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BackgroundThe European Union (EU) has committed to achieve climate neutrality by 2050. This requires a rapid reduction of greenhouse gas (GHG) emissions and ensuring that any remaining emissions are balanced through CO2 removals. Forests play a crucial role in this plan: they are currently the main option for removing CO2 from the atmosphere and additionally, wood use can store carbon durably and help reduce fossil emissions. To stop and reverse the decline of the forest carbon sink, the EU has recently revised the regulation on land use, land-use change and forestry (LULUCF), and set a target of − 310 Mt CO2e net removals for the LULUCF sector in 2030.ResultsIn this study, we clarify the role of common concepts in forest management – net annual increment, harvest and mortality – in determining the forest sink. We then evaluate to what extent the forest sink is on track to meet the climate goals of the EU. For this assessment we use data from the latest national GHG inventories and a forest model (Carbon Budget Model). Our findings indicate that on the EU level, the recent decrease in increment and the increase in harvest and mortality are causing a rapid drop in the forest sink. Furthermore, continuing the past forest management practices is projected to further decrease the sink. Finally, we discuss options for enhancing the sinks through forest management while taking into account adaptation and resilience.ConclusionsOur findings show that the EU forest sink is quickly developing away from the EU climate targets. Stopping and reversing this trend requires rapid implementation of climate-smart forest management, with improved and more timely monitoring of GHG fluxes. This enhancement is crucial for tracking progress towards the EU’s climate targets, where the role of forests has become – and is expected to remain – more prominent than ever before.

Here we provide a point-by-point response to these remarks, in particular on the potential effects of the inconsistencies in the time series of the Global Forest Change (GFC) dataset4, on the potential misattribution of natural disturbances, on the relationship with country statistics and on the effect of our findings on the carbon balance of European Union (EU) forests. [...]in the technical blog of the Global Forest Watch website, under the question \"Is the data methodology consistent throughout the time series?\" it is clearly stated that \"The current tree cover loss data uses one algorithm covering 2001-2010 and another covering 2011-2018\"7. Furthermore, where a more complete dataset is used than the one used by Palahí et al.2, the Global Forest Watch website shows that the increase in area of GFC tree cover loss due to forestry (large-scale forestry operations occurring within managed forests and tree plantations7) in the period 2016-2018 compared with 2011-2015 in large countries of the Northern Hemisphere such as Canada, China, Russia and the United States (+24%, +22%, +3% and +16%, respectively) is on average (+15%) about four times smaller than that reported for the EU (+59%). Google Earth aerial photographs and very-high-resolution images were used to detect the harvesting, while cross-checks with time series ofLandsat NDVI (normalized difference vegetation index) resolved the precise timing of the harvesting operation (Fig. 2d): if a drop in NDVI was observed in the Landsat NDVI time series, the year of disturbance was assigned.

BackgroundThe credibility and effectiveness of country climate targets under the Paris Agreement requires that, in all greenhouse gas (GHG) sectors, the accounted mitigation outcomes reflect genuine deviations from the type and magnitude of activities generating emissions in the base year or baseline. This is challenging for the forestry sector, as the future net emissions can change irrespective of actual management activities, because of age-related stand dynamics resulting from past management and natural disturbances. The solution implemented under the Kyoto Protocol (2013–2020) was accounting mitigation as deviation from a projected (forward-looking) “forest reference level”, which considered the age-related dynamics but also allowed including the assumed future implementation of approved policies. This caused controversies, as unverifiable counterfactual scenarios with inflated future harvest could lead to credits where no change in management has actually occurred, or conversely, failing to reflect in the accounts a policy-driven increase in net emissions. Instead, here we describe an approach to set reference levels based on the projected continuation of documented historical forest management practice, i.e. reflecting age-related dynamics but not the future impact of policies. We illustrate a possible method to implement this approach at the level of the European Union (EU) using the Carbon Budget Model.ResultsUsing EU country data, we show that forest sinks between 2013 and 2016 were greater than that assumed in the 2013–2020 EU reference level under the Kyoto Protocol, which would lead to credits of 110–120 Mt CO2/year (capped at 70–80 Mt CO2/year, equivalent to 1.3% of 1990 EU total emissions). By modelling the continuation of management practice documented historically (2000–2009), we show that these credits are mostly due to the inclusion in the reference levels of policy-assumed harvest increases that never materialized. With our proposed approach, harvest is expected to increase (12% in 2030 at EU-level, relative to 2000–2009), but more slowly than in current forest reference levels, and only because of age-related dynamics, i.e. increased growing stocks in maturing forests.ConclusionsOur science-based approach, compatible with the EU post-2020 climate legislation, helps to ensure that only genuine deviations from the continuation of historically documented forest management practices are accounted toward climate targets, therefore enhancing the consistency and comparability across GHG sectors. It provides flexibility for countries to increase harvest in future reference levels when justified by age-related dynamics. It offers a policy-neutral solution to the polarized debate on forest accounting (especially on bioenergy) and supports the credibility of forest sector mitigation under the Paris Agreement.

