Evidence map›Paper›PMID 41187144›Full record

ArticlePloS one2025

Utilizing FUCOM and AHP methods to identify the optimal beekeeping lands: A case study from Mardin, Türkiye.

Çağrı Mercan, Veysi Acıbuca

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Çağrı MercanDepartment of Mapping and Cadastre, Savur Vocational School, Mardin Artuklu University, Mardin, Türkiye.ORCID https://orcid.org/0000-0003-1694-0024
Veysi AcıbucaDepartment of Horticulture, Kızıltepe Faculty of Agricultural Sciences and Technologies, Mardin Artuklu University, Mardin, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Beekeeping plays a vital role in agricultural sustainability and biodiversity conservation, yet identifying ecologically suitable areas for apiculture remains challenging. The objective of this study is to evaluate and compare two Multi-Criteria Decision-Making (MCDM) methods-the Analytical Hierarchy Process (AHP) and the Full Consistency Method (FUCOM)-within a Geographic Information Systems (GIS) framework to identify optimal beekeeping areas in Mardin Province, Türkiye. Nine environmental, climatic, topographical, logistic, and socio-economic factors were selected through literature review, legal regulations, expert consultation, and field observations. Suitability maps were generated and validated using field-verified hive locations and Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) analysis. The results show that land use/cover, proximity to water sources, and precipitation were the most influential factors. Overall, 83% of hive locations coincided with areas classified as moderately suitable or higher. AHP achieved slightly higher predictive accuracy (AUC = 0.774) than FUCOM (AUC = 0.754), while FUCOM required substantially fewer pairwise comparisons, underscoring its efficiency. These findings confirm the robustness of the framework and provide a practical tool for sustainable apicultural land-use planning, offering transferable insights for policymakers, decision-makers, and beekeepers in Türkiye and other regions with similar ecological conditions.

Indexed as

BeekeepingAnimalsBeesConservation of Natural ResourcesGeographic Information Systems

Identifiers

PMID41187144
PMCPMC12585028

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.