Publications

Riparian buffer zones (RBZs) are an important instrument for environmental policies for water and biodiversity protection in managed forests. We investigate the variation of the cost of implementing RBZs within different property size classes across the size range of non-industrial forest owner properties in Southern Sweden. Using the Heureka PlanWise decision support system, we quantified the cost of setting aside RBZs or applying alternative management in them, as the relative loss of harvest volume and of net present value per property. We did this for multiple simulated as well as real-world property distributions. The variation of cost distribution among small properties was 4.2–6.9 times higher than among large properties. The interproperty cost inequality decreased non-linearly with increasing property size and levelled off from around 200 ha. We conclude that RBZs, due to the irregular distribution of streams, cause highly unequal financial consequences for owners, with some small property owners bearing a disproportionally high cost. This adds to previous studies showing how environmental considerations differentially affect property owners. We recommend decision makers to stimulate the uptake of RBZs by alleviating these inequalities between forest owners by including appropriate cost sharing or compensation mechanisms in their design. © The Author(s) 2024.

Natural disturbances play an important role in shaping the dynamics of mountain forests, yet their effects on essential ecosystem services, such as protection against natural hazards, can be significant. With the challenges posed by climate change and increasing disturbances, as well as the complexities of salvage logging, there is a growing interest in understanding post-disturbance development in unsalvaged mountain forests, alongside the advancement of decision support systems aimed at ensuring sustained provision of ecosystem services. In this study, we combined a space-for-time substitution approach with long-term monitoring data to evaluate regeneration processes and development of deadwood decay following three distinct windthrow events in Central European mountain forests that were locally unsalvaged (specifically Vaia in 2018, Kyrill in 2007, and Vivian in 1990). Our unique dataset additionally provided insights into the long-term effects of disturbance legacies and tree regeneration on protection against natural hazards. Deadwood cover gradually decreased with time since disturbance, from an average of 50% two years after Vaia to 25% twelve years after Kyrill and 15% thirty years after Vivian. Similarly, deadwood height above ground significantly decreased over time, with median values dropping from 1 to 2 m immediately after the disturbance to 25–30 cm three decades later. The decay stage and diameter of deadwood significantly influenced tree regeneration, with larger diameters of logs and deadwood in more advanced decay stage (especially less solid/soft to very loose stage), facilitating seedling establishment, thus a second wave of tree regeneration. About a quarter of saplings grew on deadwood thirty years after disturbance. The analysis of post-windthrow stand development showed an increase in tree cover and height with time since disturbance, with distinct patterns observed across different windthrow events and sites. Three decades post-disturbance, the number of trees had notably increased, with tree cover reaching 50%. Although Norway spruce remained the dominant species, the forest composition had shifted towards a predominance of broadleaves, particularly evident at lower elevations and areas with moderate browsing pressure. Our findings underscore the critical role of post-disturbance forest recovery and deadwood dynamics in promoting uneven-aged mixed forest structures, thereby enhancing forest regeneration, structural diversity, and protection against natural hazards. Emphasizing the vital importance of retaining deadwood, our study suggests that its role as a valuable substrate for enhancing resilience and ecosystem services is likely to grow in the future. © 2024 The Authors

Many life cycle assessments (LCA) studies on wooden buildings show potential to decarbonise the building industry, though often neglecting to consider the systemic changes of such a shift at the building stock scale. This study applies a consequential LCA to evaluate the transition from conventional construction to increased wood-based construction in Denmark from 2022 to 2050. The assessment models a material flow analysis of the two construction scenarios, incorporating an area forecast and case buildings. By that, we assessed suppliers' capacity to likely meet the demand for wood, steel, and concrete, employed an input-output model to enhance completeness and country representativeness for other materials' markets, and considered the competition for land by indirect land use change. We implemented a dynamic IPCC-based assessment of GHG-emissions concurrently with a carbon forest model to anticipate the relationship between the delayed carbon storage resulting from using wood in buildings and forest regrowth management. The findings indicate wood construction is the most climate-friendly option for multifamily houses. In contrast, single-family houses (SFH) and office buildings (OB) exhibit the lowest climate impacts in the conventional scenario. The SFH result could be credible due to the sizable GWP impact gap between construction scenarios despite uncertainties related to the weight proportion of sedum roofs. The less conclusive OB findings relate to the substantial steel quantities in the wood case buildings, requiring further investigation. Generally, metals, cement-based- and biobased materials demonstrate the largest climate impact among the material categories. Across all three building typologies, the change to timber construction increased the impact on nature occupation (biodiversity). In conclusion, this study emphasises the need for further research on forest management model inputs, land use change approaches, potential steel suppliers' impact, and a broader array of case studies. It is because these are influential factors in facilitating informed decision-making of the increased implementation of wood in buildings. As the first study to integrate these modelling characteristics, it contributes to the research gap concerning geographical circumstances, forestry, and markets relevant to decision support for increased wood utilisation in Europe's building industry. © 2024 The Authors

