Received: 4 March 2019  |  Accepted: 2 September 2019 DOI: 10.1111/1365-2656.13118 R E S E A R C H A R T I C L E Low fitness at low latitudes: Wintering in the tropics increases migratory delays and mortality rates in an Arctic breeding shorebird Jeroen Reneerkens1  | Tom S. L. Versluijs1 | Theunis Piersma1,2  | José A. Alves3,4  | Mark Boorman5 | Colin Corse6 | Olivier Gilg7,8  | Gunnar Thor Hallgrimsson9 | Johannes Lang8,10  | Bob Loos11 | Yaa Ntiamoa‐Baidu12,13  | Alfred A. Nuoh12 | Peter M. Potts14 | Job ten Horn2 | Tamar Lok2 1Rudi Drent Chair in Global Flyway Ecology, Conservation Ecology Group, Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands; 2Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, Utrecht University, Texel, The Netherlands; 3DBIO & CESAM – Centre for Environmental and Marine Studies, University of Aveiro, Aveiro, Portugal; 4South Iceland Research Centre, University of Iceland, Laugarvatn, Iceland; 5Global Flyway Network, Swakopmund, Namibia; 6Orkney Ringing Group, Kirkwall, UK; 7UMR 6249 Chrono‐Environnement, Université de Bourgogne Franche‐Comté, Besançon, France; 8Groupe de Recherche en Ecologie Arctique, Francheville, France; 9Institute of Biology, University of Iceland, Reykjavik, Iceland; 10Clinic for Birds, Reptiles, Amphibians and Fish, Working Group for Wildlife Biology, Justus Liebig University Giessen, Giessen, Germany; 11Global Flyway Network, Texel, The Netherlands; 12Centre for African Wetlands, University of Ghana, Legon, Accra, Ghana; 13Department of Animal Biology and Conservation Science, University of Ghana, Legon, Accra, Ghana and 14Farlington Ringing Group, Warsash, Southampton, UK Correspondence Jeroen Reneerkens Abstract Email: jeroen.reneerkens@nioz.nl 1. Evolutionary theories of seasonal migration generally assume that the costs of Funding information longer migrations are balanced by benefits at the non‐breeding destinations. European Community’s Seventh 2. We tested, and rejected, the null hypothesis of equal survival and timing of spring Framework Programme, Grant/Award Number: INTERACT 262693; Netherlands migration for High Arctic breeding sanderling Calidris alba using six and eight win- Organisation for Scientific research (NWO) ter destinations between 55°N and 25°S, respectively. ‐ Netherlands Polar Programme, Grant/ Award Number: 851.40.072 and 866.15.207; 3. Annual apparent survival was considerably lower for adult birds wintering in tropi- Waddenfonds, Grant/Award Number: cal West Africa (Mauritania: 0.74 and Ghana: 0.75) than in three European sites WF209925; Institut Polaire Français Paul Emile Victor, Grant/Award Number: 1036 (0.84, 0.84 and 0.87) and in subtropical Namibia (0.85). Moreover, compared with Interactions; Fundacão paraa Ciêncae a adults, second calendar‐year sanderlings in the tropics, but not in Europe, often Tecnologia, Grant/Award Number: SFRH/ BPD/91527/2012; Netherlands Organisation refrained from migrating north during the first possible breeding season. During for Scientific research (NWO), Grant/Award northward migration, tropical‐wintering sanderlings occurred at their final stag- Number: 016.Veni.192.245 ing site in Iceland 5–15 days later than birds wintering further north or south. Handling Editor: Lise Aubry Namibia‐wintering sanderlings tracked with solar geolocators only staged in West Africa during southward migration. 4. The low annual survival, the later age of first northward migration and the later passage through Iceland during northward migration of tropical‐wintering sander- lings, in addition to the skipping of this area during northward but not southward Jeroen Reneerkens and Tom S. L. Versluijs contributed equally. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. © 2019 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. J Anim Ecol. 2019;00:1–13. wileyonlinelibrary.com/journal/jane  |  1 2  |   Jo urnal of Animal Ecology RENEERKENS Et al. migration by Namibia‐wintering sanderlings, all suggest they face issues during the late non‐breeding season in West Africa. 5. Migrating sanderlings defy long distances but may end up in winter areas with poor fitness prospects. We suggest that ecological conditions in tropical West Africa make the fuelling prior to northward departure problematic. K E Y W O R D S demography, fitness, migration, nutrient storage strategies, site fidelity, solar geolocation, survival, timing 1  | INTRODUC TION (Alves et al., 2013), or decrease, with migration distance. The former might occur when the benefits of high habitat quality in the farthest Seasonal movements between areas of reproduction and non‐ destinations exceed the costs of longer migration distances. The breeding are suggested to maximize the fitness of migrating animals latter could occur when subordinate individuals (juveniles, small in- through benefits from favourable ecological conditions encountered dividuals, one of the sexes) are forced by competition to settle in year‐round (Lack, 1968; Newton, 2008). The overall balance be- presumed suboptimal sites furthest away from the breeding grounds tween costs and benefits of migration will depend on the distance, (Gauthreaux, 1982). route and timing of such movements and on the ecological conditions The trade‐offs shaping migration variation are difficult to study both en route and at the ‘winter’ destinations (hereafter ‘variation experimentally; instead, we have to rely on observational studies in migration’) (Alerstam & Lindström, 1990). Variation in migration‐ (Flack et al., 2016; Lok, Overdijk, Tinbergen, & Piersma, 2011). So far, related traits that underlie fitness is the basis of natural selection such studies have been limited to species whose entire geographical (Pulido, 2007), but the relationships between fitness correlates and range is north of the equator, where daily energy expenditures de- intraspecific variation in migration routines of long‐distance mi- crease with increasing migration distances (Castro et al., 1992) and/ grants, for obvious logistic reasons, have remained understudied. or studies that addressed a single demographic parameter only (Ely Migratory flights entail substantial energy expenditure (Drent & Meixell, 2016). & Piersma, 1990; Flack et al., 2016), which will increase with the Sanderlings Calidris alba offer a remarkably tractable system distance covered (Weber & Houston, 1997). The season of migra- to examine whether and how survival and/or (indicators of) re- tion has been shown to be associated with increased mortality in production are correlated with migration distance. The