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Record W4402545955 · doi:10.1007/s11056-024-10065-7

Assessing the of carbon and nitrogen storage potential in Khaya spp. stands in Southeastern Brazil

2024· article· en· W4402545955 on OpenAlexaff
Gabriel Soares Lopes Gomes, Marcos Vinícius Winckler Caldeira, Robert Gomes, Victor Braga Rodrigues Duarte, Dione Richer Momolli, Tiago de Oliveira Godinho, Sarah Ola Moreira, Paulo André Trazzi, Laio Silva Sobrinho, Angélica de Cássia Oliveira Carneiro, Mauro Valdir Schumacher

Bibliographic record

VenueNew Forests · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsOlds College
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsKhayaNitrogenCarbon fibersEnvironmental scienceAgroforestryWoody plantForestryGeographyEcologyBotanyBiologyChemistryMathematics

Abstract

fetched live from OpenAlex

The objective of this study was to assess the dynamics of carbon and nitrogen in soil, forest floor, and aboveground biomass in 9.5 years-old planted stands of three Khaya spp. ( K. grandifoliola , K. ivorensis , and K. senegalensis ). The study was conducted at the Reserva Natural Vale (RNV), Brazil. The stands were planted at 5 × 5 m spacing, distributed over rectangular plots of 1250 m 2 . Soil bulk density at the evaluated depths, as well nitrogen contents, were similar among the species. However, K. ivorensis exhibited higher carbon concentration in the soil. In general, there were no differences in carbon and nitrogen content in soil between the three species; however, the values obtained are comparable to those of the reference area–Native Forest. The carbon stocks in the aboveground biomass for K. grandifoliola , K. ivorensis , and K. senegalensis averaged 37.97, 33.66 and 33.86 Mg ha −1 , respectively ( p ≤ 0.05). These values collectively represent about 28% of the total carbon stocks across the observed compartments. Notably, the nitrogen content within the aboveground biomass did not differ among these species. Therefore, African mahogany possesses a robust potential to store both carbon and nitrogen.

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 score0.023
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 studies0.0000.000
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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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