Relationship between vegetation units and microtopography of a pasture located in a poorly drained sector of Argentina.
Bibliographic record
Abstract
The spatial distribution of vegetable communities in depressed landscapes from Rolling Pampa (Pampa Ondulada), Argentina is frequently heterogeneous. The objective of this work was to study a possible relationship between topography and functional and structural characteristics of vegetation in a pasture located in a depressed and poorly drained area. The study was carried out in a sector next to a dell from the flowing Luduena basin. The course of Luduena extends between 32o 46´ and 33o 07´ S and 60o 39´and 61o 07´ W in the Santa Fe province of Argentina. The identification of the plant communities and a topographical study allowed us to recognize three highly productive forage units. In each unit, primary production, abundance and cover were determined. Plant units were established accordingly. The results obtained suggest that vegetation cover and vegetation abundance from depressed landscapes are highly related with microtopography. A menudo, las comunidades vegetales presentes en los paisajes deprimidos de la Pampa Ondulada son espacialmente heterogeneas. El objetivo de este trabajo fue establecer si existe relacion entre las caracteristicas estructurales y funcionales de la vegetacion con la topografia, en un area mal drenada. El estudio se realizo en un sector proximo a una canada perteneciente a la cuenca del arroyo Luduena (Zavalla, Santa Fe, Argentina). El recorrido del arroyo Luduena se ubica entre los 32o 46o y 33o 07´ de latitud sur y 60o 39´ y 61o 07´ de longitud oeste. La identificacion de las comunidades vegetales y un relevamiento topografi co permitieron reconocer tres unidades forrajeras de alta productividad (UFAP). En cada una se midio la productividad primaria neta aerea, la abundancia y el grado de cobertura, y se establecieron diversas unidades de vegetacion. Los resultados sugieren que en los ambientes deprimidos la cobertura y la abundancia de la vegetacion estan altamente relacionadas con la microtopografia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".