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Ecological network assessment of forest bioenergy options using the landscape simulator LandSim: a case study of Kronoberg, southern Sweden
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering. (Environmental Management and Assessment)ORCID iD: 0000-0001-6417-4497
(Environmental Management and Assessment)ORCID iD: 0000-0002-1640-8946
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The need to adapt to climate change as well as to secure the supply of energy has led to a shift in energy consumption from fossil fuel to renewables. In this context, forest biomass is a resource that is increasingly utilised for bioenergy purposes in Sweden, which along with the extraction of industrial wood may conflict with other sustainability goals such as those related to biodiversity conservation. In order to balance between main sustainability objectives, land zoning policies and related management regimes has been proposed, differentiating between the main management categories protected areas, multi-purpose forestry and intensive forestry. The aim of this project was to develop methods and tools for integrated sustainability assessment of forest biomass extraction, in particular from bioenergy and biodiversity perspectives.

For this purpose, the landscape simulator LandSim was developed and applied in a case study in Kronoberg County in southern Sweden. Forest growth and management was simulated in 5-year time steps for the period 2010-2110. The management followed two land zoning scenarios, one applying even-aged forestry on all forest land except for protected areas (EAF-tot), and one was applying continuous cover forestry on parts of the forest land, combined with protected areas and a shorter rotation time on the other parts (CCF-int). The outcome of the simulations was raster data on tree species, volume and age for each time step and scenario. From the outcome, harvested volumes and bioenergy feedstock yields were derived. The same outcome was used for an ecological network assessment, using the indicator Equivalent Connected Area (ECA) for two model species tied to mature and old coniferous and southern broadleaved forest, respectively.

The results showed that the EAF-tot scenario implied higher yields of biomass feedstock for bioenergy than the CCF-int scenario, while the CCF-int scenario displayed more even yields over the years. By contrast, the CCF-int scenario performed substantially better than the EAF-tot scenario when it came to the ECA indicators. However, the CCF-int scenario involved a range of assumptions mirroring major uncertainties on habitat suitability, which yielded separate results and thus will need further exploration. Moreover, in order to support the model species and related biodiversity components, the forest management would need to allow larger areas to become suitable habitat, as well as to plan for habitat amount and connectivity on landscape scale in order to not only increase habitat size but also ECAs. Conclusively, the modelling framework linking the landscape simulator with the ecological network model could be used for integrated sustainability assessment of bioenergy options, integrating main policy concerns when assessing renewable energy options.

National Category
Environmental Management
URN: urn:nbn:se:kth:diva-180339OAI: diva2:892818

QS 2016

Available from: 2016-01-11 Created: 2016-01-11 Last updated: 2016-01-11Bibliographically approved
In thesis
1. Modelling trade-offs between forest bioenergy and biodiversity
Open this publication in new window or tab >>Modelling trade-offs between forest bioenergy and biodiversity
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Globally, biodiversity is declining due to loss, fragmentation and degradation of habitat, which undermines ecosystem functioning and therefore threatens also the ability of ecosystems to supply ecosystem services. Moreover, there is a need for adapting to climate change as well as securing the supply of energy, which have led to a shift in energy consumption from fossil fuel to renewables, especially biomass, which in turn put increasing pressure on ecosystems and biodiversity. In Sweden, forest bioenergy has an important role, and high forest biomass production is an important societal objective. Intensified forestry could increase the biomass production through monocultures of native or introduced tree species as well as forest fertilization. However, due to negative effects on natural forest structures and processes, a more intensive forestry could be detrimental to forest biodiversity. The balance between energy demand and the long-term capacity of ecosystems to supply goods and services as well as support biodiversity is therefore crucial. The existing energy models and research have relatively low concerns on land use, landscape and biodiversity, comparing with high enthusiastic on energy economics, climate change and greenhouse gas emission research. Consequently, it would be difficult to provide comprehensive decision support by using only these economy and climate change oriented tools. However, ecological assessment models and multi-criteria approaches exist with great potential for linking with suitable energy models. This will enable the development of more comprehensive decision support tools for assessing future energy scenarios, integrating main policy concerns when assessing renewable energy options. The research was based on a survey on existing energy models and a case study of forest biomass extraction in Kronoberg, a region in southern Sweden. The aim of this project was to develop and test methods for integrated the sustainability assessment of forest biomass extraction for bioenergy purposes by incorporating effects on biodiversity. Forest growth was simulated under two management scenarios: Even-aged-forestry (EAF) and continuous-cover-forestry (CCF), in a time period between 2010-2110. The GIS-based approaches for assessment of biomass impacts on biodiversity involved an ecological network assessment of prioritized ecological profiles across the landscape under the two scenarios.


Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. xvi, 44 p.
TRITA-LWR. LIC, ISSN 1650-8629 ; 2015:03
National Category
Environmental Sciences
Research subject
Land and Water Resources Engineering
urn:nbn:se:kth:diva-180333 (URN)978-91-7595-815-6 (ISBN)
2016-01-27, V2, Teknikringen 76, KTH, Stockholm, 14:00 (English)

QC 20160111

Available from: 2016-01-11 Created: 2016-01-11 Last updated: 2016-01-12Bibliographically approved

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