Sébastien Roques
email: se.roques@gmail.com

David B Lank

Emmanuelle Cam

Roger Pradel

Migratory sandpiper behaviour at stopover sites More Than Just Refuelling: Lengthy Stopover and Selection of Departure Weather by Sandpipers Prior to Transoceanic and Transcontinental Flights

Keywords: stopover decisions, migration, capture-recapture, Bayesian analysis, barrier effect

The evolutionary and behavioural ecology of migratory birds has received much theoretical and empirical attention. We contribute to this field by contrasting the weather at departure and stopover durations of a long-distance migratory sandpiper prior to initiating lengthy transoceanic versus transcontinental flights of potentially variable duration. Transoceanic flights provide few if any stopover options. We predicted that transoceanic migrants should therefore be more selective of energetically favourable weather at departure and have longer stopover durations prior to departing, using time as a surrogate for cumulative fuel acquisition, than transcontinental migrants. We used recent advances in capture-recapture modelling to quantify how weather conditions, length of stay, including estimated residence time prior to capture, and age class correlated with daily departure probabilities of Semipalmated Sandpipers (Calidris pusilla) at a coastal and an inland stopover site at comparable latitude. As expected, departure probabilities from both sites were higher with increasing strength of tailwinds, and the strength of this effect was larger for birds facing transoceanic versus transcontinental flights.

Cloud cover and temperature conditions at departure converged between sites at intermediate values from different background distributions. Stopover durations at both sites were substantially longer than needed if the birds were pursuing a simple tactic of arrive-fatten-leave at the stopover site. We infer that both sites provided high levels of both food and safety relative to other stages in the birds' annual cycle, which favoured lengthy stopovers and subsequent use of lengthy flights from both sites. Our study shows that recent advances of capture-recapture models can provide additional resolution to studies of the migration strategies of birds and refine our perspective on global patterns of migration routes and stopover decisions.

Migratory birds make their biannual movements between breeding and non-breeding areas in a series of flights. Selection will favour flight strategies that include 'hops skips or jumps', and variable stopover durations between flights [START_REF] Schaub | Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site[END_REF][START_REF] Warnock | Stopping vs. staging: The difference between a hop and a jump[END_REF][START_REF] Anderson | Migration distance and body condition influence shorebird migration strategies and stopover decisions during southbound migration[END_REF]) that optimize fitness [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF]. Thus, birds' internal conditions and external situations when initiating flights should provide information about the nature of selection during the subsequent migratory flight. As an extreme example, Bar-tailed Godwits (Limosa lapponica baueri) departing on spectacular 6-9 day non-stop trans-Pacific Ocean flights from Alaska to New Zealand carry fuel stores approximately equal to their airframe body mass and do so when stronger tailwinds are available [START_REF] Gill | Extreme endurance flights by landbirds crossing the Pacific Ocean: Ecological corridor rather than barrier?[END_REF]. Ecologically, sufficiently food-rich and safe staging sites must be available to permit selection favouring the evolution of such flights [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF], Ydenberg et al. 2007). But generally, theory shows that the costs of transporting excess fuel trades off against flight distance [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF]). Thus, most migration routes consist of multiple stopover sites where migrants prepare for successive stages of their journeys. Different migration strategies occur among species, among populations traversing different routes, between age classes and sexes, at different sites in a sequential journey, and even among individuals within these groups [START_REF] Mckinnon | Tracking from the tropics reveals behaviour of juvenile songbirds on their first spring migration[END_REF][START_REF] Deppe | Fat, weather, and date affect migratory songbirds' departure decisions, routes, and time it takes to cross the Gulf of Mexico[END_REF][START_REF] Hua | Springtime migratory restlessness and departure orientation of Great Knots (Calidris tenuirostris) in the south compared to the north Yellow Sea[END_REF][START_REF] Vansteelant | Wind conditions and geography shape the first outbound migration of juvenile honey buzzards and their distribution across sub-Saharan Africa[END_REF].

The decision whether to depart from a stopover site at a particular time is understood to be an evolved strategic decision rule conditioned proximately on internal state variables, principally potential food acquisition rate and current fuel stores, and environmental factors, especially weather conditions. Fuel stores can limit maximum flight ranges, and departure decisions are therefore often related to them (e.g. [START_REF] Schaub | Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site[END_REF][START_REF] Arizaga | Effect of fuel load, date, rain and wind on departure decisions of a migratory passerine[END_REF][START_REF] Schmaljohann | How do energy stores and changes in these affect departure decisions by migratory birds? A critical view on stopover ecology studies and some future perspectives[END_REF]. Assessing an individual's fuel and refuelling status usually requires its physical capture and recapture, but changes in state following a captured bird's release are in most cases unmeasured (but see e.g. [START_REF] Schmaljohann | Stopover optimization in a long-distance migrant: the role of fuel load and nocturnal take-off time in Alaskan northern wheatears (Oenanthe oenanthe)[END_REF]. Fuelling rates will vary largely as function of food abundance, predation danger, and seasonal time constraints of the individual (e.g., Ydenberg & Hope 2019). A potentially useful alternative behavioural metric that might index a bird's fuel status is the time the individual has spent at a stopover site, hereafter "Time Since Arrival" (TSA) [START_REF] Pledger | Stopover duration analysis with departure probability dependent on unknown time since arrival[END_REF][START_REF] Roques | When to depart from a stopover site? Time-since-arrival matters more than weather conditions[END_REF]. For migrants following a classic model of stopover behaviour of 'arrive-fatten-depart', TSA could provide a useful index of an individual's cumulative fuel acquisition and storage, and therefore be predictive of its likelihood of departing from a site.

