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气候变化下森林碳通量和储量不确定性的量化及其在区域明确决策中的应用:芬兰的案例研究

Quantification of forest carbon flux and stock uncertainties under climate change and their use in regionally explicit decision making: Case study in Finland.

作者信息

Junttila Virpi, Minunno Francesco, Peltoniemi Mikko, Forsius Martin, Akujärvi Anu, Ojanen Paavo, Mäkelä Annikki

机构信息

Finnish Environment Institute, Latokartanonkaari 11, 00790, Helsinki, Finland.

Department of Forest Sciences, University of Helsinki, P.O.Box 27, 00014, Helsinki, Finland.

出版信息

Ambio. 2023 Nov;52(11):1716-1733. doi: 10.1007/s13280-023-01906-4. Epub 2023 Aug 12.

DOI:10.1007/s13280-023-01906-4
PMID:37572230
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10562356/
Abstract

Uncertainties are essential, yet often neglected, information for evaluating the reliability in forest carbon balance projections used in national and regional policy planning. We analysed uncertainties in the forest net biome exchange (NBE) and carbon stocks under multiple management and climate scenarios with a process-based ecosystem model. Sampled forest initial state values, model parameters, harvest levels and global climate models (GCMs) served as inputs in Monte Carlo simulations, which covered forests of the 18 regions of mainland Finland over the period 2015-2050. Under individual scenarios, the results revealed time- and region-dependent variability in the magnitude of uncertainty and mean values of the NBE projections. The main sources of uncertainty varied with time, by region and by the amount of harvested wood. Combinations of uncertainties in the representative concentration pathways scenarios, GCMs, forest initial values and model parameters were the main sources of uncertainty at the beginning, while the harvest scenarios dominated by the end of the simulation period, combined with GCMs and climate scenarios especially in the north. Our regionally explicit uncertainty analysis was found a useful approach to reveal the variability in the regional potentials to reach a policy related, future target level of NBE, which is important information when planning realistic and regionally fair national policy actions.

摘要

不确定性是评估国家和区域政策规划中森林碳平衡预测可靠性的重要信息,但往往被忽视。我们使用基于过程的生态系统模型,分析了多种管理和气候情景下森林净生物群落交换(NBE)和碳储量的不确定性。抽样的森林初始状态值、模型参数、采伐水平和全球气候模型(GCMs)作为蒙特卡洛模拟的输入,该模拟涵盖了2015 - 2050年芬兰大陆18个地区的森林。在各个情景下,结果揭示了NBE预测不确定性大小和平均值随时间和地区的变化。不确定性的主要来源随时间、地区以及采伐木材量而变化。在模拟初期,代表性浓度路径情景、全球气候模型、森林初始值和模型参数的不确定性组合是主要来源,而到模拟期末,采伐情景占主导地位,尤其在北部与全球气候模型和气候情景相结合。我们的区域明确不确定性分析被认为是一种有用的方法,可揭示区域在实现与政策相关的未来NBE目标水平方面潜力的变异性,这是规划现实且区域公平的国家政策行动时的重要信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/41e151a4e681/13280_2023_1906_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/ccbda5233b9b/13280_2023_1906_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/910674455a37/13280_2023_1906_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/925e279da48d/13280_2023_1906_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/b6300f841b2a/13280_2023_1906_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/37bc2d783a1b/13280_2023_1906_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/41e151a4e681/13280_2023_1906_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/ccbda5233b9b/13280_2023_1906_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/910674455a37/13280_2023_1906_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/925e279da48d/13280_2023_1906_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/b6300f841b2a/13280_2023_1906_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/37bc2d783a1b/13280_2023_1906_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5faa/10562356/41e151a4e681/13280_2023_1906_Fig6_HTML.jpg

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