Strategisk planering i praktiskt skogsbruk

Med det nya planeringsverktyget Heureka kan långsiktiga och målinriktade handlingsplaner tas fram. Väsensskilda målsättningar kan innebära att planerna och dess föreslagna skogsbruksåtgärder blir mycket olika. Projektet syftar till att påvisa effekterna av vissa strategiska målsättningar genom att för skogsfastigheten Fenneslunda 2:1 i Ulricehamns kommun och Västra Götalands län, fortsättningsvis benämnd ”Fänneslunda”, presentera analysresultat på beståndsnivån – för skogsbestånd där en viss åtgärd föreslås vid en viss tidpunkt för en så hög måluppfyllelse som möjligt. Tre olika scenarier definierades och analyserades: • Scenario 1 motsvarande ett traditionellt trakthyggesbruk och referensplan i sammanhanget • Scenario 2 motsvarande ett avkastningsmaximerande skogsbruk erhållet genom virkes-produktionsgynnande åtgärder • Scenario 3 motsvarande ett skogsbruk anpassat till att gynna rekreations- och friluftsvärden, främst genom användning av hyggesfria skötselmetoder Sammanfattningsvis kan sägas att relativt modesta skillnader framträder i analysresultaten för de tre olika scenarierna, särskilt beaktande föreslagna skogsbruksåtgärder i relativ närtid och på fastighetsnivån. Det som främst påverkar den framtida skogsskötseln är den historiska skogsskötseln. Till exempel så föreslås för scenario 1 en genomsnittlig avverkning motsvarande 7 m3sk/ha och år, för scenario 2 motsvarande 8 m3sk/ha och år samt för scenario 3 motsvarande 5 m3sk/ha och år. Beaktas däremot resultaten på beståndsnivån, dvs. de beståndsvisa avverkningsförslagen, framträder desto större skillnader mellan scenarierna. Här förekommer såväl spatiala som temporala skillnader, liksom skillnader i valet av avverkningsmetod. För den intresserade och initierade läsaren återstår att tolka resultaten och själv komma fram till om det kan anses som stora eller små skillnader när de olika scenarierna jämförs

A Conceptual Landscape-Level Approach to Assess the Impacts of Forestry on Biodiversity

In this study, we propose a conceptual approach to assessing biodiversity impacts in the life-cycle assessments (LCAs) of forest wood production with a focus on Nordic managed forests at the landscape level. As a basis for our methodology, we suggest assessing the proportion of the total land area of productive forest under the control of a forest owner that fulfils certain criteria that can be regarded as having a positive impact on the development of forest biodiversity. A similar assessment of the forest management performed on the surrounding land is used to define a site-specific reference situation. In the context of an attributional LCA, the suggested method for the specification of business-as-usual (BAU) or environmental quality objectives (EQO) baselines encourages forest owners to choose forest management options that increase the proportion of productive forest land with properties that are more favorable to biodiversity over time. We illustrate the BAU baseline approach with two examples in Sweden to calculate the biodiversity impact from wood production for individual forest owners using four biodiversity indicators from the Swedish national Environmental Quality Objectives (EQOS)-'Living Forests'. The approach defined in this study is at this stage only applicable to forestry assessments. Using a BAU baseline approach similar to that used for international climate reporting is a simple but novel approach that makes use of consensuses that have already been drawn and approaches that have already been established

Accounting for a Diverse Forest Ownership Structure in Projections of Forest Sustainability Indicators

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

Costs and benefits of seven alternatives for riparian forest buffer management

Stand development in riparian forest buffers was simulated for three forest landscapes in Sweden, using data taken from a sample plot inventory along 38 streams. The objectives were: to quantify the effects on wood production and the economy of management alternatives for buffers; and to evaluate the development of important stand structures for buffer functionality. Buffer widths from 0 to 30 m were analyzed with unmanaged or selective logging as alternatives. Leaving unmanaged buffers resulted in the cost being generally proportional to the area of productive forest land covered by buffers in the landscape. The cost for the widest buffer alternative, 30 m, when left unmanaged, was between 4 and 10% of the total net present value of the entire forest landscape. Allowing selective logging to promote broadleaved trees in the buffer reduced the costs to 1-3% of the net present value. Selective logging increased the volume share of broadleaved trees in the buffer, thus enhancing some of its ecological functions. Unmanaged buffers increased the amount of dead wood more than the alternatives with selective logging. Decisions about buffer zone management must consider the trade-off between economic and environmental benefits, as well as the trade-offs between contrasting environmental goals

The multi-faceted Swedish Heureka forest decision support system: context, functionality, design, and 10 years experiences of its use

