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Use of Ecological Niche Models of Plant Species to Optimize Placement of Apiaries Cover

Use of Ecological Niche Models of Plant Species to Optimize Placement of Apiaries

Open Access
|Dec 2019

Abstract

Apiaries must be located in areas with abundant flora as they are the nutritional base for Apis mellifera. Asteraceae is one of the most diverse plant families in Mexico and several of its species are of interest for beekeepers. The objective of this study was to determine the best sites for the placement of apiaries with the use of ecological niche models (ENM) of some Asteraceae species important for bees in two basins of the state of Michoacán, Mexico. ENM for thirty species were obtained through records of their presence, twenty abiotic variables and one biotic variable, and a map of species richness was made to determine which sites would be environmentally appropriate for apiaries. The models were statistically evaluated using the AUC_Maxent, partial_ROC and the binomial tests and were verified in the field. The first two tests’ models had values of 0.70 to 1 and the binomial test’s models had values of 1. The map showed six suitable areas with the greatest richness of species. The corroboration in the field proved ENM effective by finding twenty-two of the thirty modeled species inside the predicted areas. Our results support that ENM are a good strategy to predict the ideal habitat for species important for beekeeping, and thus determine the best places to establish apiaries in the region.

DOI: https://doi.org/10.2478/jas-2019-0017 | Journal eISSN: 2299-4831 | Journal ISSN: 1643-4439
Language: English
Page range: 243 - 265
Submitted on: Oct 12, 2018
Accepted on: Apr 15, 2019
Published on: Dec 26, 2019
Published by: Research Institute of Horticulture
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2019 Yareli J. Cadena Rodríguez, Monserrat Vázquez-Sánchez, Gustavo Cruz-Cárdenas, José L. Villaseñor, published by Research Institute of Horticulture
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.