With respect to weather, wind strength and direction are strong general predictors of migratory flight initiation [START_REF] Richardson | Timing and amount of bird migration in relation to weather: A review[END_REF], 1990[START_REF] Ma | Wind conditions affect stopover decisions and fuel stores of shorebirds migrating through the south Yellow Sea[END_REF][START_REF] Gill | Hemispheric-scale wind selection facilitates bar-tailed godwit circum-migration of the Pacific[END_REF]. Stronger tailwinds enable birds to fly further and/or arrive at subsequent sites with larger energy stores, while stronger headwinds have the opposite effect and thus are expected to delay departures from stopover sites [START_REF] Butler | Wind assistance: A requirement for migration of shorebirds?[END_REF][START_REF] Åkesson | Wind selectivity of migratory flight departures in birds[END_REF], Weber & Hedenström 2000[START_REF] Grönroos | To fly or not to fly depending on winds: shorebird migration in different seasonal wind regimes[END_REF]). In addition, departure decisions have evolved with respect to probable consequences further along the migration route and their potential carryover effects on fitness consequences later in the birds' annual cycle [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF][START_REF] Bednekoff | Dynamic models of mass-dependent predation, risksensitive foraging, and premigratory fattening in birds[END_REF][START_REF] Weber | Optimal avian migration: A dynamic model of fuel stores and site use[END_REF][START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF]. For many northward migrants, intraspecific competition for nesting sites and/or mates means that fitness declines with arrival dates; southward migrants are generally thought to be under less time pressure (e.g. Yohannes et al. 2009), but may still face deadlines in subsequent parts of their annual cycle, including the timing of post-migratory flight feather moult, when birds are more vulnerable to depredation [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF], Ydenberg & Hope 2019). These broader strategic considerations may be invoked to account for otherwise enigmatic observations of shorter or longer times spent at migration stopovers.

In this study, we compared and contrasted the stopover departure decisions of southward migrating Semipalmated Sandpipers (Calidris pusilla) prior to initiating flights to non-breeding sites in South America via either a transoceanic flight from a coastal stopover site or an overland flight from an inland site (Fig. 1, [START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF][START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Gratto-Trevor | Migratory connectivity of Semipalmated Sandpipers: Winter distribution and migration routes of breeding populations[END_REF][START_REF] Brown | Migratory connectivity of Semipalmated Sandpipers and implications for conservation[END_REF]. Since using a successful transoceanic route requires a lengthy flight, we expected a priori that migrants facing a transoceanic flight should (1) have stopover durations long enough to obtain large fuel stores and (2) be highly selective about leaving in wind conditions that would aid flight in the migratory direction. But what would inland birds do? Since birds leaving the inland site have shorter flight range stopover options, they might leave after shorter stopover durations with lower fuel stores and be somewhat less selective about the weather. [START_REF] Alerstam | Detours in bird migration[END_REF] proposed that "barrier effects" such as oceans should increase overall energetic cost and danger relative to routes with stopover availabilities. In this case, all else being equal, inland birds should adopt a lower energy and safer strategy, departing after shorter stopovers and possibly being less selective about departure weather.

Alternatively, despite the potential availability of additional stopover sites en route, making a lengthy flight might be the selected strategy from the perspective of the full annual cycle, contingent on the relative refuelling rates and safety of alternative sites. In the context of classical optimal migration theory [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF], we ask whether birds following the transcontinental route behave more like energy or time minimizers, compared with coastal birds. Energy minimizers avoid the energetic cost of carrying excess fuel by departing with lighter fuel loads after shorter stopover durations. Time minimizers achieve faster overall migration speeds by carrying heavier fuel loads, despite higher energy requirements overall. Our interpretation of the patterns seen also considers tradeoffs with predation danger at stopover sites, a third dimention that interacts with and can alter predictions from simplier time-versus-energy tradeoffs (e.g. Ydenberg & Hope 2019 and references therein).

Adults and juvenile sandpipers were captured, marked, and resighted at a coastal and an inland migratory stopover location. The age classes differ in that adults migrate about a month ahead of juveniles and will undergo a post migratory wing moult, while juveniles will not.

Previous analyses of these data using simpler recapture models showed that birds remained at both stopover sites for lengthy periods of time, declining at the end of the season [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Hope | Migration of two calidrid sandpiper species on the predator landscape: How stopover time and hence migration speed vary with geographical proximity to danger[END_REF]). Here, we estimated individual's Time Since Arrival using a capture-recapture analytical approach that incorporates probabilities of entry prior to first capture and marking [START_REF] Pledger | Stopover duration analysis with departure probability dependent on unknown time since arrival[END_REF][START_REF] Lyons | Population size and stopover duration estimation using mark-resight data and Bayesian analysis of a superpopulation model[END_REF][START_REF] Roques | When to depart from a stopover site? Time-since-arrival matters more than weather conditions[END_REF]. TSA was used as a potential index of cumulative fuel storage, under the classic assumption that stopover activity consists of arrival, fuel storage at a given rate, and departure [START_REF] Schmaljohann | How do energy stores and changes in these affect departure decisions by migratory birds? A critical view on stopover ecology studies and some future perspectives[END_REF][START_REF] Roques | When to depart from a stopover site? Time-since-arrival matters more than weather conditions[END_REF]. Daily probabilities of leaving were then modelled with respect to TSA and daily weather conditions. We interpret the stopover and departure patterns found in the context of the flight options available and apparently utilized at each site, and in the context of the migrants' annual cycle.

METHODS

Study system

The study system consisted of one coastal and one inland migratory stopover area for Semipalmated Sandpipers at comparable latitudes during southward migration (Fig. 1, [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]). The coastal site was Kent Island, New Brunswick, Canada (44°35'N, 60°27'W), in the mouth of the strongly tidal Bay of Fundy. The inland site was the area around Sibley Lake, North Dakota, United States of America (46°57'N, 99°43'W), which includes a mosaic of shallow seasonal saline lakes. Both sites are intermediate stopovers situated between Arctic breeding areas and South American wintering areas. Based on morphometrics, banding returns, and subsequent tracking studies, birds at Kent Island likely originated at breeding grounds in the central and eastern Canadian Arctic, may have previously staged along the shoreline of James Bay, and were preparing for a transoceanic flight to northeastern South America [START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF][START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Richardson | Southeastward shorebird migration over Nova Scotia and New Brunswick in autumn: a radar study[END_REF][START_REF] Harrington | Semiplamated Sandpiper migration in North America[END_REF][START_REF] Morrison | Migration systems of some New World shorebirds[END_REF][START_REF] Gratto-Trevor | Migratory connectivity of Semipalmated Sandpipers: Winter distribution and migration routes of breeding populations[END_REF][START_REF] Brown | Migratory connectivity of Semipalmated Sandpipers and implications for conservation[END_REF]). Those at Sibley Lake were likely arriving from breeding grounds in Alaska or the western Canadian Arctic, and departed heading towards the Caribbean and northcentral or northwestern South America [START_REF] Richardson | Radar observations of bird movements in eastcentral Alberta[END_REF][START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF][START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Gratto-Trevor | Migratory connectivity of Semipalmated Sandpipers: Winter distribution and migration routes of breeding populations[END_REF]. Adults pass through both areas in July and early August, and moult flight feathers shortly after arrival on non-breeding grounds, while juveniles arrive through August and into early September [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF]. At both sites, birds acquire substantial fuel for their next flight. A lean Semipalmated Sandpiper weighs ca. 20-22 g, but many individuals at both sites nearly double this mass prior to departing on the next leg of their journey [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Dunn | Length of stay and fat content of migrant Semipalmated Sandpipers in eastern Maine[END_REF].

