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Record W4286643395 · doi:10.1007/s11676-022-01488-z

Key challenges and approaches to addressing barriers in forest carbon offset projects

2022· article· en· W4286643395 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Forestry Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsAdditionalityCarbon offsetTransaction costClean Development MechanismGreenhouse gasBusinessEnvironmental economicsEnvironmental resource managementEconomicsEcologyFinance

Abstract

fetched live from OpenAlex

Abstract Forest carbon offset (FCO) projects play an increasingly important role in mitigating climate change through market mechanisms in both compliance and voluntary markets. However, there are challenges and barriers to developing an FCO project, such as carbon leakage and cost-effectiveness. There have been few attempts to summarize and synthesize all types and aspects of existing challenges and possible solutions for FCO projects. This paper systematically reviews and discusses the current challenges involved in developing FCO projects, and then draws on the experience and lessons of existing projects to show how those challenges were addressed in world-leading voluntary carbon standards, namely the Verified Carbon Standard, the American Carbon Registry, the Climate Action Reserve, and Plan Vivo. These voluntary markets have rich experience in FCO projects and are responsible for a significant share of the market. From the 53 publications used in this analysis, three broad thematic categories of challenges emerged. These were related to methodology, socio-economic implications, and implementation. Methodological challenges, particularly additionality, permanence, and leakage, were the focus of 46% of the selected research papers, while socio-economic challenges, including transaction, social, and opportunity costs, were addressed by 35%. The remaining 19% of the research articles focused on implementational challenges related to monitoring, reporting, and verification. Major voluntary standards adequately addressed most of the methodological and implementational barriers by adopting various approaches. However, the standards did not adequately address socio-economic issues, despite these being the second most frequently discussed theme in the papers analyzed. More research is clearly needed on the socio-economic challenges involved in the development of FCO projects. For the development of high-quality forestry carbon offset projects, there are many challenges and no simple, universal recipe for addressing them. However, it is crucial to build upon the current science and move forward with carbon projects which ensure effective, long-term carbon sinks and maximize benefits for biodiversity and people; this is particularly important with a growing public and private interest in this field.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.324
GPT teacher head0.352
Teacher spread0.027 · 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