Data for: Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (Sialia currucoides)? 1. COMPONENTS: A. Dataset of observational diet estimates and nestling morphometrics: ECE-2021-05-00718.xls B. Data for Stable isotope mixing models: final_consumers.csv, sources_conc.csv, and tef.csv. C. Instructions for use of the datasets for B is contained in the file with the annotated code used to estimate diet using MixSIAR, called MixSIAR_code.txt 2. Author Information A. Principal Investigator Contact Information Name: Aija F White Institution: University of Northern British Columbia Address: 3333 University Way Prince George BC Email: aijawhite@gmail.com B. Associate or Co-investigator Contact Information Name: Russ Dawson Institution: University of Northern British Columbia Address: 3333 University Way Prince George BC Email: Russell.Dawson@unbc.ca 3. Date of data collection (single date, range, approximate date) : 2016-04-15 – 2016-08-15 4. Geographic location of data collection : 51.7886° N, 122.2283° W 5. Information about funding sources that supported the collection of the data: Funding was provided to RDD through a Natural Sciences and Engineering Research Council Discovery Grant (RGPIN-2015-04377). Additional funding was provided by the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund (219204), and the University of Northern British Columbia. SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: None 2. Links to publications that cite or use the data: Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (Sialia currucoides)? Ecology & Evolution, in press. 3. Links to other publicly accessible locations of the data: None 4. Links/relationships to ancillary data sets: None 5. Was data derived from another source? No. A. If yes, list source(s): 6. Recommended citation for this dataset: White, A. and Dawson, R. 2021. Data for Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (Sialia currucoides)? Ecology & Evolution, in press. DATA & FILE OVERVIEW 1. File List: A. ECE-2021-05-00718_nestling_data.xls : observational diet estimates and nestling morphometrics B. final_consumers.csv, sources_conc.csv, and tef.csv are files needed for stable isotope mixing models C. MixSIAR_code.txt: Instructions for use of the datasets for B is contained in the file with the annotated code used to estimate diet using MixSIAR 2. Relationship between files, if important: Individual identities are noted using ‘FWS’ – use this unique ID to assign the correct estimates from mixing models to individuals in the ECE data file. 3. Additional related data collected that was not included in the current data package: None 4. Are there multiple versions of the dataset? yes/no NO A. If yes, name of file(s) that was updated: i. Why was the file updated? ii. When was the file updated? METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Observations of diet and nestling morphometrics were made near Williams Lake, British Columbia, between April and August 2016. Please see the article for details regarding how video files were processed, insects caught, nestlings measured, and the specimens prepared for stable isotope analysis. Stable isotope values were determined from samples collected in the field by the Laboratory for Stable Isotope Studies at Western University, in London Ontario. 2. Methods for processing the data: We estimated the proportional contribution of 6 prey types (5 common types and ‘other,’ which were uncommon or unidentified prey) to the overall amount of biomass consumed by each nestling in provisioning recordings on days 5 and 9 of the brood-rearing period. We multiplied the number of items of each of the 5 common prey types fed to each nestling at each age by the average mass of voucher specimens of the same size (see above). To determine the proportion of biomass contributed by unknown or uncommon items we used the average mass of all common prey items of the same size class. The estimated biomass of the 5 main prey types, and any uncommon and unidentified prey, were summed to estimate the total biomass consumed by each nestling, and the proportional contribution of each type of prey was determined by dividing the mass of each type by the total estimated biomass consumed by a given nestling. Nestling identity was known in 98.7 % of feeding events, and for the few events where unknown nestlings were fed, we divided the biomass of the item equally among all nestlings in the brood. For the 186 nestlings in provisioning recordings made on day 5 and/or 9, in 74.2 % of observations (264 of 356 observation records of individual nestlings), the contribution of unidentified and uncommon prey biomass to the estimated total consumed by each nestling was ? 5 %. For these records, we removed unidentified and uncommon items from the total biomass consumed before estimating the proportional contributions for the 5 common types. For the 92 records of nestlings with > 5 % of total estimated biomass consumed from unidentified prey items (mean ± standard error [SE] = 7.5 ± 1.3 % of total estimated biomass; range: 5.2 ? 