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3 June 2019 Environmental Variables Influencing Chironomid Assemblages (Diptera: Chironomidae) in Lowland Rivers of Central Poland
Joanna Leszczyńska, Maria Grzybkowska, Łukasz Głowacki, Małgorzata Dukowska
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Chironomids (Diptera: Chironomidae) are a family of dipterans with a global distribution. Owing to their great functional diversity and ability to adapt to a wide range of environmental conditions, they often dominate in freshwater macroinvertebrate communities, playing a key role in the cycling of organic matter and the flow of energy in aquatic ecosystems. Our aim was to analyze the structure of chironomid assemblages and identify the environmental factors, including current velocity, river width, water depth, water temperature, dissolved oxygen, percentage of substrate covered by vascular plants, inorganic bottom substrate, and quantity of benthic (BPOM) and transported (TPOM) particulate organic matter, that underpin variation in species richness across a set of lowland rivers in central Poland, differing by stream order and abiotic parameters. Using an Information The oretic Approach, we formulated a set of alternative models based on previously published work, with models fitted in a Bayesian framework using Integrated Nested Laplace Approximation.The species richness of chironomids increased with river order, achieving a maximum in third and fourth order rivers, but decreased at higher orders.The best-fitting models included a positive effect of inorganic substrate index and dissolved oxygen on chironomid species richness. The quality structure of chironomid assemblages reflected the assumptions of the River Continuum Concept showing that species richness was under the influence of factors operating at both a micro- (inorganic bottom substrate) and macro-scale (dissolved oxygen).

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Joanna Leszczyńska, Maria Grzybkowska, Łukasz Głowacki, and Małgorzata Dukowska "Environmental Variables Influencing Chironomid Assemblages (Diptera: Chironomidae) in Lowland Rivers of Central Poland," Environmental Entomology 48(4), 988-997, (3 June 2019).
Received: 30 December 2018; Accepted: 24 April 2019; Published: 3 June 2019

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Bayesian inference
habitat parameters
riverine macroinvertebrates
species richness
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