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There has been a global increase in the demand for woody biomass in the last decade. The imperative to achieve the highest production per unit of land while preserving natural forest resources has expanded intensive forest cultivation in industrial plantations. The development of a global bioeconomy is expected to further increase the demand for biomass for material and energy use from industrial forest plantations. Efficiently planning supply from these timber sources requires up-to-date information on current harvesting systems. This study aims to provide an overview of existing systems and their performance in industrial plantations located in seven relevant global regions. Eight regional experts combined knowledge, supported by relevant literature, to create a unique database for benchmarking harvesting systems regarding their productivity and supply costs. Current mechanized systems can reach harvesting productivity exceeding 100 m3 per productive machine hour (PMH), while roadside costs range between 5 and 20 USD m−3 solid volume. Harvesting systems are modified continuously to adapt to plantations’ characteristics and industrial requirements in the different regions. Local socioeconomic factors and the historical sectorial evolution in each region significantly impact the selection of harvesting systems, mechanization levels, type of machinery, and resulting harvesting costs. Expanding plantations to more marginal lands requires further research on adapting agricultural/construction machinery to steep terrain plantations. International literature tends to represent large-scale, highly mechanized systems well. In contrast, fewer studies are available for characterizing small-scale systems, particularly in developing regions.

Deadwood is a key old-growth element in European forests and a cornerstone of biodiversity conservation practices in the region, recognized as an important indicator of sustainable forest management. Despite its importance as a legacy element for biodiversity, uncertainties remain on the drivers of deadwood potentials, its spatial distribution in European forests and how it may change in the future due to management and climate change. To fill this gap, we combined a comprehensive deadwood dataset to fit a machine learning and a Bayesian hurdle-lognormal model against multiple environmental and socio-economic predictors. We deployed the models on the gridded predictors to forecast changes in deadwood volumes in Europe under alternative climate (RCP4.5 and RCP8.5) and management scenarios (biodiversity-oriented and production-oriented strategies). Our results show deadwood hotspots in montane forests of central Europe and unmanaged forests in Scandinavia. Future climate conditions may reduce deadwood potentials up to 13% under a mid-century climate, with regional losses amounting to up to 22% in Southern Europe. Nevertheless, changes in management towards more biodiversity-oriented strategies, including an increase in the share of mixed forests and extended rotation lengths, may mitigate this loss to a 4% reduction in deadwood potentials. We conclude that adaptive management can promote deadwood under changing environmental conditions and thereby support habitat maintenance and forest multifunctionality.

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.

Forests provide a range of vital services to society and are critical habitats for biodiversity, holding inherent multifunctionality. While traditionally viewed as a byproduct of production-focused forestry, today's forest ecosystem services and biodiversity (FESB) play an essential role in several sectoral policies’ needs. Achieving policy objectives requires careful management considering the interplay of services, influenced by regional aspects and climate. Here, we examined the multifunctionality gap caused by these factors through simulation of forest management and multi-objective optimization methods across different regions - Finland, Norway, Sweden and Germany (Bavaria). To accomplish this, we tested diverse management regimes (productivity-oriented silviculture, several continuous cover forestry regimes and set asides), two climate scenarios (current and RCP 4.5) and three policy strategies (National Forest, Biodiversity and Bioeconomy Strategies). For each combination we calculated a multifunctionality metric at the landscape scale based on 5 FESB classes (biodiversity conservation, bioenergy, climate regulation, wood, water and recreation). In Germany and Norway, maximum multifunctionality was achieved by increasing the proportion of set-asides and proportionally decreasing the rest of management regimes. In Finland, maximum MF would instead require that policies address greater diversity in management, while in Sweden, the pattern was slightly different but similar to Finland. Regarding the climate scenarios, we observed that only for Sweden the difference in the provision of FESB was significant. Finally, the highest overall potential multifunctionality was observed for Sweden (National Forest scenario, with a value of 0.94 for the normalized multifunctionality metric), followed by Germany (National Forest scenario, 0.83), Finland (Bioeconomy scenario, 0.81) and Norway (National Forest scenario, 0.71). The results highlight the challenges of maximizing

