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Articles by Göran Ståhl

Category: Research article

article id 1000, category Research article
Sören Wulff, Cornelia Roberge, Anna Hedström Ringvall, Sören Holm, Göran Ståhl. (2013). On the possibility to monitor and assess forest damage within large scale monitoring programmes – a simulation study. Silva Fennica vol. 47 no. 3 article id 1000. https://doi.org/10.14214/sf.1000
There is a growing demand for information on forest health due to fears that climate change may cause new kinds of damage that have not previously been encountered. In many cases, forest damage monitoring is conducted exclusively within sparse large-scale grids of sample plots and it is doubtful whether these are capable of providing relevant information to support mitigation programmes or other actions required to reduce economic losses due to damage outbreaks. In this study, we used simulated sampling to assess the precision of estimators related to forest state and changes in the damage sustained by trees within an area corresponding to the Swedish region Götaland, assuming a sampling design corresponding to that used in the Swedish National Forest Inventory (NFI) under different damage scenarios. Large and uniformly distributed damage outbreaks were well captured by an NFI-type inventory, but scattered damage outbreaks produced estimates with poor precision. As a consequence, we propose that there might be a need to revise current forest damage monitoring programmes to make them more useful for monitoring the kinds of damage that are likely to arise as a consequence of climate change.
  • Wulff, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden ORCID ID:E-mail: soren.wulff@slu.se (email)
  • Roberge, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden ORCID ID:E-mail: cornelia.roberge@slu.se
  • Ringvall, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden ORCID ID:E-mail: anna.ringvall@slu.se
  • Holm, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden ORCID ID:E-mail: soren.holm@slu.se
  • Ståhl, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Skogsmarksgränd, SE-901 83 Umeå, Sweden ORCID ID:E-mail: goran.stahl@slu.se
article id 265, category Research article
Emil Cienciala, Erkki Tomppo, Arnor Snorrason, Mark Broadmeadow, Antoine Colin, Karsten Dunger, Zuzana Exnerova, Bruno Lasserre, Hans Petersson, Tibor Priwitzer, Gerardo Sanchez, Göran Ståhl. (2008). Preparing emission reporting from forests: use of National Forest Inventories in European countries. Silva Fennica vol. 42 no. 1 article id 265. https://doi.org/10.14214/sf.265
We examine the current status of greenhouse gas inventories of the sector Land Use, Land-Use Change and Forestry (LULUCF), in European countries, with specific focus on the utilization of National Forest Inventory (NFI) programs. LULUCF inventory is an integral part of the reporting obligations under the United Nations Framework Convention on Climate Change (UNFCCC) and its Kyoto Protocol. The analysis is based on two questionnaires prepared by the COST Action E43 “Harmonisation of National Forest Inventories in Europe”, which were answered by greenhouse gas reporting experts in European countries. The following major conclusions can be drawn from the analysis: 1) definitions used to obtain carbon pool change estimates vary widely among countries and are not directly comparable 2) NFIs play a key role for LULUCF greenhouse gas estimation and reporting under UNFCCC, and provide the fundamental data needed for the estimation of carbon stock changes covering not only living biomass, but increasingly also deadwood, litter and soil compartments. The study highlights the effects of adopting different definitions for two major reporting processes, namely UNFCCC and FAO, and exemplifies the effect of different tree diameter thresholds on carbon stock change estimates for Finland. The results demonstrate that more effort is needed to harmonize forest inventory estimates for the purpose of making the estimates of forest carbon pool changes comparable. This effort should lead to a better utilization of the data from the European NFI programs and improve the European greenhouse gas reporting.
  • Cienciala, Institute of Forest Ecosystem Research (IFER), Areal 1. Jilovske a.s. 1544, 254 01 Jilove u Prahy, Czech Republic ORCID ID:E-mail: emil.cienciala@ifer.cz (email)
  • Tomppo, Metla, Finnish Forest Research Institute, Finland ORCID ID:E-mail:
  • Snorrason, Icelandic Forest Research, Iceland ORCID ID:E-mail:
  • Broadmeadow, Forestry Commission, Forest Research Alice Holt Logdge, United Kingdom ORCID ID:E-mail:
  • Colin, French National Forest Inventory, France ORCID ID:E-mail:
  • Dunger, Federal Research Centre for Forestry and Forest Products, Institute of Forest Ecology and Forest Assessment, Germany ORCID ID:E-mail:
  • Exnerova, Institute of Forest Ecosystem Research, Czech Republic ORCID ID:E-mail:
  • Lasserre, Department of Environment and Territory Sciences and Technologies, University of Molise, Italy ORCID ID:E-mail:
  • Petersson, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Sweden ORCID ID:E-mail:
  • Priwitzer, National Forest Centre, Forest Research Institute. Slovak Republic ORCID ID:E-mail:
  • Sanchez, Forest Health Unit, General Directorate for Biodiversity, Environmental Ministry, Spain ORCID ID:E-mail:
  • Ståhl, Swedish University of Agricultural Sciences, Department of Forest Resource Management, Sweden ORCID ID:E-mail:
article id 496, category Research article
Hampus Holmström, Hans Kallur, Göran Ståhl. (2003). Cost-plus-loss analyses of forest inventory strategies based on kNN-assigned reference sample plot data. Silva Fennica vol. 37 no. 3 article id 496. https://doi.org/10.14214/sf.496
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 specific 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 field 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 field 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 difficult to identify what method should optimally be employed in a stand based on general stand descriptions.
  • Holmström, Regional Board of Forestry of Västra Götaland, P.O. Box 20008, SE-50420 Borås, Sweden ORCID ID:E-mail: hampus.holmstrom@svsvg.svo.se (email)
  • Kallur, ÖKA Skogsplan, Kopparvägen 45 O, SE-90750 Umeå, Sweden ORCID ID:E-mail:
  • Ståhl, Swedish Univ. of Agricultural Sciences, Dept. of Forest Resource Management and Geomatics, SE-90183 Umeå, Sweden ORCID ID:E-mail:
article id 595, category Research article
Kenneth Nyström, Göran Ståhl. (2001). Forecasting probability distributions of forest yield allowing for a Bayesian approach to management planning. Silva Fennica vol. 35 no. 2 article id 595. https://doi.org/10.14214/sf.595
Probability distributions of stand basal area were predicted and evaluated in young mixed stands of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and birch (Betula pendula Roth and Betula pubescens Ehrh.) in Sweden. Based on an extensive survey of young stands, individual tree basal area growth models were estimated using a mixed model approach to account for dependencies in data and derive the variance/covariance components needed. While most of the stands were reinventoried only once, a subset of the stands was revisited a second time. This subset was used to evaluate the accuracy of the predicted stand basal area distributions. Predicting distributions of forest yield, rather than point estimates, allows for a Bayesian approach to planning and decisions can be made with due regard to the quality of the information.
  • Nyström, SLU, Department of Forest Resource Management and Geomatics, SE-901 83 Umeå, Sweden ORCID ID:E-mail: kenneth.nystrom@resgeom.slu.se (email)
  • Ståhl, SLU, Department of Forest Resource Management and Geomatics, SE-901 83 Umeå, Sweden ORCID ID:E-mail:

Category: Review article

article id 1095, category Review article
Jonas Fridman, Sören Holm, Mats Nilsson, Per Nilsson, Anna Hedström Ringvall, Göran Ståhl. (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 vol. 48 no. 3 article id 1095. https://doi.org/10.14214/sf.1095
Highlights: National Forest Inventories supply invaluable long term time series of forest state. Recent developments and international harmonization of modern NFIs widen the scope to even include ecosystem goods, e.g. biodiversity and carbon sequestration. The combination of NFI field data with remote sensing techniques can give good estimates for areas smaller than national and regional level.
National Forest Inventories (NFIs) are becoming increasingly important worldwide in order to provide information about the multiple functions of forests, e.g. their provision of raw materials to industry, biodiversity and their capacity to store carbon for mitigating climate change. In several countries the history of NFIs is very long. For these countries a specific challenge is to keep the inventories up-to-date without sacrificing the advantages associated with long time series. At the turn of the 20th century European NFIs faced some major challenges. In this article we describe the history and the recent developments of the Swedish NFI as an example from which general observations are made and discussed. The Swedish NFI started in 1923 and has evolved from an inventory with a narrow focus on wood resources to an inventory today which aims to provide information about all major forest ecosystem services. It can be concluded that the traditional approaches of most European NFIs, e.g. to collect data through sample plot field inventories, has proved to be applicable even for a wide range of new information requirements. Specifically, detailed data about land use, trees, vegetation, and soils has found new important uses in connection with biodiversity assessments and the estimation of greenhouse gas emissions. Though time-consuming and difficult, making NFI information comparable across countries through harmonization appears to be a useful approach. The European National Forest Inventory Network (ENFIN) was formed in 2003 and has been successful in pan-European NFI harmonization.
  • Fridman, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: jonas.fridman@slu.se (email)
  • Holm, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: soren.holm@slu.se
  • Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: mats.nilsson@slu.se
  • Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: per.nilsson@slu.se
  • Ringvall, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: Anna.Ringvall@slu.se
  • Ståhl, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: goran.stahl@slu.se

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