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Quantification of the zygotic barrier between interbreeding taxa using gene flow data
Author(s) -
Bialozyt Ronald,
Niggemann Marc,
Ziegenhagen Birgit
Publication year - 2017
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/oik.03428
Subject(s) - introgression , gene flow , biology , biological dispersal , pollen , hybrid , range (aeronautics) , taxon , population , pollination , evolutionary biology , ecology , hybrid zone , botany , genetics , gene , genetic variation , demography , materials science , sociology , composite material
Hybridization and introgression via interspecific gene flow are common processes in the plant kingdom. The effectiveness of these processes is governed by the strengths of multiple zygotic barriers. These barriers have often been quantified in artificial settings using laborious and time‐consuming hand‐pollination experiments, but their quantification is nonexistent in the landscape. In this study, we utilized gene flow data within a spatially explicit simulation to assess the strengths of zygotic barriers. Our model system consisted of Populus nigra and its hybrid, P. × canadensis , which interbreed under natural conditions. The study population was located in the floodplain of the Eder River in central Germany. Pollen‐mediated introgression rates from hybrid males into the seeds of individual female trees were used as the target pattern using an inverse modeling approach. Simulations that treated pollen from both taxa equally revealed a large discrepancy between the observed and modeled rates of introgression for both taxa. The discrepancy was reduced by introducing a zygotic barrier against the pollen from the hybrid males. The best model outcome values indicated comparably strong zygotic barriers acting against pollen‐mediated introgressive gene flow into the two parental taxa, P. nigra and P. × canadensis . The sensitivity of our model was tested by applying different dispersal functions. Four common probability density functions were used along with a pollen dispersal function that had previously been fitted to gene flow data from the same dataset. The best barrier value was almost independent of the dispersal functions used here. Moreover, it was within the range previously determined in hand‐pollination‐based investigations, validating our model. These data indicate that the inverse modeling approach is a powerful method for quantifying hidden processes, and we discuss its use as a valuable tool for generating new insights into plant mating systems that are relevant to evolutionary biology and risk analyses in conservation efforts.