PubMed · 1138471
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G Paerregaard. 1975-06-02. [Editorial: Suicidal behaviour].. https://pubmed.ncbi.nlm.nih.gov/1138471/
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Genetic variation in behavioral traits allows organisms to respond and adapt to environmental challenges. Genetic variation in behavior is often affected by many genes and thus has a complex genetic basis. Inversions, the reorientation of genes along the chromosome, tightly link genetic variants together because they suppress recombination. Therefore, inversions are believed to have a major impact on phenotypic variation because they combine the effects of multiple genes, which can pleiotropically alter multiple aspects of behavior. This study investigates how the inversion In(2L)t, found in Drosophila melanogaster populations around the world, impacts different aspects of behavior in an environment-sensitive manner. We test the activity, foraging, and startle-induced behavior of flies with different In(2L)t genotypes across sex and temperatures. We observe that Drosophila homozygous for In(2L)t sleep less frequently, spend more time away from a food source, and have a longer duration of startle response. Additionally, the impacts of In(2L)t on aspects of behavior can be sex-specific and are largely consistent across temperatures. Taken together, our research demonstrates that inversions can regulate aspects of behavior, and suggests hypotheses explaining the distribution of In(2L)t across space and time.
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Many human social phenomena, such as cooperation, the growth of settlements, traffic dynamics and pedestrian movement, appear to be accessible to mathematical descriptions that invoke self-organization. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are, and whether optimal path systems can be predicted for urban planning. We use an 'active walker' model that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical, chemical and biological systems. We find that our model is able to reproduce many of the observed large-scale spatial features of trail systems.