MétaCan
Menu
Back to cohort

Nutrient recycling by fish in streams along a gradient of agricultural land use

2010· article· en· W1922366044 on OpenAlexaffabout
Henry F. Wilson, Marguerite A. Xenopoulos

Bibliographic record

VenueGlobal Change Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsTrent University
Fundersnot available
KeywordsNutrientEcosystemEnvironmental scienceNutrient cycleSTREAMSRiparian zoneAquatic ecosystemEcologyBiomass (ecology)WatershedBiologyHabitat

Abstract

fetched live from OpenAlex

Nutrient recycling is an essential ecosystem process provided by animals. In many aquatic systems, fish have been identified as important in ecosystem nutrient recycling; however, this importance can vary widely between systems. The factors controlling intersystem variation in animal-mediated nutrient cycling have rarely been examined and as such it remains unclear what impact human landscape changes will have upon these processes. Here we examined rates of nutrient recycling for temperate stream fish assemblages along a gradient of agricultural land use (proportion cropland in the watershed: 1–59%). We quantified nutrient excretion rates of both ammonium–N (NH4+–N) and phosphate (as soluble reactive phosphate: SRP) for fish assemblages at eight streams in southern Ontario, Canada with species-specific excretion measurements and quantitative assemblage sampling. For both nutrients, total assemblage excretion exhibited a strong positive relationship with riparian cropland. The distance required for fish assemblages to turn over ambient nutrient pools was shorter for cropland systems, indicating that the relative importance of excreted nutrients was higher in these systems. Based on measured uptake rates of NH4+–N in two streams (one higher cropland and one low cropland) and on modeled uptake rates for all streams, the proportion of ecosystem demand that can be satisfied by excretion is generally higher in the more agricultural streams. These patterns appear to be driven largely by disproportionate increases in fish assemblage biomass with increasing stream nutrient concentrations.

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 score0.006
Threshold uncertainty score0.997

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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations46
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueGlobal Change BiologySame topicSoil and Water Nutrient DynamicsFrench-language works237,207