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 "-".