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Scaling up the phosphorus signal from soil hillslopes to headwater catchments

2012· article· en· W1893328185 on OpenAlexaff
P. M. Haygarth, Trevor Page, Keith Beven, Jim Freer, A. Joynes, Patricia Butler, Gavin Wood, Philip N. Owens

Bibliographic record

VenueFreshwater Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Northern British Columbia
FundersBiotechnology and Biological Sciences Research CouncilUniversity of WarwickCentre for Ecology and HydrologyDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsBiogeochemical cycleEnvironmental scienceSurface runoffHydrology (agriculture)Soil waterDrainage basinGrasslandArable landManureEcologyAgricultureSoil scienceGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Summary 1. Phosphorus (P) transfer from agricultural land to freshwater systems has been studied across many scales and environmental compartments that range from understanding biogeochemical processes in soils and fields, to assessment of localised in‐stream biotic and ecological impacts. 2. This study tackles the challenges of scale when moving from soil hillslope to headwater catchment scale. The focus is on ‘process rules’ derived from reductionist approaches at the relatively fine scale, and exploring the signal and evidence thereof at the headwater catchment scale. 3. The methodology uses new data of P dynamics in agricultural grassland headwater catchments in south‐west England. 4. We found the following: (i) it was not possible to disaggregate an influence of soil (Olsen) P concentration on P export at the larger scale; (ii) there was no clear temporally dynamic relationship between P additions of fertiliser and recycled manure and the resulting P transferred to the headwater scale; however, (iii) ploughing, digging of stream channel and leakage from farm storage all affected the temporal concentration dynamics; and (iv) overall P loss was influenced by higher long‐term history of P inputs, livestock and the domination of hydrologic processes. 5. It is concluded that process rules derived at the finer soil or plot scale cannot always produce a clearly discernable signal when studied at the larger headwater catchment scale.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score1.000

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)0.0010.004

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 head0.012
GPT teacher head0.234
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

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

Citations63
Published2012
Admission routes1
Has abstractyes

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