Aquatic Ecology

Papers
(The H4-Index of Aquatic Ecology is 13. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-01-01 to 2026-01-01.)
ArticleCitations
Correction to: Aluminium in aquatic environments: abundance and ecotoxicological impacts72
Nonnative fish in the Pearl River Delta: a comprehensive analysis of salinity tolerance and potential adaptive habitat distribution in brackish waters33
Using macroinvertebrate functional traits to reveal ecological conditions of two streams in Southwest Nigeria—a case study28
Aluminium in aquatic environments: abundance and ecotoxicological impacts25
Ecosystem type modulates the effects of litter quality and litter identity on decomposition in a tropical riparian environment25
Environmental variability influences the relationship between prawn host size and ectoparasite body size: insights from a long-term stream study23
Differences in feeding ecology of the pink shrimps Penaeus brasiliensis and P. paulensis (Decapoda: Penaeidae) in Brazilian tropical ecosystems19
Ephemeral analysis on microphytobenthos in an estuarine system along the southwest coast of India18
Time for dam rebuilding by the Eurasian beaver17
Lipkea ruspoliana Vogt, 1886 (Cnidaria: Staurozoa) in Portugal: the contribution of citizen science to range extension and taxonomic discussion of rare species16
Measuring beta diversity components and beneficial effects of coarse woody habitat introduction on invertebrate and macrophyte communities in a shallow northern boreal lake; implications for offsettin15
Primary colonization and small-scale dynamics of non-indigenous benthic species: a case study14
Assessment of the diversity, ecology, and spatiotemporal dynamics of the phytoplankton community in the Tono Dam, Ghana13
Environmental descriptors and reproductive modes drive multiple facets of tadpole diversity in subtropical temporary ponds13
Utilizing deep learning to analyze circadian rhythms, color preferences, and agonistic behaviors among color variants of the freshwater crayfish13
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