species some species (Lok, Overdijk, & Piersma, 2015; Rushing et al., 2017), breeds in the High Arctic and migrates annually to temperate and but not in others (Leyrer et al., 2013; Rakhimberdiev, Hout, Brugge, tropical coasts along a range of latitudes spanning 100° (Conklin Spaans, & Piersma, 2015). A survival cost of migration would selec- et al., 2016; Loonstra, Piersma, & Reneerkens, 2016; Myers et al., tively favour shorter migration distances, unless counterbalanced 1985). During the non‐breeding season, sanderlings from a single by advantages in survival in the rest of the year, age at maturity breeding site in northeast Greenland have been shown by indi- or reproduction. Indeed, such costs have been suggested to be vidual colour‐ringing to distribute themselves along the length of traded‐off against reduced metabolic expenditure (Castro, Myers, & the entire East Atlantic Flyway (Figure 1), with annual migration Ricklefs, 1992; Kersten, Bruinzeel, Wiersma, & Piersma, 1998), re- distances varying sixfold between 3,700 and 22,200 km. Within duced competition (Lundberg & Alerstam, 1986; Myers, Maron, & their first 3–6 months of life, sanderlings, like other migratory Sallaberry, 1985) and/or higher densities of harvestable prey (Grond, shorebirds, settle at a shoreline winter area to which they return Ntiamoa‐Baidu, Piersma, & Reneerkens, 2015; Mathot, Smith, & throughout their life (Lourenço et al., 2016; Townshend, 1985). Elner, 2007; Piersma, de Goeij, & Tulp, 1993) at the non‐breeding Their large, near‐continuous variation in migration distances of- destinations. Different balances between costs and benefits across fers the possibility to explore the factors underlying the mainte- the non‐breeding range may maintain migration variation within nance of intra‐population variation in avian migration (e.g., Castro breeding populations (Gilroy, 2017). Such a balance can be the re- et al., 1992). sult of increased survival but lower reproductive success (fewer We estimated adult apparent survival, age at first northward breeding attempts or fewer offspring per attempt) with increasing migration and the timing of northward passage through a final migration distance (Fernández, O’Hara, & Lank, 2004) or, if there is staging area for sanderlings from non‐breeding sites across a huge no such trade‐off, of survival (Conklin, Senner, Battley, & Piersma, non‐breeding range between Scotland (60°N) and Namibia (25°S). 2017) and reproduction (Kentie et al., 2017) not being correlated Throughout the rest of the paper, we refer to these measures as with migration distance. Alternatively, costs and benefits of migra- fitness correlates, as they are likely to affect fitness (i.e., lifetime tion are not in balance and both survival and reproduction increase reproductive success): (a) adult survival determines life span and RENEERKENS Et al. Journal of Animal Ecolo gy    |  3 consequently the number of breeding seasons available within a life- 2.2 | Assignment of winter destinations and time (Ricklefs, 2000), (b) the age (first year or older) at which birds migration period embark on their first northward migration likely affects whether the first opportunity for reproduction is used (Stearns, 1992) and has Observations from 1 October–31 March of sanderlings colour‐ multiplicative effects on fitness because young produced by year- ringed in Zackenberg were used to assess the extent of intra‐pop- ling parents can also enter the population earlier and start produc- ulation variation in migration (Figure 1a). We divided the winter ing young themselves (Oli & Zinner, 2001), and (c) timing of staging distribution of Greenlandic sanderlings into sectors of 5 degrees at a final spring passage site is expected to affect timing of arrival latitude (Figure 1), which we considered separate winter areas at the breeding grounds, with earlier arrival often being correlated (hereafter ‘winter area’) and which we named after the country with enhanced reproductive success (Drent, Both, Green, Madsen, or region within this winter area with most observations of col- & Piersma, 2003). In the High Arctic where the window of oppor- our‐ringed individuals. Within most, but not all, winter areas, tunities for reproduction is short (Reneerkens et al., 2016), early ar- we caught ringed and/or observed colour‐ringed sanderlings at rival matters as it will affect the mating and re‐nesting opportunities a single main study site. We had sufficient data to compare fit- (Morrison, Alves, Gunnarsson, Þórisson, & Gill, 2019) in facultative ness correlates of sanderlings from eight winter areas between polygamous sanderlings (Reneerkens, Veelen, Velde, Luttikhuizen, & 25°S and 60°N (named after the country or region with most re- Piersma, 2014). As a null hypothesis, we expected no variation in the sightings within these 5 degree latitude sectors: Namibia, Ghana, above described fitness correlates with migration distance. To help Mauritania, Portugal, North Iberia, France, England and Scotland; the interpretation of the patterns, we explore whether individuals Figure 1) with distances of 1,500 to 13,000 km between breed- of different sizes, ages and sexes are differently distributed along ing and winter areas (Figure S1). Individual sanderlings have been the flyway. shown to be highly site faithful to their winter area, both within and between years (Lourenço et al., 2016). Therefore, we assumed 2  | MATERIAL S AND METHODS that for their entire life birds used the winter area in which they were observed at least once between 1 October and 31 March. 