DOI: 10.5061/dryad.w9ghx3fw9
title: Data from: Species morphology better predicts plant-hummingbird interactions across elevations than nectar traits

description: Species traits greatly influence interactions between plants and
 pollinators where floral nectar is the primary energy source fostering
 this mutualism. However, very little is known about how nectar traits
 mediate interactions in pollination networks compared to morphological
 traits. Here, we evaluated the role of morphological and nectar traits in
 shaping plant-hummingbird interaction networks along an elevation
 gradient. For this, we assessed patterns in floral phenotypic traits and
 network properties of plant species across elevations in Costa Rica. We
 also analysed whether plant species with generalised flower traits are
 ecological generalists and how morphological trait matching vs nectar
 traits affect interactions. We found marked variation in floral phenotypic
 traits and flower abundance of hummingbird-visited plant species across
 ten sites along the elevation gradient. We did not find evidence for a
 relationship between flower morphology and nectar traits or between
 morphological and ecological generalisation of plant species.
 Plant-hummingbird interaction frequency increased when the lengths of
 hummingbird bill and flower corolla were similar, indicating morphological
 matching, whereas nectar traits were unrelated to interactions. While
 nectar may play a difficult-to-detect secondary role within
 plant-hummingbird networks, our results reinforce the idea that
 morphological matching is an important factor structuring ecological
 communities.
description: <strong>Next, we include a summary of the methods and
 analyses we used in our study</strong>
 <strong>Species morphological
 traits</strong> We included in our analysis
 morphological traits of interacting species that have been reported to
 affect plant–hummingbird interactions. For plants, we measured total
 corolla length, corolla curvature and width of the corolla opening for 59
 plant species. For hummingbirds, we measured total bill length (distance
 from tip to nostril) and curvature of 220 individuals belonging to 22
 species (n = 10 per species). Measurements were taken from photos of fresh
 flowers and mist-netted hummingbird individuals in the field, complemented
 with museum specimens, and then processed with ImageJ software.
 <strong>Nectar traits and flower
 abundance</strong> We quantified daily nectar
 production and concentration per flower for common plant species visited
 by hummingbirds in the understory. We sampled these nectar traits from
 flowers that were bagged with nylon netting (~0.5-1 mm mesh size) prior to
 anthesis to prevent visitation by animal pollinators during 24 h. After
 this period, nectar was extracted with microcapillaries (10 and 15 µl
 capacity), obtaining its volume, and sugar concentration was measured by
 using a calibrated pocket refractometer (REED R9500 Brix Refractometer;
 range concentration 0-32%, g sugar per 100 g nectar). To assess patterns
 in hummingbird floral resources across elevations, in addition to
 quantifying nectar, we counted open flowers in these plants, identified
 them to species level and calculated the mean number of flowers per
 individual across species.
 <strong>Plant-hummingbird
 interactions</strong> To record the interactions
 between plant and hummingbird species in the understory, we used
 time-lapse cameras combined with automated computer vision review. Along
 the sampling transects, we placed unattended cameras on flowers that fit
 the traditional ornithophilous syndrome, i.e. those with tubular-red,
 -yellow, or -purple corollas, scentless and no landing platforms, roughly
 in proportion to their abundance. Because hummingbird-visited flowers do
 not always have these characteristics, we also considered plant species
 that fit other syndromes (e.g. bat- or insect-pollinated flowers) known to
 be visited by hummingbirds based on field observations and previous
 research. <strong>Statistical
 analysis</strong> <strong>(i) Flower
 morphology as predictor of nectar traits across
 elevations</strong> We performed phylogenetic
 generalised least squares (PGLS) to analyse (i) the variation in floral
 phenotypic traits (morphological and nectar traits) and flower abundance
 of plant species visited by hummingbirds across elevation and (ii) the
 extent to which flower morphology predicts nectar traits.