Future projections indicate an expansion for both food and energy demands, which can increase pressure on land use, while there is an urgent global need for climate change mitigation. Bioenergy is foreseen as key option to meet future energy demands and reduce greenhouse gas (GHG) emissions, however its sustainability depends on locations and regional characteristics. Simultaneously, agricultural production models that co-produce food, feed, and energy offer sustainability synergies and co-benefits, but site-specific sustainability assessments of their large-scale implementation are missing. This study presents a bottom-up approach to assess spatially explicit sustainability aspects of bioenergy-livestock integrated systems (BLI) in Brazil and shed light on their contribution to future energy demands, to climate change mitigation targets, and their impacts on selected ecosystem services, including bioenergy production, climate change mitigation, reduction of food competition, biodiversity conservation, and avoided deforestation. The proposed integration considers livestock intensification and use of biofuels by-products as animal feed supplement, taking advantage of synergies between these two value chains. The expansion of the BLI system in the Center-South region of Brazil produce up to 89 billion liters of ethanol, enough to meet future domestic ethanol demands from multiple shared socioeconomic pathways and generating surpluses for export. This production takes place on 16 million hectares of pastureland within the Sugarcane Agroecological Zoning, excluding the Amazon and Pantanal biomes, and biodiversity hotspots. BLI expansion mitigate up to 250 million tonnes of CO2eq and generate 15 billion dollars of profits. The best locations to maximize the selected ecosystem services are west of São Paulo, east of Mato Grosso do Sul, and the south-central region of the states of Goiás. This study may encourage the formulation of enhanced public policies for the integrat

Here are stored two datasets belonging to the model build for the following research article: Can Forest Management Practices Counteract Species Loss Arising from Increasing European Demand for Forest Biomass under Climate Mitigation Scenarios? Francesca Rosa, Fulvio Di Fulvio, Pekka Lauri, Adam Felton, Nicklas Forsell, Stephan Pfister, Stefanie Hellweg Environmental Science and Technology, 2023 https://doi.org/10.1021/acs.est.2c07867 The rest of the data, the code and further documentation are provided in this github repository: https://github.com/francesca-git/EU28-ForestMng-Climate

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.

We provide four data records: 1.The reference data set as a comma-separated file ("reference_data_set.csv") with the following attributes: “ID” is a unique location identifier “Latitude, Longitude” are centroid coordinates of a 100m x 100m pixel. “Land_use_ID “is a land use class: 11 - Naturally regenerating forest without any signs of human activities, e.g., primary forests. 20 - Naturally regenerating forest with signs of human activities, e.g., logging, clear cuts etc. 31 - Planted forest. 32 - Short rotation plantations for timber. 40 - Oil palm plantations. 53 - Agroforestry. “Flag” identifies a data origin: 1- the crowdsourced locations, 2- the control data set, 0 – the additional experts' classifications following the opportunistic approach. 2. The 100 m forest management map in a geoTiff format with the classes presented - "FML_v3.2.tif ". 3. The predicted class probability from the Random Forest classification in a geoTiff format - "ProbaV_LC100_epoch2015_global_v2.0.3_forest-management--layer-proba_EPSG-4326.tif" 4. Validation data set as a comma-separated file ("validation_data_set.csv) with the following attributes: “ID” is a unique location identifier “pixel_center_x” , “pixel_center_y ” are centroid coordinates of a 100m x 100m pixel in lat/lon projection “first_landuse_class “is a land use class, as in (1). “second_landuse_class “is a second possible land use class, as in (1), identified in case it was difficult to assign one class with high confidence.

The competitive advantage of traditional forest industry regions such as North America, Russia and the EU is based largely on the production and processing of coniferous (C) biomass. However, non-coniferous (NC) and recycled (R) biomass provide cost-effective alternatives to C biomass, which have already decreased the proportion of C biomass use and which can potentially have large impacts on the future development of the global forest sector. In this study, we investigate the impacts of material substitution between C, NC and R biomass on forest industry raw material use and regional competitiveness from 2020 to 2100. The analysis is based on a global spatially-explicit forest sector model (GLOBIOM-forest). Our results indicate that traditional forest industry regions can maintain their competitiveness in a baseline scenario where C and NC biomass remain imperfect substitutes, and the development of the circular economy increases the availability of R biomass. Limited availability of R biomass would increase the competitiveness of traditional forest industry regions relative to the baseline. On the other hand, a perfect substitution between C and NC biomass would decrease the competitiveness of traditional forest industry regions relative to the baseline, and increase the competitiveness of emerging forest industry regions such as South America, Asia and Africa. We also show that the increased availability of R biomass tends to decrease demand for pulpwood and might lead to an oversupply of pulpwood especially in traditional forest industry regions. This opens new perspectives for pulpwood use and/or forest management in these regions.

