Data from: The biodiversity of plant-frugivore interactions: types, functions, and consequences
Data files
Apr 10, 2026 version files 2.26 MB
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data.tsv
45.10 KB
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frug-mut_gradient.tsv
4.75 KB
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funct.tsv
5.60 KB
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prunus_data.zip
28.98 KB
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RCode.zip
2.14 MB
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README.md
21.25 KB
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SDE_euterpe.txt
2.68 KB
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SDE_prunus.txt
3.18 KB
Abstract
Pairwise plant-frugivore mutualistic interactions build up into mega-diverse networks involving dozens of interacting species, being among the most generalized interactions occurring in free-living species. These mutualisms consist of food provisioning by plants and their counterpart, plant propagule (seeds) movement by the animals, being crucial for the natural vegetation regeneration in many ecosystems. Yet we are far from understanding which part of this enormous interaction biodiversity is needed for their maintenance. I overview the diversity of interaction modes involved in these mutualisms, the main components of the seed dispersal services, and their functional diversity. I examine how interaction richness covaries with partner species richness at different scales, resulting in variable patterns of species complementarities in terms of seed dispersal effects. The functionality of most generalized plant-frugivore mutualisms relies on complementarity of effects across a high diversity of partners, yet frequently depends on just a distinct subset of them, resulting in high functional redundancy. Two distinct aspects are relevant: 1) variable quantitative effects among species; 2) variable pairwise-interaction outcomes, between the extremes of antagonism and mutualism. Frugivory, occurring at the final stage of each plant reproductive episode, entails a large, cumulative, effect of other biotic interactions occurring at earlier stages (e.g., floral herbivory, pollination, pre-dispersal fruit damage). I examine how plant-frugivore interactions mix-up with the whole biotic interactome of a plant, using the Prunus mahaleb system as a case study. The effects of distinct subsets of frugivores combine with different sets of antagonistic and mutualistic partners in other interactions, yet having a lasting signal on final seed dispersal success.
Data and code accompanying paper in Oikos Special Issue on Frugivory and Seed Dispersal (for the FSD 2024 symposium, Ilhéus, Brazil). preprint doi: 10.1101/2025.11.14.688423
This repository includes both datasets and code for analyses. Please see the main paper and the Supplementary Material.
author:
name: Pedro Jordano
affiliation:
name: Estación Biológica de Doñana, CSIC and Dept. Biol. Vegetal y Ecología, Universidad de Sevilla
date: 2025-01-21
orcid: 0000-0003-2142-9116
email: jordano@ebd.csic.es
city: Sevilla, Spain
Sharing/Access information
Links to other publicly accessible locations of the data:
- GitHub repository: https://github.com/pedroj/oikos_2026_si_frugivory
- Data on Euterpe edulis can be accessed here.
Dataset contents
Folder and file structure:
Supplementary information:
SupplMat-OIK-11991.pdf
Supplementary material accompanying the Oikos paper.
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ms_figures_files.zip
Container with the figures in pdf format.
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On Dryad
RCode.zip
R code for data analysis. (See below for full description).
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data.tsv
Biodiversity data for plant-frugivore mutualistic assemblages.
Dataset: number of interactions and nodes in plant-frugivore interaction networks.
Variables included:
id: number ID. of dataset.
code: sp, species-based network; ind: individual-based network.
sp: plant species name and family.
P: number of plant species (for sp-based networks) or plant individuals (for individual-based networks) studied.
A: number of animal species.
S: total number of nodes in the network (A+P).
I: number of distinct interactions in network.
C: connectance (C= i/(A+P)).
biome: t, tropical; nt: non-tropical.
site: study locality.
reference: Bibliographic reference.
Reference for data: Quintero et al. 2025. PNAS, doi= 10.1101/2024.02.02.578595.
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frug-mut_gradient.tsv
Body mass, percent mutualistic interaction outcomes, and type of fruit consumption/dispersal for the assemblages of Prunus mahaleb and Euterpe edulis.
From Jordano and Schupp (2000) and Galetti et al. (2013).
Variables included:
species: Frugivore species.
sp_plant: Plant species.
type: Frugivore type (seed disperser, pulp consumer, seed predator, seed disperser/pulp consumer, seed predator/pulp consumer).
pct_mut: percent fruits handled with seed ingested and dispersed away from plant.
body_mass: Body mass (g).
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funct.tsv
Functional data. Prunus mahaleb. Euterpe edulis.
Data from Jordano and Schupp 2000. Jordano et al. 2025. and Galetti et al. 2013. Additional morphological data for Euterope edulis from Bovo et al. 2018. For Prunus mahaleb. abundance data derived from N= 43 transect censuses of total length 66.4 km and totalling 4218 birds recorded. For Euterpe edulis.
