Long term hybrid zone dynamics in red- and yellow-bellied toads estimated from environmental data at allopatric and parapatric scales
Arntzen, J. W.
Show abstract
AimAims of the study are to identify environmental parameters underlying the mutual distribution in a species pair engaged in a long and winding hybrid zone, to reconstruct pattern and process of species range developments following the Last Glacial Maximum (LGM), and to open research lines for the study of hybrid zone dynamics in a model system. LocationCentral and Eastern Europe, Croatia. TaxonThe red-bellied toad Bombina bombina and the yellow-bellied toad Bombina variegata. MethodsThe construction of two-species distribution models (TSDM) at allopatric and parapatric scales and the reconstruction of geographical clines across a low mountain range, in transects with and without extensive lowland forest cover. ResultsIt is confirmed that B. variegata is a mountain species and B. bombina is a lowland dweller, with hybrid populations in between, but traditional distribution models are oversimplistic. Environmental parameters selected with TSDM at both allopatric and parapatric scales are elevation and forestation. At transects with lowland forestation hybrid zones are positioned further away from elevated areas than in the absence of lowland forest. Bombina variegata stronghold areas are characterized not just by elevation but also by forestation. Out of 17 historical Bombina studies that are evaluated for promise in the study of hybrid zone dynamics several qualify for extended research. ConclusionsThe overall species mosaic with isolated mountain strongholds suggests that B. variegata was displaced from the surrounding lowlands upon its counterparts northward advance, following post-LGM climate amelioration. Initial hybrid zone formation will have been along the lower Danube River, distant from present-day positions. Because lowland forestation constitutes a buffering effect to species replacement, current hybrid zones may not have reached equilibrium conditions, depending on deforestation history and other characters of the landscape. Future genetic work on B. variegata enclaves may shed light on the pattern and process of hybrid zone movement and species replacement, though timing and the size and environmental signature of the enclaves will affect genetic introgression in ways that may be hard to disentangle.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Holocene plant diversity dynamics shows a distinct biogeographical pattern in temperate Europe 95%
- Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains 94%
- Population dynamics of Amazonian floodplain forest species support spatial variation on genetic diversity but not range expansions through time 93%
Similar papers in this journal
- Latitudinal trends in genetic diversity and distinctiveness of Quercus robur rear edge forest remnants call for new conservation priorities 94%
- Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany 94%
- The genetic consequences of population marginality: a case study in maritime pine 93%
Similar papers in this journal
- Neglected predatory insects trigger potential Key Biodiversity Areas in threatened coastal habitats 93%
- Impacts of oil palm plantations expansion on the distribution of terrestrial mammals in South-East Asia 92%
- Taxonomic, geographic, and phylogenetic patterns in the conservation status of the squamate reptiles (Reptilia: Squamata) of Colombia 92%
Similar papers in this journal
- Spatial conservation planning of forest genetic resources in a Mediterranean multi-refugial area 95%
- Spatial patterns of evolutionary diversity in Cactaceae show low ecological representation within protected areas 94%
- Defining endemism levels for biodiversity conservation: tree species in the Atlantic Forest hotspot 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.