Kent Island was monitored from 11 July-23 September 1977, and Sibley Lake from 13 July-27 September 1978. At each site, Semipalmated Sandpipers were captured almost daily using mist-nets, and/or walk-in traps at Sibley Lake, individually marked with conspicuous individually-coded wing-tags [START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF]) and released. Marked birds were subsequently recaptured or resighted during daily surveys of the local areas. Kent Island resightings were made exclusively on the intertidal mudflats surrounding the island; Sibley Lake resightings occurred along the shore of saline Sibley Lake and adjacent wetlands. Further details on capture, marking, and resighting effort are given in [START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF][START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF].

Birds initially landing at a site may not remain present to rest and refuel (i.e. actual 'stopover'; [START_REF] Warnock | Stopping vs. staging: The difference between a hop and a jump[END_REF]. Inclusion of 'transients' will usually bias low estimates of 'migratory' emigration rates [START_REF] Bächler | The effects of permanent local emigration and encounter technique on stopover duration estimates as revealed by telemetry and mark-recapture[END_REF][START_REF] Schaub | Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site[END_REF]. At Kent Island, 26% of birds marked were never reencountered, nor were 36% of those marked at Sibley Lake [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]. A initial analyses of this dataset in a methodological paper, showed that daily survivorship estimates distinguishing first versus later captures of individuals provided better model fits than ignoring a possible capture/transient effect [START_REF] Brownie | Estimation of time-specific survival rates from tag-resighting samples: A generalization of the Jolly-Seber Model[END_REF]. Local population size may also have affected transience probability [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]. Since our interest was on the effects of meteorology and length of stay on departure decisions, we analysed only capture histories of individuals that were subsequently reencountered. The numbers of capture histories included were: 928 at Kent Island, with 759 adults and 169 juveniles, resighted 4.5 times, on average; and 1073 at Sibley Lake, with 520 adults and 553 juveniles, resighted 5.3 times on average.

Weather variables

To describe how meteorological conditions relate to the departure decisions of sandpipers, we chose four weather covariates, measured daily at sunset, when most migratory departures occurred [START_REF] Richardson | Radar observations of bird movements in eastcentral Alberta[END_REF], Richardson 1977[START_REF] Lank | Why fly by night? Inferences from tidally-induced migratory departures of sandpipers[END_REF]). Based on earlier analyses of this data set and other information on the timing of migratory departures [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Lank | Why fly by night? Inferences from tidally-induced migratory departures of sandpipers[END_REF], our metric for wind was the 24-hour-trend in the strength of the tailwind-headwind component of wind direction (hereafter 'wind'), which was the wind metric most predictive of departure decision. Radar studies and direct observations show that at that season shorebird migration in both regions occurs in along a northwest towards southeast axis (Fig. 1, [START_REF] Richardson | Radar observations of bird movements in eastcentral Alberta[END_REF][START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF][START_REF] Richardson | Southeastward shorebird migration over Nova Scotia and New Brunswick in autumn: a radar study[END_REF][START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]), which we therefore defined as the expected migratory direction. The wind effect value at sunset was calculated as follows:

𝑊𝑖𝑛𝑑 = 𝑉 * cos (𝛼 -45)
where V is wind speed (in 𝑚/𝑠) and 𝛼 the direction where the wind comes from, in °.

Subracting 45° from the wind direction creates a vector with positive values for tailwinds blowing from the northwest towards the southeast, the migratory direction. The 24-hour-trend in wind was calculated as the vector's value each day minus that of the previous day. Thus positive values indicated that tailwinds were getting stronger, and negative values that they were becoming weaker. Additional meteorological variables modeled were: temperature (°C), percent cloud cover and relative humidity, measured at sunset. Collinearity between weather covariates can lead to erroneous conclusions about the effect of particular focal weather covariates. We tested for collinearity between the weather covariates and found some significantly correlated, but not with high correlation coefficients [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]. Nonetheless, to characterize the weather patterns with respect to synoptically covarying meteorological conditions, we ran a Principal Component Analysis on the 4 meteorological variables pooled across both sites, which clearly distinguished two axes explaining 80% of the variation (Fig. 2, see Table S3 for details). We modelled departure probability with respect to both individual variables and the first two PCs.

Statistical analyses of mark-recapture data

We used a Bayesian, state-space formulation of an open population capture-recapture model that incorporates entry probabilities to a sampling area (Pledger et al. 2009[START_REF] Lyons | Population size and stopover duration estimation using mark-resight data and Bayesian analysis of a superpopulation model[END_REF]. This formulation allows modelling both birds' arrival at and departure from the stopover site. The parameters of the model are:

𝜙 𝑡 Probability of departure from sampling area between the sampling occasions t and t+1 𝜂 𝑡 Probability of arriving at the stopover area at sampling occasion t given that the individual was not there before 𝑝 𝑡 Probability of physical capture at the sampling occasion t given the individual has arrived

but not yet departed 𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 Probability of visual recapture (encounter) at the sampling occasion t given the individual has been captured and marked (wing-tagged) but has not yet departed This formulation contains one submodel for the state process (states are "not yet arrived", "present in the stopover site", "departed"), and one submodel for the observations encoded in the individual capture histories. The observation process is conditional on the current state. For each individual capture history ℎ 𝑖 , there is a true state history accounted for by the vector 𝑧 𝑖 . This vector of binary state variables describes if an individual i is present,𝑧 𝑖,𝑡 = 1, or not, 𝑧 𝑖,𝑡 = 0, in the stopover area on day t. In our study, individuals can be physically captured or simply visually resighted, thus we separated the physical capture probability from the resighting probability, noted respectively as p and psight. Birds can also be captured and resighted during the same sampling occasion. To deal with this, we used a multi-state formulation of the observation process. Consequently, in an individual capture history, we distinguished four potential events [START_REF] Pradel | Multievent: An extension of multistate capture-recapture models to uncertain states[END_REF]) denoted as 0: not seen, 1: physically captured, 2: resighted, 3: physically captured and resighted during the same occasion. This resulted in the following observation matrix 𝜃 𝑖,𝑡 that applies to an individual present: (1)

The state vector 𝑧 𝑖 . also allows us to use a new formulation of the stopover duration described in [START_REF] Lyons | Population size and stopover duration estimation using mark-resight data and Bayesian analysis of a superpopulation model[END_REF]. We computed the mean stopover duration (in days) as follows:

𝑆𝑂𝐷 = Σ 𝑖 Σ 𝑡 𝑧 𝑖,𝑡 𝑛 (2)
where n is the number of individuals and 𝑧 𝑖,𝑡 the true state variable (which defines if an individual i was present or not at the stopover area on day t). Juvenile individuals arrive later in the season at the stopover area. Thus, the entry probability (𝜂 𝑡 )was modelled as age and time-dependent.

