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David A. Lytle

Researcher at Oregon State University

Publications -  83
Citations -  6915

David A. Lytle is an academic researcher from Oregon State University. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 38, co-authored 82 publications receiving 6006 citations. Previous affiliations of David A. Lytle include University of Chicago & Cornell University.

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Adaptation to natural flow regimes

TL;DR: Here, three modes of adaptation are identified that plants and animals use to survive floods and/or droughts and the rate of evolution in response to flow regime alteration remains an open question.
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Theory, methods and tools for determining environmental flows for riparian vegetation: riparian vegetation‐flow response guilds

TL;DR: In this article, the authors propose to organize riparian plants into non-phylogenetic groupings of species with shared traits that are related to components of hydrologic regime: life history, reproductive strategy, morphology, adaptations to fluvial disturbance and adaptations to water availability.
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The role of dispersal in river network metacommunities: Patterns, processes, and pathways

TL;DR: A conceptual model is developed that predicts that the explanatory power of the river network peaks in mesic systems for obligate aquatic dispersers, and proposes directions of future avenues of research, including the use of manipulative field and laboratory experiments that test metacommunity theory in river networks.
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Hydrologic regimes and riparian forests: a structured population model for cottonwood

TL;DR: In this article, the authors developed a stochastic, density-dependent population model for the Yampa River in the western United States and found that fertility of seedlings and younger trees followed a boom-bust cycle driven by high flood mortalities while reproductive adult abundance fol- lowed a less erratic 5-15-yr periodicity driven by multiyear sequences of flows favorable to stand recruitment.
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Seasonality and predictability shape temporal species diversity.

TL;DR: This framework provides tools for examining trends at a variety of temporal scales, seasonal and beyond, and predicted that temporal beta diversity should be maximized in highly predictable and highly seasonal climates, and that low degrees of seasonality, predictability, or both would lower diversity in characteristic ways.