Background The Irish Forestry greenhouse gas (GHG) profile is undergoing a transition from a net sink to net emission because of persisting emissions from organic soils, an increase in harvest and shifts in the age class structure of plantation forests. The forestry GHG trend diverges from the required National and European Union (EU) policy pathway for land use land use change and forestry (LULUCF) and agriculture aimed at halving emissions by 2030 and achieving carbon neutrality by 2050. A recalibrated version of the Carbon Budget Model of the Canadian Forest Service (CBM-CFS3) was used to assess the impact of identified national forest policy measures on the forest GHG profile over the short to long term. Results An analysis of projected scenarios revealed that, under current silvicultural practices and afforestation policies (with existing measures—WEMs), Irish forests will continue to be a long-term emission beyond 2070 unless harvest rates and management practices are adjusted to negate the adverse impact of emissions from organic soils and fluctuations in historic afforestation rates. The implementation of additional measures (WAM) suggests that the forest sink can be sustained if harvest rates exceed 75% of the net annual increment (NAI), additional afforestation targets are met and if plantation rotation age is increased. Although additional afforestation and a reduction in deforestation is required to meet long-term carbon–neutral goals, the implementation of these policies has a minimal short-term impact on the 2030 targets set out under the National Climate Change Plan (CAP 24) and the revised EU LULUCF regulation (841/2023). Conclusion The results show that the extension of rotation age and associated reductions in harvest levels will have the greatest short-term impact on climate change mitigation, which can be delivered at a negative marginal abatement cost. However, even if WAM forest measures are implemented, Ireland is unlikely to meet the National and EU LULUCF targets by 2030 because of a decreasing forest sink.

Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).

BackgroundThe contribution of EU forests to climate change mitigation in 2021–2025 is assessed through the Forest Reference Levels (FRLs). The FRL is a projected country-level benchmark of net greenhouse gas emissions against which the future net emissions will be compared. The FRL models the hypothetical development of EU forest carbon sink if the historical management practices were continued, taking into account age dynamics. The Member States’ FRLs have been recently adopted by the European Commission with the delegated Regulation (EU) 2021/268 amending the Regulation (EU) 2018/841. Considering the complexity of interactions between forest growth, management and carbon fluxes, there is a need to understand uncertainties linked to the FRL determination.ResultsWe assessed the methodologies behind the modelled FRLs and evaluated the foreseen impact of continuation of management practices and age dynamics on the near-future EU27 + UK forest carbon sink. Most of the countries implemented robust modelling approaches for simulating management practices and age dynamics within the FRL framework, but faced several challenges in ensuring consistency with historical estimates. We discuss that the projected 16% increase in harvest in 2021–2025 compared to 2000–2009, mostly attributed to age dynamics, is associated to a decline of 18% of forest sink (26% for living biomass only).ConclusionsWe conclude that the FRL exercise was challenging but improved the modelling capacity and data availability at country scale. The present study contributes to increase the transparency of the implementation of forest-related EU policies and provides evidence-based support to future policy development.

Forests provide a series of ecosystem services that are crucial to our society. In the European Union (EU), forests account for approximately 38% of the total land surface 1 . These forests are important carbon sinks, and their conservation efforts are vital for the EU’s vision of achieving climate neutrality by 2050 2 . However, the increasing demand for forest services and products, driven by the bioeconomy, poses challenges for sustainable forest management. Here we use fine-scale satellite data to observe an increase in the harvested forest area (49 per cent) and an increase in biomass loss (69 per cent) over Europe for the period of 2016–2018 relative to 2011–2015, with large losses occurring on the Iberian Peninsula and in the Nordic and Baltic countries. Satellite imagery further reveals that the average patch size of harvested area increased by 34 per cent across Europe, with potential effects on biodiversity, soil erosion and water regulation. The increase in the rate of forest harvest is the result of the recent expansion of wood markets, as suggested by econometric indicators on forestry, wood-based bioenergy and international trade. If such a high rate of forest harvest continues, the post-2020 EU vision of forest-based climate mitigation may be hampered, and the additional carbon losses from forests would require extra emission reductions in other sectors in order to reach climate neutrality by 2050 3 . Fine-scale satellite data are used to quantify forest harvest rates in 26 European countries, finding an increase in harvested forest area of 49% and an increase in biomass loss of 69% between 2011–2015 and 2016–2018.

