Economic Valuation of Ecosystem Services by Using the Analytic Hierarchy Process and the Analytic Network Process. Comparative Analysis Between Both Methods in the Albufera Natural Park of València (Spain)
Bibliographic record
Abstract
The Analytic Multicriteria Valuation Method (AMUVAM) was designed to value environmental assets. This method and its software allow one to incorporate all the experts' decisions in a global evaluation matrix and assign a degree of importance (weight) to the criteria. This multicriteria decision aid methodology has traditionally been based on the Analytic Hierarchy Process (AHP) and the Discounted Cash Flow. However, it can be substituted by the Analytic Network Process (ANP). Although it involves a higher complexity, it considers all the current relationships between the different alternatives and criteria so it should be more accurate. Therefore, the aim of the present work is to value the ecosystem services of an environmental area by using both methods and compare the results. A real application has been presented; therefore, this work has been applied to the valuation of the Albufera Natural Park in Val ncia (Spain). This area is considered one of the most important Mediterranean wetlands of the Mediterranean countries. Having obtained the results, the method can be carried out using either of the two processes when the aim of the assessment is to get the Total Economic Value. In this case, the AHP can be used as a less time-consuming and cheaper method. However, if the goal is to value the ecosystem services, there are significant differences between both methods. Some of the services are overvalued or underestimated when the AHP has been used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".