APORTE DE BIOMASSA E NUTRIENTES POR Allagoptera arenaria NA RESTINGA DA MARAMBAIA, RIO DE JANEIRO, RJ
Bibliographic record
Abstract
O estudo avaliou a quantidade de matéria orgânica e nutrientes foliares aportados ao solo por Allagoptera arenaria em uma comunidade arbustiva de Palmae na restinga de Marambaia, Rio de Janeiro. As coletas foram realizadas em dez parcelas de 10 m x 10 m (100 m²), demarcadas aleatoriamente na formação arbustiva. Foram coletadas 3 (três) folhas de dez indivíduos adultos escolhidos aleatoriamente. Foi possível quantificar um incremento anual de massa seca de 8,2 Mg.ha-1 ano-1 para a área de estudo. Para o N, observou-se um teor de 12,3 g.kg-1, seguido de 5,7 g.kg-1 para o K, os quais representam, respectivamente, um aporte de 303 kg.N.ha-1.ano-1 e 140 kg.K.ha-1.ano-1. Para P, foi verificado teor no material foliar na ordem de 0,31 g.kg-1, com aporte de 7,4 kg.ha-1.ano-1.Palavra-chave: Ciclagem de nutrientes; ecossistemas costeiros; palmáceas; plantas focais. AbstractBiomass and Nutrient input by Allagoptera arenariain in Restinga da Marambaia, Rio de Janeiro, RJ. This research assessed the amount of organic matter and foliar nutrients in the soil from Allagoptera arenaria in a Palmae shrub community of Restinga da Marambaia, Rio de Janeiro. Samples were collected at ten randomly demarcated plots of 10 x 10m (100 m²) in the bush. We collected three (3) leaves of ten randomly chosen adults. It was possible to quantify an annual increase of dry mass of 8,2 Mg ha-1 yr-1 for the focused area. We observed for N an average grade of 12,3 g kg-1 followed by 5,7 g kg-1 for K, which respectively represent an investment of 303 kg N ha-1 year-1 and 140 kg K ha-1 year-1. We observed for P mean levels in leaf material in order of 0,31 g kg-1 with intake of 7,4kg ha-1 year-1.Keywords: Nutrient cycling; coastal ecosystems; palms; nurse plants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".