The usefulness of kNN (k Nearest Neighbour)-assigned reference sample plot data as a basis for forest management planning was studied. Cost-plus-loss analysis was applied, whereby the inventory cost for a specifi c method is added to the expected loss due to non-optimal forestry activities caused by erroneous descriptions of the forest state. Four different strategies for data acquisition were evaluated: 1) kNN imputation of sample plots based on traditional stand record information, 2) imputation based on plot-wise aerial photograph interpretation in combination with stand record information, 3) sample plot inventory in the fi eld with 5 plots per stand, and 4) sample plot inventory with 10 plots per stand. Expected losses were derived as mean values of differences between the maximum net present value and the corresponding value obtained when the treatment schedule believed to be optimal (based on data simulated according to method 1-4) was selected. The optimal choice of method was found to depend on factors such as stand maturity, stand area, and time to next treatment (thinning or clearcutting). In general, the fi eld sample plot methods were competitive in large mature stands, especially when the time to the next (optimal) treatment was short. By in each stand (within an estate) employing the method with the lowest cost-plus-loss rather than choosing the method that performed best on average for the entire estate, the total cost for inventory at the estate level could be decreased by 15-50%. However, it was found diffi cult to identify what method should optimally be employed in a stand based on general stand descriptions.
Bioenergy from boreal forests managed for productive purposes (e.g., pulp, timber) is commonly held to offer attractive options for climate change mitigation. However, this view has been challenged in recent years. Carbon balances, cumulative radiative forcing, and average global temperature change have been calculated for a variety of bioenergy management regimes in Swedish forests, and the results support the view that an increased use of forest biomass for energy in Sweden can contribute to climate change mitigation, although methodological (e.g., spatial scales) and parameter value choices influence the results significantly. We show that the climate effect of forest-based bioenergy depends on the forest ecosystems and management, including biomass extraction for bioenergy and other products, and how this management changes in response to anticipated market demands; and on the energy system effects, which determine the fossil carbon displacement and other greenhouse gas (GHG) mitigation effects of using forest biomass for bioenergy and other purposes. The public and private sectors are advised to consider information from comprehensive analyses that provide insights about energy and forest systems in the context of evolving forest product markets, alternative policy options, and energy technology pathways in their decision-making processes.
Information about the state of the forest is of vital importance in forest management planning. To enable high-precision modelling, many forest planning systems demand input data at the single-tree level. The conventional strategy for collecting such data is a plot-wise ® eld inventory. This is expensive and, thus, cost-ef® cient alternatives are of interest. During recent years, the focus has been on remote sensing techniques. The k nearest neighbour (kNN) estimation method is a way to assign plot-wise data to all stands in a forest area, using remotely sensed data in connection with a sparse sample of ® eld reference plots. Plot-wise aerial photograph interpretations combined with information from a stand register were used in this study. Nearness to a reference plot was decided upon using a regression transform distance. Standing stem volume was estimated with a relative root mean square error (RMSE) equal to 20% at the stand level, while age could be estimated with a RMSE equal to 15%. A cost-ef® cient data-capturing strategy could be to assign plot data with the presented kNN method to some types of forest, while using traditional ® eld inventories in other, more valuable, stands.
Studies report different findings concerning the climate benefits of bioenergy, in part due to varying scope and use of different approaches to define spatial and temporal system boundaries. We quantify carbon balances for bioenergy systems that use biomass from forests managed with long rotations, employing different approaches and boundary conditions. Two approaches to represent landscapes and quantify their carbon balances -expanding vs. constant spatial boundaries -are compared. We show that for a conceptual forest landscape, constructed by combining a series of time-shifted forest stands, the two approaches sometimes yield different results. We argue that the approach that uses constant spatial boundaries is preferable because it captures all carbon flows in the landscape throughout the accounting period. The approach that uses expanding system boundaries fails to accurately describe the carbon fluxes in the landscape due to incomplete coverage of carbon flows and influence of the stand-level dynamics, which in turn arise from the way temporal system boundaries are defined on the stand level. Modelling of profit-driven forest management using location-specific forest data shows that the implications for carbon balance of management changes across the landscape (which are partly neglected when expanding system boundaries are used) depend on many factors such as forest structure and forest owners' expectations of market development for bioenergy and other wood products. Assessments should not consider forest-based bioenergy in isolation but should ideally consider all forest products and how forest management planning as a whole is affected by bioenergy incentives -and how this in turn affects carbon balances in forest landscapes and forest product pools. Due to uncertainties, we modelled several alternative scenarios for forest products markets. We recommend that future work consider alternative scenarios for other critical factors, such as policy options and energy technology pathways.
Abstract:In this study, we assessed the effect of a diverse ownership structure with different management strategies within and between owner categories in long-term projections of economic, ecological and social forest sustainability indicators, representing important ecosystem services, for two contrasting Swedish municipalities. This was done by comparing two scenarios: one where the diversity of management strategies was accounted for (Diverse) and one where it was not (Simple). The Diverse scenario resulted in a 14% lower total harvested volume for the 100 year period compared to the Simple scenario, which resulted in a higher growing stock and a more favorable development of the ecological indicators. The higher proportion of sparse forests and the lower proportion of clear-felled sites made the Diverse scenario more appropriate for delivering access to common outdoor recreation activities, while the Simple scenario projected more job opportunities. Differences between the scenarios were considerable already in the medium term (after 20 years of simulation). Our results highlight the importance of accounting for the variety of management strategies employed by forest owners in medium-to long-term projections of the development of forest sustainability indicators. OPEN ACCESSForests 2015, 6 4002
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