Cargando…

Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling

Sclerotinia sclerotiorum, a fungal pathogen, causes world-wide crop losses and additional disease management strategies are needed. Modeling the climate niche of this fungus may offer a tool for the selection of biological control organisms and cultural methods of control. Maxent, a modeling techniq...

Descripción completa

Detalles Bibliográficos
Autor principal: Cohen, Susan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532795/
https://www.ncbi.nlm.nih.gov/pubmed/37755000
http://dx.doi.org/10.3390/jof9090892
_version_ 1785112045350289408
author Cohen, Susan D.
author_facet Cohen, Susan D.
author_sort Cohen, Susan D.
collection PubMed
description Sclerotinia sclerotiorum, a fungal pathogen, causes world-wide crop losses and additional disease management strategies are needed. Modeling the climate niche of this fungus may offer a tool for the selection of biological control organisms and cultural methods of control. Maxent, a modeling technique, was used to characterize the climate niche for the fungus. The technique requires disease occurrence data, bioclimatic data layers, and geospatial analysis. A cross-correlation was performed with ArcGIS 10.8.1, to reduce nineteen bioclimatic variables (WorldClim) to nine variables. The model results were evaluated by AUC (area under the curve). A final model was created with the random seed procedure of Maxent and gave an average AUC of 0.935 with an AUC difference of −0.008. The most critical variables included annual precipitation (importance: 14.1%) with a range of 450 mm to 2500 mm and the mean temperature of the coldest quarter (importance: 55.6%) with a range of −16 °C to 24 °C, which contributed the most to the final model. A habitat suitability map was generated in ArcGIS 10.8.1 from the final Maxent model. The final model was validated by comparing results with another occurrence dataset. A Z-Score statistical test confirmed no significant differences between the two datasets for all suitability areas.
format Online
Article
Text
id pubmed-10532795
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-105327952023-09-28 Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling Cohen, Susan D. J Fungi (Basel) Article Sclerotinia sclerotiorum, a fungal pathogen, causes world-wide crop losses and additional disease management strategies are needed. Modeling the climate niche of this fungus may offer a tool for the selection of biological control organisms and cultural methods of control. Maxent, a modeling technique, was used to characterize the climate niche for the fungus. The technique requires disease occurrence data, bioclimatic data layers, and geospatial analysis. A cross-correlation was performed with ArcGIS 10.8.1, to reduce nineteen bioclimatic variables (WorldClim) to nine variables. The model results were evaluated by AUC (area under the curve). A final model was created with the random seed procedure of Maxent and gave an average AUC of 0.935 with an AUC difference of −0.008. The most critical variables included annual precipitation (importance: 14.1%) with a range of 450 mm to 2500 mm and the mean temperature of the coldest quarter (importance: 55.6%) with a range of −16 °C to 24 °C, which contributed the most to the final model. A habitat suitability map was generated in ArcGIS 10.8.1 from the final Maxent model. The final model was validated by comparing results with another occurrence dataset. A Z-Score statistical test confirmed no significant differences between the two datasets for all suitability areas. MDPI 2023-08-31 /pmc/articles/PMC10532795/ /pubmed/37755000 http://dx.doi.org/10.3390/jof9090892 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cohen, Susan D.
Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title_full Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title_fullStr Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title_full_unstemmed Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title_short Estimating the Climate Niche of Sclerotinia sclerotiorum Using Maximum Entropy Modeling
title_sort estimating the climate niche of sclerotinia sclerotiorum using maximum entropy modeling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10532795/
https://www.ncbi.nlm.nih.gov/pubmed/37755000
http://dx.doi.org/10.3390/jof9090892
work_keys_str_mv AT cohensusand estimatingtheclimatenicheofsclerotiniasclerotiorumusingmaximumentropymodeling