ArticlePloS one2025
Shredder species identity over diversity: Insights into litter decomposition in ponds.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Many freshwater ecosystems rely on the decomposition of organic matter as a key process for nutrient cycling and energy flow. Small lentic freshwater ecosystems, such as ponds, often derive a large amount of energy from allochthonous detritus due to their close connection with the terrestrial environment. However, the process of leaf litter decomposition in ponds remains poorly understood. We conducted a microcosm experiment in a pond environment to investigate intra- and inter-specific variation in organic matter processing by three shredders (Tipula sp., Sericostoma sp. and Gammarus fossarum) and to assess the effects of shredder community characteristics on the mass loss of black alder (Alnus glutinosa) leaf litter. We developed a novel approach to quantify functional traits directly related to litter processing. Detailed gut content analysis revealed significant inter- and intra-specific variation in the organic matter particles ingested by individual shredder taxa. Our results showed that neither taxonomic nor functional diversity reliably predicts leaf litter decomposition rates in ponds. Instead, the keystone shredder Sericostoma showed a pronounced effect on decomposition rates driven by their unique feeding behaviour and density-dependent shifts in particle size preferences. These findings highlight the importance of a detailed understanding of species-specific functional traits and behaviour in shaping ecosystem processes, as the role of keystone species can outweigh the contributions of overall diversity measures in driving ecosystem processes.
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