PREreview of "Mining threats in high-level biodiversity conservation policies"
Notice bibliographique
Résumé
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/10685404. This study gives an overview of mining threats in high-level biodiversity conservation policies. The extraction of solid raw materials (namely sand, gravel, and limestone) poses a serious threat to biodiversity through erosion, pollution, water stress, salinization, and land-use changes. The study quantifies the degree to which threats from mining are addressed in high-level national and international biodiversity conservation policies. A review was conducted using a text-coding approach to focus on documents that mentioned mining (particularly mining for construction minerals), and policy interventions were compiled related to construction mineral mining. Country-level attributes were also considered to explain the development or lack thereof of mining related policy. The authors find that current policies fall short of clear statements and outcomes to prevent threats to biodiversity as a result of mining. An 8-point strategy is suggested to address current limitations of conservation policy and provide actionable solutions improve international biodiversity policies. Based on the findings from this study, there is a lack of clarity and sufficiently laid out goals in terms of biodiversity conservation policy to prevent landscape degradation, habitat loss, and other deleterious impacts associated with construction mineral mining. Additionally, the authors note that much of the current biodiversity conservation policy does not account for the growing demand for construction minerals, which is projected to double by 2060. The authors do a good job of addressing the gaps and weaknesses of current policy and providing strategies to improve future policy. The authors conclude that countries will develop or revise their biodiversity conservation policies based on the Montreal-Kunming GBF. However, they acknowledge that current policy does not take into account the increasing demand for construction minerals in the future. The integration of the 8-step action plan was clear and actionable, and we found it interesting that there were high amounts of mining activity in island countries like Malaysia, despite being highly susceptible to more intensive impacts of climate change such as erosion. Overall, this paper is well-written and will be a valuable publication within the conservation biology community, as the authors were able to condense and analyze a lot of policy information concisely. Major issues Title – we feel that the title is too general and can benefit by being more specific. In this case, we suggest adding "constructing mineral" in front of "mining" to clarify what type of mining the paper will address. Additionally, we suggest adding a few words mentioning the 8-step action plan, which is a large component of the paper. Perhaps "Construction mineral mining in high-level biodiversity conservation policies and strategies for improvement." Minor issues Clarify some jargon – This will likely depend on your targeted audience, but the paper could benefit by describing jargon. For example, describe the difference between national targets and national strategies. Methods – In the second paragraph, the authors mention that country-level attributes were considered in logistic regression models. We suggest either listing what these attributes are after they are mentioned (instead of later in the paragraph) or citing Table 1 so the reader can refer to them as needed. Methods – In the second paragraph, the authors mention the interaction between country size and island status. We suggest adding a description of what this interaction means. Body – The authors mention both the Kunming-Montreal GBF and the Montreal-Kunming GBF throughout the paper. Are these interchangeable and referring to the same policy? If so, we suggest using one consistent name. Step 3 of action plan – Step 3 appeared less actionable compared to other steps. We suggest that the authors elaborate on the trait-based vulnerability assessment. For example, there are so many species out there, perhaps suggest prioritizing species of importance since a trait-based analysis of all species is very ambitious. Also, we suggest that the authors elaborate more on what traits are. Which traits should be prioritized? Perhaps include examples of behavioral responses and life-history traits are specifically affected by mining. We understand that traits vary across species, but some examples may clarify the need for trait-based vulnerability assessments. Conclusion – The first sentence of the conclusion mentions that the Kunming-Montreal GBF will be used in countries to develop or revise national biodiversity strategies. We suggest that the authors explain why the Kunming-Montreal GBF was used in the conclusion. As of the time of this review, the Kunming-Montreal GBF was adopted by the UN in December 2022. Perhaps the authors should consider updating this sentence in case anything has changed since the manuscript was written. Tables & Figures – Table 1 can be difficult to interpret. We suggesting adding a regression graph to visually represent the relationship between these parameters. We also suggest simplifying Figure 2. The colors may not be color-blind accessible and the text on the right-hand side is difficult to read. The variation in shapes works well and should be kept. Competing interests The authors declare that they have no competing interests.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,080 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,011 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,058 | 0,031 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».