Even though enormous expectations for greenhouse gas mitigation in the land use sector exist at the same time worries about potential implications for sustainable development have been raised as many Sustainable Development Goals (SDGs) are closely tied to developments in the sector. Here we assess the implications of achieving selected key SDG indicators for Zero Hunger, Clean Water and Sanitation, Responsible Consumption and Production, and Life on Land on the land-based climate change mitigation potential. We find that protecting highly biodiverse ecosystems has profound impacts on biomass potentials (−30% at >12 US dollar per gigajoule) while other SDGs mainly affect greenhouse gas abatement potentials. Achieving SDGs delivers synergies with greenhouse gas abatement and may even in the absence of additional mitigation policies allow to realize up to 25% of the expected greenhouse gas abatement from land use required to stay on track with the 1.5 °C target until 2050. Future land use mitigation policies should consider and take advantage of these synergies across SDGs.

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Countries are responding to unsustainable resource extraction, rising emissions, and increasing waste streams by implementing national bioeconomy strategies. Assuming that the purpose of a bioeconomy is to replace fossil use by biogenic resource use, we estimate biomass and fossil raw material consumption (RMC) by applying multiregional input–output methodology for middle and high income countries. Next, we use a panel fixed effects model to explain RMC with economically active population, urban population, GDP, land cover, and fossil/biomass domestic material consumption. With this model, we project RMC under five Shared Socioeconomic Pathway scenarios up to 2050. The projections show an increase in per capita biomass RMC between 2010 and 2050, accompanied by—in many cases pronounced—per capita growth of fossil RMC across most of the countries and scenarios. We conclude that, if GDP continues to drive fossil RMC at its current magnitude, upcoming conditions are likely to counteract a potential bioeconomic transition and increase, instead of decrease, fossil RMC. Thus, increasing biomass use will not necessarily lead to reduced fossil resource consumption. When considering the relative scarcity of biomass, land and water, more focus needs to be placed on the relevance of technological bio-based innovations in the reconfiguration of RMC drivers.

Despite the scientific consensus on the extinction crisis and its anthropogenic origin, the quantification of historical trends and of future scenarios of biodiversity and ecosystem services has been limited, due to the lack of inter-model comparisons and harmonized scenarios. Here, we present a multi-model analysis to assess the impacts of land-use and climate change from 1900 to 2050. During the 20th century provisioning services increased, but biodiversity and regulating services decreased. Similar trade-offs are projected for the coming decades, but they may be attenuated in a sustainability scenario. Future biodiversity loss from land-use change is projected to keep up with historical rates or reduce slightly, whereas losses due to climate change are projected to increase greatly. Renewed efforts are needed by governments to meet the 2050 vision of the Convention on Biological Diversity.

An algorithm for simulation of shelterwood logging on the forest scale has been developed for the Global Forest Model (G4M). The algorithm produces adequate results in comparison to the simulation of the conventional clearcut logging. The algorithm extends the features of G4M to simulate shelterwood logging on regional and global scales.

This paper offers a conceptual analysis of the unaccounted-for cost of owning and operating used machines from an operational, financial and market perspective. It is based on input from experts and a literature review. In the scientific literature, assessing the operating cost of used machines in forest operations is typically based on standard cost assessment methods using costing/pricing input from similar unused machines. This is the case since there are usually no historical data for observed used machines available to analyze. This substitute analysis is problematic to many used and depreciated machines owners. The changing trends in forest technology attest that old machinery do not hold to the same input cost data variables or values of new machines. In fact, they belong to two rather competing different markets: (used vs. new equipment markets). With the technological, market and machinery regulations and dynamic changes, the substitute cost analysis is not representative. Better data is required to understand the cost of owning and operating used machines and the justification is the focal point of this paper. The outcome of the expert and literature analysis in this paper demonstrates that a broader understanding of the cost of a used machine is required and doable. A proposed understanding integrates the machine availability (performance), cost factors (financial) and market evaluation (price), in isolation (single piece of machine) as well as in a fleet, to assess a used machine ownership cost. The study is intended to offer forest machine operators, owners, scientists, and practitioners a proposed new approach to value used machines and further investigations and data inputs required to make used machines costing methods more relevant.

