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Record W1966172300 · doi:10.3390/f4010137

Early Effects of Afforestation with Willow (Salix purpurea, “Hotel”) on Soil Carbon and Nutrient Availability

2013· article· en· W1966172300 on OpenAlexafffundabout
Joels Ens, R. Farrell, Nicolas Bélanger

Bibliographic record

VenueForests · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsUniversité du Québec à MontréalUniversity of Saskatchewan
FundersCanadian Forest ServiceNatural Sciences and Engineering Research Council of CanadaSponsored Research and Industrial ConsultancyU.S. Forest ServiceMinistry of Agriculture - Saskatchewan
KeywordsWillowNutrientAfforestationBiomass (ecology)Environmental scienceSoil waterAgronomySalicaceaeNutrient cycleSoil carbonWoody plantAgroforestryBotanyBiologyEcologySoil science

Abstract

fetched live from OpenAlex

Willow (Salix spp.) is currently being researched as a source of biomass energy in Canada. However, it is not certain whether afforestation with willow plantations will enhance or diminish soil C storage and nutrient availability. Trees are known to have pronounced effects on biologically mediated nutrient cycling processes which can increase nutrient availability, but willows are known to be nutrient demanding. In this paper, the net effect of plantation establishment is examined at nine sites across the prairie and southern Ontario regions of Canada. Carbon, N, P, K, Ca and Mg levels in soils and harvestable biomass were compared between willow plantations and paired reference sites at the end of the first three-year rotation. Soils were depleted in total C (−2.22 mg·g−1, p < 0.05), inorganic N (−3.12 μg·N·g−1, p < 0.10), exchangeable K (−0.11 cmolc·kg−1, p < 0.10) and leachable P (−0.03 mg·g−1, p < 0.10). Exchangeable Ca was found to be consistently depleted only at the 20–40 depth. Depletion of soil K was more heavily influenced by disturbance, whereas soil N was directly affected by willow N uptake. Sites with greater growth and biocycling stabilized soil P 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.234

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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

Citations31
Published2013
Admission routes3
Has abstractyes

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