insects respond to fire is critical. Previous work has shown bees
 are often positively affected by the post-fire environment, with burned
 sites supporting greater bee abundance and diversity, and increased floral
 resources. The extent to which fire impacts variation in bumble bee site
 occupancy is not well understood, especially in higher latitude regions
 with dense, primarily coniferous forests. Occupancy models are powerful
 tools for biodiversity analyses, as they separately estimate occupancy
 probability (likelihood that a species is present at a particular
 location) and detection probability (likelihood of observing a species
 when it is present). Using these models, we tested whether bumble bee site
 occupancy is higher in burned locations as a result of the increase in
 canopy openness, floral species richness, and floral abundance. We
 quantified the impact of fire, and associated habitat changes, on bumble
 bee species' occupancy in an area with high wildfire frequency in
 British Columbia, Canada. The burn status of a site was the only
 significant predictor for determining bumble bee occurrence (with burned
 sites having higher occupancy); floral resource availability and canopy
 openness only impacted detection probability (roughly, sample bias). These
 findings highlight the importance of controlling for the influence of
 habitat on species detection in pollinator studies and suggest that fire
 in this system changes the habitat for bumble bees in positive ways that
 extend beyond our measurements of differences in floral resources and
 canopy cover.
description: Our study was conducted on the unceded territories of the Nuxalk
 and Ulkatcho First Nations, in and around Tweedsmuir Provincial Park in
 British Columbia, Canada, from June to August 2019 (Fig. 1). We
 established sites both in and adjacent to four wildfire zones, two of
 which are recent burns (2017 and 2018) and two of which are older burns
 (2009 and 2010), though the older burns had not significantly regenerated,
 as high burn severity and high elevation have limited tree and shrub
 regrowth. Three of the burns were large in scale (2,800 to over 7,000
 hectares), and the most recent burn was smaller (40 hectares). The
 unburned sites were in forest habitat adjacent to each of these burned
 areas.  We sampled a total of 26 circular sites of 100m
 diameter, 13 in areas impacted by fire (4 in each large fire and 1 in the
 smaller fire) which we call "burned" sites, and 13 in nearby
 unaffected forest, which we call "unburned" sites. We selected
 sites such that edges were a minimum of 1 km from all other site edges to
 ensure spatial independence, as bumble bee foraging most frequently occurs
 within 1 kilometre of their nest (Greenleaf 2007, Geib 2015, Kendall
 2022). We visited each site twice over the course of the season and, due
 to logistical constraints, sampled groups of 3–8 sites in spatial and
 temporal blocks with block composition differing slightly between visits.
 However, sites were re-sampled in a similar order, such that visits to
 sites were separated by similar time periods (4–6 weeks between
 revisits).  To sample bumble bees, we used blue vane
 traps (three per site), collecting samples after traps had been out for
 2–4 days, in order to ensure minimal negative impacts on bee populations
 (see Kimoto 2012 and Gibbs 2017 for evidence of negative impacts of
 long-term trap collecting). We selected blue vane traps as our primary
 collection method because our site arrangement and sampling structure
 necessitated the use of passive sampling and because previous work has
 shown that blue vanes are one of the most effective for per-sample species
 accumulation (Joshi 2015). Blue vanes are highly attractive to bumble bees
 (Stephen 2007) and have been shown to collect similar species sets to
 those obtained by active netting (Rao 2009). In addition, we performed
 supplementary spot netting surveys, only at burned sites, for 60
 person-minutes per visit either during trap setup or trap take down. We
 did not net bees at unburned sites because, early in the season, many
 unburned sites had few to no open flowers from which we could collect
 bees. Netting was conducted as long as temperature was greater than 15
 degrees C, wind speed was below 2 m/s, and there was no precipitation. We
 identified each bumble bee to species using the key in Williams'
 North American field guide (2014), and follow the bumble bee taxonomy
 therein, with the updated revision to <em>Alpinobombus</em>
 for <em>B. kirbiellus</em> (Williams 2019). 
 During sampling visits, we also recorded site-level habitat
 variables, either when blue vane traps were set up or when they were
 collected. To quantify canopy openness and floral resource availability,
 we established two 100m transects in N-S and E-W directions at each site.
 For canopy openness, we took six evenly-spaced upward-facing photographs
 per transect (using a Canon 5D MK I with Sigma 8mm f/3.5 EX DG Circular
 Fisheye Lens), for a total of 12 photos per site. We counted all open
 flowers from a total of 76 different species (we include a full list of
 floral species and information about attractiveness to bumble bees as a
 supplementary file, Online Resource 1) along each of the 3mx100m
 transects, identified to species or genus using local field guides and
 online resources (Pojar 1994, Parish 1999, e-flora-BC). We calculated
 floral abundance and species richness by pooling open flower counts
 (later, floral abundance was log-transformed) and number of flowering
 plant species across transects. We measured canopy openness at a site
 level (once per site) and floral resource information at a visit level
 (twice per site). To determine canopy openness at each
 site, we analysed the upward fisheye photos in Gap Light Analyser (GLA), a
 program designed for analysis of hemispherical canopy cover photos (Frazer
 1999). We used default settings (Registration: Geographic North, Location:
 none added, Orientation: horizontal,  Topographic shading: Use topographic
 mask data, Solar time step: 2 minutes, Azimuth regions: 36, Zenith
 regions: 9, Data source: modelled, Solar constant: 1367
 Wm<sup>-2</sup>, Cloudiness index: 0.5kt, Spectral fraction:
 0.5, Units: Mols m<sup>-2</sup> d<sup>-1</sup>,
 Beam fraction: 0.5, Sky-region brightness: UOC Model) along with a custom
 projection distortion specific to our lens. GLA relies on contrast between
 sky and foliage to determine percent canopy cover. This required that we
 sometimes draw boundaries manually and then set local thresholds
 accordingly in order to ensure correct classification. We used a blue
 colour plane, as recommended, to enhance contrast between canopy cover and
 sky. In some cases (e.g., when the sun reflected off trees) it yielded a
 "canopy" section that was brighter than sky. To ensure correct
 classification, we manually traced the canopy cover and applied the colour
 fill tool. To calculate canopy cover at the site level, we calculated the
 mean cover across the 12 photos for each site. 
description: All data are in comma-separated variable (.csv) format which can
 be read by any spreadsheet program (Microsoft Excel, Google Sheets, Apple
 Numbers) or any text editor. All code is in .R format, which can be read
 by any text editor and interpreted by the R program.