• Energy Research

AbstractForests provide a wide variety of ecosystem services (ES) to society. The boreal biome is experiencing the highest rates of warming on the planet and increasing demand for forest products. To foresee how to maximize the adaptation of boreal forests to future warmer conditions and growing demands of forest products, we need a better understanding of the relative importance of forest management and climate change on the supply of ecosystem services. Here, using Finland as a boreal forest case study, we assessed the potential supply of a wide range of ES (timber, bilberry, cowberry, mushrooms, carbon storage, scenic beauty, species habitat availability and deadwood) given seven management regimes and four climate change scenarios. We used the forest simulator SIMO to project forest dynamics for 100 years into the future (2016–2116) and estimate the potential supply of each service using published models. Then, we tested the relative importance of management and climate change as drivers of the future supply of these services using generalized linear mixed models. Our results show that the effects of management on the future supply of these ES were, on average, 11 times higher than the effects of climate change across all services, but greatly differed among them (from 0.53 to 24 times higher for timber and cowberry, respectively). Notably, the importance of these drivers substantially differed among biogeographical zones within the boreal biome. The effects of climate change were 1.6 times higher in northern Finland than in southern Finland, whereas the effects of management were the opposite—they were three times higher in the south compared to the north. We conclude that new guidelines for adapting forests to global change should account for regional differences and the variation in the effects of climate change and management on different forest ES.

AbstractAimThe aim of this study was to investigate the role of traits in beetle community assembly and test for consistency in these effects among several bioclimatic regions. We asked (1) whether traits predicted species’ responses to environmental gradients (i.e. their niches), (2) whether these same traits could predict co‐occurrence patterns and (3) how consistent were niches and the role of traits among study regions.LocationBoreal forests in Norway and Finland, temperate forests in Germany.TaxonWood‐living (saproxylic) beetles.MethodsWe compiled capture records of 468 wood‐living beetle species from the three regions, along with nine morphological and ecological species traits. Eight climatic and forest covariates were also collected. We used Bayesian hierarchical joint species distribution models to estimate the influence of traits and phylogeny on species’ niches. We also tested for correlations between species associations and trait similarity. Finally, we compared species niches and the effects of traits among study regions.ResultsTraits explained some of the variability in species’ niches, but their effects differed among study regions. However, substantial phylogenetic signal in species niches implies that unmeasured but phylogenetically structured traits have a stronger effect. Degree of trait similarity was correlated with species associations but depended idiosyncratically on the trait and region. Species niches were much more consistent—widespread taxa often responded similarly to an environmental gradient in each region.Main conclusionsThe inconsistent effects of traits among regions limit their current use in understanding beetle community assembly. Phylogenetic signal in niches, however, implies that better predictive traits can eventually be identified. Consistency of species niches among regions means niches may remain relatively stable under future climate and land use changes; this lends credibility to predictive distribution models based on future climate projections but may imply that species’ scope for short‐term adaptation is limited.