Forest productivity and response to silvicultural treatments are dependent on inherent site resource availability and limitations. Trees have deeper rooting profiles than agronomic crops, so evaluating the impacts of soils, geology, and physiographic province on forest productivity can help guide silvicultural management decisions in southern pine plantations. Here, we describe the Forest Productivity Cooperative's “Site Productivity Optimization for Trees” (SPOT) system which includes: texture, depth to increase in clay content, drainage class, soil modifiers (i.e., surface attributes, mineralogy, and additional limitations such as root restrictions), geologic formations, and physiographic province. We quantified the total area for each SPOT code in the native range of loblolly pine (Pinus taeda L.), the region's most commercially important species, and used a remotely-sensed layer to quantify SPOT code areas in managed southern pine (approximately 14 million ha). The most common SPOT code in the native range is also the most planted, a B2WekoGgPD (fine loamy, shallow depth to increase in clay, well-drained, eroded, kaolinitic, granitic, Piedmont soil), spanning 1.1 million ha total, but only 12% in managed southern pine. However, the SPOT code with the greatest percentage of managed southern pine (61%; a D4PoioAmAF, spodic, deep to increase in clay, siliceous, middle Atlantic Coastal Plain, Flatwoods soil) was the 20th most common in the native range with 474,662 ha. We used machine learning and data from decades of “Regionwide” trials to assess the variable importance of SPOT constituents, climate, planting year, and N rate on site index (base age 25 years) and found that planting year was the most important variable, showing an increase of 17 cm site index per year since 1970, followed by maximum vapor pressure deficit, and precipitation. Geology was the top-ranking SPOT variable to explain site index followed by physiographic province. The Regionwide trials represent 72 unique SPOT codes (out of over 10,000 possible in the pine plantations) and approximately one million ha (or about 7% of all soils identified as supporting managed pine). To extrapolate site index values outside of the unique soil and geologic conditions empirically represented, we created a predictive model with an R2 of 0.79 and an RMSE of 1.38 m from SPOT codes alone. With this extrapolation, the Regionwide data predicts 10.5 million ha, or 74%, of all soils under loblolly pine management in its native range. Overall, this system will allow managers to assess their current site productivity, and recommend silvicultural treatments, thus, providing a framework to optimize forest productivity in pine plantations in the southeastern US. © 2024

Rational forest planning and management is the key to a forest’s systematic construction. It is beneficial to many aspects, such as the cultivation and preservation of a forest’s ecological resources, sustainability, forest fire prevention, and others. In recent years, some effective strategies and tactics for the planning and management of forests’ systematic construction have been established. Among them, the application of geoinformatics in forest planning and management (AGFPM) is one of the most effective and promising strategies. Therefore, it is necessary to conduct a comprehensive summary and analysis of the current situation. AGFPM has effectively applied in logging operations, forest road development, forest material transport, and forest fire prevention. An analysis of the research results in the past 20 years showed that decision support tools are the most used solutions to problems related to forest planning and management, especially the analytic hierarchy process (AHP). Light detection and ranging (LiDAR) is the second most popular method. With the development of geoinformatics, it will play an increasingly important role in forest planning and management in the future. © 2024 by the authors.

