DOI: 10.5061/dryad.2v6wwpzwg
title: Data from: Frugivore traits predict plant-frugivore interactions using generalized joint attribute modeling

description: Under an adaptive hypothesis, the reciprocal influence between mutualistic
 plants and frugivores is expected to result in suites of matching
 frugivore and plant traits that structure fruit consumption. Recent work
 has suggested fruit traits can represent adaptations to broad groups of
 functionally similar frugivores, but the role of frugivore traits and
 within-species variation in structuring fruit consumption is less
 understood. To address these knowledge gaps, we assess the presence of
 reciprocal trait matching for the mutualistic ecological network
 comprising of Carollia bats that feed on and disperse Piper seeds. We used
 generalized joint attribute modeling (GJAM), a Bayesian modeling approach
 that simultaneously accounts for multiple sources of variance across trait
 types. In support of frugivore adaptation to their dietary composition and
 suggesting niche partitioning among Carollia bats, we find differential
 consumption of a suite of Piper species influenced by bat traits such as
 body size; however, the Piper morphological traits considered had no
 effect on bat consumption. Slow evolutionary rates, dispersal by other
 vertebrates, and unexamined fruit traits, such as Piper chemical bouquets,
 may explain the lack of association between bat Piper consumption and
 fruit morphological traits. We have identified a potential asymmetric
 influence of frugivore traits on plant–frugivore interactions, providing a
 template for future trait analyses of plant–animal networks. As
 intraspecific trait variation is rarely included in studies on trait
 matching, this paper contributes to closing that important knowledge gap.
description: # Data from: Frugivore traits predict plant-frugivore interactions using
 generalized joint attribute modeling
 [https://doi.org/10.5061/dryad.2v6wwpzwg](https://doi.org/10.5061/dryad.2v6wwpzwg) Bayesian models relating: 1\. head.R: relates *Carollia* traits to bite force (performance) via hierarchical ML models 2\. carollia3_0.R: relates *Carollia* traits to bite force (performance) via hierarchical Bayesian models 3\. gjam generated model of consumption relationship to traits for *Carollia* bats 4\. gjam processed model outputs 5\. piper.R: relates *Piper* traits and GJAM coefficients obtained from 3 and 4 ## Description of the data and file structure All cells marked as NA lacked data and correspond to missing data. ## Code/Software 1\. head.R: relates *Carollia* traits to bite force (performance) via hierarchical ML models. Requires data file bat_l_biteBody.csv and R library lme4. Prints results to .txt file. 2\. carollia3_0.R: relates *Carollia* traits to bite force (performance) via hierarchical Bayesian models. Requires data file bat_l_biteBody.csv, R library R2Jags, and 3 Jags files. The three Jags files are: * carollia_bf_size.txt * carollia_bf_mass.txt * carollia_bf_head.txt carollia3_0.R prints out the results of hierarchical Bayesian regressions in txt and saves an Rdata file. 3\. niche_Carollia.R: generates gjam model of consumption relationship t traits for *Carollia* bats Requires data files: * carollia_niche_xdata.csv: x or explanatory variables, bat traits * carollia_niche_ydata_trim.csv: y or response variables, bat consumption of *Piper* fruit from different species * carollia_type.csv: individual bat assignment to one of 3 species * and R libraries gjam, reshape2 and plyr plus function * bayesReg.R (which codes a function to run a Tobit and Bayesian regression from the NEON example here: [https://rstudio-pubs-static.s3.amazonaws.com/710083_480b1b43b4f0470691e95302483fdc08.html](https://rstudio-pubs-static.s3.amazonaws.com/710083_480b1b43b4f0470691e95302483fdc08.html)). This script generates the bayesian gjam model and saves an Rdata file. 4\. plot_Carollia_v2.r processes gjam model outputs. Requires data files: * models_Carollia.Rdata * and R libraries gjam, reshape2, plyr, ggplot2, MCMCvis and wesanderson This script generates the standardized summary and prints out a file called piper_medians.csv 5\. piper.R relates *Piper* traits and gjam coefficients obtained from steps 3 and 4.. Requires data files: * piper.nex: phylogeny of *Piper* plants * piper_k_traits.csv: correspondence between *Piper* traits and *Piper* species * output.csv: this is processed from piper_medians.csv to separate relate Piper species to bat trait values resulting from gjam * Requires R libraries MCMCglmm and geiger This script prints out the results of phylogenetic Bayesian regressions of gjam outputs as a function of *Piper* traits in txt and saves a Rdata file.