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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...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2023
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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 |
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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 |