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Record W2139134005 · doi:10.1139/f09-065

The influence of land use on stream biofilm nutrient limitation across eight North American ecoregions

2009· article· en· W2139134005 on OpenAlexvenueno aff
Laura T. Johnson, Jennifer L. Tank, Walter K. Dodds

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
FundersGeneral Electric
KeywordsNutrientEnvironmental scienceEcoregionSTREAMSEcosystemEcologyPhosphorusNutrient cycleAutotrophLand useBiologyEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

Nutrient diffusing substrata were used to determine the influence of inorganic nitrogen (N) and phosphorus (P) availability on community respiration (CR), gross primary production (GPP), and chlorophyll a (chl a) on inorganic and organic substrata. We incubated substrata in nine streams each in a total of eight ecoregions (n = 72 streams) located in a range of native vegetation, agriculture, and urban land-use types. On organic substrata, CR was nutrient-limited in 94% of reference streams but showed significant nutrient limitation in only 60% and 65% of agricultural and urban streams, respectively. The relative magnitude of nutrient limitation for CR on organic substrata decreased with increasing percent modified land use in the basin (agriculture + urban). On inorganic and organic substrata, GPP and chl a were rarely nutrient-limited across all ecoregions and land-use types, although the magnitude of nutrient limitation increased with increasing light availability. The effect of human land use on nutrient limitation of biofilm CR, GPP, and chl a was influenced by ecoregion, yet heterotrophic biofilms were consistently most sensitive to nutrient enrichment across ecoregions. Both heterotrophic and autotrophic biofilm constituents should be considered to fully understand stream ecosystem responses to nutrient enrichment.

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 score0.331
Threshold uncertainty score0.993

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 studies0.0010.002
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 head0.017
GPT teacher head0.203
Teacher spread0.187 · 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

Citations118
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFreshwater macroinvertebrate diversity and ecologyFrench-language works237,207