For the Swedish boreal and hemiboreal zone we projected forest dynamics, management and ES levels for all the combinations of four scenarios implementing different CCMS (Current Policy, Bioenergy, Bioeconomy and Set-aside scenario) and three climate scenarios (Constant Climate, RCP4.5 and RCP8.5). We projected the levels of ES on 29,892 plots of the Swedish National Forest Inventory (NFI), which represent all productive forest in Sweden (the 23 million ha producing ≥1 m3 of wood ha-1 yr-1, corresponding to 1.4% of the global boreal biome), including production and protected land (Fridman et al., 2014). The projections were initialized with observed levels for wood ES and the model-predicted levels for non-wood ES based on data from 2008-2012 (‘2010’ henceforth). Projections were made for the period 2010 to 2100; results were analyzed from 2020, the year of the first GHG mitigation target of the Current Policy scenario. Forest dynamics and management were projected with the Heureka system (http://www.slu.se/en/sha, Wikström et al., 2011). The Heureka core contains a set of empirical growth and yield models that simulate the development of the tree layer in five-year time steps, including models for stand establishment, diameter and height growth, ingrowth, and mortality. Climate change modifies tree growth based on the process-based vegetation model BIOMASS, indirectly implemented as an approximation model. Decomposition is modeled by the dynamic soil carbon Q-model, a cohort-based decomposition model that follows the mass loss of litter over time for different litter compartments. The Heureka application PlanWise allows for determining the optimal combination of management strategies that meet user-defined objectives and constraints. For each NFI plot and time step, a large number of management activities (such as thinning and clear felling) are simulated, that in sequence constitute different treatment schedules. In a harvest scheduling model (Johnson & Scheurman, 1977) the optimal treatment schedule for each plot is selected based on an objective function and possible constraints using a built-in optimization tool based on the ZIMPL optimization modeling language. References Fridman, J., Holm, S., Nilsson, M., Nilsson, P., Hedström Ringvall, A., & Ståhl, G. (2014). Adapting national forest inventories to changing requirements-the case of the Swedish national forest inventory at the turn of the 20th century. Silva Fennica, 48, 1095. Johnson, K.N., Scheurman, H.L. (1977). Techniques for prescribing optimal timber harvest and investment under different objectives-discussion and synthesis. Forest Science, 18, 1–30. Wikström, P., Edenius, L., Elfving, B., Eriksson, L. O., Lämås, T., Sonesson, J., Öhman, K., Wallerman, J., Waller, C., & Klintebäck, F. (2011). The Heureka forestry decision support system : an overview. http://mcfns.net/index.php/Journal/article/view/MCFNS.3-87 To reach the Paris Agreement, societies need to increase the global terrestrial carbon sink. There are many climate change mitigation solutions (CCMS) for forests, including increasing bioenergy, bioeconomy and protection. Bioenergy and bioeconomy solutions use climate-smart, intensive management to generate high quantities of bioenergy and bioproducts. Protection of (semi-)natural forests is a major component of ‘natural climate solution’ (NCS) since forests store carbon in standing biomass and soil. Furthermore, protected forests provide more habitat for biodiversity and non-wood ecosystem services (ES). We investigated the impacts of different CCMS and climate scenarios, jointly or in isolation, on future wood ES, non-wood ES, and regulating ES for a major wood provider for the international market. Specifically, we projected future ES given by three CCMS scenarios for Sweden 2020-2100. In the long term, fulfilling the increasing wood demand through bioenergy and bioeconomy solutions will decrease ES multifunctionality, but the increased stand age and wood stocks induced by rising greenhouse gas (GHG) concentrations will partially offset these negative effects. Adopting bioenergy and bioeconomy solutions will have a greater negative impact on ES supply than adopting NCS. Bioenergy or bioeconomy solutions, as well as increasing GHG emissions, will reduce synergies and increase trade-offs in ES. NCS, by contrast, increases the supply of multiple ES in synergy, even transforming current ES trade-offs into future synergies. Moreover, NCS can be considered an adaptation measure to offset negative climate change effects on the future supplies of non-wood ES. In boreal countries around the world, forestry strategies that integrate NCS more deeply are crucial to ensure a synergistic supply of multiple ES. R programming language for statistical computing (R Core Team, 2019) or a text editor. R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.Rproject.org/

From article abstract: https://doi.org/10.1016/j.biocon.2022.109491 ABSTRACT Biodiverse communities have been shown to sustain high levels of multifunctionality and thus a loss of species likely negatively impacts ecosystem functions. For most taxa, however, the roles of individual species are poorly known. Rare species, often the most likely to go extinct, may have unique traits leading to unique functional roles. Alternatively, rare species may be functionally redundant, such that their loss would not disrupt ecosystem functions. We quantified the functional role of rare species by using capture records of wood-living (saproxylic) beetle species, combined with recent databases of their morphological and ecological traits, from three regions in central and northern Europe. Using a rarity index based on species��� local abundance, geographic range, and habitat breadth, we used local and regional species removal simulations to examine the contributions of both the rarest and the most common beetle species to three measures of community functional structure: functional richness, functional specialization, and functional originality. In both regional species pools and local communities, all three of these measures declined more rapidly when rare species were removed than under common (or random) species removal scenarios. These consistent patterns across scales and among several forest types give evidence that rare species provide unique functional contributions, and that their loss may disproportionately impact ecosystem functions. This implies that conservation measures targeting rare and endangered species, such as preserving intact forests with dead wood and mature trees, can provide broader ecosystem-level benefits. Experimental research linking functional structure to ecosystem processes should be prioritized to increase our understanding of the functional consequences of species loss and to develop more effective conservation strategies. DATASET DESCRIPTION This dataset includes a) beetle capture information and b) beetle trait information from three countries: 1) Norway, 2) Finland, and 3) Germany. FILES readme.txt -- this has the information from this description section Norway_traits.csv, Finland_traits.csv, Germany_traits.csv -- these are the trait files, including all species Norway_sites.species.csv, Finland_sites.species.csv, Germany_sites.species.csv -- this has species (rows) by sites (columns); values are the number of beetles caught (for number of traps, dates, and other site covariates, see related dataset: https://doi.org/10.5061/dryad.tmpg4f50b and manuscript: https://doi.org/10.1111/jbi.14272). Species names follow GBIF taxonomic backbone. Traits_METADATA.csv -- this has information on all the fields in the trait data ACKNOWLEDGEMENTS This research was funded through the 2017-2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, for "BioESSHealth: Scenarios for biodiversity and ecosystem services acknowledging health", and with the funding organizations NFR (grant no. 295621), Formas (grant no. 2018-2435), and DLR. The German data collection was partly funded by the German Science Foundation DFG Priority Program SPP1374 "Infrastructure-Biodiversity-Exploratories" (DFG-Az: AM 149/16-3; (Regions Swabian Alb, Hainich-D��n, and Schorfheide-Chorin in Germany), project Arthropods (WE3081/21), the Bayerisches Staatsministerium f��r Ern��hrung, Landwirtschaft und Forsten, grant L55 (Region Steigerwald in Germany), and the Deutsche Bundesstiftung Umwelt (Bavarian Forest). Thanks also to Sindre Ligaard for identifying the beetle species in Norway, to Petri Martikainen and Matti Koivula for contributing to data collection and identifying beetles in Finland, and to numerous field assistants who set and maintained traps. {"references": ["https://doi.org/10.1111/cobi.12427", "https://doi.org/10.1111/1365-2656.13512"]}

