DOI: 10.6078/d1142q
title: Effects of supplemental feeding on nesting success and physiological metrics in Eastern Bluebirds (Sialia sialis)

description: Supplemental feeding is a common anthropogenic influence on wildlife
 which, dependent on natural food availability, can have positive or
 negative effects on physiological condition. Animals may respond
 negatively to supplemental feeding if the artificial food source increases
 disease risk due to aggregation. We manipulated supplemental food
 availability in a wild population of Eastern bluebirds, Sialia sialis, to
 examine the influence on physiological metrics and nesting success without
 causing birds to aggregate to access food. Adult and nestling bluebirds
 were randomly assigned to one of three feeding groups. The first treatment
 group received mealworms (Tenebrio molitor larvae) inside nest boxes
 throughout the breeding attempt, the second treatment group received
 mealworms from nest completion until nestlings hatched, and the third
 treatment group received no supplementation but was disturbed at the same
 frequency as the other two treatment groups. We collected blood samples
 from adults and nestlings to quantify bacterial killing ability,
 corticosterone levels, and heterophil to lymphocyte ratios. As measures of
 nesting success, we quantified hatching success and fledging success.
 Neither the physiological stress metrics nor the nesting success metrics
 were significantly different across the experimental groups with regard to
 treatment. This indicates Eastern bluebirds are not significantly impacted
 by supplemental mealworm feeding during breeding, at least when natural
 food sources are abundant. Removal of a supplemental food source during
 breeding also did not influence bluebird productivity. Bird feeding by
 hobbyists may attract birds to locations with available nesting sites
 without demonstrably negative or positive effects.
description: <strong>Field methods:</strong> The range of Eastern
 bluebirds extends from the central United States to the Atlantic Coast
 (Sibley et al., 2014). Bluebirds prefer to nest in edge habitats,
 including edges created by human development, which brings them into close
 contact with humans (Jones et al., 2014). Eastern bluebirds are secondary
 cavity nesters, and breed in artificial nest cavities. For this study,
 nest boxes (2015: n = 187, 2016: n = 176) located along walking trails and
 roads in Stillwater, Oklahoma (36°7′18″N 97°4′7″W) were utilized to
 manipulate the food available to breeding Eastern bluebirds. Nest boxes
 were checked 2-3 times weekly throughout the breeding season during
 March-August in 2015 and 2016. Individual boxes were monitored daily when
 complete nests were detected to determine first egg dates. Boxes were
 again monitored daily when clutches were within two days of their expected
 hatch date (clutch completion date + 13 days). Then nest boxes were
 monitored during regular nest checks to determine if fledging occurred.
 This frequency of monitoring generally follows methods used previously in
 this population (Author et al., 2012).
 <strong>Experimental manipulation of food
 availability:</strong> Small feeding cups (2 oz., plastic) were
 mounted in all nest boxes prior to the breeding season. In these cups,
 supplemental food was provided by adding fifteen mealworms (1.909 ±
 0.177g) per individual bluebird in the nest box, including both adults and
 nestlings, three times per week (~11.4 – 40 g weekly) (Smith, 2021). Each
 time the nest boxes were visited, it was noted whether the cups were empty
 or contained mealworms to track if the birds had consumed them. Any nest
 boxes with consistently full cups, likely neophobic individuals or
 recently failed nests, were removed from all analyses (9.53% of 63 boxes
 total for both years which received PART/FULL treatments and survived to
 day 5). All boxes included in the analyses consumed greater than half of
 all mealworms provided to them. The experimental groups
 were randomly allocated to FULL (2015: n = 35, 2016: n = 22), PART (2015:
 n = 26, 2016: n = 20) or CONT (2015: n = 36, 2016: n = 35) treatment
 groups. An additional subset of boxes was included as a control for
 potential effects of additional foot traffic at the boxes. The boxes in
 this second control group did not receive supplemental food and were
 visited only 2-3 times per week during regular nest monitoring. All other
 boxes, regardless of experimental treatment, were visited and opened the
 same number of times to control for any effects of disturbance. Because
 the two control groups did not differ significantly in any of the main
 effects (all p &gt; 0.058), these groups were combined in the analyses
 described below.
 <strong>Morphology:</strong> All adult birds in the
 study were captured for banding and weighing using a nest box trap no
 sooner than two days after nestlings hatched (Friedman et al., 2008). Mass
 for each individual was determined using either a digital balance
 (accuracy=0.01 g) or Pesola (accuracy=0.1 g). Nestlings were weighed on
 day 14 post-hatch (day 0=hatch day). Nestlings were banded with an
 aluminum USFWS band on day 11 post-hatch, and were examined to determine
 sex based on plumage coloration on day 14 (Pyle 1997).
 <strong>Nest Success:</strong> A clutch was
 considered complete when the number of eggs did not increase for more than
 one day. Hatching success was quantified as the proportion of eggs in the
 clutch that hatched. Fledging success was determined as the proportion of
 nestlings that left the nest after the day 14 measurement. The typical
 time to fledging in Eastern bluebirds is 17-19 days (Gowaty and Plissner,
 2015) with nestlings capable of weak flight at day 14. Nestlings absent
 from the nest after day 14 were considered successfully fledged, unless
 there was evidence of death or predation.
 <strong>Blood Sampling and Laboratory
 Methods:</strong> Blood samples (50-100 µL) were collected from all
 nestlings and adults within three minutes of removal from the nest box to
 determine CORT levels (Owen, 2011). Compared to other studies on this
 population in which CORT has been measured, CORT levels in this study were
 elevated (Author et al. 2012). In this study, we collected blood samples
 within three minutes of removal from the nest box, rather than within
 three minutes of initial disturbance, as in previous studies. All blood
 samples were taken between 0700-1100 hours to minimize variation due to
 circadian rhythms in hormone levels (Remage-Healey and Romero, 2000).