The probability of departure from the site between two days was written as a function of all previously defined weather covariates and TSA, with a slope to be estimated for each covariate.

When the slope for an effect had a 95% confidence interval that did not include 0, the effect was considered statistically significant [START_REF] Kéry | Bayesian population analysis using WinBUGS: A hierarchical perspective[END_REF].

Using the logit link, the probability of departure from the stopover area between 𝑡and 𝑡 + 1 was formulated as:

𝐿𝑜𝑔𝑖𝑡(𝜙 𝑡 ) = 𝑎 + 𝛽 𝑎𝑔𝑒 * 𝑇𝑆𝐴 𝑡 + 𝛽 * 𝐶𝑜𝑣 𝑡 (3)
Where a is the intercept, 𝛽 𝑎𝑔𝑒 the age specific TSA effect to estimate, 𝐶𝑜𝑣 𝑡 is the weather covariate and  the associated slope to estimate.

To incorporate potential effects of meteorological variables, we first ran one model for each site with the two PC axes as covariates as follows:

𝐿𝑜𝑔𝑖𝑡(𝜙 𝑡 ) = 𝑎 + 𝛽 𝑎𝑔𝑒 * 𝑇𝑆𝐴 𝑡 + 𝛽 1 * 𝑃𝐶1 𝑡 + 𝛽 2 * 𝑃𝐶2 𝑡 (4)
Then, to test effects of each weather covariate, we ran one model for each weather covariate for each site according to formula (3) to avoid collinearity problem [START_REF] Harrison | A brief introduction to mixed effects modelling and multi-model inference in ecology[END_REF]. This resulted into 8 different slope values for each weather covariate for each site (Table 2).

Analyses were performed with JAGS [START_REF] Hornik | JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling[END_REF]) using R version 3.6.1 (R Development Core Team 3.0.1. 2013). Models were run with 120,000 iterations with noninformative priors, and we checked chain mixing and the convergence [START_REF] Kéry | Bayesian population analysis using WinBUGS: A hierarchical perspective[END_REF].

The JAGS code is available in Appendix S2.

RESULTS

Stopover duration, time since arrival, and recapture probability

The mean stopover duration estimates were 9-10 days longer at Kent Island than at Sibley Lake, being 42.0 versus 33.7 days, respectively, but the CIs are wide for both estimates (Table 1 and Fig. 3). At Kent Island, the stopover durations of adults appear shorter than that of juveniles, being 40.0 versus 51.2 respectively, again with large CIs, but quite similar at Sibley Lake, averaging 32.8 versus 34.5 days (Table 1 and Fig. 3).

The probability of departure increased for all classes of individuals as their residency times increased. The coefficients of the TSA effects were significant and estimated with a high precision at both sites (see the 95% CI Table 2). The strongest TSA estimated effect was for adults at Kent Island, with a 0.13 estimated slope on the logit scale. Kent Island juveniles had estimates, of 0.09, close to values at Sibley Lake of 0.08 for adults and 0.09 for juveniles, with overlapping 95% CIs (Table 2). Controlling for weather covariates, departure probabilities remained below ca. 0.1 for over 30 days since initial arrival (Figures 4C and4D).

The physical recapture probability p was similar between the two sites (Kent Island: 0.03, Sibley Lake: 0.04), but the resighting probability psight was lower at Kent Island than at Sibley Lake (0.14 and 0.22, respectively, Table 1).

Weather Covariate Effects

The first two principle component dimensions accounted for 52% and 29%, respectively, of the total variances of the four meteorological variables (Table S3). PC1 captured covariation in temperature, humidity and cloud cover (Fig. 2A, Table S3), patterns of which clearly differed between sites (Fig. 2B, Table S1). Mean values of PC1 were -0.8  1.3 at Kent Island and 0.8  1.1 at Sibley Lake (Table S3). Kent Island had the cooler, more humid and cloudier conditions expected from a marine site, contrasting with warmer and drier inland conditions at Sibley Lake (Fig. 2B). PC2 largely captured the independent variation in 24-hour wind trend (Fig. 2A), which ranged similarly between favourable and unfavourable conditions at both sites (Fig. 2B).

Mean values of PC2 were -0.2  1.2 and 0.2  0.9 at Kent Island, and Sibley Lake, respectively.

In univariate models of each weather covariate at each site, the coefficient for 24-hour trend in headwind effect was positive at both sites (Table 2). Strengthening winds from the northwest, defined as tailwinds, increased the probability of leaving the stopover area between t and t+1. The magnitude of the effect was 0.77 at Kent Island, larger than 0.39 at Sibley Lake, with marginally overlapping 95% CIs. Each of the other weather covariates tested also had significant univariate relationships with the probability of departing from the stopover site. At both sites, lower humidity, was associated with higher departure probabilities. However, the relationships with temperature and cloud cover differed in direction between sites. At Kent Island, where the weather was generally cooler and cloudier (Fig 2B ), birds were more likely to leave under warmer and clearer skies. In contrast, at Sibley Lake, where warmer and clearer conditions prevailed, birds were more likely to leave in colder and cloudier local weather. These opposite trends produce some convergence of temperature and cloud cover conditions at intermediate values from both sites.

PC1, primarily capturing variation in temperature, humidity and cloud cover (Fig. 1A), had a significant negative effect on departure probability at Kent Island, but not at Sibley Lake (Table 2, Fig. 4A). Negative values on PC1 represent strengthening tailwinds, since the correlation between PC1 and wind is 0.-20 (Table S3). The effect of PC1 appears larger at Kent Island than at Sibley Lake; the CIs overlap, but that at Kent Island does not overlap zero. PC2, associated strongly with the independent variation in 24 hour wind (Fig. 2, Fig 4B, Table S3), had no significant effect at either site, thus most of the variation responsible for the univariate relationship with wind must have been represented through covariation in PC1. The environmental conditions correlating with departure are the ones that maximize the component β1*PC1 + β2*PC2, corresponding to the direction (β1, β2) on plane 1,2 of the PCA. The intensity of their effects are reflected by the length of the site-specific vectors shown in Fig. 2A for each site.

