Hydrological and nutrient regulation per occupation unit differ between structurally contrasting native and planted forests in the Northern Andes
Bibliographic record
Abstract
Understanding ecohydrological dynamics that result from land-use conversions is fundamental in managing ecosystem services. One common forest transformation in the tropics is the establishment of monospecific plantations with exotic species for timber exploitation, replacing highly diverse natural forests. The impacts of establishing forest plantations in hydrological processes and biogeochemical dynamics have been highly controversial, with functions from structurally homogeneous plantations being sometimes assumed to be comparable to natural forests. To assess the effects of planting exotic conifer species versus natural forests on hydrological and biogeochemical functions, we measured incoming precipitation, throughfall, and stemflow. To compare between forest types, we propose the use of basal area for standardization of hydrochemical fluxes. While net precipitation was similar among forest types, the transmission of water to the forest floor per basal area unit was significantly higher in native forests. Yet, nutrient concentrations were similar among them. However, greater nutrient enrichment per unit basal area was observed for the native species. This more efficient nutrient cycling could be related to native forests being better adapted to oligotrophic soils. The re-establishment of native species rather than with exotic species can result in more efficient hydrochemical regulation, improving the capacity of these ecosystems to produce services.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".