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Record W3158992308 · doi:10.1007/s11676-021-01329-5

Inclusion of forestry offsets in emission trading schemes: insights from global experts

2021· article· en· W3158992308 on OpenAlex
Anil Shrestha, Sarah Eshpeter, Nuyun Li, Jinliang Li, John O. Nile, Guangyu Wang

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.

Bibliographic record

VenueJournal of Forestry Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of British Columbia
FundersEuropean Commission
KeywordsAdditionalityCarbon offsetEmissions tradingInclusion (mineral)CertificationClean Development MechanismGreenhouse gasBusinessAfforestationReforestationForest managementEnvironmental economicsEnvironmental resource managementNatural resource economicsEnvironmental planningForestryEnvironmental scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Abstract Emissions trading schemes (ETSs) have been a central component of international climate change policies, as a carbon pricing tool to achieve emissions reduction targets. Forest carbon offset credits have been leveraged in many ETSs to efficiently meet emission reduction targets, yet there is little knowledge about the perceptions, experiences, and challenges associated with the forest carbon offsetting in existing and pilot ETS. Given that the future inclusion of forest carbon offset in ETS management activities and policies will require strong support and acceptability among the institutions and experts involved in ETS, this study explores the experiences and lessons learned with 16 globally engaging experts representing major existing ETSs (North America, Europe, and New Zealand) and Chinese pilot ETSs towards the inclusion of forestry offsets, major concerns and challenges with existing implementation models. Findings revealed that many respondents particularly from North America, New Zealand, and Chinese pilot systems portrayed positive attitudes toward the inclusion of forestry carbon offsets and its role in contributing to a viable ETS, while European experts were not supportive. Respondents cited leakage, permanence, additionality, and monitoring design features as the major challenges and concerns that inhibit the expansion and inclusion of forest carbon offsetting. Respondents from Chinese pilot schemes referenced a unique set of challenges related to implementation, including the increasing cost of afforestation and reforestation projects, the uncertainty in the future supply and demand for their national Certified Emissions Reduction (CER) scheme and landowner engagement. Existing and future ETSs should learn from and address the challenges experienced by global experts and carbon pricing mechanisms to design, evaluate, or enhance their forest carbon offset programs for an effective and viable system that successfully contributes to GHG mitigation practices globally. We recommend inclusion of forest carbon offsets at the early stages of ETS improves the perceptions and experience of policy makers and practitioners toward the success and potential of forestry offsets in ETS ensuring familiarity and confidence in the mechanism.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.366
Teacher spread0.316 · 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