Characterizing dispersal patterns in a threatened seabird with limited genetic structure

Hall, Laurie A.; Palsbøll, Per; Beissinger, Steven R.; Harvey, James T.; Bérubé, Martine; Raphael, Martin G.; Nelson, S. Kim; Golightly, Richard T.; McFarlane-Tranquilla, Laura; Newman, Scott H.; Peery, M. Zachariah

doi:10.1111/j.1365-294x.2009.04416.x

Cited by 30 publications

(25 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dispersers may also have lower survival or reproductive rates than non‐dispersers due to pre‐dispersal factors, costs incurred during dispersal or negative interactions with residents after settlement (Stamps et al. 2005; Benard & McCauley 2008; Hall et al. 2009).…”

Section: Demographic Connectivitymentioning

confidence: 99%

What can genetics tell us about population connectivity?

2010

View full text Add to dashboard Cite

Genetic data are often used to assess 'population connectivity' because it is difficult to measure dispersal directly at large spatial scales. Genetic connectivity, however, depends primarily on the absolute number of dispersers among populations, whereas demographic connectivity depends on the relative contributions to population growth rates of dispersal vs. local recruitment (i.e. survival and reproduction of residents). Although many questions are best answered with data on genetic connectivity, genetic data alone provide little information on demographic connectivity. The importance of demographic connectivity is clear when the elimination of immigration results in a shift from stable or positive population growth to negative population growth. Otherwise, the amount of dispersal required for demographic connectivity depends on the context (e.g. conservation or harvest management), and even high dispersal rates may not indicate demographic interdependence. Therefore, it is risky to infer the importance of demographic connectivity without information on local demographic rates and how those rates vary over time. Genetic methods can provide insight on demographic connectivity when combined with these local demographic rates, data on movement behaviour, or estimates of reproductive success of immigrants and residents. We also consider the strengths and limitations of genetic measures of connectivity and discuss three concepts of genetic connectivity that depend upon the evolutionary criteria of interest: inbreeding connectivity, drift connectivity, and adaptive connectivity. To conclude, we describe alternative approaches for assessing population connectivity, highlighting the value of combining genetic data with capture-mark-recapture methods or other direct measures of movement to elucidate the complex role of dispersal in natural populations.Keywords: adaptation, demographic connectivity, drift, emigration, F-statistics, gene flow, genetic connectivity, immigration, inbreeding, population dynamics, source-sink, spatial ecology The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power.

show abstract

Section: Demographic Connectivitymentioning

confidence: 99%

What can genetics tell us about population connectivity?

2010

View full text Add to dashboard Cite

show abstract

“…Overall, our samples covered a significant proportion of the area in which birds in this population breed on the plateau on top of Salt Pond Mountain. The isolated nature of mountaintop-breeding junco populations (Ketterson et al 1992) make them ideal for analysis of SBD using assignment methods (Hall et al 2009).…”

Section: Assignment Indices: Inferring Between-population Sbd (Immigrmentioning

confidence: 99%

Similarity in temporal variation in sex‐biased dispersal over short and long distances in the dark‐eyed junco,Junco hyemalis

2013

View full text Add to dashboard Cite

Patterns of sex-biased dispersal (SBD) are typically consistent within taxa, for example female-biased in birds and male-biased in mammals, leading to theories about the evolutionary pressures that lead to SBD. However, generalizations about the evolution of sex biases tend to overlook that dispersal is mediated by ecological factors that vary over time. We examined potential temporal variation in between- and within-population dispersal over an 11-year period in a bird, the dark-eyed junco (Junco hyemalis). We measured between-population dispersal patterns using genetic assignment indices and found yearly variation in which sex was more likely to have immigrated. When we measured within-population spatial genetic structure and mark–recapture dispersal distances, we typically found yearly SBD patterns that mirrored between-population dispersal, indicating common eco-evolutionary causes despite expected differences due to the scale of dispersal. However, in years without detectable between-population sex biases, we found genetic similarity between nearby males within our population. This suggests that, in certain circumstances, ecological pressures may act on within-population dispersal without affecting dispersal between populations. Alternatively, current analytical tools may be better able to detect within-population SBD. Future work will investigate potential causes of the observed temporal variation in dispersal patterns and whether they have greater effects on within-population dispersal.

show abstract

“…Assignment methods, where individuals are probabilistically assigned to populations based on their multilocus genotypes, were seen as an improved approach, providing contemporary estimates of gene flow and dispersal (Pritchard, Stephens, & Donnelly, 2000;Rannala & Mountain, 1997;Waser & Strobeck, 1998). However, power to detect dispersal with these methods relies on high levels of genetic structure between populations (Berry, Tocher, & Sarre, 2004;Paetkau, Slade, Burden, & Estoup, 2004; although see Hall et al, 2009), reducing their applicability in demographically dynamic populations (Lowe & Allendorf, 2010).…”

Section: Introductionmentioning

confidence: 99%

Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly

Fountain

Husby

Nonaka

et al. 2017

Evolutionary Applications

View full text Add to dashboard Cite

Dispersal is important for determining both species ecological processes, such as population viability, and its evolutionary processes, like gene flow and local adaptation. Yet obtaining accurate estimates in the wild through direct observation can be challenging or even impossible, particularly over large spatial and temporal scales. Genotyping many individuals from wild populations can provide detailed inferences about dispersal. We therefore utilized genomewide marker data to estimate dispersal in the classic metapopulation of the Glanville fritillary butterfly (Melitaea cinxia L.), in the Åland Islands in SW Finland. This is an ideal system to test the effectiveness of this approach due to the wealth of information already available covering dispersal across small spatial and temporal scales, but lack of information at larger spatial and temporal scales. We sampled three larvae per larval family group from 3732 groups over a six‐year period and genotyped for 272 SNPs across the genome. We used this empirical data set to reconstruct cases where full‐sibs were detected in different local populations to infer female effective dispersal distance, that is, dispersal events directly contributing to gene flow. On average this was one kilometre, closely matching previous dispersal estimates made using direct observation. To evaluate our power to detect full‐sib families, we performed forward simulations using an individual‐based model constructed and parameterized for the Glanville fritillary metapopulation. Using these simulations, 100% of predicted full‐sibs were correct and over 98% of all true full‐sib pairs were detected. We therefore demonstrate that even in a highly dynamic system with a relatively small number of markers, we can accurately reconstruct full‐sib families and for the first time make inferences on female effective dispersal. This highlights the utility of this approach in systems where it has previously been impossible to obtain accurate estimates of dispersal over both ecological and evolutionary scales.

show abstract

Characterizing dispersal patterns in a threatened seabird with limited genetic structure

Cited by 30 publications

References 43 publications

What can genetics tell us about population connectivity?

What can genetics tell us about population connectivity?

Similarity in temporal variation in sex‐biased dispersal over short and long distances in the dark‐eyed junco,Junco hyemalis

Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly

Contact Info

Product

Resources

About