An algorithm for simulation of shelterwood logging at the forest scale has been developed for the Global Forest Model (G4M). The algorithm was tested for a spruce forest with a mean annual increment 10 m3/(ha year) and rotation length maximizing mean annual increment, 91 years, and regeneration time 37 years in a 1000-year simulation against the conventional clearcut logging. Changing the forest management practice from the clearcut logging to the shelterwood logging results in oscillations of the biomass and harvest with decreasing amplitude until a new steady state is reached. The transition to the new steady state lasts about 600 years. At the steady state the stem biomass of the forest under shelterwood logging is about 30% greater than under the clearcut logging, while the harvest is about 3% lower. The algorithm produces adequate results in comparison to the clearcut logging. The algorithm extends the features of G4M to simulate shelterwood logging on regional and global scales.

Background and Objectives: Under the Paris Agreement, the European Union (EU) sets rules for accounting the greenhouse gas emissions and removals from forest land (FL). According to these rules, the average FL emissions of each member state in 2021–2025 (compliance period 1, CP1) and in 2026–2030 (compliance period 2, CP2) will be compared to a projected forest reference level (FRL). The FRL is estimated by modelling forest development under fixed forest management practices, based on those observed in 2000–2009. In this context, the objective of this study was to estimate the effects of large-scale uptake of alternative forest management models (aFMMs), developed in the ALTERFOR project (Alternative models and robust decision-making for future forest management), on forest harvest and forest carbon sink, considering that the proposed aFMMs are expanded to most of the suitable areas in EU27+UK and Turkey. Methods: We applied the Global Forest Model (G4M) for projecting the harvest and sink with the aFMMs and compared our results to previous FRL projections. The simulations were performed under the condition that the countries should match the harvest levels estimated for their FRLs as closely as possible. A representation of such aFMMs as clearcut, selective logging, shelterwood logging and tree species change was included in G4M. The aFMMs were modeled under four scenarios of spatial allocation and two scenarios of uptake rate. Finally, we compared our results to the business as usual. Results: The introduction of the aFMMs enhanced the forest sink in CP1 and CP2 in all studied regions when compared to the business as usual. Conclusions: Our results suggest that if a balanced mixture of aFMMs is chosen, a similar level of wood harvest can be maintained as in the FRL projection, while at the same time enhancing the forest sink. In particular, a mixture of multifunctional aFMMs, like selective logging and shelterwood, could enhance the carbon sink by up to 21% over t

Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0:5 0:5 spatial resolution. We also provide a combined "best bioenergy crop" yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 tDMha1 yr1 (DM dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are 50% higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0:5 0:5 global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenod

The archive provides supporting material for the article entitled “Bending the curve of terrestrial biodiversity needs an integrated strategy”, published in the Nature journal (https://doi.org/10.1038/s41586-020-2705-y). It contains: i) the final version of the methodological report (updating the initial version [DOI:10.22022/ESM/04-2018.15241] for this article), ii) geospatial land-use projections generated by land-use models for the various scenarios described in the article, iii) aggregated land-use model projections for other variables used in the article, iv) the code, input data and output data of the various biodiversity models applied to the land use projections, v) the code and side data to produce numbers and figures presented in the article.”

In Sweden, an estimated 0.3–0.6 million hectares (1.2–2.4% of the entire Swedish forest area) of forests are voluntary set-asides for nature conservation management (NCM). Even though these areas are crucial in Swedish biodiversity conservation, no analysis has yet been carried out of their conservation values and spatial distribution. The aim of this study was to comprehensively describe areas intended for NCM in Sweden. Based on existing habitat descriptions, six NCM area categories were defined. The occurrence of each category was determined through GIS analysis of a spatially explicit dataset containing information on 26,953 stands (136,672 ha) set aside for NCM. Of the analysed area, 86% met the criteria of at least one category. The most common category was “Old coniferous forests”, which was found to be abundant in northern Sweden, and often the only category met in stands. Out of the remaining five categories, four were more frequent in southern Sweden. In the southern regions, stands often met the criteria of two or three categories simultaneously. This mapping is a resource for further research and development of policies and strategies aimed at increasing the extent and improving the quality of nature conservation management.

