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Record W6967575450 · doi:10.5281/zenodo.10685404

PREreview of "Mining threats in high-level biodiversity conservation policies"

2024· peer-review· en· W6967575450 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typepeer-review
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityMeasurement of biodiversityCLARITYBiodiversity conservationConservation psychologyConservation Plan

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.005
Science and technology studies0.0020.002
Scholarly communication0.0060.005
Open science0.0040.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0580.031

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.

Opus teacher head0.086
GPT teacher head0.267
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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