DOI: 10.5061/dryad.kd51c5bdv
title: Data from: Sexual dimorphism does not translate into foraging or trophic niche partitioning in Peruvian boobies (Sula variegata)

description: Intraspecific competition can lead to sexual segregation of diets or
 foraging behaviors in seabirds, and in some species the resulting niche
 partitioning is facilitated by sexual dimorphism. However, environmental
 stochasticity can mediate intraspecific competition and thus the extent of
 sex-based partitioning. The Peruvian booby (Sula variegata) is a sexually
 dimorphic seabird endemic to the Humboldt Current System (HCS), a highly
 variable environment due to El Niño Southern Oscillation. To determine the
 extent of sexual partitioning in this species, we quantified the foraging
 and trophic niches of breeding Peruvian boobies at Isla Guañape Norte,
 Peru in two years with different oceanographic conditions and nesting
 propensity. Morphometrics, GPS-tracked foraging behaviors, diets via
 regurgitates, and isotopic niches were compared between sexes and years
 where sample sizes permitted. Although females were larger and in better
 body condition than males, breeding Peruvian boobies in our study did not
 exhibit sex-specific foraging or isotopic niche partitioning and had few
 differences in diet. Anchoveta (Engraulis ringens) dominated diets in both
 years, reflecting Peruvian boobies’ dependence on this prey. Overall,
 while oceanographic conditions in 2016 were unfavorable enough to reduce
 nesting propensity, these effects did not qualitatively translate to
 foraging or dietary niche partitioning between the sexes for those
 individuals who opted to breed. In combination, our results suggest weak
 intraspecific competition during our study period, and highlight how the
 foraging strategies of Peruvian boobies have adapted to the variable
 environmental conditions found in the HCS.
description: We sampled Peruvian boobies from Isla Guañape Norte (8.545°S,
 78.964°W), an island located approximately 9 km offshore of northern Peru,
 in December 2016 and in November 2019. According to the Índice Costero El
 Niño, birds were experiencing weak El Niño conditions (0.47) in December
 2016, and neutral conditions (-0.40) in November 2019.
 <strong>Morphometrics measurement collection and
 processing</strong> We sampled Peruvian boobies
 in December 2016 and in November 2019. Breeding adults were captured at
 the nest soon after dawn (06:00–08:00) using a monofilament lasso attached
 to a 5-meter telescopic pole. In 2016, adults selected for capture (14
 females and 4 males) had eggs and/or chicks less than 7 days old. In 2019,
 the selected adults (20 females and 12 males) had nests containing chicks
 between 3–8 weeks old and represented 2% of individuals found breeding on
 the study plot. Both parents were present at the nest during capture,
 ensuring that chicks or eggs were not left unattended. Sex, weight (g),
 breeding condition, culmen length (mm), tarsus length (mm), and wing chord
 (mm, naturally arched) were recorded for each captured bird. Sex was
 assigned from observed vocalizations at the nest. We
 generated a body condition index (BCI) by performing a principal
 components analysis (PCA) on the culmen, tarsus, and wing chord
 measurements of all individuals, then regressing the first principal
 component (PC1, with an eigenvalue of 2.258 explaining 75.3% of variance)
 of each individual against body mass, and finally assigning the residuals
 of this regression as the body condition index. Three birds were excluded
 from this index due to missing measurements.
 <strong>GPS tagging and
 processing<br></strong> We tagged a subset
 of captured breeding birds with a GPS device, which was attached to the
 central tail feathers using Tesa® 4651 waterproof tape. In total, we
 successfully tracked 7 females and 3 males in 2016 (15 foraging trips
 total), and 20 females and 12 males in 2019 (60 trips). Tagged birds had
 their head feathers marked using PAINTSTIK® livestock markers (LA-CO
 Industries, Inc.). In 2016, both i-gotU GT 600 (30 grams) and GyPSy-5 (14
 grams) GPS devices were used, set to record fixes every 2–10 seconds, and
 waterproofed by placing each device inside a condom and sealing it inside
 a heat-sealed polypropylene plastic bag (1 gram). In 2019, Axy-Trek Marine
 GPS devices weighing 32 grams (Technosmart Europe S.r.l., Rome, Italy)
 were used to tag birds and set to record GPS locations and dive depth in
 continuous mode every 1 second. GPS weight was 2% of the weight of the
 lightest tagged bird (1200 g). Birds were recaptured late afternoon
 (15:00–18:00) on the day of tagging. After retrieval
 and download of the GPS tracks, the data were recovered from the devices,
 examined in ArcGIS, and processed prior to analysis. In total, 10
 individuals in 2016 and 32 individuals in 2019 yielded usable tracks. As
 birds were all nesting at the colony, for each track, we first removed all
 points inside of a 300 meter radius from a point designated as the colony
 center. We then noted departures and returns for each foraging trip. If a
 single individual left and returned to the colony center multiple times,
 each unique segment between a departure/return pair of points, as bounded
 by start and end time, was defined as separate trips. After confirmation
 of foraging trips, we then visually checked for GPS data such as
 non-foraging trip activity (bathing behavior near colony immediately after
 capture and tagging of the individual) and GPS errors (single outlier
 points). These data points were removed from tracks either manually or
 using a similar radius approach. The cleaned data were imported into R,
 and each trip by each individual was assigned a unique trip identifier.
