Data from: Fine-scale kin recognition in the absence of social familiarity in the Siberian jay, a monogamous bird species

Kin recognition is a critical element to kin cooperation, and in vertebrates, it is primarily based on associative learning. Recognition of socially unfamiliar kin occurs rarely, and it is reported only in vertebrate species where promiscuity prevents recognition of first-order relatives. However, it is unknown whether the recognition of socially unfamiliar kin can evolve in monogamous species. Here, we investigate whether genetic relatedness modulates aggression among group members in Siberian jays (Perisoreus infaustus). This bird species is genetically and socially monogamous and lives in groups that are formed through the retention of offspring beyond independence, and the immigration of socially unfamiliar nonbreeders. Observations on feeders showed that genetic relatedness modulated aggression of breeders towards immigrants in a graded manner, in that they chased most intensely the immigrant group members that were genetically the least related. However, cross-fostering experiments showed that breeders were equally tolerant towards their own and cross-fostered young swapped as nestlings. Thus, breeders seem to use different mechanisms to recognize socially unfamiliar individuals and own offspring. As Siberian jays show a high degree of nepotism during foraging and predator encounters, inclusive fitness benefits may play a role for the evolution of fine-scale kin recognition. More generally, our results suggest that fine-graded kin recognition can evolve independently of social familiarity, highlighting the evolutionary importance of kin recognition for social species.dispersal dataDispersal distance of immigrantsbetween group encountersrate of between group encounters during summerduration aggressionduration of displacements and chasing events (in seconds)used microsatellitesaggression own young crossfostered youngaggression of parents towards young crossfostered young during 30 minmicrosatellites genepop dataused microsatellites for analyses, genepop formatcoancestry relatedness simulationscoancestry relatedness simulations year 1999 and 2008-2009, simulation the relatendess of offspring and unrelated individualsR_scriptR-code of the main analysesmale vs non-breeders data-setring – non-breeder identity. breeder_ring – breeder identity. obstime – observation bout length: 15min, 30min. year – year of observation. sex – sex of non-breeder. breeder_age – age of breeder. age – age of non-breeder. kinship – kinship breeder vs non-breeder: kin (parent-offspring, non-kin: breeder-immigrant). groupsize – group size. NSI – nesting success index of territory (see Griesser et al. 2008). prop_um – proportion unmanaged forest on territory (see Griesser et al. 2006). displaced – number of displacements received during 30 min. chased - number of chasing events received during 30 min. submissive - number of times submissive behaviour is displayed during 30 min. TrioML - Trio maximum likelihood r estimator. Ritland - Ritland's r estimator. DyadML - Dyad maximum likelihood r estimator. Wang_mb - Wang's r estimator. LynchLi_mb - Lynch and Li's r estimator. QuellerGt_mb - Queller and Goodnight's r estimator. LynchRd - Lynch and Ritland's r estimatormales.csvfemales vs non-breeders data-setring – non-breeder identity. breeder_ring – breeder identity. obstime – observation bout length: 15min, 30min. year – year of observation. sex – sex of non-breeder. breeder_age – age of breeder. age – age of non-breeder. kinship – kinship breeder vs non-breeder: kin (parent-offspring, non-kin: breeder-immigrant) groupsize – group size. NSI – nesting success index of territory (see Griesser et al. 2008). prop_um – proportion unmanaged forest on territory (see Griesser et al. 2006). displaced – number of displacements received during 30 min. chased - number of chasing events received during 30 min. submissive - number of times submissive behaviour is displayed during 30 min. TrioML - Trio maximum likelihood r estimator. Ritland - Ritland's r estimator. DyadML - Dyad maximum likelihood r estimator. Wang_mb - Wang's r estimator. LynchLi_mb - Lynch and Li's r estimator. QuellerGt_mb - Queller and Goodnight's r estimator. LynchRd - Lynch and Ritland's r estimatorfemales.cs