未来气候情景下太平洋西北部针叶树林分承载力

IF 1.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Natural Resource Modeling Pub Date : 2023-07-02 DOI:10.1111/nrm.12381
R. Heiderman, Mark J. Kimsey
{"title":"未来气候情景下太平洋西北部针叶树林分承载力","authors":"R. Heiderman, Mark J. Kimsey","doi":"10.1111/nrm.12381","DOIUrl":null,"url":null,"abstract":"Maximum stand density index (SDIMAX) represents the carrying capacity of a forest stand based on the relationship between the number of trees and their size. Plot‐level inventory data provided through a collaborative network of federal, state, and private forest management groups were utilized to develop SDIMAX models for important Pacific Northwest conifers of western Washington and Oregon, USA. The influence of site‐specific climatic and environmental variables was explored within an ensemble learning model. Future climate projections based on global circulation models under different representative CO2 concentration pathways (RCP 4.5 and RCP 8.5) and timeframes (2050s and 2080s) were utilized in a space‐for‐time substitution to understand potential shifts in modeled SDIMAX. A majority of the region showed decreases in carrying capacity under future climate conditions. Modeled mean SDIMAX decreased 5.4% and 11.4% for Douglas‐fir (Pseudotsuga menziesii (Mirb.) Franco) dominated forests and decreased 6.6% and 8.9% for western hemlock (Tsuga heterophylla (Raf.) Sarg.) and Pacific silver fir (Abies amabilis), dominated forests under the RCP 4.5 in the 2050s and RCP 8.5 in the 2080s, respectively. Projected future conditions often fall outside the range of any contemporary climate profile, resulting in what may be referred to as extramural conditions. Within the study region, 45% and 46% of climate variables included in the final model were extramural for the Douglas‐fir and hemlock models, respectively, under RCP 8.5 in the 2080s. Although extrapolating beyond the range of input data is not appropriate and many unknowns remain regarding future climate projections, these results allow for general interpretations of the direction and magnitude of potential shifts in forest carrying capacity.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pacific Northwest conifer forest stand carrying capacity under future climate scenarios\",\"authors\":\"R. Heiderman, Mark J. Kimsey\",\"doi\":\"10.1111/nrm.12381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Maximum stand density index (SDIMAX) represents the carrying capacity of a forest stand based on the relationship between the number of trees and their size. Plot‐level inventory data provided through a collaborative network of federal, state, and private forest management groups were utilized to develop SDIMAX models for important Pacific Northwest conifers of western Washington and Oregon, USA. The influence of site‐specific climatic and environmental variables was explored within an ensemble learning model. Future climate projections based on global circulation models under different representative CO2 concentration pathways (RCP 4.5 and RCP 8.5) and timeframes (2050s and 2080s) were utilized in a space‐for‐time substitution to understand potential shifts in modeled SDIMAX. A majority of the region showed decreases in carrying capacity under future climate conditions. Modeled mean SDIMAX decreased 5.4% and 11.4% for Douglas‐fir (Pseudotsuga menziesii (Mirb.) Franco) dominated forests and decreased 6.6% and 8.9% for western hemlock (Tsuga heterophylla (Raf.) Sarg.) and Pacific silver fir (Abies amabilis), dominated forests under the RCP 4.5 in the 2050s and RCP 8.5 in the 2080s, respectively. Projected future conditions often fall outside the range of any contemporary climate profile, resulting in what may be referred to as extramural conditions. Within the study region, 45% and 46% of climate variables included in the final model were extramural for the Douglas‐fir and hemlock models, respectively, under RCP 8.5 in the 2080s. Although extrapolating beyond the range of input data is not appropriate and many unknowns remain regarding future climate projections, these results allow for general interpretations of the direction and magnitude of potential shifts in forest carrying capacity.\",\"PeriodicalId\":49778,\"journal\":{\"name\":\"Natural Resource Modeling\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Natural Resource Modeling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1111/nrm.12381\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Resource Modeling","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1111/nrm.12381","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Pacific Northwest conifer forest stand carrying capacity under future climate scenarios
Maximum stand density index (SDIMAX) represents the carrying capacity of a forest stand based on the relationship between the number of trees and their size. Plot‐level inventory data provided through a collaborative network of federal, state, and private forest management groups were utilized to develop SDIMAX models for important Pacific Northwest conifers of western Washington and Oregon, USA. The influence of site‐specific climatic and environmental variables was explored within an ensemble learning model. Future climate projections based on global circulation models under different representative CO2 concentration pathways (RCP 4.5 and RCP 8.5) and timeframes (2050s and 2080s) were utilized in a space‐for‐time substitution to understand potential shifts in modeled SDIMAX. A majority of the region showed decreases in carrying capacity under future climate conditions. Modeled mean SDIMAX decreased 5.4% and 11.4% for Douglas‐fir (Pseudotsuga menziesii (Mirb.) Franco) dominated forests and decreased 6.6% and 8.9% for western hemlock (Tsuga heterophylla (Raf.) Sarg.) and Pacific silver fir (Abies amabilis), dominated forests under the RCP 4.5 in the 2050s and RCP 8.5 in the 2080s, respectively. Projected future conditions often fall outside the range of any contemporary climate profile, resulting in what may be referred to as extramural conditions. Within the study region, 45% and 46% of climate variables included in the final model were extramural for the Douglas‐fir and hemlock models, respectively, under RCP 8.5 in the 2080s. Although extrapolating beyond the range of input data is not appropriate and many unknowns remain regarding future climate projections, these results allow for general interpretations of the direction and magnitude of potential shifts in forest carrying capacity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Natural Resource Modeling
Natural Resource Modeling 环境科学-环境科学
CiteScore
3.50
自引率
6.20%
发文量
28
审稿时长
>36 weeks
期刊介绍: Natural Resource Modeling is an international journal devoted to mathematical modeling of natural resource systems. It reflects the conceptual and methodological core that is common to model building throughout disciplines including such fields as forestry, fisheries, economics and ecology. This core draws upon the analytical and methodological apparatus of mathematics, statistics, and scientific computing.
期刊最新文献
Predicting soil hydraulic conductivity using random forest, SVM, and LSSVM models The role of environmental tax in guiding global climate policies to mitigate climate changes in European region Predicting gully formation: An approach for assessing susceptibility and future risk Research on the impact of leadership on improving urban water efficiency and water conservation policies Assessing the load capacity curve hypothesis considering the green energy transition, banking sector expansion, and import price of crude oil in the United States
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1