 Approximately 5-10 µl of each whole blood sample was used to prepare blood
 smears in the field. The remainder of each whole blood sample was kept
 cool on ice until it was brought to the laboratory for plasma separation
 with a centrifuge at 1846 xg for seven minutes, which took place within 4
 hours of collection. Plasma was stored at -20°C until it was used in BKA
 assays, or to measure plasma CORT. Average storage length prior to BKA
 analysis was 158±3.37 days. Storage length was not significantly related
 to BKA; therefore, we did not include this as a covariate in our analyses
 (t(76)=2.28, p = 0.99). Storage length also was not significantly related
 to CORT levels; therefore, we did not include this as a covariate in our
 analyses (t(276) =0.055, p = 0.956). Slides were
 stained with Differential Quik Stain following kit instructions (Triangle
 Biomedical Sciences; Davis et al., 2008). A complete blood cell count was
 performed following the techniques described in Avian and Exotic Animal
 Hematology and Cytology (Campbell and Ellis, 2013, Clark et al., 2009) by
 an expert in white blood cell identification (IK) who was blind to the
 identity of the treatment groups. Heterophil to lymphocyte (H:L) ratios
 were calculated by dividing the total number of heterophils by the total
 number of lymphocytes. Enzyme immunoassays
 (Corticosterone ELISA Kit ADI-901-097, Enzo Life Sciences) were used to
 quantify circulating plasma CORT levels. Based on previous optimization of
 the assay for Eastern bluebirds (unpubl. data), plasma samples were
 diluted 1:40 in 1.5% steroid displacement reagent (SDR). All samples were
 run in duplicate and the corticosterone standards (20,000, 4,000, 800,
 500, 160, and 32 pg/mL) were run in triplicate. The optical density of the
 plates was then read at 405 nm on a BioTek ELx808 microplate reader.
 Samples with intra-assay coefficients of variation (CVs) higher than 15%
 were re-run (average intra-assay CV: 6.25%). The average inter-assay CV
 was 14.57%. Tryptic soy agar (Fisher Scientific,
 DF0369-17-6) plates were made under sterile conditions and stored at 4°C
 the day prior to conducting BKA assays. <em>Escherichia
 coli</em> (ATCC #8739, Microbiologics) stocks and dilutions were
 prepared the day before assays were conducted. E. coli stock solutions
 were prepared by adding one lyophilized bacteria pellet (5.6 x 107 CFU) to
 40 mL of phosphate-buffered saline (Sigma Aldrich, P-5368), which was then
 incubated at 37°C for 30 minutes and stored at 4°C. Plasma and bacteria
 were incubated in carbon dioxide independent media (Invitrogen Inc, Gibco
 media #18045). Additionally, 200 µL of 200 mM L-glutamine (Life
 Technologies, 25030-149) was added to the solution prior to incubation. To
 perform the assay, 5 µL of plasma was combined with 100 µL of the media
 solution and 10 µL of bacterial working solution. The bacteria and plasma
 were incubated together for 30 minutes at 41°C. The samples were then
 plated on agar plates and incubated for a minimum of 12 hours at 37°C.
 Control plates were prepared in the same manner as experimental plates;
 however, control plates did not contain plasma. The number of colonies on
 each plate was counted after the 12-hour incubation. Finally, the BKA of
 each plasma sample was quantified as the percent difference in the number
 of colonies on plasma treated plates compared to the number of colonies on
 control plates. <strong>Statistical
 Methods:</strong> We compared masses of nestlings on day 14 among
 supplement groups to determine if variation in supplemental feeding
 schedules affected fledging mass. We used R (v. 4.1.0) to create linear
 mixed-effects models from the <em>lme4</em> package to account
 for non-independence of nestlings and mated pairs from the same nest.
 NestID, a concatenate variable created with nest box names and start
 dates, was included as a random effect to account for non-independence and
 month was included as a fixed effect to account for seasonal variation.
 Masses of adults were collected at the time of capture and, while we did
 not anticipate an effect of our experiment on adult mass, we analyzed
 adult body mass separately using the same methods as for
 nestlings. We conducted separate analyses on adults and
 nestlings for CORT, H:L ratios, and BKA. We again used linear
 mixed-effects models from the<em> lme4 </em>package to account
 for non-independence of nestlings and included NestID, as a random effect.
 Month was also included in these analyses as a fixed effect. For CORT, we
 evaluated 56 adults and 220 nestlings. For H:L ratios, we analyzed 48
 adults and 44 nestlings, and for BKA, we analyzed 49 adults and 69
 nestlings. For nestling measures of H:L ratio, we selected one nestling at
 random from each brood prior to data collection due to constraints on
 supplies and personnel. We acknowledge that nestlings might exhibit high
 variability in physiological traits within the same nest, but we opted to
 capture population-level variation, rather than within nest variation.
 CORT and H:L ratios were not normally distributed; therefore, we
 normalized these values by log10 transformation (Lobato et al.,
 2009). To evaluate the effect of supplemental feeding
 on nesting success, we compared hatching and fledging success among
 experimental groups with month included as a fixed effect. Finally, to
 assess whether adult physiology was predictive of nesting success, we also
 determined whether CORT, BKA, or H:L ratios were associated with measures
 of nesting success across treatment groups. We used logistic regressions
 with a quasibinomial distribution for these analyses because fledging and
 hatching success varied between 0 and 1, with intermediate values
 representing portions of broods that successfully hatched or fledged. To
 ensure independence of measurements in instances when we had data from two
 adults associated with a nest, we removed one individual using a random
 number generator in Python (v. 3.6). Thus, only one adult was associated
 with success at each nest. We also included month as a factor due to the
 potential for reproductive success to vary during the season.
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