 <strong>(ii) Morphological and nectar traits as predictors
 of network metrics across elevations</strong> We
 analysed how flower phenotypic traits (morphology and nectar) influenced
 two measures of network structure: ecological specialisation and closeness
 centrality, which reflect the role and position of plant species in the
 studied communities, respectively. <strong>(iii)
 Morphological vs nectar traits as predictors of plant-hummingbird
 interactions</strong> We analysed the effect of
 species morphology on plant-hummingbird interactions by calculating the
 degree of mismatch between corresponding pairs of morphological traits
 (bill-corolla length and bill-corolla curvature) and considering a barrier
 to nectar access for each pairwise interaction. To simultaneously evaluate
 the effect of morphological and nectar traits on species interactions, we:
 (i) fitted a full generalised linear mixed model with negative binomial
 error distribution  (GLMM) as suggested for overdispersed count data,
 where we included plant-hummingbird interaction frequency as the response
 variable with an offset term on the cumulative sampling hours for each
 plant species due to its influence in the dependent variable, and seven
 fixed effects and (ii) conducted automated selection to identify minimal
 adequate models from the full model that best explain the effect of
 morphological and nectar traits on interaction frequency.
description: # Species morphology better predicts plant-hummingbird interactions across
 elevations than nectar traits This repository contains three R scripts and
 a data folder with three CSV files. The R scripts are named
 "Plant.species.level.1.R", "Plant.species.level.2.R",
 and "Interactions.level.R". The scripts
 "Plant.species.level.1.R" and
 "Plant.species.level.2.R" use the CSV file
 "1_Plant_level.csv" as data, and the
 "3_Interactions_level.R" script uses the
 "2_Interactions_level.csv" file. The ‘trees.zip’ folder includes
 the 1000 phylogenetic trees needed for the phylogenetic models for
 analyses in “Plant.species.level.1.R” and “Plant.species.level.2.R”. ###
 Scripts 1. Plant.species.level.1.R: This script assesses patterns in
 floral phenotypic traits and flower abundance of plant species along an
 elevation gradient and to what extent flower morphology predicts nectar
 traits. 2. Plant.species.level.2.R: This script assesses the influence of
 phenotypic traits and elevation on ecological generalization and
 centrality of plant species in the networks. 3. Interactions.level.R: This
 script analyzes the relative importance of species morphology and nectar
 traits in shaping plant-hummingbird interactions across elevations. These
 scripts were run in R v4.3.3, the necessary packages are specified within
 each script. The CSV files are placed in the working directory, and the
 trees are stored in a folder called "trees" within the working
 directory. The CSV files should be placed in the working directory, and
 the trees should be in a folder named "trees" within the working
 directory. ### CSV Files The `Plant.species.level.csv` file contains data
 grouped by plant species and includes the following variables: *
 “species”: plant species * “Volume”: nectar volume in microliters *
 “Concent” : nectar concentration in °Brix * “sugarmass” : nectar
 concentration in grams of sugar * “Fl_length”: corolla length in
 millimeters * “Fl_curva”: corolla curvature in millimeters -1 *
 “Fl_opening”:corolla opening in millimeters * “MeanElev”: Mean elevation
 in meters * “Abund_nectar”: Average flower abundance per individual
 sampled for nectar “Abund_transect”:Total flower abundance in the
 transects * “d.mean”: d´  specialization index * “cent.w.mean”: weighted
 closeness centrality * “cent.mean”: closeness centrality The
 `Interactions.level.csv` file contains data grouped by interaction per
 site and includes the following variables: * “Site”: Study site * “Genus”:
 plant genus * “plant_revised_name”: plant species * “Genus_h”: hummingbird
 genus * “hummingbird”: hummingbird species * “NoInterac”: number of
 interactions between a hummingbird species and a plant species at a given
 site * “Sampling.hours”: Number of hours that the cameras filmed the plant
 species at a given site * “bill_diff”: The absolute difference between
 corolla length and bill length * “barrier”: Is 1 if the length of the
 corolla is greater than the length of the bill, and 0 if it is the
 opposite * “curva_diff”: The absolute difference between corolla curvature
 and bill curvature * “Volume”: nectar volume in microliters * “Concent”:
 nectar concentration in °Brix * “Abund_transect”: Total flower abundance
 in the transects * “Abund_nectar”: Average flower abundance per individual
 sampled for nectar * “MeanElev”: Mean elevation in meters