Variables included:
species: Frugivore species.
plant: Plant species.
type: Frugivory type (see above).
frug: Percentage of diet made up of fleshy fruits (by volume).
bmass: Body mass (g).
gape: Gape width (mm) measured at the mouth commisures.
vis.10h: Visit rate to the tree, no. visits/10 h.
pct_mut: Perecentage of mutualistic interactions: based on % fruit swallowed.
birds.km: No. birds recorded per km census.
contrib_FD: Contribution to FD value. Species-specific contribution to FD. The product of the species' visitation rate (vis.10h) and total FD value for the plant. divided by the total number of visits of all frugivore species (sum(vis.10h)).
eff_per_vis: Seed disperser effectiveness per visit: no. seeds estimated to be removed from maternal tree per visit.
eff_total: vis.10h * eff_per_vis.
prop_disp_service: Proportion of species eff_total relative to the pooled value for the whole frugivore assemblage.
Abundance data (birds.km) refers to IPA from transect censuses in non-defaunated areas of SE Brazil Mata Atlantica (Galetti et al. 2013).
Visitation data (no. visits per 10h) were obtained by direct focal watches at fruiting trees for 336 h (16 tree-days per two seasons) in Prunus mahaleb and 2326 h in Euterpe edulis.
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SDE_euterpe.txt, SDE_prunus.txt
Two datasets with effectiveness components for the two studied plant species.
Prunus mahaleb frugivore assemblage. Jordano & Schupp (2000) Ecological Monographs.
Visitation data come from 107.3 h direct watches.
Variables included:
abundance- Mean no. birds censused/km, averaged for two study years.
visits- Mean no. visitis recorded to fruiting trees (/10 h).
prop_visits- Proportion of total visits recorded (feeding records) contributed by species. Relative to the total no. records in two study years.
eff_per_vis- Mean no. fruits swallowed per visit (successfully dispersed seeds).
eff_total- Visit rate * eff_per_vis*prop fruits swallowed
prop_disp_service- Proportion of total dispersal service contributed by species.
For Euterpe edulis frugivore assemblage. Galetti et al. (2013) Science. Data can be accessed here.
Variables included:
species: Frugivore species.
behav: Foraging and seed dissemination behaviour (defecation/regurgitation).
mass: Body mass (g).
gape: Gape width (mm).
frugscore: frugivory score, from 1 (sporadic fruit consumption) to 3, extremely frugivorous on E. edulis.
nvis10h: Visitation rate (/10 h).
nfrhand: No. fruits handled per visit.
nfrdisp: No. fruits ingested.
dispprob: Probability a seed is dispersed away from palm.
qc: Quantitative component of effectiveness.
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prunus_data.zip
Container with source data on Prunus mahaleb. Includes the data for analyses of multilayer structures in R.
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pmah.poll.tsv: adjacency matrix for pollination interactions.
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pmah.herb.tsv: adjacency matrix for herbivory interactions.
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pmah.disp.tsv: adjacency matrix for seed dispersal interactions.
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pm_multilayer_net_explicit.csv: supraadjency matrix in edge list format.
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pmah_attr.txt:
Variables included:
tree: tree label.
gender: sex expression. H, hermaphrodite tree. F, functionally female tree. The species is gynodioecious.
pollen: amount of pollen in anthers; n, no pollen; +, small amount of pollen; ++, moderate to large amount of pollen.
bsd: basal stem diameter (cm). In case of multistem, the largest one.
trunks: number of trunks for multistemmed trees.
cnpy: area of the horizintal projection of the canopy (m2).
cs88: Fruit crop size. Number of fruits counted at the start of the ripening season, 1988 sampling.
cs89: Fruit crop size. Number of fruits counted at the start of the ripening season, 1989 sampling.
cs8889: Fruit crop size. Number of fruits counted at the start of the ripening season, summed data for the two sampling years (1988 and 1989). Percentages of consumption and loss refer to this initial, combined, estimate of fruit crop size.
ms: percentage of fripe fruits dessicated (on branches; lost).
pic: percentage of ripe frutis pecked.
loss: percentage of fruit crop lost (ms+pic).
cons: percentage of fruits consumed. (by any type of frugivore; pic+rem).
rem: percentage of fruits removed. Estimated consumption by legitimate seed dispersers.
pop: percentage of fruits removed by insect predators/pathogens.
disp: Estimated number of seeds being dispersed. Combined estimate from cons and rem.
lossms: Estimated number of fruit being lost by dessication on branches.
totloss: Combined estimate of total fruits lost, from ms, pic and loss.
uchgt: Mean height of woody vegetation under the canopy, mesasured at four points around the tree and beneath the canopy (cm).
