DOI: 10.5061/dryad.t76hdr7zc
title: Data from: Bee phenology is predicted by climatic variation and functional traits

description: Climate change is shifting the environmental cues that determine the
 phenology of interacting species. Plant-pollinator systems may be
 susceptible to temporal mismatch if bees and flowering plants differ in
 their phenological responses to warming temperatures. While the cues that
 trigger flowering are well-understood, little is known about what
 determines bee phenology. Using Generalized Additive Models, we analyzed
 time-series data representing 67 bee species collected over nine years in
 the Colorado Rocky Mountains to perform the first community-wide
 quantification of the drivers of bee phenology. Bee emergence was
 sensitive to climatic variation, advancing with earlier snowmelt timing,
 while later phenophases were best explained by functional traits including
 overwintering stage and nest location. Comparison of these findings to a
 long-term flower study showed that bee phenology is less sensitive than
 flower phenology to climatic variation, indicating potential for reduced
 synchrony of flowers and pollinators under climate change.
description: We gathered data at 18 sites around the Rocky Mountain Biological
 Laboratory (RMBL) in the Elk Mountains of western Colorado, USA from 2009
 to 2017. Sites were located along an elevation transect (2456-3438 meters
 above sea-level) in montane and sub-alpine habitats dominated by a diverse
 mixture of perennial flowering species. We sampled bees in habitat types
 that were representative of dominant vegetation types: wet meadows
 dominated by <i>Veratrum tenuipetalum</i>, those dominated by
 <i>Salix </i>spp., rocky dry meadows, and <i>Artemisia
 </i>spp. steppe. We conducted biweekly bee abundance surveys at each
 site using pan traps (following LeBuhn et al. 2003). We set out 10 each of
 white, fluorescent yellow, and fluorescent blue pan traps along two
 approx. perpendicular 45-meter transects at intervals of 3 meters, an
 array that passively attracts bees by mimicking a display of flowers. We
 deployed pan traps between at approx. 0800 and 1700 (the period of maximum
 bee activity) only on warm, calm, sunny days and removed traps when these
 conditions changed drastically. Further details of the bee sampling are
 provided by Gezon et al. (2015).<br> <br> The catches per day
 and sampling method are given, and the data processing code is
 included.
description: Several taxonomic groups and sites were excluded for the
 analysis. See the manuscript for details on which species and sites were
 used. We encourage other researchers to use these data for further
 studies, and also to contact Michael Stemkovski (m.stemkovski@gmail.com)
 or Rebecca Irwin (reirwin@ncsu.edu) for insight on the ideosynchrosies of
 the dataset. We wish to enable others to do work using these data. The
 long-term bee phenology monitoring project is an ongoing effort that is
 headed by Rebecca Irwin, so we encourage users to get the most up-to-date
 data at https://osf.io/kmxyn/. The repository on Open Science Framework
 includes more recent years of data since the analysis of the present
 dataset.