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预测美国森林管理、市场及碳固存对高影响气候情景的响应。

Projecting U.S. forest management, market, and carbon sequestration responses to a high-impact climate scenario.

作者信息

Baker Justin S, Van Houtven George, Phelan Jennifer, Latta Gregory, Clark Christopher M, Austin Kemen G, Sodiya Olakunle E, Ohrel Sara B, Buckley John, Gentile Lauren E, Martinich Jeremy

机构信息

Dept. of Forestry and Environmental Resources, North Carolina State University, 2800 Faucette Dr, Raleigh, NC 27607, United States of America.

RTI International, 3040 East Cornwallis Rd., Research Triangle Park, NC 27709, United States of America.

出版信息

For Policy Econ. 2022 Dec 28;147:1-17. doi: 10.1016/j.forpol.2022.102898.

DOI:10.1016/j.forpol.2022.102898
PMID:36923688
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10013705/
Abstract

The impact of climate change on forest ecosystems remains uncertain, with wide variation in potential climate impacts across different radiative forcing scenarios and global circulation models, as well as potential variation in forest productivity impacts across species and regions. This study uses an empirical forest composition model to estimate the impact of climate factors (temperature and precipitation) and other environmental parameters on forest productivity for 94 forest species across the conterminous United States. The composition model is linked to a dynamic optimization model of the U.S. forestry sector to quantify economic impacts of a high warming scenario (Representative Concentration Pathway 8.5) under six alternative climate projections and two socioeconomic scenarios. Results suggest that forest market impacts and consumer impacts could range from relatively large losses (-$2.6 billion) to moderate gain ($0.2 billion) per year across climate scenarios. Temperature-induced higher mortality and lower productivity for some forest types and scenarios, coupled with increasing economic demands for forest products, result in forest inventory losses by end of century relative to the current climate baseline (3%-23%). Lower inventories and reduced carbon sequestration capacity result in additional economic losses of up to approximately $4.1 billion per year. However, our results also highlight important adaptation mechanisms, such forest type changes and shifts in regional mill capacity that could reduce the impact of high impact climate scenarios.

摘要

气候变化对森林生态系统的影响仍不确定,不同辐射强迫情景和全球环流模型下潜在的气候影响差异很大,而且不同物种和地区的森林生产力影响也可能存在差异。本研究使用一个经验性森林组成模型,来估算气候因素(温度和降水)及其他环境参数对美国本土94种森林物种的森林生产力的影响。该组成模型与美国林业部门的动态优化模型相联系,以量化在六种替代气候预测和两种社会经济情景下,高变暖情景(代表性浓度路径8.5)的经济影响。结果表明,在不同气候情景下,森林市场影响和消费者影响每年可能从相对较大的损失(-26亿美元)到适度的收益(2亿美元)不等。某些森林类型和情景下,温度升高导致更高的死亡率和更低的生产力,再加上对林产品的经济需求不断增加,到本世纪末,相对于当前气候基线,森林资源存量将减少(3%-23%)。森林资源存量减少和碳固存能力降低,每年将导致高达约41亿美元的额外经济损失。然而,我们的研究结果也凸显了重要的适应机制,如森林类型变化和区域工厂产能转移,这可能会降低高影响气候情景的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/909f0676af9c/nihms-1873333-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/b42ab004b479/nihms-1873333-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/aa6239508cf2/nihms-1873333-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/50797d754609/nihms-1873333-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/d282fce1bc57/nihms-1873333-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/05acdffe54b8/nihms-1873333-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/bd42e2294168/nihms-1873333-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/72e855900b3a/nihms-1873333-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/a4a6f77d1556/nihms-1873333-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/8c754cf8df75/nihms-1873333-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/909f0676af9c/nihms-1873333-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/b42ab004b479/nihms-1873333-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/aa6239508cf2/nihms-1873333-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/50797d754609/nihms-1873333-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/d282fce1bc57/nihms-1873333-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/05acdffe54b8/nihms-1873333-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/bd42e2294168/nihms-1873333-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/72e855900b3a/nihms-1873333-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/a4a6f77d1556/nihms-1873333-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/8c754cf8df75/nihms-1873333-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2159/10013705/909f0676af9c/nihms-1873333-f0010.jpg

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