In this study, the potential global loss of species directly associated with land use in the EU and due to trade with other regions is computed over time, in order to reveal differences in impacts between the considered alternatives of plausible bioenergy policies development in the EU. The spatially explicit study combines a life cycle analysis (LCA) for biodiversity impact assessment with a global high resolution economic land use model. Both impacts of domestic land use and impacts through imports were included for estimating the biodiversity footprint of the member states of the (EU28). The analyzed scenarios assumed similar biomass demand until 2020 but differed thereafter, from keeping the growth of demand for bioenergy constant (CONST), to a strong increase of bioenergy in line with the EU target of decreasing greenhouse gas (GHG) emissions by 80% by 2050 (EMIRED) and with the baseline (BASE) scenario falling between the other two. As a general trend, the increasing demand for biomass was found to have substantial impact on biodiversity in all scenarios, while the differences between the scenarios were found to be modest. The share caused by imports was 15% of the overall biodiversity impacts detected in this study in the year 2000, and progressively increased to 24% to 26% in 2050, depending on the scenario. The most prominent future change in domestic land use in all scenarios was the expansion of perennial cultivations for energy. In the EMIRED scenario, there is a larger expansion of perennial cultivations and a smaller expansion of cropland in the EU than in the other two scenarios. As the biodiversity damage is smaller for land used for perennial cultivations than for cropland, this development decreases the internal biodiversity damage per unit of land. At the same time, however, the EMIRED scenario also features the largest outsourcing of damage, due to increased import of cropland products from outside the EU for satisfying the EU food demand. These

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) – SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 – to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%.

This paper offers a forest operations perspective in environmentally sensitive areas (ESAs) in Europe and the United States. The objective is to help inform key sustainability knowledge gaps in forest operations to reduce impacts on the environment and the equipment operators in these increasingly targeted and difficult to operate in areas. Under existing guidelines and best management practices, the protection of ecosystem services linked to soil, water, wildlife and biodiversity have rightly received the highest considerations. However, the connection between protecting these ecological values, safe operational practices and technological advancements is rarely well articulated. One means to address the operational and technological gap is the selection of equipment and tailor the work conditions to terrain type, forest features and management objectives. To that effect, this paper discusses the environmental, planning, equipment selection and operator considerations and proposes possible solutions and guidelines to contain both the operators’ safety and environmental risks in forest operations.

In a global bioeconomy, benchmarking costs is essential in the evaluation of current forest harvesting systems and addressing decisions on the most efficient supply chains for available forest resources. Benchmarking cost rates in forestry is challenging, due to a lack of harmonized terminology and difficulties in collecting information on comparable forest technologies. This study provides a first-time series of cost factors to be used when modeling and evaluating the cost competitiveness of forest felling and processing operations on a global scale. It is based on an expert survey using a standardized method of data collection. This benchmarking identifies and updates the knowledge of technical and socio-economic factors capable of influencing the cost rates of forest felling and processing operations across different regions. This study is expected to act as a reference for larger investigations, and for regular updates, with the aim to provide current data that can be used by forest practitioners and decision makers for improving their cost efficiency and for designing future supply systems more effectively.

Competition for woody biomass between material and energy uses is expected to further increase in the future, due to the limited availability of forest resources and increasing demand of wood for material and bioenergy. Currently, methodological approaches for modeling wood production and delivery costs from forest to industrial gates are missing. This study combines forest engineering, geographically explicit information, environmental constraints and economics in a bottom-up approach to assess cost–supply curves. The estimates are based on a multitude of wood supply systems that were assigned according to geographically explicit forestry characteristics. For each harvesting and transportation system, efficiencies were modeled according to harvesting sites and main delivery hubs. The cost–supply curves for roundwood and logging residues as estimates for current time and for the future (2030) show that there are large regional differences in the potential to increase extraction in the EU28. In most EU Member States, the costs of logging residues extraction increase exponentially already for low levels of mobilization, while extraction of roundwood can be increased to a larger extent within reasonable costs (30–40 $/m3). The large differences between countries in their harvest potential highlight the importance of spatially explicit analyses.

