10.5061/DRYAD.B2RBNZS9R
Unglaub, Bianca
0000-0003-4959-7373
Leipzig University
Cayuela, Hugo
Université Laval
Schmidt, Benedikt R.
0000-0002-4023-1001
University of Zurich
Preißler, Kathleen
0000-0003-2841-8575
Leipzig University
Glos, Julian
University of Hamburg
Steinfartz, Sebastian
Leipzig University
Context-dependent dispersal determines relatedness and genetic structure
in a patchy amphibian population
Dryad
dataset
2021
Deutsche Forschungsgemeinschaft
https://ror.org/018mejw64
STE 1130/7-1
2021-07-30T00:00:00Z
2021-07-30T00:00:00Z
en
485198 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Dispersal is a central process in ecology and evolution with far reaching
consequences for the dynamics and genetics of spatially structured
populations (SSPs). Individuals can adjust their decisions to disperse
according to local fitness prospects, resulting in context-dependent
dispersal. By determining dispersal rate, distance, and direction, these
individual-level decisions further modulate the demography, relatedness,
and genetic structure of SSPs. Here, we examined how context-dependent
dispersal influences the dynamics and genetics of a Great Crested Newt
(Triturus cristatus) SSP. We collected capture-recapture data of 5564
individuals and genetic data of 950 individuals across a SSP in northern
Germany. We added genetic data from six sites outside this SSP to assess
genetic structure and gene flow at a regional level. Dispersal rates
within the SSP were high but dispersal distances were short. Dispersal was
context-dependent: individuals preferentially immigrated into high-quality
ponds where breeding probabilities were higher. The studied SSP behaved
like a patchy population, where subpopulations at each pond were
demographically interdependent. High context-dependent dispersal led to
weak but significant spatial genetic structure and relatedness within the
SSP. At the regional level, a strong hierarchical genetic structure with
very few first-generation migrants as well as low effective dispersal
rates suggest the presence of independent demographic units. Overall, our
study highlights the importance of habitat quality for driving
context-dependent dispersal and therefore demography and genetic structure
in SSPs. Limited capacity for long-distance dispersal seems to increase
genetic structure within a population and leads to demographic isolation
in anthropogenic landscapes.
Demographic Data (CMR and Presence/Absence Data): We surveyed 33 water
bodies using mark-recapture methods for the presence, demography and
reproduction of crested newts between 2012 and 2014. Newts were captured
during two capture sessions (cs) per year, one early (April/May) and one
late (June/July) in the breeding season. Every capture session thereby
consisted of three consecutive capture events in intervals of two days.
Within the context of a presence/absence analysis, all sites were surveyed
for one more day in late July/early August in order to detect larvae. If a
pond dried out and was therefore not surveyed during a capture session,
such an event was treated as a missing observation. Newts were captured
using Ortmann’s funnel traps which were evenly distributed along the
shoreline of a pond. The number of traps deployed per capture event varied
according to pond perimeter (one trap per 10m shoreline), ranging from one
to 27 traps. For individual recognition of newts during the CMR study, we
used photographs of the ventral side of an individual which provides a
natural marking in form of a highly variable but individually unique and
stable color pattern through the time. Recaptured individuals were
identified automatically by the software AmphIdent. Microsatellite
Genotypes: Tissue samples were taken from seven sampling sites by
puncturing the tails of captured great crested newts (Triturus cristatus)
using micro haematocrit capillary tubes (Carl Roth, Ø 1.6 mm) and were
then stored in 80% ethanol. Total genomic DNA was extracted using the
sodium dodecyl sulfate (SDS)-proteinase K/ Phenol-Chloroform extraction
method. Genomic DNA was stored in Tris-EDTA buffer (10 mM Tris-HCl, 0.1 mM
EDTA, pH 8.0) and used for all subsequent reactions. Each individual
sample was mugenotyped for 17 microsatellite loci. Primers were combined
in three multiplex mixes (Drechsler et al., 2013). 10 µl Type-it Multiplex
PCRs (Qiagen) containing 1 µl of genomic DNA were performed. The PCR
profile was as follows: (1) 5 min at 95°C, (2) 30 s at 94°C, (3) 90 s at
an annealing temperature of 60°C, (4) 60 s at 72°C, (5) return to step 2
for 30 times, (6) 30 min at 60°C. Obtained PCR products were diluted with
50-200 μl water depending on the strength of obtained PCR products. 1 µl
of each diluted multiplex reaction was added to 20 μl of Genescan 500-LIZ
size standard (Applied Biosystem) and then run on an ABI 3730 96-capillary
or an ABI 3130 16-capillary automated DNA-sequencer. Allele scoring of
microsatellite loci was performed using Genemarker software (SoftGenetics
version 1.95).
Microsatellite Genotypes: Missing values are coded "-9".
Presence/Absence Data: Missing values are coded "-".