National environmental goals are not fully achieved in Swedish forestry due to the conflict between biodiversity conservation and forestry´s focus on profitability. Swedish forestry is characterized by considerable freedom, and forest owners' choice of management methods is often influenced by economic profitability. Nearly half of the productive forest land is privately owned, highlighting the significant impact of private forest owners' management methods on achieving environmental goals. Encouraging forest owners to voluntarily certify their forests can play a role in preserving biological diversity and achieving environmental objectives.

The study aims to investigate how forest certification can promote the conservation of natural values within Swedish forestry. The initial focus of the research has been to explore the motivations of private forest owners for certifying their forests and to analyze the perceived effects of certification. In addition, the study intends to identify potential incentives for certification and biodiversity conservation.

Qualitative interviews with forest owners in Dalsland were conducted to gather data for the study. Through qualitative content analysis, interviews were categorized based on three sustainability dimensions - economic, ecological, and social - to understand the sustainability effects achieved.

The results indicate that forest certification has led to several effects across all sustainability dimensions. While many forest owners share common experiences with certification, each owner also brings their own individual context to the experience. In conclusion, the primary motivation for forest certification among owners has been financial incentives. Moreover, it implies that certification has yielded additional effects that could prove advantageous in efforts towards conserving biological diversity and achieving environmental goals.

This article investigates how the Swedish forest industry, as represented by the three largest Swedish private forest companies (Svenska Cellulosa AB, Stora Enso, and Holmen), through their main public relations (PR) channels frame the current dominant Swedish forestry model and alternative models that are promoted by the European Union (EU). The content analysis of the three companies’ trade magazines published between 2019 and 2022 explores the patterns in the PR framing of the forest management models with respect to economic, environmental, and social aspects. The time interval is centered by the July 2021 announcement of the EU’s new Forest Strategy for 2030. The magazines’ target audience is private forest owners, from whom Svenska Cellulosa AB, Stora Enso, and Holmen buy 40–50% of the timber used in production. The main finding of the study is that these corporations did not present alternative methods as viable options to replace the Swedish forestry model. The magazines, with some individual variations, respond to the alternative methods promoted by the EU and environmental associations by an increased emphasis on the benefits, mainly environmental, of the Swedish forestry model–framing the model as not only the most profitable but also the most ecologically sustainable. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

This thesis examines the diverse perspectives of stakeholders in sustainable forest management and the co-production of knowledge through collaborative efforts. Existing literature has proved the complex interrelations among a wide range of stakeholders, including landowners, government entities, forestry households, industries, residents, and environ mentalists, emphasising the need to understand their viewpoints for effective management.

The study focuses on Japan's Forestry Policy Council, analysing the council's meetings to assess the distinct pathways each stakeholder group advocates and how they co-produce knowledge, particularly through the active involvement of academia.

The findings reveal varied pathways promoted by different stakeholders, with institutional stakeholders like the Forestry Agency pushing for comprehensive policies, while industrial stakeholders seek economic viability, and civil society organisation stakeholders prioritise environmental sustainability.

The present author underscores the significance of academic involvement in policy development for sustainable forestry, given their capacity for long-term, integrative perspectives that meld scientific knowledge with public interests.

Invasive plants are an increasing problem in society and pose a major threat to our ecosystem, infrastructure, health and biodiversity. The high cost of controlling the spread of invasive plants is a fact and modern satellites can provide the data needed to map the presence of these invasive plant species. Previous studies for mapping invasive plants have used classification methods such as Support Vector Machine (SVM), Random Forest (RF) and texture analysis algorithms. Information on whether more simple classification methods can be used to perform a similar classification of vegetation is limited. Likewise, studies for mapping only the invasive tree species Pinus contorta. This study relies on the use of both pixel-based and object-based classifications to identify and classify the contorta pine. Which form of classification method is appropriate varies as all plants have different spatial and spectral characteristics. A method that works for classifying one species does not necessarily mean that it will be applicable to another species. The data used in the study are satellite images from 2018 collected by Sentinel-2 with a resolution of 10 x 10 meters. The data was then processed in ArcMap 10.8 software during all stages of the analysis. Four different forms of classification were performed to find the most appropriate method for classifying the contorta pine. The classification results were validated against the Swedish University of Agricultural Sciences (SLU) raster map of contorta stands in the selected study area located north of Härnösand and showed inconclusive results. Each classification was compared to SLU's mapping and with the help of a critical success index (CSI) that shows the performance of the classification model successful hits (A), overestimated (B) and miss (C), the results could be more easily analyzed and interpreted. The methods used in the classification model of Pinus contorta showed 0.5-0.9% correct classification.