Trade-Offs for Climate-Smart Forestry in Europe Under Uncertain Future Climate

Forests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate-smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi-criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad-leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad-leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad-leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon-intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade-offs must be assessed when developing concrete strategies for climate-smart forestry

Impact on air quality from increasing cruise ship activity in Copenhagen port

The impact of the growing cruise ship industry on air quality levels was investigated at the port of Copenhagen, Denmark. In 2018, 345 cruise ships visited Copenhagen, emitting 291 tons of NO _x near the city centre. A spatiotemporal cruise ship emission inventory was developed for 2018 based on port list information, engine data, main and auxiliary engine power functions, and NO _x emission factors, and was implemented in the OML-Multi atmospheric dispersion model. Evident plume effects from the cruise ships, which were traced by introducing the concept of likely concentration contribution, were obtained in the modelled and measured concentrations at Langelinie Quay, which is the busiest cruise ship terminal in Copenhagen port. Hourly peak values of NO _x well above 200 μ g m ^−3 were obtained at the top of a residential building at Langelinie Quay. The emissions from cruise ships were increasing the annual concentration of NO _2 in the port area by up to 31% at ground level, and 86% 50 m above the ground in comparison to the urban background level. No exceedance of the European annual limit value of NO _2 was obtained. The short-term impact of cruise ships was more pronounced with local exceedances of the hourly European limit value for NO _2 . Increasing cruise ship activity in Copenhagen port leads to air quality deterioration on short time scales with implications for human health

Workshop on assessments of National Carbon Budgets within the Nordic Region:Current status and sensitivity to changes

The three-day workshop organized by the three Nordic research projects, ECOCLIM, LAGGE and SnowCarbo brought together scientists and other actors from Nordic countries to communicate and discuss research on carbon budget estimations in the Nordic region. Through presentations of most recent research in the field and following scientific discussions, the workshop contributed to strengthen the scientific basis of the identification and quantification of major natural carbon sinks in the Nordic region on which integrated climate change abatement and management strategies and policy decisions is formed from. This report summarizes presentations and discussions from the four thematic sessions, Observations of carbon sinks and sources, Modeling the carbon budget, Remote sensing data for carbon modeling, and Impacts of future climate and land use scenarios and gives an overview of the current status and knowledge on research on assessments of national carbon budgets as well as on projections and sensitivity to future changes in e.g. management and climate change in the Nordic Region

Using Free Air CO₂ Enrichment data to constrain land surface model projections of the terrestrial carbon cycle

International audiencePredicting the responses of terrestrial ecosystem carbon to future global change strongly relies on our ability to model accurately the underlying processes at a global scale. However, terrestrial biosphere models representing the carbon and nitrogen cycles and their interactions remain subject to large uncertainties, partly because of unknown or poorly constrained parameters. Parameter estimation is a powerful tool that can be used to optimise these parameters by confronting the model with observations. In this paper, we identify sensitive model parameters from a recent version of the ORgainzing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model that includes the nitrogen cycle. These sensitive parameters include ones involved in parameterisations controlling the impact of the nitrogen cycle on the carbon cycle and, in particular, the limitation of photosynthesis due to leaf nitrogen availability. We optimise these ORCHIDEE parameters against carbon flux data collected on sites from the FLUXNET network. However, optimising against present-day observations does not automatically give us confidence in future projections of the model, given that environmental conditions are likely to shift compared to the present day. Manipulation experiments give us a unique look into how the ecosystem may respond to future environmental changes. One such type of manipulation experiment, the Free Air CO2 Enrichment (FACE) experiment, provides a unique opportunity to assess vegetation response to increasing CO2 by providing data under ambient and elevated CO2 conditions. Therefore, to better capture the ecosystem response to increased CO2, we add the data from two FACE sites to our optimisations, in addition to the FLUXNET data. We use data from both CO2 conditions of FACE, which allows us to gain extra confidence in the model simulations using this set of parameters. We find that we are able to improve the magnitude of modelled productivity. Although we are unable to correct the interannual variability fully, we start to simulate possible progressive nitrogen limitation at one of the sites. Using an idealised simulation experiment based on increasing atmospheric CO2 by 1 % yr−1 over 100 years, we find that optimising against only FLUXNET data tends to imply a large fertilisation effect, whereas optimising against FLUXNET and FACE data (with information about nutrient limitation and acclimation of plants) decreases it significantly