For several decades, computerized forest decision support systems (DSS) have helped managers and decision makers to analyze different management options and supported the search for preferred management alternatives. In Sweden, a country rich in forests and with a long tradition in intensive forest management, such systems have been developed and available since the 1970s. Changes in societal as well as in forest owners' preferences and objectives in the 1990s led to a need for forest DSS handling broader perspectives compared to precedent single-objective timber-oriented systems. In Sweden, this led to the initiation of a research programme in the beginning of the 2000s aiming at developing a versatile and multi-objective forest DSS, resulting in the first version of the Heureka forest DSS released in 2009. The system handles several forest values, such as timber and biofuel production, carbon sequestration, dead wood dynamics, habitat for species, recreation and susceptibility to forest damages (spruce bark beetle, wind-throw and root rot). It contains a suite of software for different problem settings and geographical scales and uses simulation as well as optimization techniques. Three software handle projections of the forest using a common core of growth and yield models for simulating forest dynamics. A fourth software, built for multi-criteria decision analysis and including a web-version, enables also group decision making and participatory planning. For more than 10 years, the Heureka system has been used in teaching, environmental analysis, research and as decision support in practical forestry. For example, several research groups using the system for analyses in different problem areas have so far published more than 80 scientific papers. The system is used for nation-wide forest impact analysis for policy support and all large and many medium-sized forest owners use it for their long-term forest planning, meaning that it directly influences forest management decisions and activities on more than 50% of the Swedish forest area. Besides presenting the present system and its use, we also discuss lessons learned and potential future development

Data acquisition for forestry planning by remote sensing based sample plot imputation

In forestry planning, accurate description of the state of the forests is essential. Advanced planning models often require input data with high resolution, i.e. data at the single-tree level. Field inventory procedures based on sample plot measurements are usually employed. However, such methods are expensive, so cost-efficient alternatives would be attractive. In the work described in this thesis, inventory methods based on imputation of reference sample plot data were evaluated. The reference material consisted of data from previously performed field inventories. The k nearest neighbour (kNN) method was used, in which all variables available at the reference plots were simultaneously estimated for the target areas. The imputations were based on information derived from interpretations of aerial photographs, optical satellite data, radar data (airborne sensor), and existing stand records. To account for differences in the qualities of the different information sources combined in the kNN estimations, distance metrics were defined and applied using regression functions. The utility of various types of forecasted reference material was evaluated. Increasing the length of forecasts of reference sample plot data increased the mean square error (MSE) in stem volume estimates. However, by excluding disturbed plots (due to thinnings) from the reference material, plot data forecasted for up to 25 years could be used without severely decreasing the accuracy of the estimations. Using aerial photo interpretations together with stand records, kNN estimates of stem volume with relative root MSEs (RMSEs) of 14-20% at the stand level were obtained. More accurate estimates were obtained for a northern test site, in comparison with results from southern Sweden. Combining optical satellite data and radar data significantly improved results, giving a RMSE in standwise stem volume estimates of 22%, compared to 30% for the best single-sensor case. Consequences of using kNN estimations in a planning context were evaluated by a cost-plus-loss approach. The total cost of undertaking an inventory was obtained by summing the actual inventory cost and the net present value of expected future losses due to non-optimal decisions caused by erroneous data. Input data obtained by imputation of reference sample plots were compared with traditional field sample plot inventories. Results indicated that the total cost of an inventory could be reduced by 15-50% by integrating different methods; imputation could be applied for some types of stands while more accurate field inventories should be carried out in others. It is not necessarily the most valuable stands that should be inventoried by careful field measurements, but many of those with a treatment impendi

Combining remotely sensed optical and radar data in kNN-estimation of forest variables

The use of optical and radar data for estimation of forest variables has been investigated and evaluated by employing the k nearest neighbor (kNN) method. The investigation was performed at a test site located in the south of Sweden consisting mainly of Norway spruce and Scots pine forests with standwise stem volume in the range of 0–430 m3 ha–1. The kNN method imputes weighted reference plot variables to areas to be estimated (target areas), facilitating further use of data in forestry planning models. Remotely sensed multispectral optical data from the SPOT-4 XS satellite and radar data from the airborne CARABAS-II VHF SAR sensor were used, separately and combined, to define weights in the kNN algorithm. The weights were inversely proportional to the image feature distance between the reference plot and the target area. The distance metric was defined using regression models based on the image data sources. Positive impact on the accuracies of stem volume and age estimates was found by combining the two image data sources. Stem volume, at stand level, was estimated with a RMSE of 37 m3 ha–1 (22% of the true mean value) using the combination of optical and radar data, compared to 50 m3 ha–1 (30%) for the best single-sensor case in this study. In conclusion, the results indicate that the accuracy of forest variable estimations was substantially improved by using multisensor data

Averaging absolute GPS positionings made underneath different forest canopies

Dealing with data collection of natural resources for management planning purposes, there is an interest in capturing the spatiality, i.e. the geographical location of the features of interest. The Global Positioning System (GPS) provides a tool, both for navigation and positioning, although not without limitations. Several sources of errors have impact on the positional accuracy. Differential GPS increases the accuracy but might in certain applications be unavailable. Navigating in difficult terrain (e.g. mountain areas), where traditional maps give little or no guidance, highlights the benefits of GPS. By applying a not-so-advanced algorithm, arithmetical averaging, using absolute (non-differential) GPS measurements, it is possible to improve the positional accuracy. Initial horizontal mean errors are decreased by 50 % after approx. 10 minutes of active logging of singular GPS-positions and averaging these. Improvement of the accuracy continues thereafter, although substantial improvements require long time of observation. The impact of the canopy was marginal, however assumed to cause longer time of logging in dense forests before a certain number of positions are obtained, compared to measurements made under a clear sky. However, it must be pointed out that the results are of somewhat doubtful value, since the conditions were drastically changed when the intentional distortion of the GPS-signals (the Selective Availability, SA) was stopped. In the current situation, the different structure of the remaining errors leads to a limited use of averaging. This study was carried out just before the SA was stopped, which happened quite unexpectedly in May 2000