DOI: 10.5061/dryad.z8w9ghxff
title: Failed despots and the equitable distribution of fitness in a subsidized species

description: Territorial species are often predicted to adhere to an ideal despotic
 distribution and under-match local food resources, meaning that
 individuals in high-quality habitat achieve higher fitness than those in
 low-quality habitat. However, conditions such as high density, territory
 compression, and frequent territorial disputes in high-quality habitat are
 expected to cause habitat quality to decline as population density
 increases and, instead, promote resource matching. We studied a highly
 human-subsidized and under-matched population of Steller’s jays
 (Cyanocitta stelleri) to determine how under-matching is maintained
 despite high densities, compressed territories, and frequent agonistic
 behaviors, which should promote resource matching. We examined the
 distribution of fitness among individuals in high-quality, subsidized
 habitat, by categorizing jays into dominance classes and characterizing
 individual consumption of human food, body condition, fecundity, and core
 area size and spatial distribution. Individuals of all dominance classes
 consumed similar amounts of human food and had similar body condition and
 fecundity. However, the most dominant individuals maintained smaller core
 areas that had greater overlap with subsidized habitat than those of
 subordinates. Thus, we found that 1) jays attain high densities in
 subsidized areas because dominant individuals do not exclude subordinates
 from human food subsidies and 2) jay densities do not reach the level
 necessary to facilitate resource matching because dominant individuals
 monopolize space in subsidized areas. Our results suggest that
 human-modified landscapes may decouple dominance from fitness and that
 incomplete exclusion of subordinates may be a common mechanism
 underpinning high densities and creating source populations of
 synanthropic species in subsidized environments.
description: <strong>Study system and sampling.</strong> We
 studied populations of Steller’s jays in two campgrounds within Big Basin
 Redwoods State Park, Santa Cruz County, California (hereafter Big Basin;
 Figure 1), to test our hypotheses about resource under-matching. Because
 of the availability of human food subsidies and previously established
 high fitness of jays utilizing campground areas, we considered campgrounds
 to be high-quality habitat and surrounding forest areas to be of lower
 quality (West and Peery 2017; West et al. 2019). We collected data during
 three breeding seasons, mid-May – mid-August, in 2017, 2018, and 2019. We
 captured and banded jays with unique color combinations for individual
 recognition and to assess individual fitness (see next sections). We used
 call playback and a combination of mist nets (Avinet Research Supply) and
 live traps (Havahart and homemade) to capture jays during all three years
 of the study. To characterize jay space use, we also deployed radio
 transmitters (Model A1070, Advanced Telemetry Systems) on jays using
 backpack-style harnesses made of 0.1” natural tubular spectra tape (Bally
 Ribbon Mills) in each year of the study. Handling time was kept to a
 minimum (usually &lt;5 minutes, slightly longer for birds receiving
 radio tags), and samples taken are discussed in the subsequent sections.
 All appropriate guidelines for humane and ethical use of animals in
 research were followed, and research was conducted under IACUC protocol
 A005411-R01-A01 and scientific collection permit SC-13714. To our
 knowledge, no Steller’s jays were injured or died as a result of our
 activities. To examine jay space use, we tracked each
 radio tagged jay to determine their precise location (± 10 m) 25-35 times
 per season. We allowed at least two hours between relocations of the same
 individual to ensure independence between relocations (Swihart and Slade
 1985), and we varied the time of day during which we tracked individuals.
 We also collected roost locations (between 2200 and 0300) to ensure that
 we fully characterized jay home ranges. We tracked birds by searching on
 foot with telemetry equipment and marked jay locations using a handheld
 GPS unit. Observations of jays and jay behavior throughout the breeding
 season allowed us to assess the breeding status of jays and determine the
 identities of socially monogamous jay pairs. We only used male jays for
 these analyses because female jays are generally subordinate to males
 (Brown 1963), and our sample size of uniquely identified females did not
 allow dominance assessment. <strong>Defining
 dominance classes.</strong> We classified jays into dominance
 classes by conducting controlled feeding trials (hereafter ‘behavior
 trials’) at picnic tables. Because jays have site-based dominance where
 territorial defense typically weakens as distance from the nest site
 increases (Brown 1963), we determined a dominance ranking of jays at
 individual picnic tables dispersed throughout the entire campground to
 ensure we fully captured spatial variation in dominance for each
 individual. During each trial, we placed approximately 10 peanuts at the
 center of a picnic table and then observed jays as they interacted with
 conspecifics to exploit the food source (Brown 1963; West and Peery 2017).
