Christopher M Wade, Justin S Baker, Gregory Latta, Sara B Ohrel, Justine Allpress
{"title":"预测美国人工林可能扩张的空间分布。","authors":"Christopher M Wade, Justin S Baker, Gregory Latta, Sara B Ohrel, Justine Allpress","doi":"10.1093/jofore/fvz054","DOIUrl":null,"url":null,"abstract":"<p><p>As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources is expected to increase. With the increased use of plantation practices, it is important to understand the influence that forest plot characteristics have on the likelihood of where these practices are occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. This study estimates a spatially explicit logistical regression function to assess the likelihood that forest plots will be planted based on physical, climate, and economic factors. The empirical results are used to project the potential spatial distribution of forest planting, at the intensive and extensive land-use margins, across illustrative future scenarios. Results from this analysis offer insight into the factors that have driven forest planting in the United States historically and the potential distribution of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration).</p>","PeriodicalId":15821,"journal":{"name":"Journal of Forestry","volume":"117 6","pages":"560-578"},"PeriodicalIF":1.8000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a0/82/nihms-1564530.PMC7061452.pdf","citationCount":"0","resultStr":"{\"title\":\"Projecting the Spatial Distribution of Possible Planted Forest Expansion in the United States.\",\"authors\":\"Christopher M Wade, Justin S Baker, Gregory Latta, Sara B Ohrel, Justine Allpress\",\"doi\":\"10.1093/jofore/fvz054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources is expected to increase. With the increased use of plantation practices, it is important to understand the influence that forest plot characteristics have on the likelihood of where these practices are occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. This study estimates a spatially explicit logistical regression function to assess the likelihood that forest plots will be planted based on physical, climate, and economic factors. The empirical results are used to project the potential spatial distribution of forest planting, at the intensive and extensive land-use margins, across illustrative future scenarios. Results from this analysis offer insight into the factors that have driven forest planting in the United States historically and the potential distribution of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration).</p>\",\"PeriodicalId\":15821,\"journal\":{\"name\":\"Journal of Forestry\",\"volume\":\"117 6\",\"pages\":\"560-578\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a0/82/nihms-1564530.PMC7061452.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forestry\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1093/jofore/fvz054\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forestry","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1093/jofore/fvz054","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
Projecting the Spatial Distribution of Possible Planted Forest Expansion in the United States.
As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources is expected to increase. With the increased use of plantation practices, it is important to understand the influence that forest plot characteristics have on the likelihood of where these practices are occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. This study estimates a spatially explicit logistical regression function to assess the likelihood that forest plots will be planted based on physical, climate, and economic factors. The empirical results are used to project the potential spatial distribution of forest planting, at the intensive and extensive land-use margins, across illustrative future scenarios. Results from this analysis offer insight into the factors that have driven forest planting in the United States historically and the potential distribution of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration).
期刊介绍:
The Journal of Forestry is the most widely circulated scholarly forestry journal in the world. In print since 1902, the mission of the Journal of Forestry is to advance the profession of forestry by keeping forest management professionals informed about significant developments and ideas in the many facets of forestry. The Journal is published bimonthly: January, March, May, July, September, and November.