2.1 | Individual marking However, 99 of 3,148 individuals were observed in two different winter areas. Sixty‐four of these individuals were observed in ad- Sanderlings were captured at three High Arctic breeding sites in jacent winter areas (i.e., in both England and France, or in different northeast Greenland (Zackenberg, Karupelv Valley and Hochstetter 5 degree latitude sectors within Ghana) and assigned to the winter Forland), at staging areas during migration (SW Iceland, N Scotland area in which they were most often observed. The remaining 35 in- and the Dutch Wadden Sea) and in winter areas (Scotland, England, dividuals were removed from all analyses as it remained uncertain France, north Iberia, Portugal, Mauritania, Ghana and Namibia; whether this concerned observational errors or true movements Table 1). In total, information on 5,863 individual sanderlings cap- between winter areas. Only 0.6% of all observations occurred tured between 1 January 1977 and 15 October 2013 (Table 1) was more than 1 degree latitude north or south of an individual's aver- used for the analyses of morphology and age and sex composition. age winter latitude (Figure S2). Of all 5,863 captured individuals, 5,220 (89%) were individually In all our analyses below, we considered individuals to have em- colour‐ringed from 1 October 2006–31 March 2013 with unique barked on northward migration if they were observed outside the combinations of two colour‐rings on each tarsus and an addi- wintering period 1 October–31 March and if they were observed at tional flag (i.e., an extended colour‐ring) on either tarsus or tibia. least 2 degrees latitude further north of their average winter latitude. During the 7‐year period 2007–2013, we checked the presence of colour‐ringed sanderlings at all winter areas (except for Scotland 2.3 | Variation in sex, age and size with and north Iberia), and in Iceland during northward staging, to esti- winter latitude mate the three fitness correlates simultaneously (see below). The winter destination was known for 3,397 colour‐ringed individuals, Birds were molecularly sexed based on DNA extracted from blood of which 3,148 wintered in one of the eight studied winter areas samples (Table 1), using primer set 2602F/2669R (van der Velde, (see below). Different subsets of these 3,148 birds were used to Haddrath, Verkuil, Baker, & Piersma, 2017). The eight sanderlings analyse adult survival, age‐dependent probability of migration to deployed with a geolocator at Karupelv Valley were molecularly breeding areas and the timing of northward migration (see below). sexed using the 2550F/2718R primer pair (Fridolfsson & Ellegren, To analyse the timing of northward migration, we included birds 1999). We determined the age (‘juvenile’ [first‐year] or ‘adult’ from winter destinations as long as these destinations generated [older than first‐year]) based on plumage characteristics (Prater, a minimum of ten observations of at least five birds during north- Marchant, & Vuorien, 1977). We examined whether the probabil- ward migration in Iceland. Birds caught between 1 October and ity of catching a female (excluding winter areas with <20 birds of 31 March across the entire winter range, whether colour‐ringed or known sex) or a juvenile differed between winter areas using a not, were used to analyse variation in morphometrics, sex and age generalized linear mixed effect model with a binomial error struc- ratio with latitude. ture. We included year as a random effect and compared models 4  |   Jo urnal of Animal Ecology RENEERKENS Et al. with and without winter area as a fixed effect on the basis of Bill lengths (n = 2,674) of birds captured in the winter area were AIC (Burnham & Anderson, 2002) using R‐package lme4 (Bates, measured with callipers to the nearest 0.1 mm and wing lengths Maechler, Bolker, & Walker, 2015). (stretched with completed moult of 10th primary; n = 2,603) with RENEERKENS Et al. Journal of Animal Ecolo gy    |  5 F I G U R E 1   (a) Locations where sanderlings, individually colour‐ringed at Zackenberg, a breeding site in northeast Greenland (white dot), were observed in winter (between 1 October and 31 March; red dots). The size of the red dots is indicative of the number of individuals. The dark yellow and light blue areas indicate the breeding location and the winter range of Greenlandic sanderlings (based on van de Kam, Ens, Piersma, & Zwarts, 2004, modified after Reneerkens et al., 2009). The grey horizontal lines indicate the zones of 5 degrees latitude which separate winter areas as used in our analyses. Winter areas in bold were analysed for both timing of northward migration and adult survival. (b–h) Seven tracks of six individual sanderlings equipped with a solar geolocator in northeast Greenland. Numbers in the right top of each panel are ring numbers, below which the years of southward (autumn) migration and northward (spring) migration are given. Two tracks in 2013–2014 and 2015–2016 of the same individual with ring number 8,223,401 are shown in separate, adjacent panels. Southward movements are indicated with black lines in which staging sites (stationary periods as indicated by FLightR) are downward triangles. Northward migration tracks are in orange, with upward triangles indicating staging sites. The size of the triangles indicates the length of the staging period. The sex of each tracked bird is shown in the lower left corner of each panel. Small white dots indicate the location of solar geolocator deployment and retrieval (i.e., Zackenberg, except for 8,214,904 which was ringed and recaptured at Karupelv Valley). (i) Dates at which individuals arrived in the Arctic (i.e., permanent daylight was recorded) in relation to the date of departure from the winter area for the six tracked sanderlings. Colour of the dots refers to winter areas in West Africa (yellow) or Namibia (purple) and letters in the dots to the corresponding tracks in panels b–h rulers to the nearest mm, and their body mass was measured to the model was not outperformed by the model containing a main effect nearest gram (n = 2,525). Because sanderlings in Namibia start fuel- of winter area (ΔAIC = 0.5; Figure S3). ling for northward migration around 1 March (Summers & Waltner, We estimated adult apparent survival (Φ) and resighting prob- 1979), we selected body mass data collected between 1 October and ability (p) using Cormack–Jolly–Seber (CJS) models (Lebreton & 28 February only. For Namibia, we used archived data from 1971 to Burnham, 1992). To estimate survival from winter to summer (1 1979, whereas data from other sites were collected in recent years January to 1 July) and from summer to winter (1 July to 1 January), (Table 1). We assumed that no change in size occurred over time (but we used a 6‐month resighting period (1 October–31 March) in an in- see (Lank et al., 2017)). As sanderlings of different age classes are of dividual's winter area (‘winter’) and a 6‐month resighting period (1 similar size and show only a small degree of sexual dimorphism with a April–30 September) at sites at least 2° north of an individual's winter great overlap in size between sexes (Lourenço et al., 2016), we pooled area (‘summer’). While the resighting periods are long relative to the the ages and sexes. We explored whether bill and wing length and intervals over which survival is estimated, a simulation study showed body mass varied linearly or quadratically with winter latitude based that this does not bias, yet actually increases the precision of