Browsing by Author "Shen Y"

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    Genomic signatures of cooperation and conflict in the social amoeba
    (1/01/2015) Ostrowski EA; Shen Y; Tian X; Sucgang R; Jiang H; Qu J; Katoh-Kurasawa M; Brock DA; Dinh C; Lara-Garduno F; Lee SL; Kovar CL; Dinh HH; Korchina V; Jackson LR; Patil S; Han Y; Chaboub L; Shaulsky G; Muzny DM; Worley KC; Gibbs RA; Richards S; Kuspa A; Strassmann JE; Queller DC
    © 2015 Elsevier Ltd. Summary Cooperative systems are susceptible to invasion by selfish individuals that profit from receiving the social benefits but fail to contribute. These so-called "cheaters" can have a fitness advantage in the laboratory, but it is unclear whether cheating provides an important selective advantage in nature. We used a population genomic approach to examine the history of genes involved in cheating behaviors in the social amoeba Dictyostelium discoideum, testing whether these genes experience rapid evolutionary change as a result of conflict over spore-stalk fate. Candidate genes and surrounding regions showed elevated polymorphism, unusual patterns of linkage disequilibrium, and lower levels of population differentiation, but they did not show greater between-species divergence. The signatures were most consistent with frequency-dependent selection acting to maintain multiple alleles, suggesting that conflict may lead to stalemate rather than an escalating arms race. Our results reveal the evolutionary dynamics of cooperation and cheating and underscore how sequence-based approaches can be used to elucidate the history of conflicts that are difficult to observe directly.
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    UAV Assisted Livestock Distribution Monitoring and Quantification: A Low-Cost and High-Precision Solution
    (MDPI AG, 29/09/2023) Ji W; Luo Y; Liao Y; Wu W; Wei X; Yang Y; Shen Y; Ma Q; He X; Yi S; Sun Y
    Grazing management is one of the most widely practiced land uses globally. Quantifying the spatiotemporal distribution of livestock is critical for effective management of livestock-grassland grazing ecosystem. However, to date, there are few convincing solutions for livestock dynamic monitor and key parameters quantification under actual grazing situations. In this study, we proposed a pragmatic method for quantifying the grazing density (GD) and herding proximities (HP) based on unmanned aerial vehicles (UAVs). We further tested its feasibility at three typical household pastures on the Qinghai-Tibetan Plateau, China. We found that: (1) yak herds grazing followed a rotational grazing pattern spontaneously within the pastures, (2) Dispersion Index of yak herds varied as an M-shaped curve within one day, and it was the lowest in July and August, and (3) the average distance between the yak herd and the campsites in the cold season was significantly shorter than that in the warm season. In this study, we developed a method to characterize the dynamic GD and HP of yak herds precisely and effectively. This method is ideal for studying animal behavior and determining the correlation between the distribution of pastoral livestock and resource usability, delivering critical information for the development of grassland ecosystem and the implementation of sustainable grassland management.