 GPS points for each trip were exported. This data was used to further
 calculate foraging trip metrics, EMbC, and kernel densities as described
 in the paper. For foraging trip metrics, we calculated
 total trip distance, maximum distance from colony, and trip duration in
 using the <em>sp</em> (v.1.4-5; 55),
 <em>adehabitatLT</em> (v.0.3.27; 56), and <em>lubridate
 </em>(v1.7.9; 57)<em> </em>packages in R (v4.2.2; 58).
 Specifically, we determined the duration of each trip by calculating the
 absolute date/time difference between the earliest departure point and the
 latest return point. We determined maximum distance from colony by
 specifying the latitude/longitude coordinates of the colony, calculating
 the distance to colony from each GPS point (km), and taking the maximum
 value returned for each bird and each trip. We determined total trip
 distance by calculating the distance between successive points via taking
 the difference between the latitude/longitude coordinates of each pair of
 points and totaling up these distances for each individual trip.
 We characterized at-sea behaviors of boobies using the
 Expectation Maximization binary Clustering<em>
 </em>(<em>EMbC</em>) algorithm (v2.0.4; 59). It uses two
 input variables (speed and turning angle) to determine and assign one of
 four behaviors to sets of velocity/turn pairs in the movement
 data. <strong>Tissue collection for stable
 isotopes (δ<sup>13</sup>C and
 δ<sup>15</sup>N)</strong> We
 collected 0.5 ml of blood from the tarsal vein of all captured breeding
 birds. We preserved collected blood in vials with 1 ml of 99.9% ethanol
 from a common source. Peruvian booby whole blood
 samples were dried and homogenized using a mortar and pestle.
 Approximately 0.6 mg of each sample was then loaded into tin cups and
 flash-combusted using a Costech ECS4010 elemental analyzer. These samples
 were analyzed for carbon and nitrogen stable isotopes
 (δ<sup>13</sup>C and δ<sup>15</sup>N) using an
 interfaced Thermo Delta XP continuous flow stable isotope ratio mass
 spectrometer. Raw δ values were normalized on a two-point scale using
 glutamic acid reference materials with low and high values (i.e., USGS-40
 (δ<sup>13</sup>C = −26.4‰, δ<sup>15</sup>N =
 −4.5‰) and USGS-41 (δ<sup>13</sup>C = 37.6‰,
 δ<sup>15</sup>N = 47.6‰)). Sample precision based on repeated
 sample and reference material was 0.1‰ and 0.2‰ for
 δ<sup>13</sup>C and δ<sup>15</sup>N, respectively.
 Stable isotope ratios are expressed in δ notation in per mil units (‰).
 The R<sub>standard</sub> values were based on the Vienna
 PeeDee Belemnite (VPDB) for δ<sup>13</sup>C and atmospheric
 N<sup>2</sup> for δ<sup>15</sup>N.
 <strong>Diet collection and
 processing</strong> Stomach samples were obtained
 either through induced regurgitation of captured boobies upon return from
 a feeding trip or at random from either the periphery of the nesting sites
 or beaches. In 2016, sampling occurred from December 15th to the
 22<sup>nd</sup>, and we induced regurgitation of randomly
 selected birds when they returned to the nest (<em>n </em>=
 82). Unfortunately, the sex of birds was not recorded in 2016. In 2019,
 sampling occurred from November 16th to December
 8<sup>th</sup>, and we induced regurgitation of sexed birds
 that were equipped with GPS loggers immediately upon their return from a
 feeding trip (<em>n </em>= 25). Whole prey in undigested
 samples were sorted, identified, and measured. After the identification of
 prey items, we assessed the frequency of occurrence of each prey species,
 diet composition by species (percent mass), total regurgitate mass, number
 of prey items, and individual prey size (total length in mm). Total fish
 length was measured from the snout to the end of the tail fin. Intact fish
 were assessed by direct measurement (accuracy ±1 mm), while measurements
 for partially digested <em>Engraulis ringens</em> were
 obtained by digitally measuring an intact sagittal otolith with a Zeiss
 Stemi SV 6 dissecting microscope with a digital SPOT RT camera attachment
 and Image-Pro Plus software (Opelco; accuracy ± 0.01 mm).