survival on AIC (Burnham & Anderson, 2002). All statistical tests were per- estimates (O’Brien, Robert, & Tiandry, 2005). Furthermore, the av- formed using software r version 3.5.1 (R Core Team, 2018). erage date of observation during winter and summer (relative to the start of each season) was similar among birds from different winter 2.4 | Seasonal adult survival areas (Figure S4). Assuming that all alive individuals from the sampled (discrete) winter areas are available for detection during the summer We estimated seasonal apparent survival using encounter histories season (i.e., are not permanently or temporary absent), estimates of based on live observations of individually colour‐ringed individuals apparent survival will closely resemble true survival (hereafter re- that spent the non‐breeding period at six of the eight winter areas ferred to as ‘survival’). We believe this to be a reasonable assumption, along the non‐breeding range of Greenlandic sanderlings (Figure 1a). as summer resightings are made at all key spring and autumn staging Even though we did not capture and mark sanderlings in France and sites, supplemented by many auxiliary resightings along the entire Namibia, we could use individuals ringed elsewhere along the flyway migratory range. during migration or breeding that were later on observed in France In the full model, both Φ and p were modelled as a function of or Namibia in winter. To avoid any bias, we started such encounter group (i.e., winter area; g), year and season as well as their inter- histories in the year of observation after the year of capture (where active effects (Φsite*year*season psite*year*season). We compared reduced the next year starts after the summer, on 1 July). Consequently, only parameterizations of Φ and p (see Table S2 for a complete list of adult (i.e., >1 year old) birds were included in this analysis. To have parametrizations). sufficient number of observations of birds from all winter areas in Models were run with program MARK (White & Burnham, 1999) most of the years, we selected the years 2007 to 2013 for this analy- using the RMark package (Laake, 2013) in program r version 3.5.1 sis (Table S1), which is the same period during which we observed (R Core Team, 2018). We used the Akaike's information criterion sanderlings in Iceland to document the timing of northward migra- corrected for low sample size and overdispersion (QAICc, Burnham tion (see below). This resulted in a dataset of 1,358 colour‐ringed in- & Anderson, 2002) to select the best approximating model among dividuals with known winter areas (sample sizes: England 94, France the 40 candidate models. Models with ΔQAICc <2 without uninfor- 166, Portugal 158, Mauritania 415, Ghana 484 and Namibia 41). mative parameters (Arnold, 2010) were considered as supported Note that the number of seasons between colour‐ringing and the by the data. We assessed the goodness of fit of our data to the start of the encounter histories did not differ between individuals full model using program U‐Care version 2.3.2 (Choquet, Lebreton, from the six different winter areas (Poisson GLM: an intercept‐only Gimenez, Reboulet, & Pradel, 2009). There was only moderate lack 6  |   Jo urnal of Animal Ecology RENEERKENS Et al. TA B L E 1  Number of full‐grown individuals (i.e., excluding non‐fledged birds in Greenland) ringed and/or molecularly sexed per study site within the range of Greenlandic sanderlings. Season during which animals were caught refers to the breeding period (B; June–10 August in Greenland), the migration period (M;1 April ‐ 30 September outside Greenland) and in winter (W; 1 October–31 March). ‘n’ refers to the number of birds captured, ‘n marked’ refers to the number of birds that were individually colour‐ringed, and ‘n sexed’ refers to the number of individuals that were molecularly sexed. The winter area of individuals that were caught during the breeding period or during migration may or may not be known; see the different analyses within the Materials and Methods for sample sizes per winter area. Notice that in some studied winter areas, there was no main study site where birds were caught. Hence, no study sites in France and north Iberia are mentioned in this table Location Coordinates Period n marked n sexed (country) (decimal degrees) Season (years) n (%) (%) Hochstetter Forland 75.16666, −19.75000 B 2010–2013 108 107 (99%) 86 (80%) (Greenland) Zackenberg 74.46665, −20.56684 B 2007–2013 268 267 (100%) 263 (98%) (Greenland) Karupelv Valley 72.49994, −23.99954 B 2011–2013 52 52 (100%) 27 (52%) (Greenland) Sandgerði 64.04261, −22.71404 M 2007–2013 1,218 1,205 (99%) 560 (46%) (Iceland) Sanday 59.24081, −2.51783 M,W 1987–2013 378 163 (43%) 167 (44%) (Scotland) Wadden Sea 53.24967, 5.24271 M, W 2007–2013 750 505 (67%) 285 (38%) (Netherlands) Hayling Island 50.78336, −0.93620 M,W 2001–2013 103 103 (100%) 0 (0%) (England) Tagus estuary 38.74658, −8.97778 M,W 2008–2013 382 381 (100%) 13 (3%) (Portugal) Iwik, Banc d’Arguin 19.87754, −16.30356 W 2002–2013 1,483 1,302 (88%) 922 (62%) (Mauritania) Esiama 4.92577, −2.33373 M,W 2007–2013 1,136 1,135 (100%) 194 (21%) (Ghana) Swakopmund −22.71218, 14.52589 W 1971–1979 34 0 (0%) 0 (0%) (Namibia) of fit (χ2 = 238.83, df = 165, p < .001), which we corrected for by on northward migration, they can be observed during the summer implementing a variance inflation factor (ĉ = 1.45). season). We set this probability to one for adults, but allowed this probability to vary between sites for first‐year birds (i.e., only in the 2.5 | Age of first northward migration first season after they were captured as juvenile). The transition probability from the unobservable to the observable state was also For this analysis, we used individuals that were caught and indi- set to one, so that first‐year individuals can only be in the unob- vidually colour‐marked during the winter season in the winter areas servable (non‐migratory) state in the first summer after capture, England (38 juveniles, 221 adults), Portugal (88 juveniles, 196 adults), but not later on. To avoid identifiability problems, we assumed the Mauritania (489 juveniles, 365 adults) or Ghana (318 juveniles, 500 same survival for observable and unobservable individuals and the adults; Table S3). same resighting probabilities for first‐year and adult birds from the Multi‐event mark–recapture models (Pradel, 2005) were used same winter area. We modelled Φ and p using the parametrization to estimate the probability of migration of first‐year birds relative from the best