Chir pine forest and pre-monsoon drought determine spatial, and temporal patterns of forest fires in Uttarakhand Himalaya
Associated with farming practices (between 300 and 2000 m elevations), human-ignited small, and patchy surface forest fires occur almost every year in Uttarakhand (between 28°43`– 31°27` N and 77°34`– 81°02`E; area 51,125 km 2 ), a Himalayan state of India. Using fire incidence data of 19 years (200...
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| Veröffentlicht in: | Tropical ecology 2024-03, Vol.65 (1), p.32-42 |
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| creator | Singh, Ripu Daman Gumber, Surabhi Sundriyal, R. C. Ram, Jeet Singh, Surendra P. |
| description | Associated with farming practices (between 300 and 2000 m elevations), human-ignited small, and patchy surface forest fires occur almost every year in Uttarakhand (between 28°43`– 31°27` N and 77°34`– 81°02`E; area 51,125 km
2
), a Himalayan state of India. Using fire incidence data of 19 years (2002–2020) generated by MODIS, we analysed the factors which drive temporal and spatial patterns of fire in the region. The fire incidence data were organized by 24 forest divisions, the unit of state forest management and administration. The standardized regression model showed that pre-monsoon temperature (March to May or mid-June), proportional area of the forest division under chir pine (
Pinus roxburghii
) forest (positive effect), and pre-monsoon and winter precipitation (negative effect) accounted for 56% of the variance in fire incidence density (FID). The pre-monsoon temperature (warmer) and precipitation (lower) were significantly different in 2009, 2012, 2016 and 2019, the years with high FID (average 54.9 fire/100 km
2
) than the rest of years with low FID (average 20.9 fire/100 km
2
). During the two decades of warming, high FID (> 30 incidence per year /100 km
2
) occurred after every three to four years, and fire peaks tended to increase with time. The study suggests that effective fire management can be attained by improving pre-monsoon precipitation forecasting and targeting forest compartments with a higher occurrence of chir pine and fire-vulnerable oaks. Furthermore, since fires are human-ignited, periodical analysis of changes in population distribution and communities’ dependence on forests would need to be conducted. |
| doi_str_mv | 10.1007/s42965-023-00306-9 |
| format | Article |
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2
), a Himalayan state of India. Using fire incidence data of 19 years (2002–2020) generated by MODIS, we analysed the factors which drive temporal and spatial patterns of fire in the region. The fire incidence data were organized by 24 forest divisions, the unit of state forest management and administration. The standardized regression model showed that pre-monsoon temperature (March to May or mid-June), proportional area of the forest division under chir pine (
Pinus roxburghii
) forest (positive effect), and pre-monsoon and winter precipitation (negative effect) accounted for 56% of the variance in fire incidence density (FID). The pre-monsoon temperature (warmer) and precipitation (lower) were significantly different in 2009, 2012, 2016 and 2019, the years with high FID (average 54.9 fire/100 km
2
) than the rest of years with low FID (average 20.9 fire/100 km
2
). During the two decades of warming, high FID (> 30 incidence per year /100 km
2
) occurred after every three to four years, and fire peaks tended to increase with time. The study suggests that effective fire management can be attained by improving pre-monsoon precipitation forecasting and targeting forest compartments with a higher occurrence of chir pine and fire-vulnerable oaks. Furthermore, since fires are human-ignited, periodical analysis of changes in population distribution and communities’ dependence on forests would need to be conducted.