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Record W4409425063 · doi:10.1080/10807039.2025.2490081

Impact of the tradeoff between urbanization and ecological construction on the supply and demand balance of carbon sequestration services in China

2025· article· en· W4409425063 on OpenAlexaff
Jinghu Pan, Xiangbing Han, Wenle Yang

Bibliographic record

VenueHuman and Ecological Risk Assessment An International Journal · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsScience North
FundersNational Natural Science Foundation of China
KeywordsChinaUrbanizationBalance (ability)Carbon sequestrationNatural resource economicsSupply and demandBusinessBalance of natureCarbon fibersEcologyEconomicsGeographyEconomic growthComputer scienceMicroeconomicsBiologyCarbon dioxide

Abstract

fetched live from OpenAlex

Clarifying the spatiotemporal distribution characteristics of the supply-demand balance of ecosystem carbon sequestration services and the impact of human activities and natural factors on it is of great value for exploring nature-based carbon neutrality solutions. This study quantified and mapped the supply and demand of carbon sequestration services in China in 2001, 2010, and 2019, clarified the spatiotemporal distribution pattern of the supply-demand balance of carbon sequestration services in terrestrial ecosystems, identified the tradeoff relationship between urbanization and ecological construction, and analyzed its impact on the supply-demand balance of carbon sequestration services. Results indicate that China’s demand and supply for ecological carbon sequestration services increased gradually from 2001 to 2019. Spatial mismatches are becoming more pronounced as the supply-demand balance for carbon sequestration services is weakening across all regions. Urbanization and ecological construction have a mostly synergistic relationship, but the strength of synergy progressively declines. The balance of carbon sequestration services supply and demand is affected by the tradeoffs between ecological construction and urbanization. The research results provide s a theoretical reference for formulating differentiated emission reduction and sink enhancement policies and promoting the coordinated development of human-environment relations.

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 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)0.000
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 score0.011
Threshold uncertainty score0.163

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.285
Teacher spread0.276 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2025
Admission routes1
Has abstractyes

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