Publications

Download a complete list of scientific publications by EFI researchers: 2020 |2019 |2018 | 2017 | 2016 | 2015 | 2014 | 2013

 

Published on
Spatial planning of green infrastructure has become well established since the turn of the millennium. However, as a planning and policy concept alone it lacks the focus and immediacy that decision
Climate change
Policy
Resilience
Urban forests
Published on
Special issue "Forest ownership change: trends and issues" aims to contribute to a better understanding of the role of forest owners in forest management, not only through forest owner typology
Forest management
Forest owners
Governance
Innovation
Policy
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The European forest sector phases numerous demands and challenges, and the need to mitigate and adapt to climate change might just be the biggest one of them. The issue is well acknowledged in high
Climate change
Forest management
Policy support
Resilience
Risk
Published on
Based on two in-depth case studies of mountain-bike trails in rural areas of Switzerland, the article analyses the role SI plays in increasing the benefits of forest-based recreation for providers and
Innovation
Policy
Rural development
Published on
This open access article employed content analysis of the main global policy documents related to FLEGT and REDD+ to identify the potential contributions of the two regimes to SFM, and strategies to
FLEGT
Policy
REDD+
Published on
This article focuses on the EU and national policies that have the potential to support social Innovation in rural areas and maps possible future policy efforts in this regard. Reference: Ludvig, A
Civil society
Innovation
Policy
Rural development
Sustainability
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This publication focuses on global drivers of change from the perspective of their relationships with how society functions. By analyzing them in depth through multidisciplinary, interdisciplinary
Network
Research
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This book provides a critical, evidence-based analysis of REDD+ implementation so far, without losing sight of the urgent need to reduce forest-based emissions to prevent catastrophic climate change.
Climate change
Ecosystem services
REDD+
Published on
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at risk of damage in storms.
Models
Planted forests
Risk
Storms