Ecological disruptive selection acting on quantitative loci can drive sympatric speciation is a research paper published in npj Systems Biology and Applications (2024). On theSindex it has a DataRank of 0.118. It has been cited 1 time, with 1 citing works in its 1-hop citation network.
AbstractThe process of speciation generates biodiversity. According to the null model of speciation, barriers between populations arise in allopatry, where, prior to biology, geography imposes barriers to gene flow. On the other hand, sympatric speciation requires that the process of speciation happen in the absence of a geographical barrier, where the members of the population have no spatial, temporal barriers. Several attempts have been made to theoretically identify the conditions in which speciation can occur in sympatry. However, these efforts suffer from several limitations. We propose a model for sympatric speciation based on adaptation for resource utilization. We use a genetics-based model to investigate the relative roles of prezygotic and postzygotic barriers, from the context of ecological disruptive selection, sexual selection, and genetic architecture, in causing and maintaining sympatric speciation. Our results show that sexual selection that acts on secondary sexual traits does not play any role in the process of speciation in sympatry and that assortative mating based on an ecologically relevant trait forces the population to show an adaptive response. We also demonstrate that understanding the genetic architecture of the trait under ecological selection is very important and that it is not required for the strength of ecological disruptive selection to be very high in order for speciation to occur in sympatry. Our results provide an insight into the kind of scenarios in which sympatric speciation can be demonstrated in the lab.
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Base Score Contribution
0.104
From this paper's citation signal
Citation Network Contribution
0.0135
From 1 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 88% comes from its base citations and 12% from the citation network (1 citing paper contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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