supported model from the adult survival analysis to adult birds, while accounting for potential differences in Φ and described above and compared the two models in which the mi- p in relation to winter area and season. We used the same winter gration probability of first‐year birds is either constant or winter and summer resighting seasons as in the adult survival analysis and area‐dependent. defined three states: (a) alive and observable, (b) alive and unob- These models were constructed and run in program E‐Surge servable and (c) dead; and two events: (a) observed and (b) not ob- (Choquet, Rouan, & Pradel, 2009). Since no formal goodness‐of‐fit served. All individuals started in the observable state when caught tests exist for multi‐event models, we assessed the goodness of fit during winter in their winter area. The probability to stay in the for the CJS model Φsite psite*year*season (ignoring the unobservable observable state between the winter in which the birds were ringed state) in U‐Care (Choquet, Lebreton, et al., 2009). There was only and the subsequent summer (migration and breeding) season can moderate lack of fit (χ2 = 305, df = 167, p < .001) that we corrected be interpreted as migration probability (only when birds embark for (ĉ = 1.87). RENEERKENS Et al. Journal of Animal Ecolo gy    |  7 2.6 | Timing of northward migration 2013 in Karupelv Valley (2 males, 3 females and 3 of unknown sex). The geolocators were attached to a leg flag, which did not affect Iceland is the last possible staging site on northward migration before annual return rates (Brlík et al., 2019; Weiser et al., 2016). We re- birds migrate to their Arctic breeding area. Observations in Iceland trieved eight of the 52 geolocators (15%), seven of which we were were thus considered the best possible indicator of arrival time in the able to download data from. Six geolocators from five individuals Arctic breeding grounds. During northward staging in Iceland, be- (three males and two females) were from Zackenberg and one from tween 1 April and 15 June, we collected 1,870 observations of 289 Karupelv Valley (a female). Light intensity data collected by the ge- individuals with known winter area (Scotland: 45, England: 55, France: olocators were analysed using the FlightR package (Rakhimberdiev, 114, Spain: 10, Portugal: 23, Mauritania: 19, Ghana: 14, Namibia: 7; Saveliev, Piersma, & Karagicheva, 2017) in r. For details about the Table S4). Observations of individuals in the year of first capture in data selection and analysis, see Appendix S1. Iceland were excluded. Multiple observations of the same individual at the same date and location were considered single observations. 3  | RESULTS Following the methods in Zuur, Ieno, Walker, Saveliev, and Smith (2009), we applied a linear mixed effect model using the nlme package 3.1 | Sizes, body mass, age and sexes of sanderlings in r (Pinheiro, Bates, DebRoy, & Sarkar, 2015) with date (day of year, along the flyway centred around the mean) of observation in Iceland as a response vari- able and sex and winter area as additive fixed effects. Only 67% of the Bill length did not vary with latitude. Our best supported model sanderlings were molecularly sexed, so we included ‘unknown’ as a third was an intercept‐only model that was not outperformed by a model category next to male and female. The model with the main effects and with a linear effect of latitude (dAIC = 1.0) nor a quadratic effect of the interaction between sex and winter area was our full model. latitude (ΔAIC = 0.8) (Figure S5a). Wing length varied quadratically We first visually explored the residuals of the full model for with latitude with shortest wings at lowest latitudes (ΔAIC = 4.3 normality and homoscedasticity. Normality and homoscedasticity compared to a model with a linear effect of latitude and ΔAIC = 4.8 assumptions for linear models were violated. However, linear regres- compared to an intercept‐only model), but with a maximum mean sion is relatively robust against violations of normality assumptions, difference in wing length of only 1.5 mm on a mean of 126.4 mm especially when sample sizes are large (Fitzmaurice, Laird, & Ware, (1.2%) between the winter areas at the highest latitudes (Scotland 2004). Violations of homoscedasticity in the linear mixed model and Namibia). Body mass also varied quadratically with latitude were dealt with by fitting different variance structures to our mod- (ΔAIC = 349.5 compared to a model with a linear effect of latitude els (Table S5). We compared 32 full models with different combi- and ΔAIC = 552.6 to an intercept‐only model) and was lowest close nations of variance structures and random effects. The considered to the equator (Figure S5c). The maximum mean difference in body random effects in our models included a random intercept for year, mass between Scotland and Mauritania was 7.9 g on an overall mean individual, individual nested within year and models without random of 49.7 g (16%). Thus, in contrast to wing length, the variation in body effects. The variance structures used included separate variances mass with latitude appears to be of biological relevance. The pro- for each winter area, sex or year (the VarIdent function in the nlme portion of juveniles caught was 0.32 on average but varied across package) and model variance as an exponential function of the fitted winter areas (ΔAIC = 337 compared with the intercept‐only model) values in general and separately for each non‐breeding area, sex or due to the high proportion of juveniles (0.54, 95% confidence inter- year (VarExp). Last, we used a combination of model variance struc- val: 0.42–0.68) in Mauritania (Figure S5d). The proportion of females tures (VarComb) by combining model variance as an exponential ranged between 0.42 and 0.63 and varied between winter areas function of the fitted values with a separate variance for each winter (ΔAIC = 19.9 with the intercept‐only model), with the lowest pro- area (Table S5). The models were fitted using restricted maximum portion of females in Mauritania (0.41, 0.32–0.51), and a majority of likelihood estimation and compared based on AIC. Models within 2 females in Ghana (0.62, 0.54–0.70) and Scotland (0.55, 0.41–0.69) ΔAIC of the best model were considered equally parsimonious, but (Figure S5e). models with additional parameters to other strongly supported mod- els were not considered fitting the data well because model deviance 3.2 | Lower adult survival in West Africa compared is not reduced sufficiently to overcome the penalty of 