Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

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25Despite the ecological importance of long-distance dispersal in insects, its underlying mechanistic 26 basis is poorly understood. One critical question is how insects interact with the wind to increase 27 their travel distance as they disperse. To gain insight into dispersal using a species amenable to 28 further investigation using genetic tools, we conducted release-and-recapture experiments in the 29Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically-baited traps 30 in a 1 km-radius ring around the release site, equipped with machine vision systems that captured 31 the arrival times of flies as they landed. In each experiment, we released between 30,000 and 32200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify 33 the influence of wind on flies' dispersal behavior. Our results confirm that even tiny fruit flies could 34 disperse ~15 km in a single flight in still air, and might travel many times that distance in a 35 moderate wind. The dispersal behavior of the flies is well explained by a model in which animals 36 maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along 37 their body axis, and allow the wind to advect them sideways. The model accounts for the 38 observation that flies actively fan out in all directions in still air, but are increasingly advected 39 downwind as winds intensify. In contrast, our field data do not support a Lévy flight model of 40 dispersal, despite the fact that our experimental conditions almost perfectly match the core 41 assumptions of that theory. 42 Significance Statement 43Flying insects play a vital role in terrestrial ecosystems, and their decline over the past few 44 decades has been implicated in a collapse of many species that depend upon them for food. By 45 dispersing over large distances, insects transport biomass from one region to another and thus 46 their flight behavior influences ecology on a global scale. Our experiments provide key insight into 47 the dispersal behavior of insects, and suggest that these animals employ a single algorithm that 48 is functionally robust in both still air and under windy conditions. Our results will make it easier to 49 study the ecologically important phenomenon of long-distance dispersal in a genetic model 50 organism, facilitating the identification of cellular and genetic mechanisms. 51 52

The targeted LipidXplorer method implemented using common phenolic fragmentation patterns, was found to be able to annotate more phenolics than MZMine® that is based on automated queries on the available databases. Additionally, screening for ascarosides, natural products with unrelated structures to plant phenolics collected from the nematode Caenorhabditis elegans, demonstrated the specificity of this method by cross-testing both groups of chemicals in both plants and nematodes.