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Record W4414169829 · doi:10.1007/s10750-025-05960-9

Impacts of atmospheric nitrogen deposition and lake browning on planktonic biomass ratios and nutrient accumulation in northern lakes

2025· article· en· W4414169829 on OpenAlexaff
Ann‐Kristin Bergström, Irena F. Creed, Anders Jönsson, Peter D. F. Isles, Erik Geibrink, Danny C. P. Lau

Bibliographic record

VenueHydrobiologia · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Toronto
FundersVetenskapsrådetCarl Tryggers Stiftelse för Vetenskaplig ForskningSvenska Forskningsrådet FormasParkinson’s Disease Foundation of India
KeywordsZooplanktonSestonPlanktonCopepodDominance (genetics)NutrientPhytoplanktonBiomass (ecology)

Abstract

fetched live from OpenAlex

Abstract Nitrogen (N) deposition and dissolved organic carbon (DOC) levels in northern lakes are shifting due to climate change and atmospheric deposition declines, altering the availability of light and nutrients in these ecosystems. Yet their impacts on the biomass, stoichiometry, and the structure of planktonic food chains remain uncertain. We therefore investigated zooplankton-to-seston biomass ratios (Z:S in C, N, and P) across 34 Swedish lakes with varying N deposition, DOC concentration, and fish predation control. Mean Z:S values were 2.9% for C, 7.5% for N, and 7.7% for P, with substantial regional variation. Z:S ratios were higher in lakes with lower atmospheric N deposition, improved seston quality, and greater calanoid copepod dominance in zooplankton. The strong link between zooplankton stoichiometry and community composition underscores the role of calanoids in regulating nutrient dynamics in northern lakes. Fish predation reduced zooplankton biomass but did not significantly alter Z:S ratios or zooplankton community composition. Meanwhile, increasing DOC dampened the higher Z:S in low N deposition lakes by reducing calanoid dominance and promoting more uniform zooplankton assemblages. Our findings suggest that lake browning counteracts the expected increase in Z:S ratios associated with recovery from atmospheric N deposition, potentially altering nutrient transfer in lake food webs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.227
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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