Between 2010 and 2014, we equipped 561 adult tree swallows with an archival light-level geolocator (hereafter referred to as “geolocators”) at the 12 breeding sites (Fairbanks, Alaska, 65.90°N, 147.70°W; Vancouver, British Columbia, 49.21°N, 123.18°W; Prince George, British Columbia, 53.85°N, 123.02°W; Beaverhill, Alberta, 53.40°N, 112.50°W, Saskatoon, Saskatchewan, 52.17°N, 106.10°W; Ames, Iowa, 42.11°N, 93.59°W; Saukville, Wisconsin, 43.40°N, 88.00°W; Boone, North Carolina, 36.21°N, 81.67°W; Long Point, Ontario, 42.62°N, 80.46°W; Ithaca, New York, 42.50°N, 76.50°W; Sherbrooke, Québec, 45.55°N, 72.60°W; Wolfville, Nova Scotia, 45.10°N, 64.39°W). Overall, we retrieved 161 geolocators, 133 of which were free from malfunctions. Each bird was tracked for a 1-year period. Of these 133, we obtained reproductive history from 105 individuals. Birds from Vancouver, Alaska, Iowa, and North Carolina were not included in this study, either because of small sample size or because individuals at these sites were outliers based on migration distances within their respective flyway. Eighty-nine individuals (46 females and 43 males) were therefore used in this study.

Light data from geolocators were analyzed using the BAStag package 0.1.3 (Wotherspoon et al., 2013) and FlightR package version 0.3.6 (Rakhimberdiev et al., 2015b) with R version 3.2.3 (R Core Development Team, 2016). The FlightR package works well for open area birds, and it uses a state-space hidden Markov model to estimate daily locations. For step-by-step details about geolocator deployment and analysis see Knight et al. (2018). Given the well-defined light transitions, geolocator error was minimal (46 ± 90 km in latitude and 52 ± 90 km in longitude; Gow et al., 2019). Geolocator error was calculated based on averaged location estimates from the breeding site (Gow et al., 2019). We followed the definitions in Gow et al. (2019) for determining wintering site, and identifying departure and arrival at sites. Briefly, locations were determined by calculating the mean location of all daily locations from a stationary period. We considered birds to have departed from the wintering site if they made a large (≥ 250 km) northward movement, lasting for at least 2 d, away from a stationary position. Given that tree swallows may use more than one wintering site (Knight et al., 2018), the last wintering site was defined as the last location that a tree swallow spent at least 28 d. Breeding arrival date was defined as the first day tree swallows had location estimates consistently matching those of the known breeding site.

Tree swallows breed in natural tree cavities or nest boxes throughout the southern half of Canada and the north/central United States; they generally have clutches of 4–7 eggs (Winkler et al., 2011). All tree swallows in our study were single-brooded, although some females attempted a second clutch if their first nest was depredated. Tree swallow clutch sizes increase with breeding latitude (Dunn et al., 2000). At each study site, nest boxes were checked every 1–7 days (with most sites checking nests every 1–3 days) to obtain the following breeding information from individuals in the year following geolocator deployment: first egg date (date on which the first egg of the first clutch of the season was laid), clutch size (number of eggs laid in the first clutch of the season), and number of young fledged (number of young estimated to have survived to fledging). All failed nests were counted as zero in our analyses. We determined breeding arrival date (date bird first arrived at the breeding site), and spring migration distance for each tree swallow carrying a geolocator. We calculated spring migration distance as the great circle distance between the last overwintering site and the breeding site (i.e., spring migration distance; Figure 1; Bradley et al., 2014). The arrows in Figure 1 show the general pathways used to calculate migration distance for each population. Most tree swallows migrated during the spring equinox making it difficult to estimate the true travel route. Thus, for consistency among individuals we calculated migration distance using several points along the migration pathways for tree swallows defined by Bradley et al. (2014; Figure 1). The connections between wintering and breeding sites are available in Knight et al. (2018).

