DOI: 10.5061/dryad.44j0zpcsm
title: Data from: Trophic niche overlap decreases in related mesocarnivore species

description: In natural environments, competition between species is a crucial factor
 for the survival or demise of populations. Therefore, understanding the
 mechanisms that promote species coexistence is crucial in community and
 evolutionary ecology. The phylogenetic limiting to similarity hypothesis
 (PLSH) posits that closely related species should experience greater
 competition due to niche conservatism, leading to higher overlap in
 resource use. However, studies have shown mixed results regarding the
 influence of phylogenetic distance and other abiotic and biotic factors on
 interspecific competition. This study, which is based on an extensive
 bibliographic review of more than 200 sources over nearly five decades,
 explores the role of phylogenetic relatedness, body mass differences, and
 environmental factors such as primary productivity, in shaping trophic
 niche overlap among mesocarnivores across ten global biomes. Our results
 suggest that phylogenetic distance and body mass differences are the most
 significant predictors of trophic niche overlap, while environmental
 factors like primary productivity also play a crucial role. These findings
 highlight the complexity of species interactions, emphasizing that trophic
 niche overlap is influenced by a combination of factors. This study
 contributes to a deeper understanding of the dynamics governing species
 coexistence and the assembly of ecological communities.
description: # Data from: Trophic niche overlap decreases in related mesocarnivore
 species This repository contains the datasets and analysis files used in
 the study by Sarabia et al. (2025). All materials are freely available for
 use, provided appropriate citation of the original article. The three
 folders are as follows: * **phylogenetic_dist**: Contains the
 extrapolation of phylogenetic distances from *cytochrome b* data to
 mitochondrial distances in carnivores. Includes pairwise distance tables
 and Python scripts testing regression models and regression trees. *
 **pianka**: Includes the compiled dietary dataset from all reviewed
 studies, a Python script to calculate Pianka’s niche overlap coefficients,
 and the resulting pairwise comparisons across species, ecoregions, and
 biomes. * **GLM**: Contains the extended analytical dataset integrating
 phylogenetic, ecological, and abiotic variables, along with the R scripts
 used to run Generalized Linear Mixed Models (GLMMs) testing the
 relationship between Pianka’s overlap coefficients and explanatory
 variables. Notes: * This dataset contains two csv files
 (pianka-reduced.csv & results.csv, in pianka.zip), that are
 |-delimited with a comma decimal, and an Excel file that is
 comma-delimited with a period decimal (Analyses_table.xlsx in GLM.zip).
 These files are presented as they are. If modifications are performed on
 these files, necessary modifications in R and python scripts in each
 folder need to be done.  * Ecoregion numerical values are assigned
 according to Olson et al. (2001) Terrestrial Ecoregions of the World: A
 New Map of Life on Earth: A new global map of terrestrial ecoregions
 provides an innovative tool for conserving biodiversity, BioScience,
 Volume 51, Issue 11, November 2001, Pages 933–938,
 [https://doi.org/10.1641/0006-3568(2001)051\[0933:TEOTWA\]2.0.CO;2](https://doi.org/10.1641/0006-3568\(2001\)051[0933:TEOTWA]2.0.CO;2)  ## Repository contents ### **phylogenetic_dist.zip**: Contains the extrapolation of phylogenetic distances from cytochrome B data to mitochondrial distances in carnivores. Files included: * *1.cytb_v_mito.Geffen_1995.Hassanin_2021.md* - A markdown document that details the extrapolation of cytochrome-B and mitochondrial phylogenetic distances between carnivores, extracted from Geffen et al. (1996) "Size, Life-History Traits, and Social Organization in the Canidae: A Reevaluation" (cyt-B distances) and Hassanin et al. (2021) "Evolutionary history of Carnivora (Mammalia, Laurasiatheria) inferred from mitochondrial genomes" (mitochondrial DNA distances) * *table_comp.cytb.mito.csv* - A composed table with 92 pairwise phylogenetic distances from both publications; contains the phylogenetic comparisons of cytochrome B and mitogenomes of each of the reported species. * *2.regression.lines.py* - A python script that explores several regression models between both phylogenetic distance tables. * *2.regression.trees.py* - A python script that explores several regression trees between both phylogenetic distance tables. ### **pianka.zip**: