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Modelling forest carbon stock changes as affected by harvest and natural disturbances. II. EU-level analysis

Overview of attention for article published in Carbon Balance and Management, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

policy
2 policy sources
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3 X users

Citations

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36 Dimensions

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100 Mendeley
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Title
Modelling forest carbon stock changes as affected by harvest and natural disturbances. II. EU-level analysis
Published in
Carbon Balance and Management, August 2016
DOI 10.1186/s13021-016-0059-4
Pubmed ID
Authors

Roberto Pilli, Giacomo Grassi, Werner A. Kurz, Jose V. Moris, Raúl Abad Viñas

Abstract

Forests and the forest sector may play an important role in mitigating climate change. The Paris Agreement and the recent legislative proposal to include the land use sector in the EU 2030 climate targets reflect this expectation. However, greater confidence on estimates from national greenhouse gas inventories (GHGI) and more comprehensive analyses of mitigation options are needed to seize this mitigation potential. The aim of this paper is to provide a tool at EU level for verifying the EU GHGI and for simulating specific policy and forest management scenarios. Therefore, the Carbon Budget Model (CBM) was applied for an integrated assessment of the EU forest carbon (C) balance from 2000 to 2012, including: (i) estimates of the C stock and net CO2 emissions for forest management (FM), afforestation/reforestation (AR) and deforestation (D), covering carbon in both the forest and the harvest wood product (HWP) pools; (ii) an overall analysis of the C dynamics associated with harvest and natural disturbances (mainly storms and fires); (iii) a comparison of our estimates with the data reported in the EU GHGI. Overall, the average annual FM sink (-365 Mt CO2 year(-1)) estimated by the CBM in the period 2000-2012 corresponds to about 7 % of total GHG emissions at the EU level for the same period (excluding land use, land-use change and forestry). The HWP pool sink (-44 Mt CO2 year(-1)) contributes an additional 1 %. Emissions from D (about 33 Mt CO2 year(-1)) are more than compensated by the sink in AR (about 43 Mt CO2 year(-1) over the period). For FM, the estimates from the CBM were about 8 % lower than the EU GHGI, a value well within the typical uncertainty range of the EU forest sink estimates. For AR and D the match with the EU GHGI was nearly perfect (difference <±2 % in the period 2008-2012). Our analysis on harvest and natural disturbances shows that: (i) the impact of harvest is much greater than natural disturbances but, because of salvage logging (often very relevant), the impact of natural disturbances is often not easily distinguishable from the impact of harvest, and (ii) the impact of storms on the biomass C stock is 5-10 times greater than fires, but while storms cause only indirect emissions (i.e., a transfer of C from living biomass to dead organic matter), fires cause both direct and indirect emissions. This study presents the application of a consistent methodological approach, based on an inventory-based model, adapted to the forest management conditions of EU countries. The approach captures, with satisfactory detail, the C sink reported in the EU GHGI and the country-specific variability due to harvest, natural disturbances and land-use changes. To our knowledge, this is the most comprehensive study of its kind at EU level, i.e., including all the forest pools, HWP and natural disturbances, and a comparison with the EU GHGI. The results provide the basis for possible future policy-relevant applications of this model, e.g., as a tool to support GHGIs (e.g., on accounting for natural disturbances) and to verify the EU GHGI, and for the simulation of specific scenarios at EU level.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 15%
Student > Ph. D. Student 13 13%
Student > Master 11 11%
Student > Bachelor 10 10%
Other 8 8%
Other 14 14%
Unknown 29 29%
Readers by discipline Count As %
Environmental Science 34 34%
Agricultural and Biological Sciences 10 10%
Earth and Planetary Sciences 4 4%
Engineering 4 4%
Economics, Econometrics and Finance 4 4%
Other 12 12%
Unknown 32 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 June 2023.
All research outputs
#4,406,002
of 26,017,215 outputs
Outputs from Carbon Balance and Management
#76
of 232 outputs
Outputs of similar age
#68,538
of 353,933 outputs
Outputs of similar age from Carbon Balance and Management
#1
of 6 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 232 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.1. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,933 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them