Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential
The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/14/8/1577 |
| _version_ | 1797584717997932544 |
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| author | Monika P. Calef Jennifer I. Schmidt Anna Varvak Robert Ziel |
| author_facet | Monika P. Calef Jennifer I. Schmidt Anna Varvak Robert Ziel |
| author_sort | Monika P. Calef |
| collection | DOAJ |
| description | The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (<i>Picea mariana</i> (Mill.) B.S.P.) and lodgepole pine (<i>Pinus contorta</i> Dougl. ex Loud. var. <i>latifolia</i> Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas. |
| first_indexed | 2024-03-10T23:56:35Z |
| format | Article |
| id | doaj.art-b5401bcbf5f44742b174dd890b103021 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-10T23:56:35Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-b5401bcbf5f44742b174dd890b1030212023-11-19T01:08:45ZengMDPI AGForests1999-49072023-08-01148157710.3390/f14081577Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire PotentialMonika P. Calef0Jennifer I. Schmidt1Anna Varvak2Robert Ziel3Environmental Studies, Soka University of America, Aliso Viejo, CA 92656, USAInstitute of Social and Economic Research, University of Alaska Anchorage, Anchorage, AK 99508, USAMath/Science, Soka University of America, Aliso Viejo, CA 92656, USAGeophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USAThe boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (<i>Picea mariana</i> (Mill.) B.S.P.) and lodgepole pine (<i>Pinus contorta</i> Dougl. ex Loud. var. <i>latifolia</i> Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas.https://www.mdpi.com/1999-4907/14/8/1577boreal forestwildfireinterior AlaskaYukonmachine learning model |
| spellingShingle | Monika P. Calef Jennifer I. Schmidt Anna Varvak Robert Ziel Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential Forests boreal forest wildfire interior Alaska Yukon machine learning model |
| title | Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential |
| title_full | Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential |
| title_fullStr | Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential |
| title_full_unstemmed | Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential |
| title_short | Predicting the Unpredictable: Predicting Landcover in Boreal Alaska and the Yukon Including Succession and Wildfire Potential |
| title_sort | predicting the unpredictable predicting landcover in boreal alaska and the yukon including succession and wildfire potential |
| topic | boreal forest wildfire interior Alaska Yukon machine learning model |
| url | https://www.mdpi.com/1999-4907/14/8/1577 |
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