DISCUSSION

We estimated the stopover durations, effects of Time Since Arrival and meteorological conditions on the daily departure probabilities of Semipalmated Sandpipers from stopover sites during southeastward migratory journeys. Birds at Kent Island, New Brunswick were preparing for a lengthy transoceanic flight, while those at Sibley Lake, North Dakota, were preparing for overland flights of unknown lengths. We proposed that contrasting the stopover durations and departure behaviour of migrants from the sites would provide information about the migratory strategies of comparable sandpiper populations when the migratory routes did or did not provide access to intermediate downstream stopover sites. At both sites, birds departed with favourable winds, and had lengthy stopover durations for most of the season, suggesting preparation for lengthy migratory flights even when intermediate sites were available. However, birds at both sites stayed substantially longer than necessary to simply refuel and continue migratory journeys, suggesting that in the context of the birds' annual cycles, being at each of these locations at those seasons had high fitness value. There were, however, quantitative differences between migrants' behaviour at the two sites. Birds at Kent Island had somewhat greater selectivity with respect to wind conditions at departure, and adults at that site had longer stays than juveniles or birds at Sibley Island. Below, we interpret the patterns found as adjustment of migratory strategy related to the differences in the downstream stopover options of each migratory route, within the context of the birds' annual cycles.

Weather effects

At both sites, birds had higher probabilities of initiating migratory flight after tailwinds had been strengthening for the past 24 hours. Departure with stronger tailwinds is expected on first principles and from previous studies (Table 1, [START_REF] Richardson | Radar observations of bird movements in eastcentral Alberta[END_REF][START_REF] Richardson | Timing and amount of bird migration in relation to weather: A review[END_REF], 1979, 1990[START_REF] Alerstam | Bird migration[END_REF][START_REF] Weber | Optimal avian migration: A dynamic model of fuel stores and site use[END_REF][START_REF] Åkesson | Wind selectivity of migratory flight departures in birds[END_REF][START_REF] Loonstra | Adverse wind conditions during northward Sahara crossings increase the in-flight mortality of Black-tailed Godwits[END_REF]. Surface winds assisting southeastwardly flight were blowing when migratory departures were directly observed (Fig 1B). From a synoptic weather point of view, as expected, sandpipers from both sites thus do depart on days with tailwinds, reducing cost of flight per kilometre travelled [START_REF] Tsvey | Influence of body condition and weather on departures of first-year European Robins, Erithacus rubecula, from an autumn migratory stopover site[END_REF][START_REF] Arizaga | Effect of fuel load, date, rain and wind on departure decisions of a migratory passerine[END_REF][START_REF] Ma | Wind conditions affect stopover decisions and fuel stores of shorebirds migrating through the south Yellow Sea[END_REF][START_REF] Grönroos | To fly or not to fly depending on winds: shorebird migration in different seasonal wind regimes[END_REF][START_REF] Dossman | The effects of wind and fuel stores on stopover departure behavior across a migratory barrier[END_REF].

We predicted that birds facing transoceanic flight would show greater selectivity in departure conditions than those facing transcontinental flight, and indeed, the effect size of change in headwind component was stronger at Kent Island than at Sibley Lake. Kent Island birds also showed stronger relationships with the integrated measures of meteorological covariation than the birds at Sibley Lake. Although the background weather regimes differed with respect to temperature, cloud cover and humidity, they were similarly variable in terms of the general distributions of favourable winds (Fig. 2). In the current study, favourable weather for migration occurred at fairly regular 4-5 day intervals at both sites throughout the migration season, with regular passage of cyclonic and anticyclonic weather systems, and the patterns in the specific years studied were typical of longer term weather regimes [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]). Thus, systematic differences in meteorological migration opportunities do not account for differences in selectivity between sites. Greater selectivity for wind assistance can trade-off against speed of migration; [START_REF] Mccabe | The influence of wind selectivity on migratory behavioral strategies[END_REF], argued that in general, time minimizers might be less selective because of fitness decreases associated with waiting for favourable weather conditions. In our cases, however the lengthy stopover durations shown by both of our migratory populations indicate that neither were time minimizers during much of the season (see below), and both populations selected tailwinds for departure.

Despite lower values of humidity in general at Sibley Lake (Fig. 2), the relationship between relative humidity and departure probability was negative at both sites. This is sensible in a synoptic sense, since northwesterly winds at both sites would likely bring in drier air. This effect may reflect a direct effect of rain, but also the fact that more humid air increases the cost of flight and decreases visibility (Åkesson et al. 2001). Similar effects have been found in other situations [START_REF] Åkesson | Reed warbler orientation: initiation of nocturnal migratory flights in relation to visibility of celestial cues at dusk[END_REF][START_REF] Deppe | Fat, weather, and date affect migratory songbirds' departure decisions, routes, and time it takes to cross the Gulf of Mexico[END_REF][START_REF] Roques | When to depart from a stopover site? Time-since-arrival matters more than weather conditions[END_REF], such as passerines selecting nights with lower humidity to cross the Gulf of Mexico [START_REF] Deppe | Fat, weather, and date affect migratory songbirds' departure decisions, routes, and time it takes to cross the Gulf of Mexico[END_REF].

The direction of temperature and cloud cover effects were opposite at the two sites.

Sandpipers were more likely to leave Kent Island with higher than average temperatures and less cloud cover for that site, while those at Sibley Lake left with lower than average temperatures and greater cloud cover for the site. Since Kent was generally cooler and cloudier than Sibley Lake (Fig. 2), this pattern produces a convergence of departure conditions between sites under intermediate conditions of both variables. Greater cloud cover decreases the visibility of the sky, and since migratory birds use the stars for the orientation (Wiltschko & Wiltschko 1988), including Semipalmated Sandpipers [START_REF] Lank | Celestial Orientation by Migrating Sandpipers[END_REF], dense cloud cover could present initial navigational difficulties. Low cloud cover in particular may have a strong negative impact on the probability of departing from a stopover area, while high altitude clouds will have little effect [START_REF] Martin | The Visual Problems of Nocturnal Migration[END_REF][START_REF] Koistinen | Bird migration patterns on weather radars[END_REF].

PC1, which was strongly and approximately evenly weighted by humidity, cloud cover, and temperature, captured most of the covariation in departure probability from both stopover sites. Despite being heavily weighted by tailwind trend, PC2 was not strongly related to departure probability, although it may have been more so at Kent Island than at Sibley Lake.