uccovr: Mean percent cover of woody vegetation under the canopy, estimated from each of the four sectors (quadrants) beneath the canopy.
ochgt: Mean height of woody vegetation outside the canopy- up to a meter away from canopy edge, mesasured at four points around the tree and outside the canopy (cm).
occovr: Mean percent cover of woody vegetation outside the canopy, estimated for each of the four sectors (quadrants) outsid the canopy and up to 1 m distance from the canopy's edge.
d1: Distance to first conspecific neighbor tree (m).
d2: Distance to second conspecific neighbor tree (m).
ntree: number of conspecific trees in a 15 m radius around the focal tree.
drock: Distance to nearest rock outcrops.
dforest: Distance to nearest edge of the pine forest.
diam1: Largest diameter of the canopy's horizontal projection (m).
diam2: Second largest diameter of the canopy's horizontal projection (m).
perim: Perimeter of the canopy's horizontal projection (m).
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pmah_multilayer_data.csv
Variables included:
no: Numerical code.
plant: Tree id code.
animal: Animal/fungi species name.
w: Interaction frequency.
layer: Layer id.
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node_names_supramux_132.txt: List of taxa names and tree codes in the supra-adjacency matrix.
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Code/Software
The RCode* folder (compressed file RCode.zip) contains scripts, .Rmd, and .qmd files for data analyses in R.
RCode.zip
Container with all the code and analysis files, in R. It includes two folders, as described above:
/functions
/multiplex
The /functions folder contains scripts with R function for multilayer analyses in muxViz and infomap.
The /multiplex folder contains code in .Rmd and .qmd files including commented notes and thorough descriptions of the analyses. A part of the analyses, for infomap, are done with binaries included in the /multiplex/src-exe/ subfolder.
The analysis flow is described and delineated in the files: ms_analyses.qmd, emln_analyses.qmd, infomap.Rmd, pru_muxviz.qmd, and multiplex_correlates.qmd.
NOTE: Code for multilayer analysis with the muxViz package is provided in a separate subfolder (/multiplex/src-exe/). It requires specific installation of external binaries. I’ve run it on R version 4.0, since several required packages have not recent versions.
R Packages used
The R packages used for analyses are fully listed in the Supplementary Material file.
We used R version 4.4.1 (R Core Team 2024) and the following R packages: ade4 v. 1.7.22 (Chessel, Dufour, and Thioulouse 2004; Dray and Dufour 2007; Dray, Dufour, and Chessel 2007; Bougeard and Dray 2018; Thioulouse et al. 2018), ape v. 5.8.1 (Paradis and Schliep 2019), bayestestR v. 0.15.0 (Makowski, Ben-Shachar, and Lüdecke 2019), boot v. 1.3.31 (A. C. Davison and D. V. Hinkley 1997; Angelo Canty and B. D. Ripley 2024), correlation v. 0.8.6 (Makowski et al. 2020b, 2022), datawizard v. 1.0.0 (Patil et al. 2022), devtools v. 2.4.5 (Wickham et al. 2022), easystats v. 0.7.3 (Lüdecke et al. 2022), effectsize v. 1.0.0 (Ben-Shachar, Lüdecke, and Makowski 2020), equatiomatic v. 0.3.3 (Anderson, Heiss, and Sumners 2024), FD v. 1.0.12.3 (Laliberté and Legendre 2010; Laliberté, Legendre, and Shipley 2014), geometry v. 0.5.1 (Habel et al. 2025), ggcorrplot v. 0.1.4.1 (Kassambara 2023), gridExtra v. 2.3 (Auguie 2017), here v. 1.0.1 (Müller 2020), insight v. 1.0.1 (Lüdecke, Waggoner, and Makowski 2019), kableExtra v. 1.4.0 (Zhu 2024), knitr v. 1.49 (Xie 2014, 2015, 2024), lattice v. 0.22.6 (Sarkar 2008), lme4 v. 1.1.36 (Bates et al. 2015), Matrix v. 1.7.1 (Bates, Maechler, and Jagan 2024), modelbased v. 0.8.9 (Makowski et al. 2020a), parameters v. 0.4.1 (Lüdecke et al. 2020), performance v. 0.13.0 (Lüdecke, Ben-Shachar, et al. 2021), permute v. 0.9.7 (Simpson 2022), report v. 0.6.0 (Makowski et al. 2023), see v. 0.9.0 (Lüdecke, Patil, et al. 2021), tidyverse v. 2.0.0 (Wickham et al. 2019), usethis v. 3.1.0 (Wickham et al. 2024), vegan v. 2.6.8 (Oksanen et al. 2024).
Package citations
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