 Initial <em>E. ringens </em>length was estimated using the
 equation <em>fish length (cm) = 0.798 + 3.33 (otolith length
 [mm]).</em>
description: # Sexual dimorphism does not translate into foraging or trophic niche
 partitioning in Peruvian boobies (Sula variegata)
 [https://doi.org/10.5061/dryad.kd51c5bdv](https://doi.org/10.5061/dryad.kd51c5bdv) This dataset contains data collected in the field (GPS tracks, morphometrics, stable isotope, prey data) as well as processed data derived from field movement data through the use of various R packages (EMbC and foraging trip data). ## Description of the data and file structure This dataset contains 6 data files ('data_PEBO_embc', 'data_PEBO_foraging_trips', 'data_PEBO_gps', 'data_PEBO_morphometrics_isotope', 'data_PEBO_prey_measurements', and 'data_PEBO_regurgitates'). Observations in separate data files are linked through an individual key ID "bird_id" and/or trip ID "trip_id". However, some unique observations appear only in 'data_PEBO_prey_measurements' and 'data_PEBO_regurgitates'. ###### 'data\_PEBO\_embc' This file contains the individual GPS points of foraging trips along with their at-sea behavior classifications as assigned by the EMbC algorithm. Variables (columns) in 'data_PEBO_embc' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'trip_id' = a unique identifier assigned to each individual trip, created by combining 'bird_id' and the number of the unique bird's foraging trip[s] * 'group' = group the bird belongs to, grouped by year and sex * 'dTm' = date and time of GPS location, in yyyy-mm-dd, hh:mm format. The seconds measurement has been stripped by the EMbC analysis. * 'lat' = latitude, using the WGS 84 coordinate system * 'long' = longitude, using the WGS 84 coordinate system * 'class' = a numeric identifier for behaviors assigned by the EMbC package (1-4, with 5 indicating algorithmic inability to assign a behavior) * 'code' = an abbreviated code for EMbC package-assigned behaviors (LL, LH, HL, HH), where the first initial denotes low or high velocity and the second initial denotes low or high turn radius (NA = unassigned behavior) * 'behavior' = a plain language category for EMbC package-assigned behaviors: resting, intensive foraging, travelling, relocating (NA = unassigned behavior) ###### 'data\_PEBO\_foraging\_trips' This file contains trip metrics obtained from foraging trips identified and extracted from the raw GPS tracks of tagged boobies, where each row is a unique foraging trip (individual birds appear in several rows if they made multiple trips). Variables (columns) in 'data_PEBO_foraging_trips' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'species' = species of sampled individual * 'locality' = location (island) where individual was sampled * 'year' = year in which the individual was sampled * 'sex' = sex of the sampled individual * 'trips' = total number of foraging trips the sampled individual took * 'trip_id' = a unique identifier assigned to each individual trip, created by combining 'bird_id' and the number of the unique bird's foraging trip[s] * 'dursecs' = duration of foraging trip in seconds * 'durhours' = duration of foraging trip in hours * 'start_datetime' = start date and time of foraging trip (when the sampled individual left the breeding colony), in yyyy-mm-dd, hh:mm format * 'end_datetime' = end date and time of foraging trip (when the sampled individual returned to the breeding colony), in yyyy-mm-dd, hh:mm format * 'totaldist' = total distance travelled during the foraging trip, in km * 'maxdist' = maximum distance from the breeding colony, as measured from the farthest point travelled during the foraging trip to the designated colony center, in km * 'distallat' = latitude of the farthest point from the breeding colony, using the WGS 84 coordinate system * 'distallon' = longitude of the farthest point from the breeding colony, using the WGS 84 coordinate system * 'start_time' = start time of foraging trip (when the sampled individual left the breeding colony), in hh:mm:ss format * 'end_time' = end time of foraging trip (when the sampled individual returned to the breeding colony), in hh:mm:ss format * 'nest_eggs' = how many eggs the sampled individual had in the nest * 'nest_chicks' = how many chicks the sampled individual had in the nest * 'chicksize' = size of chick(s) in nest, if present (NA = size not recorded) ###### 'data\_PEBO\_gps' This file contains the GPS tracks of the foraging trips identified and extracted from the raw GPS movement data. Variables (columns) in 'data_PEBO_gps' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'trip_id' = a unique identifier assigned to each individual trip, created by combining 'bird_id' and the number of the unique bird's foraging trip[s] * 'group' = group the bird belongs to, grouped by year and sex * 'dTm' = date and time of GPS location, in yyyy-mm-dd, hh:mm:ss format * 'lat' = latitude, using the WGS 84 coordinate system * 'long' = longitude, using the WGS 84 coordinate