Producción y descomposición de hojarasca en el bosque natural de Cayo Quemado, Livingston, Izabal, Guatemala
Bibliographic record
Abstract
Los bosques naturales de los sistemas marino costeros son importantes por los bienes y servicios ambientales que prestan. Sin embargo, en la Costa Atlántica del país son vulnerables a múltiples amenazas. Como parte de un inventario de carbono del bosque natural Cayo Quemado, se cuantificó la producción y descomposición de hojarasca de las especies vegetales predominantes por unidad de área: Mangle rojo (Rhizophora mangle) 38.14%, zapotón (Pachira aquatica) 19.07%, cahue (Pterocarpus officinalis) 18.56% y anonillo (Rollinia pittieri) 7.22%. En bloques de 30 x 30 m, fueron colocadas en forma aleatoria trampas de 2 x 2 m, y bolsas de descomposición con 200 g de hojarasca fresca, con tres repeticiones, con lecturas cada 30 días. Se concluye que el mangle rojo aportó 0.6015, el zapotón 0.2701, el cahué 0.1836 y el anonillo 0.1119 para un total de 1.1671 MgC/ha, equivalentes a 4.28 MgCO2/ha. Así mismo, se determinó que después de cinco meses de descomposición la masa seca remanente fue de cahué (47.9%), zapotón (40.94%), mangle (38.86%) y anonillo (30.41%) en base a peso seco. El rol de las especies vegetales asociadas a los manglares es de suma importancia por su naturaleza recalcitrante y preservación del Cayo Quemado per se.
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 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 | 0.001 | 0.001 |
| 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".