Calculations of Pianka's niche overlap coefficients between the diets of various carnivore species. Files included: * *pianka-reduced.csv* - contains a dataset of carnivore diets in the period 1971-2024 * Paper: source publication. * Ecoregion, BIOME: ecoregion and biome of the diet (according to Olson et al. 2001; doi: 10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2) * Type_of_Species: species category as specified in text * \1. Medium-sized canids: coyote (C. latrans), Eurasian golden jackal (C. aureus), African golden wolf (C. lupaster), silver or black-backed jackal (Lupullela mesomelas), side-striped jackal (L. adusta). * \2. Small-sized felids: African wildcat (Felis lybica), European wildcat (F. silvestris), jungle cat (F. chaus), black-footed cat (F. nigripes), leopard cat (Prionailurus bengalensis), bobcat (Lynx rufus). * \3. Foxes of the Vulpini tribe: red fox, kit fox (Vulpes macrotis), Cape fox (V. chama), Blanford’s fox (V. cana), swift fox (V. velox), gray fox (Urocyon cinereoargenteus), bat-eared fox (Otocyon megalotis). * \4. Mustelids: honey badger (Mellivora capensis), American badger (Taxidea taxus), pine marten (Martes martes), stone marten (M. foina). * Species: species name abbreviation as specified in text (AGW: African golden wolf; AWC: African wildcat; BBJ: Black-backed jackal; BC: Bobcat; BEF: Bat-eared fox; BF: Blanford fox; CF: Cape fox; EUGJ: Eurasian golden jackal; EuL: Eurasian lynx; GF: Gray fox; HB: honey badger; JC: Jungle cat; KF: Kit fox; LC: Leopard cat; Martes: European pine marten; RF: Red fox; SF: Silver fox; WC: Eurasian wildcat) * Dietary categories (WU: Wild ungulates; MUWM: Medium-sized wild mammals (2-30 kg); CARN: other carnivores; DOM: domestic mammals; HARE: lagomorphs; SM: small mammals (rodents and &lt;2kg); BIRD: birds (domestic and wild); REPT: reptiles and amphibians; FISH: fish and marine/riverine molluscs and crustaceans; ARTHR: Arthropods; PLANTS: Plant material; OTHER: other unidentified organic material; WASTE: waste/inorganic material) and Percentage (total result sum). All units under these columns indicate percentages of each dietary category. Empty cells indicate values of 0% for the food categories aforementioned. * *pianka-comp.py* - A python homemade script that takes an input table of values of dietary items and their frequency of occurrence (Fr) and calculates the Pianka overlap coefficient per pair of diets per ecoregion, comparing different types of species using pianka-reduced.csv as input and results.csv as output. * *results.csv* - The output table of pianka-comp.py, summarizing pairwise comparisons between rows in pianka-reduced.csv. * rows: rows of pianka-reduced.csv that were compared. * type_of_species: species numerical classes compared (1,2,3,4 as aforementioned) * pianka: Pianka's overlap coefficient * species: species being compared * Ecoregion: as in Olson et al. (2001) * biome: numeral values 1-10 as aforementioned. ### **GLM.zip**: GLMM analyses testing the relationship between all relevant variables and the Pianka overlap coefficients. * *Analyses_table.xlsx*: expanded *results.csv* table with pairwise genetic and mass comparisons and abiotic variables. Categories included: * spe1, spe2,(species 1 & 2), * specat1, specat2, (species categories 1 & 2 as in Sarabia et al. 2025 Oikos, doi: 10.1002/oik.11324), * row1, row2: (rows occupied in file pianka-reduced.csv), * ecoregion_id, ecoregion_name,(ID number and name of ecoregions as in Olson et al. (2001)) * biome (numerical values are assigned as follows: Mediterranean (1), Temperate Europe (2), East Africa (3), Kalahari (4), Temperate Asia (5), Tropical Asia (6), 'Mediterranean' North America (7), Temperate North America (8), Desert (9), South African grasslands (10)) * phyldist: mitochondrial DNA-based phylogenetic distances as calculated in phylogenetic_dist section. * massdiff: biomass difference between compared species, in kg. * Pianka, Pianka_10: Pianka's overlap coefficient and its values multiplied by 10. * NDVI, NDVI_log: real and log-based values of Normalized Difference Vegetation Index per ecoregion. * Avg_prec, Avg_prec_log, Stdev_prec, Stdev_prec_log (Average and standard deviation of precipitation per year, mm/year and log values), * Avg_elev and Avg_elev_log (Average elevation in meters and log values) * Avg_t_min, Avg_t_min/10, Avg_t_max, Avg_t_max_log (Average max and min temperature and log values, in ºC) * Max_carnivores, Avg_carnivores: Maximum and average carnivore richness per ecoregion. * Pianka_analyses.R: GLMM analyses testing the relationship between all relevant variables from Analyses_table.xlsx.