 We recorded every banded individual present at each trial, the winner and
 loser of each interaction, and the aggression level of each interaction on
 a 0-5 scale. An aggression level of zero indicated that individuals did
 not interact when feeding at the same time on a table, and so no winner
 was recorded. Aggression levels were defined as follows: 1: one jay
 wing-flapped and vocalized with an ‘aap’ or ‘wek’ call at another; 2: one
 jay displaced another; 3: one jay chased another; 4: jays aggressively
 sidled with one another but did not make contact; 5: jays physically
 fought with one another (West and Peery 2017). We evaluated the results of
 behavior trials to determine the most dominant bird at each table. To be
 considered dominant at a table, an individual had to win at least 3
 interactions at that table. At each table, an individual was considered
 dominant if it won the most interactions at that table or if it always won
 interactions against the bird that won the most interactions. In cases
 where there was not a consistent winner between two individuals that
 consistently won against all other individuals, or where consistent
 winners did not interact with one another, we classified the bird with the
 higher average aggression score in contests that they won as dominant. In
 cases where individuals’ wins and aggression scores tied, both were
 considered dominant at a given table. An individual was also considered
 dominant at a given table if it was the only individual (with the
 exception of its mate) to appear for two or more 15-minute trials at a
 specific table on different days. There were occasionally tables at which
 not enough interactions occurred to determine a dominant bird. We
 conducted between one and six trials at each of 49 picnic tables in
 Bloom’s Creek Campground and 65 picnic tables in Huckleberry Campground
 each year. We determined dominance for each year
 separately because dominance and core areas could shift from year to year.
 Within each year, we overlaid core areas (see below for core area
 delineation methods) in ArcMap (version 10.7; ESRI 2019) with the results
 of the behavior trials at each picnic table, and then classified jays into
 three social classes. ‘High’ dominance included individuals that were
 dominant at tables within and outside their core area, ‘medium’ dominance
 included individuals that were dominant only within their core area, and
 ‘low’ dominance included individuals that were not dominant anywhere
 within the campground (Figure 2). We used this method, rather than
 traditional Elo-ratings or other established methods because jay dominance
 hierarchies shift spatially throughout a given area (Brown 1963) and
 because we were simply interested in identifying the most dominant
 individual rather than revealing the entire dominance hierarchy.
   <strong>Human food subsidy
 consumption.</strong> We evaluated individual consumption of human
 food subsidies using stable isotope analysis of
 δ<sup>13</sup>C in primary feathers.
 δ<sup>13</sup>C is a useful indicator of human food
 consumption because human foods are often made up of corn (a
 C<sub>4</sub> plant) and corn byproducts, making them enriched
 in the heavy isotope of carbon. This makes them isotopically
 distinguishable from natural prey items in western North America because
 primary production in this area is driven by native
 C<sub>3</sub> plants (Newsome et al. 2010; West et al. 2016).
