Evaluating the productivity of four main tree species in Germany under climate change with static reduced models

International audienceAbstract Key messageWe present simple models of forest net primary production (NPP) in Germany that show increasing productivity, especially in mountainous areas, under warming unless water becomes a limiting factor. They can be used for spatially explicit, rapid climate impact assessment. ContextClimate impact studies largely rely on process-based forest models generally requiring detailed input data which are not everywhere available. AimsThis study aims to derive simple models with low data requirements which allow calculation of NPP and analysis of climate impacts using many climate scenarios at a large amount of sites. MethodsWe fitted regression functions to the output of simulation experiments conducted with the process-based forest model 4C at 2342 climate stations in Germany for four main tree species on four different soil types and two time periods, 1951–2006 and 2031–2060. ResultsThe regression functions showed a reasonable fit to measured NPP datasets. Temperature increase of up to 3 K leads to positive effects on NPP. In water-limited regions, this positive effect is dependent on the length of drought periods. The highest NPP increase occurs in mountainous regions. ConclusionRapid analyses, using reduced models as presented here, can complement more detailed analyses with process-based models. Especially for dry sites, we recommend further study of climate impacts with process-based models or detailed measurements

Integrating parameter uncertainty of a process-based model in assessments of climate change effects on forest productivity

The parameter uncertainty of process-based models has received little attention in climate change impact studies. This paper aims to integrate parameter uncertainty into simulations of climate change impacts on forest net primary productivity (NPP). We used either prior (uncalibrated) or posterior (calibrated using Bayesian calibration) parameter variations to express parameter uncertainty, and we assessed the effect of parameter uncertainty on projections of the process-based model 4C in Scots pine (Pinus sylvestris) stands under climate change. We compared the uncertainty induced by differences between climate models with the uncertainty induced by parameter variability and climate models together. The results show that the uncertainty of simulated changes in NPP induced by climate model and parameter uncertainty is substantially higher than the uncertainty of NPP changes induced by climate model uncertainty alone. That said, the direction of NPP change is mostly consistent between the simulations using the standard parameter setting of 4C and the majority of the simulations including parameter uncertainty. Climate change impact studies that do not consider parameter uncertainty may therefore be appropriate for projecting the direction of change, but not for quantifying the exact degree of change, especially if parameter combinations are selected that are particularly climate sensitive. We conclude that if a key objective in climate change impact research is to quantify uncertainty, parameter uncertainty as a major factor driving the degree of uncertainty of projections should be included

Fire, late frost, nun moth and drought risks in Germany's forests under climate change

Ongoing climate change affects growth and increases biotic and abiotic threats to Germany's forests. We analysed how these risks develop through the mid-century under a variety of climate change scenarios using the process-based forest model 4C. This model allows the calculation of indicators for fire danger, late frost risk for beech and oak, drought stress and nun moth risk. 4C was driven by a set of 4 simulations of future climate generated with the statistical model STARS and with 10 simulations of future climate based on EURO-CORDEX model simulations for the RCP2.6, RCP4.5 and RCP8.5 pathways. A set of about 70000 forest stands (Norway spruce, Scots pine, beech, oak, birch), based on the national forest inventory describing 98.4 % of the forest in Germany, was used together with data from a digital soil map. The changes and the range of changes were analysed by comparing results of a recent time period (1971–2005) and a scenario time period (2011–2045). All indicators showed higher risks for the scenario time period compared to the recent time period, except the late frost risk indicators, if averaged over all climate scenarios. The late frost risk for beech and oaks decreased for the main forest sites. Under recent climate conditions, the highest risk with regard to all five indicators was found to be in the Southwest Uplands and the northern part of Germany. The highest climate-induced uncertainty regarding the indicators for 2011–2045 is projected for the East Central Uplands and Northeast German Plain

Quantifying the impact of key factors on the carbon mitigation potential of managed temperate forests

