DOI: 10.5061/dryad.1jwstqjs6
title: Data in support of: Species-specific interactions in an avian-bryophyte dispersal network

description: Animal dispersal of plant propagules fundamentally alters the success of
 dispersal events, and thus shapes plant community composition through
 time. While this is well-documented in seed plants, spore-bearing plants
 have received little attention with regard to this phenomenon. Birds are
 particularly attractive as a potential bryophyte dispersal vector given
 their highly motile nature as well as their association with bryophytes
 when foraging and building nests. Despite this, species-specific dispersal
 relationships between birds and bryophytes have never been examined. We
 captured birds in Gifford Pinchot National Forest in the Pacific Northwest
 of the United States to sample their legs and tails for bryophyte spores.
 We found 24 bryophyte species across 34 species of bird. We examined the
 level of specialization 1) within the overall interaction network to
 assess community-level patterns and 2) at the plant species level to
 determine the effect of bird behavioral type on the plant-animal
 interaction. Our results suggest that associations within the network are
 more constrained (specialized) than expected by chance. Additionally, we
 found that avian foraging guild impacted the variety of bryophytes found
 on an individual bird. Foliage gleaners and ground foragers had
 particularly specialized associations within the overall
 disperser-bryophyte network. Our findings suggest that diffuse
 bird-bryophyte dispersal networks are likely to be common in habitats
 where birds readily encounter bryophytes and that further work aimed at
 understanding individual bird-bryophyte species relationships may prove
 valuable in determining nuance within this newly described dispersal
 mechanism.
description: <b>(a) Mist netting and
 sampling birds for bryophytes</b> To sample bird surfaces for
 bryophyte spores, we captured birds along a recreational trail adjacent to
 the Wind River Experimental Forest within Gifford Pinchot National Forest,
 WA, Pacific Northwest, USA. We deployed ten 12-x-3m, 30 mm mesh mist nets
 from dawn to midafternoon throughout an Oregon Ash (<i>Fraxinus
 latifolia </i>Bentham) forest, surrounding a banding station at 45
 48’40” N, 121 56’35” W. We checked nets at least every 30 minutes,
 retaining birds for banding and sampling prior to release. Our site is
 adjacent to mixed Western Hemlock (<i>Tsuga heterophylla
 </i>Sargent) and Douglas-Fir (<i>Pseudotsuga menziesii
 </i>(Mirbel)) forest, and is bounded on one side by a small patch of
 meadow. The variety of surrounding habitat at our field site generated a
 diversity of avifauna with different habitat and foraging predilections.
 We sampled the legs and tails of each captured individual for bryophytes
 using cotton swabs (see [54] for details). Birds were additionally fitted
 with individually numbered USGS leg bands to account for recaptures. Avian
 capture data, along with age, sex, and morphometrics were submitted to the
 USGS Bird Banding Laboratory. In order to better contextualize the
 bryophytes sampled from bird surfaces relative to the abundance of
 bryophytes in our field site, we measured the cover of bryophytes on both
 tree trunks and the ground by quadrat sampling every 10 meters along
 multiple transects. We sampling along transects both in the Oregon Ash
 dominant forest that contained our mist nets, as well as adjacent Douglas
 Fir dominant forest. <b>(b) Sample processing and
 molecular methods</b> Samples were vortexed twice
 each for one minute in filtered tap water and vacuum filtered onto gridded
 0.45 µm mixed cellulose ester membranes (EMD Millipore). We placed filters
 onto 60-x-15 mm petri plates containing BCD nutrient agar [55] and grew
 them under a 12:12 L:D light cycle at approximately 500 lux at room
 temperature (22-25°C). Plates that germinated over the next year were
 stored and later sampled for tissue. DNA was extracted using the
 manufacturer’s protocol (Sigma Aldrich Extract-N-Amp PCR kit) and frozen
 for storage. Samples were later thawed and the trnF-L region [56–59] of
 the chloroplast genome was amplified via PCR using the manufacturer’s
 protocol. PCR products were Sanger sequenced on ABI 3730xl instruments
 (Functional Biosciences, Inc.). Additionally, we sequenced known species
 collected at our field site to improve our ability to confirm species
 identification.    <b>(c) Sequence processing and tree
 building</b> We aligned forward and
 reverse Sanger reads to generate a consensus sequence for each sample,
 which we then trimmed to remove primer annealing sites. Samples were then
 preliminarily identified by comparison with NCBI accessioned trnF-L
 sequences via BLAST search [60]. Both bird swab and known field sample
 sequences were aligned in Geneious (v. 8.0.5) and used to build an UPGMA
 tree using the <i>ape </i>and <i>phangorn
 </i>packages in the R statistical computing platform version 3.3.3
 [61–63]. Known samples from the field were used to confirm avian-derived
 sample identities before being removed from the tree. One
 <i>Orthotrichum</i> grouping of sequences failed to align
 appropriately within our tree and was removed from our analysis of
 phylogenetic distance. Finally, the single <i>Marchantia</i>
 sample in our dataset was removed prior to analyzing phylogenetic because
 it proved to be an overly influential outgroup, resulting in our final
 tree. Both avian species and family were substituted for bryophyte species
 names in separate trees for use in analyzing phylogenetic distance, and
 individual species associations plotted across the bryophyte
 phylogeny. <b>(d) Data
 analysis</b> Avian-bryophyte
 dispersal networks were assessed by examining bipartite (two level)
 ecological network structure. While initially developed for assessing the
 interaction between two trophic levels, these methods have since been
 applied to a variety of interaction networks, including dispersal networks
 [64,65]<b>. </b>The level of specialization (H2’) of the
 overall network was assessed using an information theoretic approach
 derived from Shannon’s Diversity Index. This global network index was then
 compared to a null distribution of specialization developed by iterating
 species interactions over 1000 runs while maintaining species abundances
 present in the original dataset [66]. Significance (p value) of a given
 network-level degree of specialization when compared to a random
 distribution of associations can be derived as the proportion of values of
 the random distribution of values that exceed or are equal to the observed
 H2’ [67]. We conducted a similar analysis on subsets of the interaction
 network based on avian behavioral group, allowing for a comparison of
 specialization across behavioral groups. We additionally calculated
 species-level specialization (d’) of the bryophytes in the overall
 avian-association network, as well as subset networks defined by avian
 behavioral guild [68]. We assessed how avian foraging guild impacts
 bryophyte specialization by building linear models comparing d’ for each
 bryophyte species in the total dataset to d’ within networks constructed
 from individual behavioral types. We analyzed Faith’s
 Phylogenetic Distance (PD) by treating each avian species as an aggregate
 “site” type, calculating the minimal path of connectivity across the
 bryophyte tree of all species found on each individual bird species
 (Figure S3). For each species, a sample-size controlled null distribution
 was generated by permuting bryophyte species identities randomly 1000
 times across the tree and calculating minimal path of connectivity [69].
 Observed values of PD were compared with the mean ± 95% CI of the null
 distributions to determine whether avian-vectored bryophyte species were
 more clumped than random. Analyses and visualizations were constructed in
 R using the <i>bipartite</i>, <i>picante</i>, and
 <i>ggplot2</i> packages [70–72].