This means that most of the univariate relationship between departure probability and wind trend had been captured by PC1 through covariation between wind and the other variables (Table S2).

Modelling Considerations

The stopover durations estimated in this study incorporate estimates of entry probabilities to a sampling area prior to first capture. They are thus longer than the minimum lengths of stay (marking to last sighting) presented by [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF], the conditional residence times estimated from Lank's data by [START_REF] Hope | Migration of two calidrid sandpiper species on the predator landscape: How stopover time and hence migration speed vary with geographical proximity to danger[END_REF], and the minimum lengths of stay found in a separate study on the coast of Maine [START_REF] Dunn | Length of stay and fat content of migrant Semipalmated Sandpipers in eastern Maine[END_REF]. Including time prior to capture should make the values estimated in the current study more realistic. Lank (1983, unpublished analyses) tested for relationships between daily emigration rates and prevailing daily weather conditions, using emigration rates estimated using a simpler capture-recapture model [START_REF] Brownie | Estimation of time-specific survival rates from tag-resighting samples: A generalization of the Jolly-Seber Model[END_REF]. The emigration rate-meteorology relationships in that study were weaker than those shown here (Table 2), suggesting that the approach taken in the current study provided more useful estimates. [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF] speculated that permanent local dispersal may have partially obscured relationships between the emigration rates and actual migratory departure probability, which also applies to our current analysis [START_REF] Bächler | The effects of permanent local emigration and encounter technique on stopover duration estimates as revealed by telemetry and mark-recapture[END_REF][START_REF] Schmaljohann | How do energy stores and changes in these affect departure decisions by migratory birds? A critical view on stopover ecology studies and some future perspectives[END_REF]. Our study provided some perspective on the local dispersal issue by distinguishing between physical and visual recapture events in the modelling process. The sites had similar physical recapture rates, but visual reencounter rate was lower at Kent Island than at Sibley Lake (Table 2). Regular surveys at Kent Island were restricted to birds visible from the island itself; small numbers of ad hoc sightings of wing tagged birds by local bird watchers at nearby sites were not included in the capture history. In contrast, regular surveys were made at additional waterbodies near Sibley Lake when these sites were used by birds as a function of changing rainfall conditions. The higher visual reencounter rate at Sibley Lake likely reflects the observers' greater ability to track local movements of birds at that stopover site. Separate parameterization of physical and visual reencounters thus added precision and highlighted sampling patterns between sites and data sources. We conclude from this that the potential effects of local dispersal would have weakened relationships with meteorological variables more at Kent Island than at Sibley Lake.

If so, our conclusion of greater selectivity in departure weather at Kent Island is conservative.

Lengthy Stopover Durations

As argued in the introduction, preparing for a non-stop transoceanic flight rather than an overland flight should favour the acquisition of larger fuel stores, since the latter provides opportunities for shorter flights from the stopover sites. Consistent with our prediction, estimated stopover durations were ca. 10-15 days longer prior to transoceanic relative to transcontinental flights for adults and juveniles, respectively (Table 1, Fig. 3). Further, the samples of birds captured and tagged at Kent Island averaged 3.4 g. heavier than those caught at Sibley Lake (33.0 versus 29.6 g, [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]).

We motivated this study in part by suggesting that stopover duration might be a useful index of cumulative refuelling that could be estimated without recapturing marked individuals, assuming a classical model of stopover behaviour as 'arrive-fatten-depart'. As expected under this model, the effects of estimated Time Since Arrival were positive and predictive of departure probabilities. Rapid refuelling often has been found at stopover sites, and the TSA approach used here should work best in analyses of such situations, namely for time-minimizing migrants whose stopover behaviour fits [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF].

Despite the utility of TSA as a predictor of departures in our study, the stopover durations of most sandpipers at both sites are substantially longer than those expected if the stopover behaviour of these migrants was a good fit with the classical model. The model coefficients for TSA were small and quite similar at both sites (Table 2). Also, the departure probability curves as a function of TSA are low and nearly flat for the first 30 days (Fig. 4C and 4D). [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF] provided information on the arrival mass, fattening rate, and departure masses at each site, inferred by comparing the masses of the daily samples of sandpipers caught throughout the season, and on successive days when weather was or was not favourable for southeastward migration. Lank estimated that departure masses from Sibley Lake were only about 2 g less than those from Kent Island (e.g. 16 vs. 18 g on birds with lean masses of 20-22 g). Thus, despite the availability of stopover opportunities en route, the transcontinental migrants were also preparing for lengthy flights.

At Kent Island, [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF] estimated that adults arrived with an average of 5-6 g of fuel. Some, identified by colour-dyed breasts, had previously staged further north along the east coast of James Bay. Juveniles arrived at Kent Island lighter than adults. At Sibley Lake, many birds of both ages arrived with little or no fuel stores, potentially having flown directly from western Nearctic breeding grounds. Lank estimated fattening rates of up to 2.5 g/day at Kent Island and 1.5 g/day at Sibley Lake. The rate for Kent Island is high relative to those estimated for shorebirds at other sites [START_REF] Alerstam | Optimal bird migration: The relative importance of time, energy, and safety[END_REF][START_REF] Anderson | Migration distance and body condition influence shorebird migration strategies and stopover decisions during southbound migration[END_REF]. But even at a lower rate, birds arriving completely lean at both sites could have added the 20-24 g of fuel needed to support maximal transoceanic or trans-continental flights in ca. 15 days, far fewer than their estimated mean stopover durations of 40.0 and 51.2 d for adults and juveniles at Kent Island, respectively, and 33.7 and 32.8 d at Sibley Lake (Table 1). If birds fit the classic model, we would expect clear inverse relationships between mass at capture and subsequent length of stay, as has indeed been found in many other situations (e.g. [START_REF] Schaub | Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site[END_REF]. No such relationship occurred at either Kent Island or Sibley Lake [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF]), or at Dunn et al.'s (1988) coastal site. Since favourable departure weather occurs at regular 4-5 day intervals [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF], see above), waiting for favourable departure conditions (e.g. [START_REF] Mccabe | The influence of wind selectivity on migratory behavioral strategies[END_REF] would not add more than a few days to stopover durations. None of the sandpipers captured at these sites in our study was moulting, which can explain lengthy stays at stopover sites [START_REF] Jehl | Aspects of the molt migration[END_REF]). We conclude that for most of the season the sandpipers at both sites were not in a hurry to undertake their next, lengthy, migratory flight. At James Bay, a major stopover site for central and eastern migrants further north, the relationship between length of stay and fuel loads at capture for Semipalmated Sandpipers and other shorebirds was actually positive early in the season, but did become negative towards the end [START_REF] Anderson | Migration distance and body condition influence shorebird migration strategies and stopover decisions during southbound migration[END_REF]. This finding also points towards a relatively leisurely southward migration schedule.