30.3 %), we used the method of Robinson et al. (2015) to allocate unknown items to one of 6 prey types (5 common and ‘other,’ uncommon prey) before estimating dietary proportions. Briefly, this method simulates the most probable allocation of unidentified items among all possible prey types, based on the proportions of identified prey of each type delivered to an individual during the recording. The best solution identified during the simulations was then used in calculating the proportions of biomass of each prey type using voucher sample masses, as detailed above. We then calculated the dietary proportions of the 5 main prey types for nestlings that consumed < 5 % of estimated biomass from uncommon prey after removing the biomass contributed by the ‘other’ category, as detailed above. Individuals that had > 5 % of estimated biomass consumed from the ‘other’ category at this point were excluded from further analyses, leaving a sample of 162 nestlings from 50 broods whose diets were eligible for estimation using SIMM. 3. Instrument- or software-specific information needed to interpret the data: R, any version compatible with MixSIAR; MixSIAR package Stata 14.0 4. Standards and calibration information, if appropriate: n/a 5. Environmental/experimental conditions: n/a 6. Describe any quality-assurance procedures performed on the data: n/a 7. People involved with sample collection, processing, analysis and/or submission: The authors. DATA-SPECIFIC INFORMATION FOR: ECE_2021-05-00718_nestling_data.xls 1. Number of variables: 42 2. Number of cases/rows: 363 3. Variable List: broodID – identity of brood FWS – identity of individual d13C – Ratio of carbon isotopes in feather,  ? values (‰) in parts per thousand, relative to Vienna PeeDee Belemnite (VPDB) as follows: ?X = (ratio of sample/ratio of standard) ? 1. d15N - – Ratio of nitrogen isotopes in feather,  ? values (‰) in parts per thousand, relative to atmospheric N2 (AIR) standards, respectively, as follows: ?X = (ratio of sample/ratio of standard) ? 1. sia_nstl – stable isotope analysis of feather, yes/no overall_prop_other – overall proportion of ‘other’ biomass, % other_biomass_high – other biomass > 5 %, yes/no d5_obs – yes/no, observed on day 5 d9_obs - yes/no, observed on day 9 d5_other_prop - overall proportion of ‘other’ biomass on day 5 d9_other_prop - overall proportion of ‘other’ biomass on day 9 exclude_simm – yes/no, exclude from mixing models box – nestbox identity nest – nest number broodsize – number of nestlings in brood d15_sample_date – date of day 15 sampling d15_julian – date of sampling converted to Jan 1 = 1 obs_date – date of feeding observation, where Jan 1 = 1 obs_num – number of observations obs_age – age of brood at observation est_type – type of estimate of diet composition (obs = observational) total_mass_delivered – total biomass consumed by individual in grams commonprey_mass – biomass contributed by common prey types in grams btl_prop – proportion of biomass consumed from beetles cic_prop– proportion of biomass consumed from cicadas ghop_prop – proportion of biomass consumed from grasshoppers larv_prop– proportion of biomass consumed from larva spid_prop – proportion of biomass consumed from spiders d15wt – body weight on day 15 in grams d15prime – 8th primary feather length on day 15 in mm d15tars – tarsus length on day 15 in mm wt_const – mass growth rate constant prime_const – 8th primary feather growth rate constant tars_const – tarsus growth rate constant d1wt – weight on day 1 in grams d3tars – tarsus on day 3 in mm d9prime – 8th primary feather length on day 9 in mm sex – sex of nestling sexcode – sex of nestling coded for analysis (0= female, 1 = male) headbill – head-bill length on day 15 in mm ketone – blood ketone concentration on day 13 in mmol/L fate – outcome for individual, failed (dead) or fledged (left nest alive) 4. Missing data codes: Left blank 5. Specialized formats or other abbreviations used: n/a B. final_consumers.csv 1. Number of variables: 4 2. Number of cases/rows: 162 3. Variable List: broodID – identity of brood FWS – identity of individual d13C – Ratio of carbon isotopes in feather,  ? values (‰) in parts per thousand, relative to Vienna PeeDee Belemnite (VPDB) as follows: ?X = (ratio of sample/ratio of standard) ? 1. d15N - – Ratio of nitrogen isotopes in feather,  ? values (‰) in parts per thousand, relative to atmospheric N2 (AIR) standards, respectively, as follows: ?X = (ratio of sample/ratio of standard) ? 1. C. sources_conc.csv 1. Number of variables: 7 2. Number of cases/rows: 5 3. Variable List: Prey – type of prey Meand13C – mean ratio of carbon isotopes in feather,  ? values (‰) in parts per thousand, relative to Vienna PeeDee Belemnite (VPDB) as follows: ?X = (ratio of sample/ratio of standard) ? 1. Meand15N – mean ratio of nitrogen isotopes in feather,  ? values (‰) in parts per thousand, relative to atmospheric N2 (AIR) standards, respectively, as follows: ?X = (ratio of sample/ratio of standard) ? 1. SDd13C – standard deviation of ratio of carbon isotopes in feather,  ? values (‰) in parts per thousand, relative to Vienna PeeDee Belemnite (VPDB) as follows: ?X = (ratio of sample/ratio of standard) ? 1. SDd15N – standard deviation of ratio of nitrogen isotopes in feather,  ? values (‰) in parts per thousand, relative to atmospheric N2 (AIR) standards, respectively, as follows: ?X = (ratio of sample/ratio of standard) ? 1. Concd13C – concentration of 13C Concd15N – concentration of 15N n – number of specimens used for stable isotope analysis D. tef.csv 1. Number of variables: 5 2. Number of cases/rows: 5 3. Variable List: Prey – type of prey Meand13C – mean enrichment of carbon between source and consumer. Meand15N – mean enrichment of nitrogen between source and consumer. SDd13C – standard deviation of enrichment of carbon between source and consumer. SDd15N – standard deviation of enrichment of nitrogen between source and consumer.