Geographic information system applications in bee research

• Autores: Rojas Briceño, Nilton B., Silva López, Jhonsy O., Guzman Valqui, Betty Karina, Ix Balam, Manuel A., Ramos Tejeda, José L., Oliva Cruz, Manuel, Veneros, Jaris, García, Ligia
• Formato: artículo
• Fecha de Publicación: 2026
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.inia.gob.pe:20.500.12955/3165
• Enlace del recurso: http://hdl.handle.net/20.500.12955/3165; https://doi.org/10.3390/insects17060566
• Nivel de acceso: acceso abierto
• Materia: Apiculture; Apicultura; Beekeeping; Bees; Abejas; Floral resource; Recurso floral; Geographic Information Systems; Sistemas de información geográfica; Honey bee; Abeja de la miel; Multicriteria decision analysis; Análisis multicriterio de decisión; Pollinators; Polinizadores; Remote sensing; Teledetección; Spatial analysis; Análisis espacial; https://purl.org/pe-repo/ocde/ford#4.01.00; Biodiversidad, Biodiversity; Cambio climático, Climate change; Servicio de los ecosistémicos, Ecosystem services; Paisaje, Landscape; Cartografía, Cartography; Habitat connectivity; Conectividad del hábitat.

Bees play crucial ecological, economic, and environmental roles, and research on them increasingly includes a spatial dimension. Geographic Information Systems (GISs) enable the acquisition, storage, analysis, management, and visualization of spatial data. However, GIS applications in bee research have expanded while remaining dispersed across topics, tools, taxa, and methodological approaches. This study provides a comprehensive and updated review of GIS applications in bee research by integrating bibliometric analysis with a structured synthesis of GIS purposes and techniques. A total of 228 publications were analyzed to assess publication trends, co-authorship patterns, keyword themes, study areas, taxonomic coverage, GIS application themes, and methodological tools. GIS was used to select suitable apiary sites, map floral resources, analyze bee behavior, assess diseases and pests, monitor bee products, evaluate urban and landscape contexts, and predict climate change effects. The main GIS-related approaches included multicriteria decision analysis (MCDA), remote sensing, species distribution models (SDMs), spatial interpolation, WebGIS platforms, and emerging machine-learning applications. The review also identified underrepresented taxa, especially wild bees, stingless bees, and other Apis species. Future advances should integrate MCDA with data-driven models, improve floral-resource mapping with remote sensing, and strengthen reproducibility through standardized spatial data and workflows.