Life History Perspectives

Why were stopover durations so long at both sites, despite the apparent availability of food resources and favourable weather for departures at regular intervals? Answering this question requires taking a life history perspective, including migrants' age and prospects at subsequent stages of their annual cycles [START_REF] Bednekoff | Dynamic models of mass-dependent predation, risksensitive foraging, and premigratory fattening in birds[END_REF][START_REF] Weber | Optimal avian migration: A dynamic model of fuel stores and site use[END_REF][START_REF] Houston | Models of optimal avian migration: state, time and predation[END_REF][START_REF] Weber | Should I stay or should I go? Testing optimality models of stopover decisions in migrating birds[END_REF].

Adults had shorter stopover durations than juveniles (Fig. 3). If we assume that at both age classes were preparing for similar migratory flights, the shorter duration for adults could indicate that their refuelling rate was higher, and/or reflect their arrival at Kent Island with higher fat stores, which did occur. [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF] concluded that adults and juveniles present concurrently at Kent Island had similar daily mass increases. In addition, at Kent Island, adults may have been more likely than juveniles to be preparing for a direct transoceanic flight. In both [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF] and [START_REF] Dunn | Length of stay and fat content of migrant Semipalmated Sandpipers in eastern Maine[END_REF]'s studies, fewer juveniles than would be expected demographically utilized the coastal stopover sites. There is evidence that juvenile Semipalmated Sandpipers generally make shorter transoceanic flights by leaving from sites further south, possibly after first moving southwesterly down the Atlantic coast [START_REF] Harrington | Semiplamated Sandpiper migration in North America[END_REF][START_REF] Anderson | Migration distance and body condition influence shorebird migration strategies and stopover decisions during southbound migration[END_REF]: their supplementary Fig. 3). Thus, adults had shorter lengths of stay despite being more likely to be preparing for a longer journey. In conclusion, as argued above, since none of these birds were fattening as rapidly as possible, stopover duration and fuel levels were to a considerable extent decoupled for these birds. Thus, we will look for alternative explanations for lengthy stopovers. [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF] argued that the evolution of migratory routes involving lengthy migratory flights depends not only on the existence of staging sites with sufficient food to fuel flights, but also, critically, low predation danger at such sites, since birds become quite vulnerable when carrying stores needed to fuel such flights. Schedules of migrating falcons may thus influence both the timing and routes of migration, including Semipalmated Sandpipers in particular [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF], Ydenberg et al. 2007). Models of migration's role within annual cycles stress the importance of date in the season, usually with fitness penalties for late arrivals (e.g. [START_REF] Weber | Optimal avian migration: A dynamic model of fuel stores and site use[END_REF]. For southward migrating Semipalmated Sandpipers, [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF] argued that adults face stronger seasonal deadlines than juveniles to arrive at their non-breeding grounds by a given date, in order to mitigate the increased vulnerability they experience during post-migratory wing moult to later-migrating avian predators. Since juveniles do not replace their feathers immediately on arrival, adults should put a higher priority on earlier arrivals on moulting sites further south, and thus have shorter stopover durations particularly later in the season. [START_REF] Hope | Migration of two calidrid sandpiper species on the predator landscape: How stopover time and hence migration speed vary with geographical proximity to danger[END_REF] showed that conditional residency times calculated from this dataset were truncated at the end of the season, coinciding with the approach of migrant Peregrine Falcons (Falco peregrinus) towards the stopover sites.

When the observations reported here were made in the late 1970s, falcon populations were in fact relatively low, due to residual effects from the extensive use of DDT, and during the migratory seasons both sites were quite safe with respect to avian predators (Ydenberg et al. 2017). No attacks from falcons were observed at Kent Island. At Sibley Lake, only a few observations of Prairie Falcons (Falco mexicanus) and resident Short-eared Owls (Asio flammeus) attacking sandpipers were made [START_REF] Lank | Dispersal and predation rates of wing-tagged Semipalmated Sandpipers Calidris pusilla and an evaluation of the technique[END_REF]. Although proximate disturbance and danger was lacking, from an evolutionary sense, the predictable seasonal pattern of increasing danger may indeed have influenced birds' departure decisions towards the end of the season [START_REF] Lank | Effects of predation danger on migration strategies of sandpipers[END_REF][START_REF] Hope | Migration of two calidrid sandpiper species on the predator landscape: How stopover time and hence migration speed vary with geographical proximity to danger[END_REF], Ydenberg & Hope 2019), but for much of the time there was little direct threat.

We infer that during most of the season, both these sites provided quite favourable habitat for Semipalmated Sandpipers, making these ideal places to stage on migration [START_REF] Pomeroy | Feeding-danger trade-offs underlie stopover site selection by migrants[END_REF], or indeed to allocate time to, broadly considered in the context of the full annual cycle.

Conclusions

Migratory populations of the same species of sandpipers traversing different migration routes had different relationships between departure probabilities with respect to time present at the site and meteorological variables. The open population capture-recapture model we used incorporates entry probabilities to a sampling area and provided novel estimates of stopover durations and departure probabilities. As expected, strong tailwinds favoured migratory departures, somewhat more strongly along a route where birds were initiating a non-stop transoceanic flight compared with a transcontinental flight that allowed for stopovers at shorter distances. However, stopover durations were lengthy at both sites studied, suggesting that birds were not simply arriving, refuelling, and leaving as quickly as possible. Time since arrival was nonetheless predictive of departure, despite likely violations in this case of seasonal homogeneity in departure probability, an underlying assumption of the modelling approach.

We recommend the further application of this approach, particularly for time minimizing migrants, combined with counts if available [START_REF] Lyons | Population size and stopover duration estimation using mark-resight data and Bayesian analysis of a superpopulation model[END_REF][START_REF] Lok | Accounting for heterogeneity when estimating stopover duration, timing and population size of red knots along the Luannan Coast of Bohai Bay[END_REF]) towards the analysis of migratory stopover and departure probabilities. Sibley Lake and Kent Island. Flocks leaving each study site were followed optically until they disappeared from view (details in [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF][START_REF] Lank | Why fly by night? Inferences from tidally-induced migratory departures of sandpipers[END_REF]. Vanishing bearings were assigned to one of 16 compass points at Kent Island, or to the nearest compass degree at Sibley Lake. Mean vector bearings (mvb) and statistical significance (p) were calculated using [START_REF] Baschelet | Circular Statistics in Biology[END_REF].