2 AIC for the with Europe and Namibia additional parameters (Arnold, 2010). Four fixed effects models were considered: sex, winter area and additive and interaction effects of Adult survival probabilities differed considerably between sander- sex and winter area. lings from the different winter areas. In the best supported model, survival probabilities differed between winter areas but not between 2.7 | Itineraries assessed by solar geolocation seasons (Table 2, Figure 2a). Resighting probability was most par- simoniously explained by an interaction between winter area and We deployed solar geolocators (Intigeo‐W65A9, Migrate Technology time (Table 2, Figure S6). In the three European winter areas, adult Ltd) on 44 sanderlings in June–July 2013 and 2015 at Zackenberg sanderlings showed annual survival ranging from 0.84 in France (95% (26 males and 18 females) and on eight sanderlings in June–July confidence interval: 0.78–0.89) and Portugal (0.74–0.91) to 0.87 8  |   Jo urnal of Animal Ecology RENEERKENS Et al. TA B L E 2  Models for seasonal Model QAICc ΔQAICc wi K QDeviance survival of adult sanderlings at six winter Φ(winter area) p(winter 5,800 0 0.53 84 1,480 areas along the East Atlantic Flyway in area*year*season) 2007–2013. Of 40 candidate models, Φ(winter area + season) p(winter 5,801 1.05 0.31 85 1,479 only those with ΔQAICc <65 are shown. area*year*season) Model parameterization is explained in Φ(winter area*season) p(winter 5,803 3.51 0.09 90 1,471 Table S2. Models are ranked by ascending area*year*season) ΔQAICc, wi is the model weight, and K is the number of parameters Φ(constant) p(winter area*year*season) 5,805 5.34 0.04 79 1,496 Φ(season) p(winter area*year*season) 5,806 5.84 0.03 80 1,495 Winter area 100 (a) 90 80 70 1 (b) 0.75 0.5 0.25 0 160 (c) 155 150 145 140 135 −20 0 20 40 60 Latitude winter area (degrees) F I G U R E 2  Fitness correlates for sanderlings wintering in different areas. Latitudes are those from the main study sites within winter areas. Dots are averages, and error bars indicate 95% confidence intervals. (a) Annual adult survival probabilities of six winter areas within Greenlandic sanderlings’ flyway. Survival estimates are those from the most parsimonious model from a set of 40 used to explain year‐ round observation histories at and outside the study sites (See Materials and Methods and Table 2, Table S2). (b) Probability that juvenile relative to adult sanderlings migrated northwards in the summer following the winter during which individuals were caught and individually colour‐ringed in four winter areas. Estimates are based on a multi‐event mark–recapture model (see Materials and Methods). (c) Timing of northward migration through Iceland of sanderlings wintering in eight winter areas. The average timing of migration through Iceland is estimated from the most parsimonious linear mixed effects model with individual nested within year as random effects (see Materials and Methods). Day of year 140 represents 20 May. The 95% confidence intervals are based on a normal distribution for the survival probabilities and on a t‐distribution for the migration dates (0.70–0.95) in England, all very similar to the estimate of 0.85 (0.73– 3.3 | Sanderlings from West Africa are more likely 0.92) for sanderlings wintering in Namibia (Figure 2a). Annual survival to forego their first northward migration probabilities of adult sanderlings at tropical latitudes in Mauritania (0.74; 0.69–0.78) and Ghana (0.75; 0.70–0.79) were considerably The model in which migration probability of first‐year birds was lower (Figure 2a). site‐dependent was much better supported than the model with Migration date Probability of through Iceland juvenile migration (day of year) (relative to adults) Annual adult survival (%) Namibia Ghana Mauritania Portug N ao lrth Iber F iar E an ng cl eand Scotland RENEERKENS Et al. Journal of Animal Ecolo gy    |  9 constant migration probability (ΔQAICc = 11.38). While juvenile During northward migration, individuals staged longest in NW and adult sanderlings from England and Portugal were estimated Europe between 51–57°N (Figure 1b–h, Table S6), although one in- to be equally likely to migrate northward in the season after dividual had a marginally longer refuelling stage in Spain than in the capture, juveniles from Ghana and especially Mauritania were Wadden Sea in one of the 2 years (Table S6). Four of the six individu- much less likely to do so than adults from the same winter areas als staged in the Wadden Sea during northward migration (Figure 1b– (Figure 2b). Our estimate of probability of northward migration h, Table S6). The other two individuals staged at the north‐west coast by first‐year birds is relative to adults within the same winter of the United Kingdom before a direct flight to the Arctic (Figure 1a; area. Thus, the absolute estimates may differ if the probability Table S6). At least two individuals had a final stopover in Iceland be- to embark on northward migration is not 1 for adults and differs fore continuing to Greenland (Figure 1b,c, Table S6). Date of depar- between sites. In recent years, the resighting probabilities dur- ture from the wintering destination was tightly correlated with the ing summer of birds wintering in Ghana were lower than of birds date of arrival in the Arctic (F1,5 = 20.3, p = .006, R 2 = 0.76; Figure 1i). adj from the other three winter areas (Figure S7), suggesting that also adults wintering in Ghana may have a lower probability to embark on northward migration, implying an even lower fitness of birds 4  | DISCUSSION wintering in Ghana. In contrast to our prediction of equal survival and timing of migra- 3.4 | In spring, sanderlings from West Africa migrate tion across their large non‐breeding range, we found that sander- later through Iceland lings from winter areas in West Africa had (a) lower adult survival, (b) delayed first northward migration and (c) later passage through Timing of spring migration through Iceland depended on the winter their last spring staging site in Iceland than birds wintering either area; the most parsimonious model only included a main effect of further north or south. Individual fitness correlates of sanderlings winter area (Table 3). Time of passage did not linearly increase with thus varied across their large non‐breeding range, but did not in- migration distance, as sanderlings from Namibia were present at the crease with migration distance. Sanderlings from low‐latitude winter same time as birds wintering in Europe (around 25 May; Figure 