The demand for forest biomass as raw material for a wide range of products in the developing bioeconomy is expected to increase. Along with a constant pressure on forestry to increase its productivity, this development has led to the search for new procurement methods and new assortments. The present study assessed innovative supply chain practices, with a particular focus on the integrated supply of stemwood and residual tree parts. The assortments considered included tree sections, long tops, saw logs with stump cores and small whole trees from thinnings. The assessment included geographically explicit modelling of the supply chain operations and estimation of supply cost and energy use for three industrial locations in Northern Sweden. The innovative supply chains were compared to conventional, separate, harvest of stemwood and logging residues. We conclude that integrated harvest of tops and branches with stemwood assortments, as well as whole-tree harvest in early thinnings, has a significant potential to reduce the supply cost for the non-stemwood assortments. Stump wood generally remains the most expensive assortment. The energy use analysis confirms earlier research showing that the energy input is relatively small compared to the energy content of the harvested feedstock.

The objective of the study was to improve knowledge on effects of harvested tree size and density of undergrowth on the operational efficiency of a bundle-harvester that produces 2.6 m long bundles, with ca. 60–70 cm diameter, in early fuel wood thinnings. In total 26 time study plots were marked out in 30 to 35 year old Scots pine dominated stands with initial density of 2800–9300 trees/ha and stem size range of 15–43 dm3. Ten of the units, randomly chosen, were precleared of undergrowth trees (≤2.5 cm at breast height diameter) prior to harvesting. There were no significant differences between treatments (preclearing vs. no preclearing) in properties or operational efficiency of the harvested and remaining stands. The average height of cut trees and volume of cut stems were 7.4 m and 16.2 dm3, respectively, and on average, 3554 trees/ha were removed. The bundles had a mean fresh mass of 439 kg and the mass was correlated to the proportion of birch trees cut. The productivity was, on average, 3.1 OD t/PM0H (6.6 fresh t/PM0H; 15.1 bundles/PM0H, where PM0H is productive machine hours, without delays) and was modeled with the harvested stem volume (dm3) as a single independent variable. The study provides complementary knowledge to earlier studies of the system’s performance, especially for harvesting stems <30 dm3. Its productivity was limited by the cutting efficiency and could probably be significantly increased by using a felling and bunching head that could cut and accumulate trees during continuous boom movements. Thus, it would be informative to evaluate such a system in various early thinning stand conditions, including assessments of its manoeuvrability in more difficult terrain.

Understanding the characteristics of unutilized biomass resources, such as small-diameter trees from biomass-dense thinning forests (BDTF) (non-commercially-thinned forests), can provide important information for developing a bio-based economy. The aim of this study was to describe the areal distribution, characteristics (biomass of growing stock, tree height, etc.) and harvesting potential of BDTF in Sweden. A national forest inventory plot dataset was imported into a geographical information system and plots containing BDTF were selected by applying increasingly stringent constraints. Results show that, depending on the constraints applied, BDTF covers 9-44% (2.1-9.8 M ha) of the productive forest land area, and contains 7-34% of the total growing stock (119-564 M OD t), with an average biomass density of 57 OD t ha^-1. Of the total BDTF area, 65% is located in northern Sweden and 2% corresponds to set-aside farmlands. Comparisons with a study from 2008 indicate that BDTF area has increased by at least 4% (about 102 000 ha), in line with general trends for Sweden and Europe. Analyses revealed that the technical harvesting potential of delimbed stemwood (over bark, including tops) from BDTF ranges from 3.0 to 6.1 M OD t yr^-1 (7.5 to 15.1 M m^3 yr^-1), while the potential of whole-tree harvesting ranges from 4.3 to 8.7 M OD t yr^-1 (10.2 to 20.6 M m3 yr^-1) depending on the scenario considered. However, further technological developments of the harvest and supply systems are needed to utilize the full potential of BDTF.

Biofuels are promoted as an option to reduce climate emissions from the transport sector. As most biofuels are currently produced from land based crops, there is a concern that the increased consumption of biofuels requires agricultural expansion at a global scale, leading to additional carbon emissions. This effect is called Indirect Land Use Change, or ILUC. The EU Renewable Energy Directive (2009/28/EC) directed the European Commission to develop a methodology to account for the ILUC effect. The current study serves to provide new insights to the European Commission and other stakeholders about these indirect carbon and land impacts from biofuels consumed in the EU, with more details on production processes and representation of individual feedstocks than was done before. ILUC cannot be observed or measured in reality, because it is entangled with a large number of other changes in agricultural markets at both global and local levels. The effect can only be estimated through the use of models. The current study is part of a continuous effort to improve the understanding and representation of ILUC.