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Data from: Genetic diversity in a long-lived mammal is explained by the past’s demographic shadow and current connectivity

Lehnen, Lisa, University of Greifswald
Jan, Pierre-Loup, INRAE
Besnard, Anne-Laure, INRAE
Fourcy, Damien, INRAE
Kerth, Gerald, University of Greifswald
Biedermann, Martin, Verein für Umweltmanagement und Nachhaltigkeit in Finanzinstituten
Nyssen, Pierrette, Plecotus
Schorcht, Wigbert, NACHTaktiv
Petit, Eric, INRAE, https://orcid.org/0000-0001-5058-5826
Puechmaille, Sébastien, University of Greifswald, https://orcid.org/0000-0001-9517-5775
lisa.lehnen@posteo.de, pierreloup.jan@gmail.com, anne-laure.besnard@inrae.fr, damien.fourcy@inrae.fr, gerald.kerth@uni-greifswald.de, martin.biedermann@gmx.de, pierrette.nyssen@gmail.com, wigbert.schorcht@web.de, eric.petit@inrae.fr, sebastien.puechmaille@umontpellier.fr
Published Sep 07, 2021 on Dryad. https://doi.org/10.5061/dryad.27q46m2

Cite this dataset

Lehnen, Lisa et al. (2021). Data from: Genetic diversity in a long-lived mammal is explained by the past’s demographic shadow and current connectivity [Dataset]. Dryad. https://doi.org/10.5061/dryad.27q46m2

Abstract

Within-species genetic diversity is crucial for the persistence and integrity of populations and ecosystems. Conservation actions require an understanding of factors influencing genetic diversity, especially in the context of global change. Both population size and connectivity are factors greatly influencing genetic diversity; the relative importance of these factors can however change through time. Hence, quantifying the degree to which population size or genetic connectivity are shaping genetic diversity, and at which ecological time scale (past or present), is challenging, yet essential for the development of efficient conservation strategies. In this study, we estimated the genetic diversity of 42 colonies of Rhinolophus hipposideros, a long-lived mammal vulnerable to global change, sampling locations spanning its continental northern range. We present an integrative approach that disentangles and quantifies the contribution of different connectivity measures in addition to contemporary colony size and historic bottlenecks in shaping genetic diversity. In our study, the best model explained 64% of the variation in genetic diversity. It included historic bottlenecks, contemporary colony sizes, connectivity and a negative interaction between the latter two. Contemporary connectivity explained most genetic diversity when considering a 65 km radius around the focal colonies, emphasizing the large geographic scale at which the positive impact of connectivity on genetic diversity is most profound and hence the minimum scale at which conservation should be planned. Our results highlight that the relative importance of the two main factors shaping genetic diversity varies through time, emphasizing the relevance of disentangling them to ensure appropriate conservation strategies.

Usage notes

Microsatellite genotypes

Csv file containing distinct (consensus) genotypes used in the analysis. ID: Population names as in Table 1 and Fig. S7. Columns two to nine: names of microsatellite loci. Each allele is coded by three digits, resulting in a six digit code per locus per sample.
Genotypes.csv
 

Genetic diversity and associated explanatory variables

The file "Data_Table_Genetic_diversity_in_a_long-lived_mammal.csv" is a data table with headers that contains genetic and connectivity data on R. hipposideros maternity colonies. Each record (=line) corresponds to a different R. hipposideros maternity colony. The variables on each line include the following:
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Variable                              Column(s)          Type

------------------------------

PopID                                         1                Character

Hs                                               2                Numeric

AllelicRichness                           3               Numeric
BayesFactorMSVAR                  4                Numeric

BottleneckStatus                         5                Logical

NearestNeighbour                       6                Numeric

NbIndXXXXkm2                       7-68           Integer
NbColXXXXkm2                       69-130      Integer

WeightedNumberofIndividual     131           Numeric

ForestAreaXXXXkm2                 132-193    Numeric

ForestPerimeterXXXXkm2         194-255     Numeric
------------------------------

Each XXXX in the variable name corresponds to an integer between 100 and 6000 (see below). These variables have the following definitions:

PopID                           is the bat colony identification code

Hs                                            is the expected heterozygosity of the bat colony
AllelicRichness                       is the allelic richness of the colony corrected for sample size
BayesFactorMSVAR               is the Bayes Factor obtained through MSVAR computation
BottleneckStatus                      is the result of MSVAR computation as a logical (TRUE : Bottlenecked population, FALSE : Non-bottlenecked)
NearestNeighbour                    is the distance to the nearest bat colony, in meters.
NbIndXXXXkm2                    is the number of R. hipposideros from other maternity colonies contained in a buffer centered on the colony within an area of XXXX km2.
NbColXXXXkm2                    is the number of others R. hipposideros maternity colonies contained in a buffer centered on the colony within an area of XXXX km2.

WeightedNumberofIndividual  is the number of R. hipposideros from other maternity colonies weighted by the negative exponential dispersal kernel
ForestAreaXXXXkm2              is the area (m²) of mixed and deciduous forest contained in a buffer centered on the colony within an area of XXXX km2.
ForestPerimeterXXXXkm2      is the perimeter (m) of mixed and deciduous forest patches contained in a buffer centered on the colony within an area of XXXX km2.


Further details and explanations about the origin and computation of these variables are provided in the Materials & Methods section of the paper "Genetic diversity in a long-lived mammal is explained by the past’s demographic shadow and current connectivity" by L. Lehnen, P.-L. Jan, A.-L. Besnard, D. Fourcy, G. Kerth, M. Biedermann, P. Nyssen, W. Schorcht, E. J. Petit, S.J. Puechmaille.

For additional information, please send an e-mail to pierreloup.jan@gmail.com

Funding

RESPONSE exchange grant, Award: (awarded to PLJ)

Deutsche Forschungsgemeinschaft, Award: RTG 2010 Research Training Program (German Science

PROCOPE/DAAD, Award: project number 57211773 (awarded to SJP)

PROCOPE/PHC, Award: project number 35454SB (awarded to EJP)

Office National des Forets

Location

Austria
Czech Republic
Belgium
Western Palearctic
Europe
France
Germany