2c). areas in West Africa seem to perform poorly. In contrast to the situa- Birds from Ghana were observed in Iceland 5–11 days later and tion in other sandpipers (Fernández et al., 2004; O’Hara, Fernández, those from Mauritania 9–15 days later than birds from European Becerril, Cueva, & Lank, 2005), the delayed age of first northward winter destinations and Namibia. migration by sanderlings wintering in West Africa was not compen- sated for by higher adult survival, although potential trade‐offs with 3.5 | Sanderlings skip West Africa other demographic parameters (e.g., enhanced juvenile survival and/ during northward migration or reproductive success at older ages) cannot be excluded and war- rant further study. How can these patterns be explained? Do sand- Of the seven geolocator tracks from six individuals, four individu- erlings of relatively poor overall condition end up in West Africa? als wintered in West Africa (three in Mauritania and one in Guinea‐ Or do differences in non‐breeding habitat quality explain this pat- Bissau) and two in Namibia (Figure 1b–h, Table S6). In contrast to tern? Interestingly, while they used West‐African staging sites during their southward migration, birds wintering in Namibia did not stage southward migration (Figure 1b–h), during northward migration the in West Africa during northward migration (Figure 1g,h). Instead, two tracked individuals from Namibia flew 7,500 km non‐stop across they made non‐stop flights of ca. 7,500 km (assuming great circle the African continent during northward migration. distances) across the African continent including the Sahara de- Unlike other shorebirds (Nebel et al., 2002; O’Hara, Fernández, sert (Figure 1g,h). All West‐African wintering individuals migrated Haase, Cueva, & Lank, 2006), we found no convincing evidence for non‐stop from Africa to Europe (Figure 1b–h), but one of the two larger sanderlings to winter farther south or in a pattern matching Namibian wintering individuals briefly stopped at the Mediterranean their fitness correlates (Figure S5). Although sanderlings had a lower coast in Libya and Tunisia (Figure 1h, Table S6). body mass in tropical winter areas compared with areas further away TA B L E 3  Models for timing of northward migration through Iceland with different fixed effects. We fitted a random structure with individual nested within year (~1|Year/Individual) and varExp(form=~fitted(.)) as variance structure (Table S5) for all models. See Materials and Methods for explanation. The following parameters are shown: residual degrees of freedom (df), log‐likelihood (logLik), Akaike's information criterion (AIC), the difference in AIC with the top‐supported model (ΔAIC), model weights (wi) and residual deviance (deviance) Model df logLik AIC ΔAIC wi Deviance Winter area 18 −5,420.84 10,877.7 0 0.67 10,841.7 Winter area + Sex 20 −5,419.54 10,879.1 1.4 0.33 10,839.1 Winter area * Sex 34 −5,412.31 10,892.62 15.0 0 10,824.6 Sex 13 −5,535.13 11,096.3 218.6 0 11,070.3 10  |   Jo urnal of Animal Ecology RENEERKENS Et al. from the equator, this may be explained by adaptive fuel storage in conditions at the end of the wintering period. Even though returning colder and more unpredictable temperate areas (Kelly & Weathers, to West Africa is not the best option at the population level, individ- 2002; Lima, 1986) instead of being interpreted as poorer individual uals surviving their first year of life would have experienced that it conditions of birds in tropical winter areas. The proportion of juve- ‘worked’ for them. Assuming an absence of exploratory migrations niles was considerably larger in Mauritania (Figure S5d) compared along the West‐African coast, only the southernmost wintering birds with the other winter areas. However, we believe that this is to a would have had the opportunity to collect information on habitat large extent caused by catching method (Robinson et al., 2005), as quality along the length of the flyway. Furthermore, habitat quality birds in Mauritania were caught with bait during high tide, when ju- will vary within and between years. If conditions in West Africa de- veniles are more prone to continue foraging compared with adults teriorate throughout most wintering periods, for example through (J. Reneerkens personal observations). In Ghana, where sanderlings depletion of food stocks (Ahmedou Salem, Geest, Piersma, Saoud, performed equally poor as in Mauritania, juvenile proportions were & Gils, 2013), individuals staging at these sites during southward mi- much lower. Based on an examination of the annual cycles of shore- gration (Figure 1) may initially encounter profitable conditions and birds, it was concluded earlier that there is little support for the decide to stay, but get ‘trapped’ when conditions get worse. idea that subordinate individuals are forced south by competition The population of sanderlings along the East Atlantic Flyway (Meltofte, 1996). Thus, we consider it unlikely that sanderlings of rel- has been growing for decades (van Roomen et al., 2015), which may atively poor overall condition end up in West Africa. lead to disproportionally large densities of individuals relative to Many different ecological aspects combine to determine the the resources. For both Great Britain (Méndez, Gill, Alves, Burton, quality of non‐breeding habitats (Piersma, 2012), with food avail- & Davies, 2018) and Ghana (Ntiamoa‐Baidu, Nuoh, Reneerkens, & ability being of key importance. For shorebirds, it has been shown Piersma, 2014), there is evidence that the growing sanderling pop- that prey quality and prey biomass are lowest close to the equator ulation reached ‘carrying capacity’ at preferred sites, buffering the (Aharon‐Rotman, Gosbell, Minton, & Klaassen, 2016; Piersma et use of some sites by forcing individuals to settle in alternative sites al., 1993, 2005). In these tropical areas, the relatively low harvest- of (presumed) lower quality (Gill et al., 2001; Moser, 1988). At a local able prey biomass (Aharon‐Rotman et al., 2016; Catry et al., 2016; scale, high densities of birds competing for resources may limit their Piersma et al., 1993) would result in low fuelling rates and low body performance and eventually limit flyway scale population growth masses at northward departure in a closely related High Arctic sand- (Gunnarsson, Gill, Petersen, Appleton, & Sutherland, 2005). piper, the Red Knot Calidris canutus (Piersma et al., 2005). Indeed, Over half of the flyway population of sanderlings winters in West food availability during migratory fuelling