</description><identifier>ISSN: 0564-3295</identifier><identifier>EISSN: 2661-8982</identifier><identifier>DOI: 10.1007/s42965-023-00306-9</identifier><identifier>PMID: 37362779</identifier><language>eng</language><publisher>New Delhi: Springer India</publisher><subject>Agricultural practices ; Biodiversity ; Biomedical and Life Sciences ; Coniferous forests ; Conservation Biology/Ecology ; Drought ; Ecology ; Ecosystems ; Forest & brush fires ; Forest fires ; Forest management ; Forests ; Landscape Ecology ; Life Sciences ; MODIS ; Monsoon forecasting ; Monsoon precipitation ; Monsoons ; Pine ; Pinus roxburghii ; Population distribution ; Precipitation ; Precipitation forecasting ; Regression models ; Research Article ; Weather forecasting ; Wind ; Winter precipitation</subject><ispartof>Tropical ecology, 2024-03, Vol.65 (1), p.32-42</ispartof><rights>International Society for Tropical Ecology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>Copyright Scientific Publishers Mar 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c475t-7d37f6df16221d0d0967d911bc4cc5fe6377fd309cb39b3715edb2f6361e317f3</citedby><cites>FETCH-LOGICAL-c475t-7d37f6df16221d0d0967d911bc4cc5fe6377fd309cb39b3715edb2f6361e317f3</cites><orcidid>0000-0002-2875-2664 ; 0000-0003-3139-9301 ; 0000-0003-2438-9041</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s42965-023-00306-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s42965-023-00306-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37362779$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Singh, Ripu Daman</creatorcontrib><creatorcontrib>Gumber, Surabhi</creatorcontrib><creatorcontrib>Sundriyal, R. C.</creatorcontrib><creatorcontrib>Ram, Jeet</creatorcontrib><creatorcontrib>Singh, Surendra P.</creatorcontrib><title>Chir pine forest and pre-monsoon drought determine spatial, and temporal patterns of forest fires in Uttarakhand Himalaya</title><title>Tropical ecology</title><addtitle>Trop Ecol</addtitle><addtitle>Trop Ecol</addtitle><description>Associated with farming practices (between 300 and 2000 m elevations), human-ignited small, and patchy surface forest fires occur almost every year in Uttarakhand (between 28°43`– 31°27` N and 77°34`– 81°02`E; area 51,125 km
2
), a Himalayan state of India. Using fire incidence data of 19 years (2002–2020) generated by MODIS, we analysed the factors which drive temporal and spatial patterns of fire in the region. The fire incidence data were organized by 24 forest divisions, the unit of state forest management and administration. The standardized regression model showed that pre-monsoon temperature (March to May or mid-June), proportional area of the forest division under chir pine (
Pinus roxburghii
) forest (positive effect), and pre-monsoon and winter precipitation (negative effect) accounted for 56% of the variance in fire incidence density (FID). The pre-monsoon temperature (warmer) and precipitation (lower) were significantly different in 2009, 2012, 2016 and 2019, the years with high FID (average 54.9 fire/100 km
2
) than the rest of years with low FID (average 20.9 fire/100 km
2
). During the two decades of warming, high FID (> 30 incidence per year /100 km
2
) occurred after every three to four years, and fire peaks tended to increase with time. The study suggests that effective fire management can be attained by improving pre-monsoon precipitation forecasting and targeting forest compartments with a higher occurrence of chir pine and fire-vulnerable oaks. Furthermore, since fires are human-ignited, periodical analysis of changes in population distribution and communities’ dependence on forests would need to be conducted.</description><subject>Agricultural practices</subject><subject>Biodiversity</subject><subject>Biomedical and Life Sciences</subject><subject>Coniferous forests</subject><subject>Conservation Biology/Ecology</subject><subject>Drought</subject><subject>Ecology</subject><subject>Ecosystems</subject><subject>Forest & brush fires</subject><subject>Forest fires</subject><subject>Forest management</subject><subject>Forests</subject><subject>Landscape Ecology</subject><subject>Life Sciences</subject><subject>MODIS</subject><subject>Monsoon forecasting</subject><subject>Monsoon precipitation</subject><subject>Monsoons</subject><subject>Pine</subject><subject>Pinus roxburghii</subject><subject>Population distribution</subject><subject>Precipitation</subject><subject>Precipitation forecasting</subject><subject>Regression models</subject><subject>Research Article</subject><subject>Weather forecasting</subject><subject>Wind</subject><subject>Winter precipitation</subject><issn>0564-3295</issn><issn>2661-8982</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kUFv1DAQhS0EosvCH-CALHHhUMPYTuz4hNCKUqRKvbRny4nt3ZTEDnZSaf893m5boIeeRvJ873meHkLvKXymAPJLrpgSNQHGCQAHQdQLtGJCUNKohr1EK6hFRThT9Ql6k_MNgOC0lq_RCZdcMCnVCu03uz7hqQ8O-5hcnrEJFk_JkTGGHGPANsVlu5uxdbNL4wHMk5l7M5zeobMbp5jMgMtjAULG0T9Y-b4M3Ad8Pc8mmV-7g-C8H81g9uYteuXNkN27-7lG12ffrzbn5OLyx8_NtwvSVbKeibRcemE9FYxRCxaUkFZR2nZV19XeCS6ltxxU13LVcklrZ1vmBRfUcSo9X6OvR99paUdnOxfmcq6eUrkj7XU0vf5_E_qd3sZbTYFVUImqOHy6d0jx91KC6bHPnRsGE1xcsmYNB0YVlCLW6OMT9CYuKZR8mkPFgDVMNoViR6pLMefk_OM1FPShWn2sVhdHfVetVkX04d8cj5KHLgvAj0Auq7B16e_fz9j-Af_VsTs</recordid><startdate>20240301</startdate><enddate>20240301</enddate><creator>Singh, Ripu Daman</creator><creator>Gumber, Surabhi</creator><creator>Sundriyal, R. 