DOI: 10.5281/zenodo.18016801
title: A comprehensive, multi-method dataset of plant-frugivore interactions in a Mediterranean hotspot

description: # DOÑANA FRUGIVORY

Datasets and code accompanying our manuscript "_A comprehensive, multi-method dataset of plant-frugivore interactions in a Mediterranean hotspot_" in review in _Scientific Data_. Authors:Eva Moracho, Juan Miguel Arroyo, Blanca Arroyo-Correa, Gemma Calvo, Pablo Homet, Jorge Isla, Miguel Jácome-Flores, Irene Mendoza, Elena Quintero, Francisco Rodríguez-Sánchez, Pablo Villalva, Pedro Jordano

--------------## Files:

|___/MS_FRUGINT/INPUT_DATA

       |___BC_seed.csv

       |___BC_visit.csv

       |___CAM.csv

       |___MN_1983.csv

       ___MN_2024.csv 

       |___OBS_HR.csv

       |___OBS_JP.csv

       |___TRACK.csv

|___/MS_FRUGINT/INTERACTIONS

       ___FRUGINT_byMethod_gts.csv 

       ___FRUGINT_finalMatrix.csv

|___/MS_FRUGINT/TRAITS

       |___FRUGINT_birdTraits.csv

       |___FRUGINT_mammalTraits.csv 

       |___FRUGINT_plantTraits.csv



Data record

 All datasets are named following the pattern FRUGINT_filename.ext and include metadata and variable descriptions in the Methods section to facilitate reuse. Data include 13 files divided into 3 folders and one R script, named following the pattern “FRUGINT_filename.ext”. Please see the main paper for the figures and bibliographic references cited below.

The INPUT_DATA folder contains eight .csv datasets that serve as the primary input for integration using the R script FRUGINT_method_merge.R. Some datasets are provided at record-level, reporting individual interaction events between a plant and an animal at a specific time and location (namely, DNA-barcoding datasets from visits: BC_visit.csv, from seeds: BC_seed.csv, the camera dataset: CAM.csv, track records: TRACK.csv, and mist-netting data from 2019–2024: MN_2024.csv). These datasets were compiled by merging data from multiple surveys for each method and include the following fields: method (one of the main methods used in this study), sub-method (any specifics on the main method, e.g., barcoding data is generated from seeds or visits, and seeds were collected from either underneath a focal plant, in open landscape or transects), vegetation (one of the habitat types covered in this study, see Fig.1), sampling site (where applicable, e.g., plant species where trays were placed for DNA-barcoding), area (location), coordinates, sampling ID (focal individual or site identifier), date, animal species, plant species, and sampling effort (sampling time and/or sampling area per sampling ID, where available). Other datasets are provided at species-level, summarizing interaction frequencies between species pairs by method, location, or time period (namely, mist-netting data from 1981–1983: MN_1983.csv, and direct observation datasets from two localities: OBS_HR.csv and OBS_JP.csv).

The INTERACTIONS folder contains two .csv datasets: (1) FRUGINT_byMethod_gts.csv, which includes the total interaction number (int.total), the probability of interaction encounter as standardized total pairwise interactions by the grand total (PIE), and (2) FRUGINT_finalMatrix.csv, an adjacency matrix of all plant-frugivore species in the study area, each matrix cell showing the standardized average probability of the pairwise interaction across methods (meanPIE), and the maximum value (maxPIE).

The TRAITS folder includes three .csv datasets: the FRUGINT_plantTraits.csv file includes species names according to the World Checklist of Vascular Plants (WCVP67), species abbreviations (codes used in Fig. 3 and Fig. 4), higher taxonomic levels, plant form, disperser taxa (derived from FRUGINT compilation), fruit morphology and color (type, diameter, fresh mass, pulp dry mass, seed mass, seed number), nutrient composition (lipids, proteins, carbohydrates, ash, fiber); the FRUGINT_birdTraits.csv file includes species names according to standard lists of birds (AviList69), species abbreviations (codes used in Fig. 3 and Fig. 4), higher taxonomic levels, ecomorphology (body mass, culmen width, culmen height, wing length, tail length, tarsus length, gape width, gut passage time), diet, frugivore type, conservation status and source (reference to data source for each species); the FRUGINT_mammalTraits.csv file includes species names according to standard lists of mammals68, species abbreviations (codes used in Fig. 3 and Fig. 4), higher taxonomic levels, biometry (body mass, head-body length, tail length, height, foot length, ear length), diet, conservation status and source (reference to data source for each species). See variable details in Methods, section 4.
description: Mutualistic plant-animal interactions for seed dispersal are crucial for vegetation dynamics, benefiting over half of the world's plant species. Beyond the tropics, the Mediterranean biome harbors the highest proportion of species adapted to endozoochory, yet major gaps remain in quantifying interaction diversity in these biodiversity-rich areas and their links to ecosystem functioning. High-resolution, quantitative interaction data are essential not only to fill these gaps but also to enable large-scale ecological modeling of species interactions across biomes. Here, we present the FRUGivory INTegration (FRUGINT) dataset — an extensive collection of quantitative frugivory interactions and associated species traits from a Mediterranean biodiversity hotspot in southwestern Spain. By integrating six complementary sampling methods (camera trapping, continuous-monitoring cameras, DNA- barcoding, mist-netting, direct observation and track records) across multiple years, the dataset overcomes limitations of sampling biases, variable effort and spatio-temporal heterogeneity. FRUGINT yields robust estimates of regional-scale plant-frugivore networks based on pairwise interaction probabilities. The dataset encompasses both common and numerous rare interactions, offering a valuable resource for advancing research on plant-animal interactions, network ecology, and biodiversity conservation.