ALBERT

Description: Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely-used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models’ performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapor pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe’s common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

Description: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors. ISIMIP2a is the first simulation round of the second phase of ISIMIP, focusing on historical simulations of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. This dataset contains ISIMIP2a simulation data from thirteen local forest models: 3D-CMCC FEM (3D-CMCC-FEM LUE, Collalti et al. 2014, 2016), 3D-CMCC-CNR-BGC (3D-CMCC-FEM BGC, Collalti et al. 2019, Collalti et al. 2020), 3PG (Landsberg et al. 2002), 3PGN-BW (Landsberg et al. 1997, Xenakis et al. 2008), 4C (Reyer et al. 2013, Lasch-Born et al. 2020), BASFOR (van Oijen et al. 2014, Cameron et al. 2013), ForClim (Bugmann et al. 2006), FORMIND (Bohn et al. 2014), GOTILWA+ (Nadal-Sala et al. 2017, Keenan et al. 2010, Gracia et al. 2011), Landscape-DNDC (Haas et al. 2012, Grote et al. 2008, 2010, 2011, Holst et al. 2009, Lindauer et al. 2014), PREBAS (Minunno et al. 2016, Valentine et al. 2005), SALEM (Aussenac et al. 2021) and SIBYLA (Fabrika and Ďurský 2006, Hlásny et al. 2014).

Description: Forests play a key role in a bio-based economy by providing renewable materials, mitigating climate change, and accommodating biodiversity. However, forests experience massive increases in stresses in their ecological and socioeconomic environments, threatening forest ecosystem services supply. Alleviating those stresses is hampered by conflicting and disconnected governance arrangements, competing interests and claims, and rapid changes in technology and social demands. Identifying which stresses threaten forest ecosystem services supply and which factors hamper their alleviation requires stakeholders' perceptions. Stakeholder-oriented stress tests for the supply of forest ecosystem services are therefore necessary but are not yet available. This perspective presents a roadmap to develop a stress test tailored to multiple stakeholders' needs and demands across spatial scales. We provide the Cascade and Resilience Rosetta, with accompanying performance- and resilience indicators, as tools to facilitate development of the stress test. The application of the stress test will facilitate the transition toward a bio-based economy in which healthy and diverse forests provide sustainable and resilient ecosystem services.

Description: Tropospheric ozone and particulate matter affect human health and cause vegetation stress, dysfunction and damages. In this study we investigate the effect of increasing urban vegetation i.e. tree species on atmospheric chemistry, a potential urban management strategy to counteract high levels of local pollutants such as ozone, OH and PM10 caused by e.g. traffic. We use an extended version of an atmospheric chemistry box model including detailed gas-phase chemistry, mixing layer height variation and secondary organic aerosol calculations based on observations for Berlin, Germany. It is shown to accurately simulate the observed ozone volume mixing ratios during the intensive measurement period in July 2014 (BAERLIN2014) if basic parameters such as nitrogen oxides, meteorological conditions, PM10 concentrations as well as volatile organic compounds (VOCs) are considered as 1 h resolved datasets. Based on this setup the effects of changing present day vegetation mixture by 24 different relevant tree species and of urban greening is tested to elucidate benefits and drawbacks in order to support future urban planning. While the present day vegetation causes boundary layer ozone to decline slightly at 35 °C, individual tree types alter the ozone production rate and concentration as well as the secondary organic aerosol mass in different ways. Our results suggest that trees intensively emitting isoprene such as black locust, European oak and poplar result in higher ozone and total PM10 concentrations than at present, while tree species emitting primarily monoterpenes such as beech, magnolia and wayfaring trees yield less of both. This is in line with the similar behaviour of OH concentration and new particle formation rates. Thus, for future urban planning including urban greening, consideration of the beneficial and harmful aspects of tree species need to ensure that citizens benefit from and are not being negatively affected by climate adaptation strategies.