Trade‐Offs for Climate‐Smart Forestry in Europe Under Uncertain Future Climate

Forests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate‐smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi‐criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad‐leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad‐leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad‐leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon‐intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade‐offs must be assessed when developing concrete strategies for climate‐smart forestry.Plain Language Summary: Forests help mitigate climate change by storing carbon and via avoided emissions when wood products replace more carbon‐intensive materials. At the same time, forests provide many other “ecosystem services (ESs)” to society. For example, they provide timber, habitat for various species, and they cool their surrounding regions. They are, however, also vulnerable to ongoing climate change. Forest management must consider all these aspects, which is particularly challenging considering the uncertainty about future climate. Here, we propose how this may be tackled by computing optimized forest management portfolios for Europe for a broad range of future climate pathways. Our results show that changes to forest composition are necessary. In particular, increased shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs. However, these increased shares also lead to decreases in harvest rates, posing a conflict between wood supply and demand. We further show that the mitigation potential of forests strongly depends on how carbon‐intensive the replaced materials are. Consequently, should these materials become “greener” due to new technologies, the importance of wood products in terms of climate change mitigation decreases. Our study highlights that we cannot optimize every aspect, but that trade‐offs between ESs need to be made.Key Points: Strategies for climate‐smart forestry under a range of climate scenarios always lead to trade‐offs between different ecosystem services (ESs). Higher shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs, but lead to decreased timber provision. The mitigation potential of forests strongly relies on substitution effects which depend on the carbon‐intensity of the alternative products.European Forest Institute (EFI) Networking Fund http://dx.doi.org/10.13039/501100013942Bayerisches Staatsministerium für Wissenschaft und Kunst, Bayerisches Netzwerk für Klimaforschung (BayKliF) http://dx.doi.org/10.13039/501100004563Swedish Research Council FormasGerman Federal Office for Agriculture and Food (BLE)https://doi.org/10.5281/zenodo.6667489https://doi.org/10.5281/zenodo.661295

Trade‐Offs for Climate‐Smart Forestry in Europe Under Uncertain Future Climate

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Evaluation of soil carbon dynamics after forest cover change in CMIP6 land models using chronosequences

International audienceLand surface models are used to provide global estimates of soil organic carbon (SOC) changes after past and future change land use change (LUC), in particular re-/deforestation. To evaluate how well the models capture decadal-scale changes in SOC after LUC, we provide the first consistent comparison of simulated time series of LUC by six land models all of which participated in the coupled model intercomparison project phase 6 (CMIP6) with soil carbon chronosequences (SCCs). For this comparison we use SOC measurements of adjacent plots at four high-quality data sites in temperate and tropical regions. We find that initial SOC stocks differ among models due to different approaches to represent SOC. Models generally meet the direction of SOC change after reforestation of cropland but the amplitude and rate of changes vary strongly among them. The normalized root mean square errors of the multi model mean range from 0.5 to 0.8 across sites and 0.1-0.7 when excluding outliers. Further, models simulate SOC losses after deforestation for crop or grassland too slow due to the lack of crop harvest impacts in the models or an overestimation of the SOC recovery on grassland. The representation of management, especially nitrogen levels is important to capture drops in SOC after land abandonment for forest regrowth. Crop harvest and fire management are important to match SOC dynamics but more difficult to quantify as SCC rarely report on these events. Based on our findings, we identify strengths and propose potential improvements of the applied models in simulating SOC changes after LUC

Author Correction: Trade-offs in using European forests to meet climate objectives

In this Letter, in “About 75% of this reduction is expected to come from emission reductions and the remaining 25% from land use, land-use change and forestry”, ‘25%’ should read ‘1%’ and '75%' should read '99%'. In the sentence “The carbon-sink-maximizing portfolio has a small negative effect on annual precipitation (−2 mm) and no effect on air temperature (Table 1)” the word ‘precipitation’ was omitted. Denmark was accidentally deleted during the conversion of Fig. 1. The original Letter has been corrected online

Trade-offs in using European forests to meet climate objectives

International audienc