system ###### 'data\_PEBO\_morphometrics\_isotope' This file contains the biometric measurements and whole blood stable isotope values (carbon and nitrogen) for each individual bird. Variables (columns) in 'data_PEBO_morphometrics_isotope' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'species' = species of sampled individual * 'locality' = location (island) where individual was sampled * 'year' = year in which the individual was sampled * 'date_capture' = date the individual was sampled, in yyyy-mm-dd format * 'time_capture' = time the individual was sampled, in hh:mm format * 'weight_g' = weight, in grams * 'culmen_mm' = length of the culmen, in millimeters * 'tarsus_mm' = length of the tarsus, in millimeters * 'wing_mm' = wing chord measurement, naturally arched, in millimeters * 'BCI' = body condition index. Values for this index were created through performing a principal components analysis (PCA) on the culmen, tarsus, and wing chord measurements of all individuals, regressing the first principal component of each individual against body mass, and then assigning the residuals of this regression as the BCI for each individual. * 'sex' = sex of the sampled individual * 'samplemass_blood_mg' = dry weight of blood weighed out for stable isotope analysis, in milligrams * 'Ccontent_blood' = carbon content (mass) of sample, in milligrams * 'Ccontent_%_blood' = carbon elemental concentration of sample, as percentage of dry weight * 'd13C_blood' = carbon isotopic value of sample, expressed in the delta (δ) notation using per mil units (‰) * 'Ncontent_blood' = nitrogen content (mass) of sample, in milligrams * 'Ncontent_%_blood' = nitrogen elemental concentration of sample, as percentage of dry weight * 'd15N_blood' = nitrogen isotopic value of sample, expressed in the delta (δ) notation using per mil units (‰) * 'CNratio_blood' = carbon to nitrogen elemental ratio of sample * 'notes' = collection analysis notes ###### 'data\_PEBO\_prey\_measurements' This file contains the total lengths of prey (anchoveta, *Engraulis ringens*) recovered from regurgitate samples. Note that the individual birds that were sampled for regurgitate data are *not* the individuals from which movement data was collected. Variables (columns) in 'data_PEBO_prey_measurements' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'species' = species of sampled individual * 'locality' = location (island) where individual was sampled * 'sex' = sex of the sampled individual * 'collection_date' = date the regurgitate was collected, in yyyy-mm-dd format (NA = date not recorded) * 'year' = year in which the regurgitate was sampled * 'prey_species' = species of prey item * 'prey_no' = number of prey item, determined based on total number of prey counted in the same bolus of regurgitate * 'TL_cm' = total length of prey item, in centimeters ###### 'data\_PEBO\_regurgitates' This file contains information about the prey composition of regurgitates. Note that the individual birds that were sampled for regurgitate data are *not* the individuals from which movement data was collected. Variables (columns) in 'data_PEBO_regurgitates' are described as follows: * 'bird_id' = a unique identifier for each individual bird that was sampled * 'species' = species of sampled individual * 'locality' = location (island) where individual was sampled * 'sex' = sex of the sampled individual * 'collection_date' = date the regurgitate was collected, in yyyy-mm-dd format * 'year' = year in which the regurgitate was sampled * 'all_data_available' = notes whether all prey composition metrics were recorded (e.g. mass, quantity of prey) * 'FO_anchoveta' = presence/absence of anchoveta, *Engraulis ringens* (1 = present, 0 = absent) * 'FO_silverside' = presence/absence of Peruvian silverside, *Odontesthes regia* (1 = present, 0 = absent) * 'FO_saury' = presence/absence of saury, also known as king gar, *Scomberesox saurus scombroides* (1 = present, 0 = absent) * 'mass_anchoveta_g' = mass of anchoveta in regurgitate sample, in grams (NA = mass not measured) * 'mass_silverside_g' = mass of Peruvian silverside in regurgitate sample, in grams * 'mass_saury_g' = mass of king gar in regurgitate sample, in grams * 'mass_total_g' = total mass of all prey items in regurgitate sample, in grams (NA = mass not measured) * 'percent_anchoveta' = percent mass of anchoveta, calculated as a proportion of total prey mass * 'percent_silverside' = percent mass of Peruvian silverside, calculated as a proportion of total prey mass * 'percent_saury' = percent mass of king gar, calculated as a proportion of total prey mass * 'count_anchoveta' = number of anchoveta observed in regurgitate sample (NA = anchoveta not counted) * 'count_silverside' = number of Peruvian silverside observed in regurgitate sample * 'count_saury' = number of king gar observed in regurgitate sample * 'count_total' = total number of prey items observed in regurgitate sample (NA = total not counted) * 'notes' = collection analysis notes