VARIATIONS IN ECOSYSTEM SERVICE VALUES AND LOCAL ECONOMY IN RESPONSE TO LAND USE: A CASE STUDY OF WU'AN, CHINA
Bibliographic record
Abstract
ABSTRACT In an industrial/mining city, land use, ecosystem service values (ESVs) and local economy have a close relation. The study reported in this paper is conducive to optimising land use and to balancing ecosystem services and local economy. The aim is to provide useful information and advice for industrial/mining cities concerned with sustainable development. Wu'an, which is rich in mineral resources and an important energy supplier in Hebei Province, is selected as the study area. The ecosystem service value coefficients of industrial ecosystem and urban ecosystem are estimated adopting the cost method and applied to the city from 1996 to 2005. The temporal and spatial changes of the ESVs estimated within the entire ecosystem, sub‐ecosystems and individual ecosystem services are analysed and discussed based on land use. The results show that land use in Wu'an had a great influence on the ESVs and especially the project of converting farmland into forests determined the entire ecosystem structure and functions. Additionally, the study shows the comparing relationships between ecosystem service values and local economy through various mathematical expressions. One significant relationship can be abstracted into an inverse curve (zone) under restrained conditions. The conclusions suggest that the rapid local economy development should build on a reasonable land use with emphasis on the high ecosystem services. Copyright © 2011 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".