 We clipped approximately 50 mm of the most recently grown new primary
 flight feather from each captured jay at the end of the breeding season
 (early-mid August) at least 40 days after the conclusion of behavior
 trials. Because feathers incorporate the isotopic signature of the diet
 during periods of feather growth (Hobson and Clark 1992) and a primary
 feather takes approximately 30 days to grow, these feather samples
 represented breeding season diet but were not contaminated by any peanut
 consumption that occurred during the behavior trials. We rinsed feather
 samples thrice in 2:1 Chloroform:Methanol solution to remove surface
 contaminants and then homogenized them using scissors. Homogenized
 feathers were dried for approximately 72 hours at 55˚C. Analysis of
 δ<sup>13</sup>C was conducted at the University of New Mexico
 Center for Stable Isotopes using a Thermo Scientific Delta V mass
 spectrometer connected to a high-temperature conversion elemental analyzer
 and a Costech 4010 elemental analyzer. We report
 δ<sup>13</sup>C results as parts per mil (‰) ratio relative to
 the international standard, Vienna-Pee Dee Belemnite limestone. We
 examined the relationship between dominance class and human food subsidy
 consumption using a linear mixed model with individual as a random effect
 because we captured some of the same individuals in multiple years of the
 study. We used δ<sup>13</sup>C as the continuous response
 variable and categorical dominance class (i.e., low, medium, high) as the
 fixed effect. We also included year as a fixed effect to correct for some
 heteroscedasticity in the residuals. Results are presented as the
 estimated marginal mean averaged over the three years of the study and a
 95% confidence interval. <strong>Fitness
 metrics.</strong> To understand how fitness was distributed among
 birds in different dominance classes, we collected data on body condition
 (i.e., body mass and growth bar width) and annual fecundity (i.e., number
 of fledged young). We conducted analyses using the ‘lme4’ package (version
 1.1-21; Bates et al. 2015) and compared means between dominance classes
 when necessary using the ‘emmeans’ package (version 1.6.1; Lenth 2021) in
 the R Statistical Environment (R Core Team 2020).  We
 measured two indices of body condition: body mass and growth bar width. We
 measured body mass using a Pesola scale when birds were recaptured at the
 end of the breeding season (early-mid August). We standardized body mass
 for body size using tarsus length cubed, an index of body volume (West and
 Peery 2017). We measured tarsus length using calipers during the same
 capture event at which body mass was measured. We then multiplied these
 values by 10,000 for ease in reporting results. We first evaluated body
 mass among the dominance classes using a linear mixed model with
 individual as a random effect. However, the variance of the random effect
 was estimated as zero, and thus we removed it and simply used a two-way
 ANOVA. Standardized body mass was the continuous response variable, and we
 used dominance class and year as categorical factors. We did not include
 an interaction effect between dominance class and year because there was
 no reason to expect a different relationship between body mass and
 dominance among years.  We used growth bar width as
 another indicator of individual body condition. A feather growth bar
 consists of one dark band produced during the day, and one light band,
 produced at night (Wood 1950). Together, one set of bands constitutes
 feather growth in a 24-hour period (Wood 1950; Grubb 2006). Feather growth
 is energetically costly, and therefore the ability to grow feathers faster
 (i.e., wider growth bars) is positively correlated with nutritional status
 (Grubb 1991). We collected the newest newly grown rectrix, determined by
 molt pattern and presence of feather sheaths, from each jay recaptured at
 the end of the breeding season, at least 40 days after the conclusion of
 behavior trials. Growth bars reflect nutrition during the time of feather
 growth and thus, because we took a newly grown feather, growth bar width
 was not contaminated by any peanuts that may have been consumed during the
 behavior trials. We standardized growth bar width by body size using
 tarsus length cubed, as we did for body mass, and multiplied it by 100,000
 for ease in reporting. We then used a linear mixed model with individual
 as a random effect to assess the relationship between dominance class and
 growth bar width. We used standardized growth bar width as the continuous
 response variable and we used dominance class and year as additive fixed
 effects. Results are presented as the estimated marginal mean averaged
 over the three years of the study and a 95% confidence interval.
