Interannual changes in δ15N baseline in a lake–swamp–river food web: effects of summer precipitation in West Siberian forest steppe View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2020-08-09

AUTHORS

Gen Kanaya, Natalia I. Yurlova, Elena N. Yadrenkina, Jun-ichi Okano, Shuichi Shikano

ABSTRACT

Frequency and intensity of precipitation events can alter hydrological conditions of lotic systems and material inflow from the catchment. In this study, interannual changes in food web structure were investigated in a lake–swamp–river system in the semi-arid West Siberian forest-steppe region using carbon and nitrogen stable isotope ratios (δ13C and δ15N). The δ15N signatures of aquatic producers and consumers including zooplankton, benthic invertebrates, and fish sharply increased (up to 7.2‰ in range) in 2009 under high summer precipitation. This would reflect the inflow of 15N-rich nutrients accumulated in the catchment through natural and anthropogenic activities, e.g., sewage, livestock farming, evaporation, and/or microbial denitrification. In 2010, benthic producers including epiphytes and macrophytes were more 13C-enriched, which is likely due to limited supply of dissolved inorganic carbon (DIC) under water stagnation, leading to a large isotopic fractionation during photosynthesis. However, 13C-enrichments in the benthic producers were not reflected to those of aquatic consumers in the habitat. Interannual changes in δ13C of particulate organic matter (POM; a proxy of phytoplankton) were reflected to those of zooplankton, benthic invertebrates, and fish fry, suggesting the trophic importance of autochthonous phytoplankton in the system. These findings suggest that occasional precipitation events in semi-arid forest-steppe regions can modify nutrient flux from the catchment, leading to changes in δ15N baseline in the lotic food web. More... »

PAGES

217-233

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10533-020-00694-3

DOI

http://dx.doi.org/10.1007/s10533-020-00694-3

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https://app.dimensions.ai/details/publication/pub.1130001287


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