Background: Forests mitigate climate change by reducing atmospheric CO2-concentrations through the carbon sink in the forest and in wood products, and substitution effects when wood products replace carbon-intensive materials and fuels. Quantifying the carbon mitigation potential of forests is highly challenging due to the influence of multiple important factors such as forest age and type, climate change and associated natural disturbances, harvest intensities, wood usage patterns, salvage logging practices, and the carbon-intensity of substituted products. Here, we developed a framework to quantify the impact of these factors through factorial simulation experiments with an ecosystem model at the example of central European (Bavarian) forests. Results: Our simulations showed higher mitigation potentials of young forests compared to mature forests, and similar ones in broad-leaved and needle-leaved forests. Long-lived wood products significantly contributed to mitigation, particularly in needle-leaved forests due to their wood product portfolio, and increased material usage of wood showed considerable climate benefits. Consequently, the ongoing conversion of needle-leaved to more broad-leaved forests should be accompanied by the promotion of long-lived products from broad-leaved species to maintain the product sink. Climate change (especially increasing disturbances) and decarbonization were among the most critical factors influencing mitigation potentials and introduced substantial uncertainty. Nevertheless, until 2050 this uncertainty was narrow enough to derive robust findings. For instance, reducing harvest intensities enhanced the carbon sink in our simulations, but diminished substitution effects, leading to a decreased total mitigation potential until 2050. However, when considering longer time horizons (i.e. until 2100), substitution effects became low enough in our simulations due to expected decarbonization such that decreasing harvests often seemed the more favorable solution. Conclusion: Our results underscore the need to tailor mitigation strategies to the specific conditions of different forest sites. Furthermore, considering substitution effects, and thoroughly assessing the amount of avoided emissions by using wood products, is critical to determine mitigation potentials. While short-term recommendations are possible, we suggest risk diversification and methodologies like robust optimization to address increasing uncertainties from climate change and decarbonization paces past 2050. Finally, curbing emissions reduces the threat of climate change on forests, safeguarding their carbon sink and ecosystem services

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

Climate change reduces winter overland travel across the Pan-Arctic even under low-end global warming scenarios

Amplified climate warming has led to permafrost degradation and a shortening of the winter season, both impacting cost-effective overland travel across the Arctic. Here we use, for the first time, four state-of-the-art Land Surface Models that explicitly consider ground freezing states, forced by a subset of bias-adjusted CMIP5 General Circulation Models to estimate the impact of different global warming scenarios (RCP2.6, 6.0, 8.5) on two modes of winter travel: overland travel days (OTDs) and ice road construction days (IRCDs). We show that OTDs decrease by on average −13% in the near future (2021–2050) and between −15% (RCP2.6) and −40% (RCP8.5) in the far future (2070–2099) compared to the reference period (1971–2000) when 173 d yr−1 are simulated across the Pan-Arctic. Regionally, we identified Eastern Siberia (Sakha (Yakutia), Khabarovsk Krai, Magadan Oblast) to be most resilient to climate change, while Alaska (USA), the Northwestern Russian regions (Yamalo, Arkhangelsk Oblast, Nenets, Komi, Khanty-Mansiy), Northern Europe and Chukotka are highly vulnerable. The change in OTDs is most pronounced during the shoulder season, particularly in autumn. The IRCDs reduce on average twice as much as the OTDs under all climate scenarios resulting in shorter operational duration. The results of the low-end global warming scenario (RCP2.6) emphasize that stringent climate mitigation policies have the potential to reduce the impact of climate change on winter mobility in the second half of the 21st century. Nevertheless, even under RCP2.6, our results suggest substantially reduced winter overland travel implying a severe threat to livelihoods of remote communities and increasing costs for resource exploration and transport across the Arctic

Higher site productivity and stand age enhance forest susceptibility to drought-induced mortality

Warmer and drier conditions increase forest mortality worldwide. At the same time, nitrogen deposition, longer growing seasons and higher atmospheric $CO_{2}$ concentrations may increase site productivity accelerating forest growth. However, tree physiological studies suggest that increased site productivity can also have adverse effects, reducing adaptation to drought. Understanding such intricate interactions that might foster tree mortality is essential for designing activities and policies aimed at preserving forests and the ecosystem services they provide. This study shows how site factors and stand features affect the susceptibility of Scots pine to drought-induced stand-level mortality. We use extensive forest data covering 750,000 ha, including 47,450 managed Scots pine stands, of which 2,547 were affected by mortality during the drought in 2015-2019. We found that the oldest and most dense stands growing on the most productive sites showed the highest susceptibility to enhanced mortality during drought. Our findings suggest that increasing site productivity may accelerate the intensity and prevalence of drought-induced forest mortality. Therefore, climate change may increase mortality, particularly in old and high-productive forests. Such exacerbated susceptibility to mortality should be considered in forest carbon sink projections, forest management, and policies designed to increase resilience and protect forest ecosystems

Forest-based climate change mitigation and adaptation in Europe

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Forest carbon allocation modelling under climate change

Peer reviewe

Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites

The process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model