Evidence map›Paper›PMID 37572230›Full record

ArticleAmbio2023

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

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

Erratum issuedAbstract read
In one paragraph

Article in Ambio, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Virpi JunttilaFinnish Environment Institute, Latokartanonkaari 11, 00790, Helsinki, Finland. virpi.junttila@syke.fi.ORCID http://orcid.org/0000-0003-4128-8568
Francesco MinunnoDepartment of Forest Sciences, University of Helsinki, P.O.Box 27, 00014, Helsinki, Finland.
Mikko PeltoniemiNatural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790, Helsinki, Finland.
Martin ForsiusFinnish Environment Institute, Latokartanonkaari 11, 00790, Helsinki, Finland.
Anu AkujärviFinnish Environment Institute, Latokartanonkaari 11, 00790, Helsinki, Finland.
Paavo OjanenDepartment of Forest Sciences, University of Helsinki, P.O.Box 27, 00014, Helsinki, Finland.
Annikki MäkeläDepartment of Forest Sciences, University of Helsinki, P.O.Box 27, 00014, Helsinki, Finland.

Funding

Academy of Finland 101000574Academy of Finland 312912Academy of Finland 335958Academy of Finland 344722Academy of Finland 345532Academy of Finland 347848BiodivERsA BiodivClim ERA-Net CofundFinnish Ministry of the Environment VN/28536/2020Finnish Ministry of the Environment VN/33334/2021Finnish Ministry of the Environment VN/5082/2020Horizon 2020 101000574Strategic Research Council 335958
6 · The paper itself

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.

Indexed as

CarbonCarbon CycleClimate ChangeDecision MakingForestsFinlandModels, TheoreticalUncertaintyCarbonClimate changeForest carbon dynamicsPolicy planningProcess-based modellingUncertainty quantification

Identifiers

PMID37572230
PMCPMC10562356

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.