Globally-used forestry herbicides and their potential for impacts on soil and water resources
Bibliographic record
Abstract
Globally, land management activities can significantly alter ecosystem\ncomponents on temporal and spatial scales. Alterations in wildlife habitat and potentially adverse impacts on soils and aquatic ecosystems are notable social concerns in the field of forest vegetation management (FVM. However studies have shown that FVM which usually occurs 1-3 times over a 20-100+ year-long crop rotation represents a minor impact compared to those resulting from population growth, forest harvest, or to agricultural activities which occur several times annually. FVM activities include plant protection, noxious weed control, conifer and hardwood culture restoration of semi-natural areas and improvement of recreational areas and wildlife\nhabitat. FVM may be accomplished using a variety of tools including\nmechanical, manual, chemical, biological, and silvicultural methods. Among these tools, chemical herbicides combined with various silvicultural methods are often the preferred approach to FVM because they are the most cost efficient, reliable and effective means available. Herbicides may be spot applied, injected into single stems, applied in discreet bands, or broadcast applied either by aerial or ground-based equipment. More than 30 forest herbicide active ingredients are registered for use in various countries for\nFVM. The registration process usually includes exhaustive toxicological, environmental impact and environmental fate studies. Fewer than 10 of these active ingredients represent more than 85% of the total amount of forestry herbicide applied worldwide. This paper will review the evidence from published research which indicates that contrary to popular opinion there is little potential for long-term detrimental impacts on soil and water resources. / Un bilan à l`échelle internationale est fait sur l`emploi des herbicides à usage forestier et leur impact sur la qualité de l`eau et les micro-organismes du sol. La liste des principaux herbicides utilisés est établie. Une analyse bibliographique est ensuite réalisée permettant d`établir une comparaison de leurs principales caractéristiques écotoxicologiques. Le volume d`herbicide utilisé en forêt est faible puisqu`il est de l`ordre de 1 % du volume global utilisé alors que la surface forestière est beaucoup plus élevée proportionnellement. Les auteurs concluent à l`absence de risques écotoxicologiques pour le milieu aquatique et les micro-organismes du sol si les utilisateurs respectent les conditions d`application homologuées.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".