This paper aims to demonstrate the use of qualitative research methods, specifically in-depth interviews, to explore the intangible and often difficult-to-quantify needs for forestry scenario modelling in Lithuania, which are frequently not adequately perceived. The study involved informants representing key actors in forest policy, forest management, research, and education. A total of 21 informants from 11 different institutions, which hold significant power and expertise in forest decision making, were interviewed. The purpose of these interviews was to gather their perspectives on the potential forest decision support system in the country, aiming to address most of their needs. The interview questions explored various aspects, including the requirements for forestry scenario modelling, the desired level of detail and information content for decision making, and both functional and nonfunctional requirements for the scenario modelling system. It is worth noting that the expected functionality of the planned forest DSSs aligns with modern international standards. Nevertheless, the diversity of perspectives, wishes, visions, and intentions of key Lithuanian forestry actors regarding the aims, objectives, and essential functionality of forestry scenario modelling tools were identified. The understanding of the requirements for modern forest DSSs was greatly influenced by the current forestry paradigms in the country and the professional experiences of individual informants. In conclusion, our findings demonstrate that the utilization of qualitative research, particularly through in-depth interviews, has proven to be a highly effective tool for accurately specifying the requirements of a modern forest DSS. It helped mitigate preconceived notions and address gaps in the envisioned product, specifically by developing a framework of core solutions for the national forestry and land-use scenario modelling system. © 2024 by the authors.

Appropriate forest thinning measures can mitigate the conflicting relationship between past excessive afforestation and current increasing regional water deficiency in dryland ecosystems. However, since blind intervention in forest landscapes may incur additional economic costs and cause the loss of ecosystem services, forest thinning in drylands mostly exists in scientific discussions and is seldom implemented in reality. In this study, we propose an advanced technical route to predict the spatial arrangement of potential forest thinning locations under different policy scenarios. Taking Shanxi Province in China as a case study, we simulated eight policy scenarios for different stakeholders to assess the benefits and costs after forest thinning in the future. The results show that a water deficit of 533 million m3 exists in Shanxi Province that could potentially be mitigated by means of forest thinning. Under different policy scenarios, the thinned area ranged from 1142.91 to 1195.47 km2, which would result in an additional soil loss of 1.77–3.02 million m3/year and a loss of carbon sequestration of 3.15–3.24 million t/year. Considering both soil conservation and food security scenarios can help minimize the direct costs and loss of forest carbon sequestration capacity and maintain a sustainable landscape pattern. The method can be used as a decision support tool to identify the potential locations of forest thinning and resulting consequences under water scarcity conditions in drylands and to support stakeholders in making scientific adaptive forest landscape optimization decisions. © 2023 John Wiley & Sons Ltd.

Amidst the increasing frequency and severity of forest fires globally, the imperative of effective post-fire forest restoration has gained unprecedented significance. This study outlines a comprehensive approach to post-fire forest restoration and discusses its implementation through spatial decision-making systems. The methodology involves utilizing multi-criteria analysis (MCA) to identify and prioritize criteria based on their relative importance. This allows for the creation of easily assessable alternatives and their application to spatial maps, providing local officials with valuable information. To achieve optimal decision-making, the study utilized the Analytic Hierarchy Process (AHP) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods along with Spatial Decision Support Systems (SDSS) to generate a suitability map. The results highlight that 28% of the study area is well-suited for post-fire forest restoration, with 44% moderately appropriate, while 3% is deemed unsuitable for restoration until the end of 2023 due to severe soil loss or inherent geographical challenges. © 2024 by the authors.

According to estimates, the world population is expected to be around 9 billion by 2050. Related to this, the number of people suffering from hunger is increasing day by day. Unconscious use of agricultural lands, climate changes, and the effect of increasing population, the problem of food needs increase the pressure on agriculture. In order to meet the need for food effectively, studies in areas such as sustainable land/forest management, improvement of cultivation areas, and agricultural policies should be carried out urgently. Increasing productivity by improving agricultural activities is important in terms of realizing the potential of agricultural lands. In this study, a plant production plan is created according to the relevant data on the agricultural lands in a city. The aim is to create a sustainable production plan and to present a model that will increase the economic return that maximizes the return that was established. In the study, a mixed-integer model that maximizes the return is developed and it is aimed to determine which plants will grow in which region and to make a production plan accordingly. The distinctive value of the study is to propose a new decision support system for planning studies in Turkey in the field of agricultural production. As a result of the success of the project in the desired way, a system that will help the decision-makers in the relevant field will be gained, as well as contribute to the literature. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.