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C. ; Ram, Jeet ; Singh, Surendra P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c475t-7d37f6df16221d0d0967d911bc4cc5fe6377fd309cb39b3715edb2f6361e317f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Agricultural practices</topic><topic>Biodiversity</topic><topic>Biomedical and Life Sciences</topic><topic>Coniferous forests</topic><topic>Conservation Biology/Ecology</topic><topic>Drought</topic><topic>Ecology</topic><topic>Ecosystems</topic><topic>Forest & brush fires</topic><topic>Forest fires</topic><topic>Forest management</topic><topic>Forests</topic><topic>Landscape Ecology</topic><topic>Life Sciences</topic><topic>MODIS</topic><topic>Monsoon forecasting</topic><topic>Monsoon precipitation</topic><topic>Monsoons</topic><topic>Pine</topic><topic>Pinus roxburghii</topic><topic>Population distribution</topic><topic>Precipitation</topic><topic>Precipitation forecasting</topic><topic>Regression models</topic><topic>Research Article</topic><topic>Weather forecasting</topic><topic>Wind</topic><topic>Winter precipitation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Singh, Ripu Daman</creatorcontrib><creatorcontrib>Gumber, Surabhi</creatorcontrib><creatorcontrib>Sundriyal, R. 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2
), a Himalayan state of India. Using fire incidence data of 19 years (2002–2020) generated by MODIS, we analysed the factors which drive temporal and spatial patterns of fire in the region. The fire incidence data were organized by 24 forest divisions, the unit of state forest management and administration. The standardized regression model showed that pre-monsoon temperature (March to May or mid-June), proportional area of the forest division under chir pine (
Pinus roxburghii
) forest (positive effect), and pre-monsoon and winter precipitation (negative effect) accounted for 56% of the variance in fire incidence density (FID). The pre-monsoon temperature (warmer) and precipitation (lower) were significantly different in 2009, 2012, 2016 and 2019, the years with high FID (average 54.9 fire/100 km
2
) than the rest of years with low FID (average 20.9 fire/100 km
2
). During the two decades of warming, high FID (> 30 incidence per year /100 km
2
) occurred after every three to four years, and fire peaks tended to increase with time. The study suggests that effective fire management can be attained by improving pre-monsoon precipitation forecasting and targeting forest compartments with a higher occurrence of chir pine and fire-vulnerable oaks. Furthermore, since fires are human-ignited, periodical analysis of changes in population distribution and communities’ dependence on forests would need to be conducted.</abstract><cop>New Delhi</cop><pub>Springer India</pub><pmid>37362779</pmid><doi>10.1007/s42965-023-00306-9</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2875-2664</orcidid><orcidid>https://orcid.org/0000-0003-3139-9301</orcidid><orcidid>https://orcid.org/0000-0003-2438-9041</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Tropical ecology, 2024-03, Vol.65 (1), p.32-42 |
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| language | eng |
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| source | SpringerLink Journals |
| subjects | Agricultural practices Biodiversity Biomedical and Life Sciences Coniferous forests Conservation Biology/Ecology Drought Ecology Ecosystems Forest & brush fires Forest fires Forest management Forests Landscape Ecology Life Sciences MODIS Monsoon forecasting Monsoon precipitation Monsoons Pine Pinus roxburghii Population distribution Precipitation Precipitation forecasting Regression models Research Article Weather forecasting Wind Winter precipitation |
| title | Chir pine forest and pre-monsoon drought determine spatial, and temporal patterns of forest fires in Uttarakhand Himalaya |
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