has been shown to pos- Africa (van Roomen et al., 2015), where we show that adult survival itively influence timing of migration and survival of Red Knots and and presumably also (lifetime) reproductive success are lowest. Bar‐tailed Godwits Limosa lapponica (e.g., Atkinson et al., 2007; Clearly, the settling decisions of juveniles will determine their fitness Rakhimberdiev et al., 2018) and explained why less proficiently for- (Senner, Conklin, & Piersma, 2015) and it is of interest whether and aging juvenile shorebirds may skip northward migration (Hockey, to what extent social learning and/or the early environment—at the Turpie, & Velásquez, 1998). On the basis of (a) the lower survival Arctic tundra, during the first southward migration or at the chosen and later passage through Iceland of sanderlings wintering in West winter area—impact such decisions. Africa, (b) the correlation between date of departure from the winter area and date of arrival in the Arctic and (c) the fact that sanderlings ACKNOWLEDG EMENTS skipped West Africa during northward migration, we suggest that the conditions in West Africa were somehow ecologically compro- This study is based on the efforts of more than 2,000 observ- mised, especially during the season of northward migration. Outside ers reporting colour‐ringed sanderlings. We especially thank the period of northward fuelling, sanderlings have a higher food Guðmundur Örn Benediktsson, John Bowler, Ruth Croger, Anne intake in Ghana compared with the Netherlands. However, food de Potier, Benjamin Gnep, Kim Fischer, Kirsten Grond, Eileen quality in Ghana is much poorer and sanderlings in Ghana spent con- Hughes, Hilger Lemke, Pedro Lourenço, Andy Johnson, Pierre siderable more time processing indigestible shell fragments (Grond Leon, Jelle Loonstra, Sebastien Nedellec, Afonso Rocha, Brian et al., 2015). When fuelling for northward migration, this could result Rogers, Ron Summers, Jan van Dijk and Hein Verkade. Anneke Bol, in lower fuelling rates in Ghana compared with the Netherlands. Marco van der Velde and Yvonne Verkuil molecularly sexed the Sanderlings show strong within‐ and between‐year winter site majority of birds, Maria Teixeira and Jérôme Moreau sexed eight fidelity (Lourenço et al., 2016). In large long‐lived birds, winter site individuals. Ron Porter created flags for geolocator attachment. fidelity has been shown to increase with age (e.g., Lok et al., 2011; Eldar Rakhimberdiev answered questions concerning FLightR Marchi et al., 2010), but we have no evidence that sanderlings move and Allert Bijleveld, Jesse Conklin, Rosemarie Kentie, Thomas to different winter areas after their first year of life. Why would Oudman, Janne Ouwehand, Emma Penning, Eldar Rakhimberdiev, individuals return to areas where conditions are such that survival Brett Sandercock, Ron Summers, Yvonne Verkuil and two re- is low and departure difficult or late? Here we are reminded that viewers critically commented on drafts. Benjamin Gnep created function is not a cause (Hogan, 2017): sanderlings will not be able to Figure 1. Annual expeditions to Mauritania were organized by build up the knowledge on what is coming with respect to ecological NIOZ, and we especially thank Maarten Brugge, Anne Dekinga, RENEERKENS Et al. Journal of Animal Ecolo gy    |  11 Jutta Leyrer and Bernard Spaans for their contributions. The Parc ‘depletion by shorebirds’ hypothesis. Estuarine, Coastal and Shelf National du Banc d'Arguin granted research permits and facili- Science, 136, 26–34. https ://doi.org/10.1016/j.ecss.2013.11.009 Alerstam, T., & Lindström, Å. (1990). Optimal bird migration: The relative tated access. J.R. and T.S.L.V. thank Aarhus University for logis- importance of time, energy, and safety. In E. Gwinner (Ed.), Bird mi‐ tical support at Zackenberg. Benoît Sittler organized expeditions gration: Physiology and ecophysiology (pp. 331–351). Berlin, Germany: to Karupelv Valley. The Farlington Ringing Group provided can- Springer. non‐net equipment. This work was supported by two grants from Alves, J. A., Gunnarsson, T. G., Hayhow, D. B., Appleton, G. F., Potts, P. the Netherlands Polar Programme (851.40.072 and 866.15.207) of M., Sutherland, W. J., & Gill, J. A. (2013). Costs, benefits, and fitness consequences of different migratory strategies. Ecology, 94, 11–17. the Netherlands Organisation for Scientific research (NWO) and https ://doi.org/10.1890/12‐0737.1 from the Metawad project awarded by Waddenfonds (WF209925) Arnold, T. W. (2010). Uninformative parameters and model selection to JR and TP. The measurements in Mauritania had their begin- using Akaike’s information criterion. Journal of Wildlife Management, nings in the Prins Bernhard Cultuurfondsprijs to TP. JR and TP 74, 1175–1178. https ://doi.org/10.1111/j.1937‐2817.2010.tb012 36.x Atkinson, P. W., Baker, A. J., Bennett, K. A., Clark, N. A., Clark, J. A., Cole, also received INTERACT grants for Transnational Access from the K. B., … Sitters, H. P. (2007). Rates of mass gain and energy deposi- European Community's Seventh Framework Programme (grant tion in red knot on their final spring staging site is both time‐ and con- agreement No262693). JR received a generous donation from dition‐dependent. Journal of Applied Ecology, 44, 885–895. https: // World Wildlife Fund Netherlands. JAA was supported by FCT doi.org/10.1111/j.1365‐2664.2007.01308.x Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear (SFRH/BPD/91527/2012). OG and Loïc Bollache were supported mixedeffects models using lme4. Journal of Statistical Software, 67, by the French Polar Institute (IPEV; program ‘1036 Interactions') 1‐48 https ://doi.org/10.18637/j ss.v067.i01. and TL by a Veni grant (no. 016.Veni.192.245) from NWO. The au- Brlík, V., Koleček, J., Burgess, M., Hahn, S., Humple, D., Krist, M., … thors declare no conflict of interest. Procházka, P. (2019). Weak effects of geolocators on small birds: A meta‐analysis controlled for phylogeny and publication bias. Journal of Animal Ecology. https ://doi.org/10.1111/1365‐2656.12962 AUTHORS’ CONTRIBUTIONS Burnham, K., & Anderson, D. (2002). Model selection and multi‐model inference: A practical information‐theoretic approach (2nd ed.). New J.R., Y.N.‐B. and T.P. conceived the ideas. J.R., T.S.L.V., T.P., J.A.A., York, NY: Springer. M.B., C.C., G.T.H., O.G., J.L., B.L., Y.N.‐B., A.A.N., P.M.P. and J.t.H. Castro, G., Myers, J., & Ricklefs, R. (1992). Ecology and energetics of collected data; J.R., T.S.L.V. and T.L. analysed the data. 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