Vast majority of forestry research on innovations is based on case studies, which makes it difficult to ascertain their distribution across Europe. The relation between innovating activity and the forest within which it takes place is also an under-explored research area. In this study, we address these problems by combining survey data, spatially explicit datasets and machine learning to devise geographical probability distribution of innovation development across Europe. We differentiate between innovations focused on provision of wood and those which focus on biodiversity protection, carbon storage and forest recreation. We also show that most of the variability in the data depicting innovation development can be explained by place-based variables, such as the amount of tree biomass in the forest, tree species composition, nature protection status, terrain ruggedness and road density. Results suggest the need to further explore the role of ‘place-based’ contextual variables in innovation development and highlight various issues that different policies might face when aiming to modify forest management practices in Europe.

Distribution of forest-based innovations across Europe / Lovrić, Marko; Torralba, Mario; Orsi, Francesco; Pettenella, Davide; Mann, Carsten; Geneletti, Davide; Plieninger, Tobias; Primmer, Eeva; Hernandez-Morcillo, Monica; Thorsen, Bo Jellesmark; Lundhede, Thomas; Lasse, Loft; Wunder, Sven; Winkel, Georg. - In: ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS. - ISSN 2210-4224. - 58:(2026), pp. 10106601-10106615. [10.1016/j.eist.2025.101066]

Distribution of forest-based innovations across Europe

Orsi, Francesco;Geneletti, Davide;
2026-01-01

Abstract

Vast majority of forestry research on innovations is based on case studies, which makes it difficult to ascertain their distribution across Europe. The relation between innovating activity and the forest within which it takes place is also an under-explored research area. In this study, we address these problems by combining survey data, spatially explicit datasets and machine learning to devise geographical probability distribution of innovation development across Europe. We differentiate between innovations focused on provision of wood and those which focus on biodiversity protection, carbon storage and forest recreation. We also show that most of the variability in the data depicting innovation development can be explained by place-based variables, such as the amount of tree biomass in the forest, tree species composition, nature protection status, terrain ruggedness and road density. Results suggest the need to further explore the role of ‘place-based’ contextual variables in innovation development and highlight various issues that different policies might face when aiming to modify forest management practices in Europe.
2026
Lovrić, Marko; Torralba, Mario; Orsi, Francesco; Pettenella, Davide; Mann, Carsten; Geneletti, Davide; Plieninger, Tobias; Primmer, Eeva; Hernandez-Mo...espandi
Distribution of forest-based innovations across Europe / Lovrić, Marko; Torralba, Mario; Orsi, Francesco; Pettenella, Davide; Mann, Carsten; Geneletti, Davide; Plieninger, Tobias; Primmer, Eeva; Hernandez-Morcillo, Monica; Thorsen, Bo Jellesmark; Lundhede, Thomas; Lasse, Loft; Wunder, Sven; Winkel, Georg. - In: ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS. - ISSN 2210-4224. - 58:(2026), pp. 10106601-10106615. [10.1016/j.eist.2025.101066]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/484751
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