We interpreted clutch size and the number of young fledged differently between sexes. For females, clutch size and the number of young fledged are direct measures of reproductive success. However, because there is rampant extra-pair paternity in tree swallows (e.g., 50–89%; Lifjeld et al., 1993; Barber et al., 1996; Kempenaers et al., 2001; Whittingham and Dunn, 2001; O'Brien and Dawson, 2007), the number of young fledged likely does not represent realized (i.e., genetic) reproductive success of males. Realized reproductive success would account for both a male's potential paternity lost within his nest and potential paternity gained via extra-pair fertilizations outside the social pair bond. Given that we did not have genetic paternity data from our sites, we could not include realized reproductive success of males in our study. Thus, for males, the number of young fledged within the social pair bond (the variable we measured and included in our study) more accurately reflects the quality of the social partner rather than true reproductive success in a given season. First egg dates and clutch size also mainly reflect the quality of the social partner rather than true reproductive parameters for males, meaning that the only reproductive variable that is solely influenced by males was breeding arrival date. Breeding arrival date may have subsequent carry-over effects that may influence the quality of the social mates that a male is able to acquire.

A network analysis by Knight et al. (2018) showed how breeding populations segmented into three migratory flyways: Western, Central, and Eastern. We chose to combine the Western and Central flyways because of the small sample of birds in the Western flyway (n = 11) and because these two flyways had similar means and standard deviations (s.d.) of migration distance (Western: 3,833 ± 795 km; Central: 4,217 ± 1,082 km; Table 1). We eliminated 4 populations from our analyses that had a small sample size (Vancouver, BC and Ames, IA) and/or represented extreme southern and northern regions of the tree swallows' range (Fairbanks, AK and Boone, SC). The populations we included from the Western and Central flyways (hereafter referred to as the Central flyway for simplicity) were Prince George, BC, Beaverhill, AB, and Saskatoon, SK (N = 36; female = 13; male = 23; Figure 1A), and those in the Eastern flyway were Saukville, WI, Long Point, ON, Ithaca, NY, Sherbrooke, QC, and Wolfville, NS (N = 53; female = 33; male = 20; Figure 1B).

Prior to executing the path analysis, we undertook two types of data standardizations to help separate the potential effects of breeding location on life-history variation from the effects on individuals migrating farther than other individuals within their flyway. First, we standardized each variable by flyway (sexes pooled) by subtracting the mean then dividing by the standard deviation (i.e., z-transformation). This allowed us to control for flyway effects. Second, we z-transformed these data across all individuals independent of flyway. If there was a positive effect of migration distance on first egg date, clutch size, or young fledged when the dataset was standardized across all individuals, then this may indicate the relationship was due to life-history factors rather than migration distance per se. In contrast, when standardizing by flyway, if there is a negative relationship between migration distance on first egg date, clutch size or young fledged, then this may suggest a potential carry-over effect of migration distance.

Following this standardization, we evaluated the direct and indirect effects of migration duration, migration distance, breeding arrival date, first egg date, and clutch size on the number of young fledged using a multi-level path modeling framework (Shipley, 2000, 2009). We included a random effect of “breeding site” to account for local-level effects across the 8 breeding populations. All mixed effects models were fitted with a Gaussian distribution, as the response variables best fit this distribution, using the nlme package (Pinheiro et al., 2018) in R 3.5.2 (R Core Development Team, 2018). We identified the most parsimonious path model based on Akaike's Information Criterion corrected for sample size (AICc; Shipley, 2000, 2009, 2013). We evaluated four different sets of path models, separated by sex and standardization method (i.e., standardized by flyway or standardized across individuals).

We structured the path models based on previous knowledge of tree swallow ecology. For each set of path models, we started by fitting a global model, which included direct effects of spring migration duration, spring migration distance, breeding arrival date, first egg date, and clutch size on the number of young fledged. We removed terms associated with uninformative estimates for young fledged first, followed by those with uninformative estimates for clutch size, first egg date, breeding arrival date, and migration distance. We determined the order of deletion using AICc to assess the terms with the least support in each submodel using maximum likelihood estimation (MuMIn package; Barton, 2016; see Figure S1 for path analysis sub-models). We removed terms from the path model if their deletion did not increase the AIC by at least two units (Table S1). Models were not averaged because top models were all nested within preceding models (Arnold, 2010).

From the path analysis, we calculated direct effects of one variable on another as well as indirect effects (Mitchell, 1993). Indirect effects were calculated by taking the product of all possible pathways (path coefficients) from one variable to another. Direct effects occur between variables and are generated by path coefficients (regression beta coefficients). Because we standardized the dataset prior to conducting the path analysis we did not need to standardize the path coefficients. The total effect was calculated as the sum of all indirect and direct effects from one variable to another.

