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Impactos das doses e do parcelamento da fertilização na produtividade, lixiviação e ciclagem de nutrientes em plantações de eucalipto

2011· dissertation· pt· W1498482029 on OpenAlexaff
Paulo Henrique Müller da Silva

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsImpact
Fundersnot available
KeywordsNutrientLeaching (pedology)FertilizerEnvironmental scienceEucalyptusSowingPlant litterAgronomyNutrient cycleHuman fertilizationBiomass (ecology)Soil fertilitySoil waterBiologyBotanyEcologySoil science

Abstract

fetched live from OpenAlex

Impacts of doses and split fertilization on productivity, leaching and nutrient cycling in eucalypt plantationIt is occurring, in Brazil, the expansion of planted forest area with species that belong to the Eucalyptus genus, one of the reasons is the high biomass productivity resulting from the research and the operational improvements that have been implemented during the last decades.In several field experiments, has been observed an increase of eucalypts growth by using a higher amount of fertilizers.But excessive or inappropriate application of fertilizers may generate the fertilizer waste and nutrients leaching that may contaminate soil and watertable.The objective of this study was to evaluate the effect of fertilization doses in the biomass production and nutrient cycling from the eucalypt plantation, as well as evaluating the N and K leaching in the soil after the application of split and single dose of N and K fertilization.The experiment was set up in the Anhembi city (State of São Paulo), and it was constituted by five treatments with doses of fertilizers and N and K in split application (4 times) and also a treatment with a single dose of N and K application, 3 months after planting.It was evaluated the wood volume, root and shoot biomass, concentrations and stocks of nutrients in eucalypts biomass (mineralomass), the efficiency of nutrient use, the nutrient transference from the canopy to the soil through litter production (leaf-fall), internal nutrients cycling (biochemical cycle), the water flow and leaching of N and K in the soil at the depths of 20 and 90 cm.The eucalypts responded positively to the increased fertilization doses, especially in the first year, with higher productivity (height, DBH and biomass).Treatment with the highest dose for 24 months produced 105 tons ha -1 of biomass, 48% higher than the treatment without fertilization, with only 71 tons ha -1 .However the effect of higher doses was more evident at an early stage of tree growth, up to 12 months of age.However, the difference decrease over time, and at 24 months there were not significant differences among the treatments with fertilization application.Fertilization also resulted in higher nutrients accumulation (mineralomass) in all tree components (leaves, branches, wood, bark and roots) and increased nutrient transfer to the soil through deposition of leaf litter.Thus, the eucalypts applied the highest addition of fertilization dose returned to the soil through litter, about 50 kg ha -1 yr -1 of N, 20 kg ha -1 yr -1 of K and 80 kg ha -1 yr -1 of Ca, while the treatment without fertilization transferred to the soil only 25 kg ha -1 yr -1 of N, 6.5 kg ha -1 yr -1 of K and 47 kg ha -1 yr -1 of Ca during 12 months (between 12 to 24 months after planting).It was observed more efficient use of nutrients from the eucalypts with lower nutrients availability.Also, there were no significant differences in the growth of eucalypts from the treatments with split N and K application and single N and K application.However, there was a higher leaching of K and N, 90 cm deep, in the single application treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2011
Admission routes1
Has abstractyes

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