The repository contains the data and codes supporting the findings of the study: Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity, which can be found in the zip file "euclimate_vs_natpolicy-main.zip". Further, the repository includes the raw forest simulation data used as input for the multi-objective optimizations and the raw optimization outputs of each study region. The codes to run the national optimization can be retrieved from https://doi.org/10.5281/zenodo.6631109. Abstract: The European Union (EU) set clear climate change mitigation targets to reach climate neutrality, accounting for forests and their woody biomass resources. We investigated the consequences of increased harvest demands resulting from EU climate targets. We analysed the impacts on national policy objectives for forest ecosystem services and biodiversity through empirical forest simulation and multi-objective optimization methods. We show that key European timber-producing countries – Finland, Sweden, Germany (Bavaria) – cannot fulfil the increased harvest demands linked to the ambitious 1.5°C target. Potentials for harvest increase only exists in the studied region Norway. However, focusing on EU climate targets conflicts with several national policies and causes adverse effects on multiple ecosystem services and biodiversity. We argue that the role of forests and their timber resources in achieving climate targets and societal decarbonization should not be overstated. Our study provides insight for other European countries challenged by conflicting policies and supports policymakers.

ABSTRACTWood use generates technosphere carbon credits (TCCs) through avoided fossil‐based emissions and net sequestration of carbon into the technosphere (harvested wood products and geological storage). We investigated how large and uncertain TCCs of wood use per carbon harvested are considering the current and alternative ways of using wood, and the effects of the decarbonization of societies over 25‐, 50‐, and 100‐year time horizons. We applied stochastic simulation and scenario analysis using Finnish market structure as a baseline to demonstrate the use of the TCC calculator created. The mean value of TCCs of wood use were between 0.2 and 0.5 tC/tC with an uncertainty range from 0.1 to 0.8 tC/tC, depending on the scenario. The uncertainties were mainly concerned with the extent to which (1) fossil‐based emissions are avoided through substitution (displacement factors) and (2) fossil‐based raw materials are substituted (substitution rates). Assumptions on the decarbonization of societies reduced TCCs of wood use significantly over time. TCCs of wood use can be increased by directing wood into uses that substitute fossil‐intensive materials and have a long lifetime, such as construction materials, and increasing energy recovery and avoiding emitting carbon at the end of life of harvested wood products by carbon capture and storage. However, they were very likely to be considerably lower than forest carbon debits resulting from harvesting additional wood for substitution under all considered circumstances and under a wide but reasonable range of stochastic parameter values. Thus, the result emphasizes the need to reduce overall consumption of goods to mitigate climate change.

The MultiOptForest Optimization Notebook was developed for the project "MultiForest - Management for multifunctionality in European forests in the era of bioeconomy" (https://www.jyu.fi/BERG/berg-projects-1/forest-values). The optimization framework provides a set of rules that can be used to create a unique multi-objective optimization problem. Particularly, it can be used to optimize forest management for forest ecosystem service and biodiversity objectives, while seeking an efficient management solution for individual forest entities (forest stands). The optimization problem can be created by adjusting the settings in a Jupyter notebook and a graphical user interphase (GUI). The optimization tool was developed under the lead of the company Silo AI together with project partners from: University of Jyväskylä, Technical University of Munich, Norwegian Institute of Bioeconomy Research, and Swedish University of Agricultural Sciences. For more details see README.md