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Revista Chapingo serie ciencias forestales y del ambiente

versão On-line ISSN 2007-4018versão impressa ISSN 2007-3828

Resumo

MARTINEZ-RINCON, Sigifredo; VALDEZ-LAZALDE, José R.; SANTOS-POSADAS, Héctor M. de los  e  SANCHEZ-MARTINEZ, Guillermo. Risk of infestations by Dendroctonus mexicanus Hopkins and Dendroctonus frontalis Zimmermann bark beetles in forests of Michoacán. Rev. Chapingo ser. cienc. for. ambient [online]. 2022, vol.28, n.1, pp.37-55.  Epub 02-Fev-2024. ISSN 2007-4018.  https://doi.org/10.5154/r.rchscfa.2020.11.069.

Introduction:

Severe Dendroctonus spp. infestations are reported in North and Central America. Dendroctonus mexicanus Hopkins and Dendroctonus frontalis Zimmermann are recognized as forest pests and are common in the state of Michoacán, Mexico.

Objective:

To model current and future (2015-2039) spatial distribution of risk of D. mexicanus and D. frontalis infestation in forests of Michoacán, Mexico.

Materials and methods:

Multicriteria evaluation techniques, including the analytic hierarchy process and fuzzy membership functions, were combined with climate and biophysical variables to obtain forest infestation risk maps for D. mexicanus and D. frontalis under current and future climate scenarios.

Results and discussion:

Climate, fire, tree density and topography were identified as relevant criteria influencing bark beetle outbreaks. The maximum risk value estimated for D. mexicanus was 0.78 and 0.83 for the current and future scenarios, respectively; for D. frontalis these values correspond to 0.84 and 0.85, respectively. In terms of area, high risk of infestation by D. mexicanus increased from 3.9 % (current scenario) to 5.0 % (future scenario); for D. frontalis it decreased from 10.8 % to 9.6 %. The very high-risk value remained constant (0.35 %) for both species and scenarios.

Conclusions:

Forests of the Transversal Volcanic Belt (in the northeastern part of Michoacán) have the highest risk of bark beetle infestation in the two modeled scenarios.

Palavras-chave : Climate change; spatial modeling; conifer insects; forest pest; Analytic Hierarchy Process..

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