DOI: 10.5061/dryad.q2bvq83jc
title: Niche Differentiation Data

description: Understanding variation in social grouping patterns among animal taxa is
 an enduring goal of ethologists, who seek to evaluate the selective
 pressures shaping the evolution of sociality. Cohesive association with
 conspecifics increases intragroup feeding competition and is posited as an
 important pressure affecting grouping patterns. Furthermore, in sexually
 dimorphic species, males and females may have different nutritional
 requirements, which may lead to suboptimal foraging in mixed-sex groups.
 How do animals living in permanent social groups mitigate these foraging
 costs? Niche differentiation is often hypothesized as a mechanism, but
 rigorous and detailed tests of the extent and context of differences in
 diet and habitat use, key tenets of this hypothesis, are rare. We
 investigated the potential for niche differentiation in foraging activity
 budget and environment use in a population of wild white-faced capuchin
 monkeys ( Cebus imitator ) in northwestern Costa Rica. Using a robust
 dataset of 15 879 foraging scan samples collected from 4 groups over 13
 months, we found that smaller individuals - e.g. juveniles and females -
 forage more often on smaller branches. We additionally found clear
 evidence of predator sensitive foraging wherein the smallest individuals
 spend less time on the ground during invertebrate foraging. Importantly,
 niche differentiation was far more evident overall during invertebrate
 foraging, likely due to spatial constraints and environmental homogeneity
 imposed by fruit patches. In sum, we found considerable variation in
 habitat use across age and sex classes, likely attributable to differences
 in size and relative predation risk. These variables likely reduce
 intraspecific feeding competition by promoting differential diet and
 habitat use. Our results also provide insight into the limits of niche
 differentiation as a strategy for competition reduction and may shed light
 on the evolution of fission- fusion dynamics in highly frugivorous
 species.
description: We collected behavioural data from April 2016 – September 2016
 and from January 2017 – July 2017. The study population comprised 113
 individually identifiable white-faced capuchin monkeys from 4 social
 groups, which ranged in size from 15-30 individuals in 2016 and from 18-33
 individuals in 2017. We observed each group during at least one “rotation”
 per month, where rotations comprised 2-5 consecutive observation days from
 dawn (04:45-05:30) until dusk (18:00-19:00). We recorded behavioural data
 using Samsung Galaxy Tab 4 tablets loaded with PrimateLogger (developed by
 Scott Johnson for Android devices), which recorded a date/time stamp and
 UTM coordinates for each line of text entered. During group follows, we
 conducted instantaneous scans (Altmann, 1974) every 30 minutes on each
 hour and half hour mark (e.g. 05:00, 05:30, 06:00, etc.). We identified as
 many individual monkeys as possible within 10 minutes and recorded their
 behavioural states (see supplementary material). As each individual and
 its behavioural state was identified, we also recorded its relative height
 in the canopy, the support substrate type, and the support substrate angle
 it was using at the moment the individual was first observed. During fruit
 foraging we recorded the species of fruit; during invertebrate foraging we
 recorded whether the behaviour was visual searching/gleaning or extractive
 in nature. To minimize biasing data collection in favor of central
 individuals, we sought to begin scans with a different monkey each time
 and moved around the group. Daily maximum temperature (degrees Celsius) is
 recorded daily as this site using a Kestrel thermometer. Daily rainfall
 (cm) is recorded with a cylindrical rain gauge. Monthly fruit biomass
 (kg/ha) is estimated based on monthly phenological survey. 
description: FruitDifficultyScansXDays_Dryad.csv ; CSV file in which rows are
 all scans per animal per day; file includes fruit difficulty
 variable IndividHabitatFruitScansXDays_Dryad.csv ; CSV
 file in which rows are all fruit scans per animal per day
 IndividHabitatInvertebrateScansXD_Days_Dryad.csv ; CSV file in
 which rows are all invertebrate scans per animal per day
 IndividScanStatesXDays_Dryad.csv ; CSV file in which rows are all
 scans per animal per day MonthlyFruitBiomass_Dryad.csv
 ; CSV file in which rows are esimated fruit biomass (kg/ha) per
 month RotationsREW_Dryad.csv ; CSV file in which rows
 are IDs of each data collection rotation
 rotationDate16_17_Dryad.csv ; CSV file in which rows are IDs of
 each data collection rotation