We compared migration distances between sex and standardization type using a linear mixed effects model (LMM). We included breeding site as a random effect. We used post-hoc pairwise differences to compare migration distances between the sexes standardized by flyway or across individuals.

Because total effect values summarize all direct and indirect pathways between migration distance to the number of young fledged, we also produced a predictive model. This model involved first summarizing the effect of migration distance on the number of young fledged using the total effect values and standard deviations (s.d.) for each variable (Bart and Earnst, 1999). For example, the effect of migration distance on number of young fledged was expressed as: s.d. (migration distance) = s.d. (young fledged^*total effect). We took the mean migration distance and used it to predict differences in the number of young fledged across different migration distances. We only developed predictive models for the sex and standardizations in which there was at least one effect of migration distance on a reproductive metric.

This study was carried out in accordance with the principles of Animal Utilization Protocols or Animal Care Protocols and was approved by each University of the primary researcher for each field site.

Tree swallows migrated on average 2,930 ± 1,110 km (range: 1,496–4,879 km). While males migrated farther and showed more variation in migration distances than females (males: 3,110 ± 1,187 km; females: 2,761 ± 1,017 km), there was no evidence the sexes arose from different distributions (LMM: β = −61.89 ± 82.44, t = −0.75, p = 0.45; Table 1). Females migrated significantly farther and had different distributions in their migration distances in the Central flyway than the Eastern flyway (LMM: β = 2,129 ± 261, t = 8.14, p < 0.001; Table 1), and a similar pattern was observed for males (LMM: β = 2,201 ± 161, t = 13.66, p < 0.001; Table 1). Males spent more time on average migrating than females but this difference was not significant (LMM: β = 5.58 ± 4.67, t = 1.19, p = 0.24; Table 2). In the Central flyway, females spent significantly more time on spring migration compared to the Eastern flyway (LMM: β = 15.58 ± 6.0, t = 2.60, p < 0.01; Table 2). Although males in the Central flyway spent more days migrating in the spring than in the Eastern flyway, this was not significantly different (LMM: β = 13.13 ± 7.24, t = 1.81, p = 0.14; Table 2).

For females, migration distance negatively affected the number of young fledged (Figure 2). Females migrating the shortest distances within their flyway fledged more young compared to those migrating the farthest distances, suggesting a direct carry-over effect of migration distance on young fledged. In contrast, for males there was no effect of migration distance on clutch size or young fledged, but males that spent longer migrating in the spring arrived later to the breeding site. Breeding arrival date positively influenced first egg dates in females, but males that arrived later had social mates that laid their first clutches earlier. For females, first egg dates did not influence clutch size. Earlier breeding males had social mates that produced larger clutches than later breeding males. For females, clutch size positively affected the number of young fledged, and males mated to females that laid large clutches also fledged more young. Overall, the total effect of migration distance on number of young fledged for females was −0.55 ± 0.33, resulting in a predicted 1.33 fewer young for every 1,017 km they migrated (Figure 3).

Migration distance in females directly and positively affected migration duration, first egg dates, and young fledged (Figure 2). Given the later first egg dates and higher number of young fledged in the Central flyway than the Eastern flyway (Table 2), results from the path analysis showed that females migrating the farthest distances (most birds in the Central flyway) fledged more young and also began breeding later than females migrating shorter distances (most birds in the Eastern flyway). For males, migration distance had a positive direct effect on migration duration, and the male's social mate's first egg date and clutch size. Furthermore, males traveling the farthest distances (typically in the Central flyway) began breeding later and their social mate had larger clutches than those migrating shorter distances (typically the Eastern flyway). But the negative relationship between first egg date and clutch size suggested that males with social mates that began breeding later had smaller clutches. Overall, the total effect of migration distance on young fledged for females was 0.31, which implied that females fledged 0.74 more young for every 1,017 km farther they migrated. For males, the total effect of migration distance on young fledged was 0.16, which implied that males fledged 0.26 more young for every 1,186 km farther they migrated (Figure 3).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer, MH, declared past collaborations with several of the authors, DN, DW, CT, and EB, to the handling editor.