Background 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 CO 2 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. Results Overall, the average annual FM sink (−365 Mt CO 2 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 CO 2 year −1 ) contributes an additional 1 %. Emissions from D (about 33 Mt CO 2 year −1 ) are more than compensated by the sink in AR (about 43 Mt CO 2 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. Conclusions 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.

A recent article by Luyssaert et al. (Nature 562:259–262, 2018) analyses the climate impact of forest management in the European Union, considering both biogeochemical (i.e., greenhouse gases, GHG) and biophysical (e.g., albedo, transpiration, etc.) effects. Based on their findings, i.e. that additional net overall climate benefits from forest management would be modest, the authors conclude that the EU “should not rely on forest management to mitigate climate change”. We first explain that most of the additional EU GHG mitigation effort by 2030 is expected to come from emission reductions and only a very small part from forestry, even when forest bioenergy is allowed for. Nevertheless, the inclusion of forest management in climate change mitigation strategies is key to identifying the country-specific optimal mix, in terms of overall GHG balance, between strategies focused on conserving and/or enhancing the sink and strategies focused on using more wood to reduce emissions in other GHG sectors. Then, while acknowledging the importance that biophysical effects have on the climate, especially at the local and seasonal scale, we argue that the net annual biophysical climate impact of forest management in Europe remains more uncertain than the net CO2 impact. This has not been adequately emphasized by Luyssaert et al. (2018), leading to conclusions on the net overall climate impact of forest management that we consider premature and applied to a partially biased perception of European policy towards forestry and climate change. To avoid further confusion in the debate on how forestry may contribute to mitigating climate change, a more constructive dialogue between the scientific community and policy makers is needed.

Background According to the post-2012 rules under the Kyoto protocol, developed countries that are signatories to the protocol have to estimate and report the greenhouse gas (GHG) emissions and removals from forest management (FM), with the option to exclude the emissions associated to natural disturbances, following the Intergovernmental Panel on Climate Change (IPCC) guidelines. To increase confidence in GHG estimates, the IPCC recommends performing verification activities, i.e. comparing country data with independent estimates. However, countries currently conduct relatively few verification efforts. The aim of this study is to implement a consistent methodological approach using the Carbon Budget Model (CBM) to estimate the net CO 2 emissions from FM in 26 European Union (EU) countries for the period 2000–2012, including the impacts of natural disturbances. We validated our results against a totally independent case study and then we compared the CBM results with the data reported by countries in their 2014 Greenhouse Gas Inventories (GHGIs) submitted to the United Nations Framework Convention on Climate Change (UNFCCC). Results The match between the CBM results and the GHGIs was good in nine countries (i.e. the average of our results is within ±25 % compared to the GHGI and the correlation between CBM and GHGI is significant at P < 0.05) and partially good in ten countries. When the comparison was not satisfactory, in most cases we were able to identify possible reasons for these discrepancies, including: (1) a different representation of the interannual variability, e.g. where the GHGIs used the stock-change approach; (2) different assumptions for non-biomass pools, and for CO 2 emissions from fires and harvest residues. In few cases, further analysis will be needed to identify any possible inappropriate data used by the CBM or problems in the GHGI. Finally, the frequent updates to data and methods used by countries to prepare GHGI makes the implementation of a consistent modeling methodology challenging. Conclusions This study indicates opportunities to use the CBM as tool to assist countries in estimating forest carbon dynamics, including the impact of natural disturbances, and to verify the country GHGIs at the EU level, consistent with the IPCC guidelines. A systematic comparison of the CBM with the GHGIs will certainly require additional efforts—including close cooperation between modelers and country experts. This approach should be seen as a necessary step in the process of continuous improvement of GHGIs, because it may help in identifying possible errors and ultimately in building confidence in the estimates reported by the countries.