Individual Winter Movement Strategies in Two Species of Murre (Uria spp.) in the Northwest Atlantic

Abstract

Individual wintering strategies and patterns of winter site fidelity in successive years are highly variable among seabird species. Yet, an understanding of consistency in timing of movements and the degree of site fidelity is essential for assessing how seabird populations might be influenced by, and respond to, changing conditions on wintering grounds. To explore annual variation in migratory movements and wintering areas, we applied bird-borne geolocators on Thick-billed Murres (Uria lomvia, n = 19) and Common Murres (U. aalge, n = 20) from 5 colonies in the Northwest Atlantic for 2–4 consecutive years. Thick-billed Murres ranged widely and among-individual wintering strategies were highly variable, whereas most Common Murres wintered relatively near their colonies, with among-individual variation represented more by the relative use of inshore vs. offshore habitat. Within individuals, some aspects of the wintering strategy were more repeatable than others: colony arrival and departure dates were more consistent by individual Common than Thick-billed Murres, while the sizes of home ranges (95% utilization distributions) and distances travelled to wintering area were more repeatable for both species. In consecutive years, individual home ranges overlapped from 0–64% (Thick-billed Murres) and 0–95% (Common Murres); and the winter centroids were just 239 km and 169 km apart (respectively). Over the 3–4 year timescale of our study, individuals employed either fixed or flexible wintering strategies; although most birds showed high winter site fidelity, some shifted core ranges after 2 or 3 years. The capacity among seabird species for a combination of fidelity and flexibility, in which individuals may choose from a range of alternative strategies, deserves further, longer term attention.

Consistent variation in individual migration strategies of brown skuas

“…This could ultimately lead to variation in individual migration patterns of seabirds at some spatial scale across years. Indeed, although most species show high individual consistency in non-breeding destinations at a large spatial scale (Phillips et al 2005, Müller et al 2014, there are exceptions; in addition, in almost all species there is extensive variation both among and within individuals in routes, use of staging areas and timing (Quillfeldt et al 2010, Dias et al 2011, McFarlane Tranquilla et al 2014.…”

Methods for detecting and quantifying individual specialisation in movement and foraging strategies of marine predators

“…Hamer et al 2001, Gray et al 2005, Vander Zanden et al 2013, Oppel et al 2015 or with linear mixed-effects models with individual identities treated as a random effect (e.g. Dias et al 2011, Matich et al 2011, Grist et al 2014, McFarlane Tranquilla et al 2014, Kernaléguen et al 2015, Wake field et al 2015. Note that the framework proposed by Bolnick et al (2002), examining the within-individual component and between-individual component of a niche, is essentially the same as the residual variance (within-individual variance) and between-individual variance when using mixed-effects models.…”

“…It is possible to study individual specialisation in space, and not only in trip characteristics, based on distances between the centroid of the locations at 2 different times for the same individuals tracked during the breeding season (Navarro & González-Solís 2009, Ceia et al 2014, or between centroids in different winters (Dias et al 2011, McFarlane Tranquilla et al 2014, Yamamoto et al 2014, Lea et al 2015. Distances can also be calculated between pairs of migratory routes (e.g.…”

“…evaluate the statistical significance of individual consistency), one approach is to use distances calculated for pairs of centroids or routes as the response variable in a (G)LMM with individual (same vs. different) as a random effect, and check for the significance of the random effect (Dias et al 2013). The second, and more widely used approach, is to compare the calculated within-individual distances with a null distribution of distances generated by reshuffling either locations or migratory tracks between individuals (Navarro & González-Solís 2009, Dias et al 2011, McFarlane Tranquilla et al 2014). This method based on distances does not take into account the spread of the locations around the centroids: hence, although useful to detect a shift in the general distribution, it would not detect a change only in range size.…”

“…This method has been used to compare foraging areas in consecutive trips during the breeding season , Pettex et al 2012, Soanes et al 2013, and areas used from one year to the next (Chilvers 2008, McFarlane Tranquilla et al 2014, Muller et al 2014). The problem is that it does not exploit the information on the complete UDs (cf.…”