Evidence for an Association between Post-Fledging Dispersal and Microsatellite Multilocus Heterozygosity in a Large Population of Greater Flamingos

Abstract

Dispersal can be divided into three stages: departure, transience and settlement. Despite the fact that theoretical studies have emphasized the importance of heterozygosity on dispersal strategies, empirical evidence of its effect on different stages of dispersal is lacking. Here, using multi-event capture-mark-recapture models, we show a negative association between microsatellite multilocus heterozygosity (MLH; 10 loci; n = 1023) and post-fledging dispersal propensity for greater flamingos, Phoenicopterus roseus, born in southern France. We propose that the negative effects of inbreeding depression affects competitive ability and therefore more homozygous individuals are more likely to disperse because they are less able to compete within the highly saturated natal site. Finally, a model with the effect of MLH on propensity of post-fledgling dispersers to disperse to the long-distance sites of Africa was equivalent to the null model, suggesting that MLH had low to no effect on dispersal distance. Variations in individual genetic quality thus result in context-dependent heterogeneity in dispersal strategies at each stage of dispersal. Our results have important implications on fitness since sites visited early in life are known to influence site selection later on in life and future survival.

Offspring Microbiomes Differ Across Breeding Sites in a Panmictic Species

“…In this study, we used the Greater Flamingo, Phoenicopterus roseus , as a biological model to examine spatial variation in enteric microbiome in a long-lived colonial waterbird species. Previous work has provided evidence for panmixia across all breeding colonies at the scale of the Mediterranean (Geraci et al, 2012; Gillingham et al, 2017), as a result of high dispersal rates (Barbraud et al, 2003; Balkız et al, 2010; Sanz-Aguilar et al, 2012; Gillingham et al, 2013). We investigated the cloacal bacterial microbiome of fledglings (i.e., juvenile individuals about to take flight but still fed by parents) using 16S rRNA gene sequencing as a non-invasive proxy of enteric microbiome at nine Mediterranean breeding colonies across four breeding seasons.…”

Adult survival selection in relation to multilocus heterozygosity and body size in a tropical bird species, the Zenaida dove, Zenaida aurita

“…First, heterozygosity-fitness correlations (HFCs) are expected to be weak in natural populations (Chapman et al 2009;Szulkin et al 2010), and it has been argued that their identification would most often require the use of a much larger set of genetic markers than usual (Chapman et al 2009;Hoffman et al 2014;. However, significant correlations between various life history traits or sexually selected traits and multilocus heterozygosity (MLH) based on a limited number (<25) of microsatellites have been recently evidenced in several species (see for instance Harrison et al 2011;Agudo et al 2012;Wetzel et al 2012;Gillingham et al 2013;Cain et al 2014;Forcada and Hoffman 2014;Herdegen et al 2014), suggesting that the use of a large set of markers is not always necessary. In addition, there is evidence that, under certain circumstances, a small panel of microsatellite markers (n = 11) can produce equally strong or even stronger HFCs as a large panel of single-nucleotide polymorphism markers (Fortsmeier et al 2012).…”

“…In particular, CMR analysis makes the estimation of both genetic and phenotypic effects on survival tractable in a wide range of species and, for that reason, can be a powerful tool in evolutionary biology (Clobert 1995;Cooch et al 2002). Still, the use of capture-recapture modelling to assess the relative influences of genetic and phenotypic qualities on survival remains limited (see, however, Armstrong and Cassey 2007; Banks et al 2010;Gillingham et al 2013;Forcada and Hoffman 2014).…”

Contrasting heterozygosity‐fitness correlations across life in a long‐lived seabird

“…However, we would hypothesize that the observed heterozygosity‐recruitment correlation could potentially be due to a negative heterozygosity‐dispersal correlation. The importance of heterozygosity for dispersal decisions has been highlighted by theoretical studies (Motro, ; Roze & Rousset, ), but empirical studies are still rare (Gillingham, Cezilly, Wattier, & Bechet, ; Liebgold, Kramer, Roomian, Dolezar, & Cabe, ; Shafer, Poissant, Cote, & Coltman, ; Vanpé et al, ). In mountain goats ( Oreamnos americanus , Shafer et al, ) and greater flamingos ( Phoenicopterus roseus , Gillingham et al, ), however, heterozygosity was negatively correlated with dispersal, which supports the fitness‐associated dispersal hypothesis (FAD, Hadany, Eshel, & Motro, ; Shafer et al, ).…”