The black triangle on the outside of each circle shows the mean direction towards which surface winds were blowing at the time of the departures. Both figures adapted from [START_REF] Lank | Migratory behavior of Semipalmated Sandpipers at Inland and Coastal Staging Areas[END_REF], which provides references to the migration site accounts used in A.

[ 1 -

 1 𝑝 𝑡 -𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 + (𝑝 𝑡 * 𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 ) 𝑝 𝑡 * (1 -𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 ) 𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 * (1 -𝑝 𝑡 ) 𝑝 𝑡 * 𝑝𝑠𝑖𝑔ℎ𝑡 𝑡 ] For an individual 𝑖 that has not yet entered the stopover area or has left it (𝑧 𝑖,𝑡 = 0), ℎ 𝑖,𝑡 = 0with probability equal to 1. This formulation allows us to estimate the time since arrival (TSA) for each individual. This covariate is a non-observable variable that can be computed with the sum of the true states 𝑧 𝑖,𝑡 up to time t, and represents the time of presence of the individual 𝑖 at time 𝑡 in the stopover area: 𝑇𝑆𝐴 𝑖,𝑡 = ∑ 𝑧 𝑖,𝑠 𝑡-1 𝑠=1

Figure 1 :

 1 Figure 1: A. Breeding (diagonal hatching) and nonbreeding grounds (crosshatching) of

Figure 2 .

 2 Figure 2. Principal component analysis of the four weather variables. A) Length and direction

Table 1 .

 1 Weber, T.P. & Hedenström, A. 2000. Optimal stopover decisions under wind influence: The effects of correlated winds. J. Theor. Biol. 205: 95-104. Mean and credible intervals (CI) of the resighting probability (psight), the capture probability (p) and stopover duration by age of southward migrating Semipalmated Sandpipers estimated from the models following equation 4. Estimates from Kent Island derived from 4178 encounters in capture histories from 759 adults and 169 juveniles; those from Sibley Lake derived from 5613 encounters in capture histories from 520 adults and 553 juveniles.

	Wiltschko, W. & Wiltschko, R. 1988. Magnetic versus celestial orientation in migrating
	birds.
	Ydenberg, R.C., Butler, R.W. & Lank, D.B. 2007. Effects of predator landscapes on the
	evolutionary ecology of routing, timing and molt by long-distance migrants. J. Avian
	Biol. 38: 523-529.
	Ydenberg, R.C, Barrett, J., Lank, D.B., •Xu, C. & Faber M. 2017. The redistribution of
	non-breeding dunlins in response to the post-DDT recovery of falcons. Oecologia 183:
	1101-1110. DOI 10.1007/s00442-017-3835-2

Ydenberg, R.C. & Hope, D.D. 2019. Danger management and the seasonal adjustment of migratory speed by sandpipers. J. Avian Biol. 50: jav.02202. Yohannes, E., Biebach, H., Nikolaus, G. & Pearson, D.J. 2009. Migration speeds among eleven species of long-distance migrating passerines across Europe, the desert and eastern Africa. J. Avian Biol. 40: 126-134. doi:10.1111/j.1600-048X.2008.04403.x Tables

Table 2 .

 2 Mean, standard deviation (Sd) and credible intervals (CI) of the estimated effects of covariates on departure probability. The first part of the table shows the results from the equation 4 with TSA (β 1age ) and PCA axes covariates. The second part of the table shows the results from the equation 3, which included TSA (β 1age ) and coefficients for weather covariates effects (β 2 , β 3 , β 4 , β 5 ). Estimated values of intercept and TSA effects for each univariate models are not shown in this table as they are mostly similar to the ones of equation 4.

			Kent Island		Sibley Lake
		Mean	Sd	CI	Mean	Sd	CI
	Intercept	-8.85	0.55	-9.17, -7.94	-9.44	0.68	-10.87, -8.20
	(𝛽 1𝑎𝑑𝑢𝑙𝑡 ) TSA	0.13	0.01	0.11, 0.14	0.08	0.01	0.07, 0.10
	(𝛽 1𝑗𝑢𝑣𝑒𝑛𝑖𝑙𝑒 ) TSA	0.09	0.01	0.06, 0.10	0.09	0.01	0.07, 0.10
	PCA Axis 1	-0.48	0.15	-0.80, -0.20	-0.08	0.12	-0.30, 0.15
	PCA Axis 2	0.22	0.19	-0.16, 0.58	0.06	0.11	-0.18, 0.26
	(𝛽 2 ) Wind	0.77	0.13	0.52, 1.01	0.39	0.08	0.23, 0.54
	(𝛽 3 )Temperature	0.84	0.16	0.52, 1.15	-0.19	0.05	-0.30, -0.09
	(𝛽 4 ) Humidity	-0.58	0.18	-0.95, -0.23	-1.06	0.17	-1.43, -0.73
	(𝛽 5 ) Cloudcover	-0.33	0.16	-0.66, -0.02	0.42	0.11	0.20, 0.65

  Table 2). B) Scatterplot of daily local weather observations with respect to PC1 and PC2 scores (light blue: Kent Island, dark blue: Sibley Lake). Figure 3. Estimated stopover duration by age classes at Kent Island and Sibley Lake. Adults: red, Juveniles: blue. Box plots show: median (thick line), first and third quartiles boundaries, lines extend to 1.5 times the box boundaries, and black dots show outliers.

			Age
			Adult
	Estimated stopover duration in days	20 40 60	Juvenile
		Kent Island	Sibley Lake
		Stopover site

Data collection by DBL was supported by NSF grants BNS-7518905 and 7813016 to Stephen T Emlen and William T Keeton. DBL thanks Stephen Emlen for his input and patience with respect to publication of this work.

Emmanuelle Cam was supported by the French Laboratory of Excellence project "TULIP" (ANR-10-LABX-41; ANR-11-IDEX-0002-02). We thank three anonymous reviewers, Associate Editor and Editor for their helpful comments.

DATA AVAILABILITY STATEMENT

All data used here are available on the personal correspondence author github account.

.

Table S3. Correlations between weather covariates and dimensions. Eigenvalues and % of variance of dimensions are also displayed.