 We estimated annual fecundity (i.e., number of fledglings
 produced) for individual jays by either locating and monitoring nests
 until the young fledged (n = 4) or by following radio-tagged birds and
 observing how many fledglings they interacted with (e.g. begging or
 feeding behavior; <em>n</em> = 47). Fledgling Steller’s jays
 follow and receive food from their parents for 30 days or more after
 fledging (Walker et al. 2020; EHW and KB <em>pers.
 observations</em>), so it was possible to determine nest success and
 number of fledglings by closely observing both members of the pair after
 nesting was completed. When possible, we also banded juveniles so that we
 could discern identities when we observed family groups on multiple
 occasions. While locating nests and measuring components of reproduction
 like lay date, clutch size, hatching success, and nestling condition would
 have been ideal, we did not have the resources to conduct thorough nest
 searches. We instead used fledging success as our measure of annual
 fecundity (Weatherhead and Dufour 2000).  We treated
 annual fecundity two different ways for analysis. We first considered
 annual fecundity as continuous and compared the mean number of fledglings
 per male per year among dominance classes using a linear mixed model with
 individual as a random effect. The variance of the random effect was
 estimated to be zero, so we removed it from the model and assumed
 independence among all annual fecundity estimates. Due to small sample
 sizes and non-normality in the distribution of fecundity data, we used a
 Kruskal-Wallis test for the final comparison of mean annual fecundity
 between dominance classes. In our second approach, we treated fecundity as
 a binary indicator of nest success by grouping birds according to whether
 they successfully fledged offspring or not. We then conducted a
 chi-squared test to determine if there was any relationship between
 ordinal dominance class and nest success.
 <strong>Space use. </strong>To characterize jay space
 use, we delineated home ranges and core areas for each radio-tagged
 individual. We defined a home range as the 95% Utilization Distribution
 for each individual jay (West et al. 2016), and we analyzed relocation
 data using the adehabitatHR package (Calenge 2006) in the R Statistical
 Environment (R Core Team 2020). Next, we delineated core areas following
 methods from Vander Wal and Rodgers (2012). Specifically, we plotted each
 jay’s utilization distribution area against the isopleth volume (Figure
 S1) and identified the isopleth at which the slope was closest to one
 (Vander Wal and Rodgers 2012). This point represents the threshold at
 which proportional home range area begins to increase at a greater rate
 than the probability of use, and we used that isopleth to define the
 borders of each jay’s core area (Vander Wal and Rodgers 2012). We chose
 this method, rather than using an arbitrary 50% utilization distribution,
 in an effort to ensure that our core areas accurately represented the
 areas that received the greatest use (see Appendix S1 for a comparison of
 methods). Finally, we removed seven individuals from all further analyses
 because their core areas did not overlap campground areas, so we could not
 accurately assess their dominance class. We originally
 planned to examine both core area size and home range size in relation to
 dominance class, but because these two measurements were highly positively
 correlated (r = 0.97), we only considered core area size. We
 log-transformed core area size to meet the assumption of normal
 distribution and then used a linear mixed model with individual as a
 random effect to examine the relationship between dominance class and core
 area size. The variance of the random effect was estimated as zero, so we
 removed it from the model and used a two-way ANOVA with dominance class
 and year as categorical factors. Results are presented as the estimated
 marginal mean averaged over the three years of the study and a 95%
 confidence interval. To compare the spatial
 distribution of core areas in relation to high-quality habitat, we
 calculated the proportion of overlap between each individual’s core area
 and the campground area. To delineate the campground boundary, we created
 a 10-m buffer around each campsite and used the minimum bounding geometry
 tool in ArcMap (version 10.7.1; ESRI 2019) to create minimum convex hull
 polygons around the two campgrounds. We calculated the area of overlap
 between individual core areas and campgrounds and then divided by the
 total area of individual core areas to determine the proportion of each
 individual’s core area that overlapped with the campground. Steller’s jays
 in their first breeding season rarely breed (Brown 1963, West and Peery
 2017), and we observed that some of these individuals utilized a strategy
 of being subordinate ‘floaters’ in which they maintained a high degree of
 overlap with campground areas. Our hypotheses were restricted to
 territorial, breeding jays, and we therefore included only individuals
 known to be in at least their second breeding season in this analysis. To
 test whether highly dominant individuals had more overlap with campgrounds
 than subordinates, we conducted a two-way ANOVA, with the proportion of
 core area overlap with campgrounds as the response, and dominance class
 and year as explanatory variables.
description: Data fle is in csv format, can be opened using Microsoft Excel
 and statistical programs (all analyses were completed in the R Statistical
 Environment).