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volume 70 pages 101739

Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain)

Publication typeJournal Article
Publication date2022-09-01
scimago Q1
wos Q1
SJR1.491
CiteScore11.4
Impact factor7.3
ISSN15749541, 18780512
Computer Science Applications
Computational Theory and Mathematics
Ecology, Evolution, Behavior and Systematics
Applied Mathematics
Ecology
Modeling and Simulation
Ecological Modeling
Abstract
Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are helpful multi-criteria methods used by the decision-makers to prioritize the ecosystem services provided to humankind by a natural area. Despite being the most common in this field, as it is the easiest and quickest method, AHP simplifies reality by distributing criteria as a hierarchy. As many ecosystem services are firmly connected, this simplification can alter the results owing to the inherent subjectivity of the decision-makers' judgments when completing the required pairwise comparisons. In contrast, ANP considers the relationships among criteria, drawing a complex network that can help in reducing subjectivity and uncertainty. This study aims to compare how both the methods deal with these possible biases. This study prioritizes the ecosystem services provided by a farming area in an internationally recognized wetland with various interconnected services. The case study was conducted in a rice field area raised in the Guadalquivir marshes located within the Doñana Biosphere Reserve in Spain. After applying both methodologies, the results conclude that AHP considerably overestimates the most abstract services. Generally, decision-makers overvalue cultural services as they are socially more visible than others, and in AHP, they are not compared directly with other elements. Additionally, when a problem impacts the production and many people are affected, AHP also magnifies its importance because it is in the limelight. Therefore, ANP is an efficient method when a study requires higher accuracy and coexists with intangible assets despite the benefits and drawbacks of each multi-criteria method. • AHP overestimates cultural services, especially the most abstract ones. • ANP is more advisable as it considers interdependence among criteria. • Despite being more time-consuming and complex, ANP reduces biases. • Momentary problems increase biases in both methods, but ANP decreases them. • Water shortage disturbs the results since it is a crucial problem farmers face. • The market does not value 50% of the ecosystem services in the marshes.
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Jorge-García D., Estruch Guitart V. Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain) // Ecological Informatics. 2022. Vol. 70. p. 101739.
GOST all authors (up to 50) Copy
Jorge-García D., Estruch Guitart V. Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain) // Ecological Informatics. 2022. Vol. 70. p. 101739.
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RIS Copy
TY - JOUR
DO - 10.1016/j.ecoinf.2022.101739
UR - https://doi.org/10.1016/j.ecoinf.2022.101739
TI - Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain)
T2 - Ecological Informatics
AU - Jorge-García, David
AU - Estruch Guitart, Vicent
PY - 2022
DA - 2022/09/01
PB - Elsevier
SP - 101739
VL - 70
SN - 1574-9541
SN - 1878-0512
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2022_Jorge-García,
author = {David Jorge-García and Vicent Estruch Guitart},
title = {Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain)},
journal = {Ecological Informatics},
year = {2022},
volume = {70},
publisher = {Elsevier},
month = {sep},
url = {https://doi.org/10.1016/j.ecoinf.2022.101739},
pages = {101739},
doi = {10.1016/j.ecoinf.2022.101739}
}