Current issue: 59(3)

Under compilation: 60(1)

Scopus CiteScore 2023: 3.5
Scopus ranking of open access forestry journals: 17^th
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Silva Fennica vol. 60 | 2026

Category : Research article

article id 25061, category Research article

Juha-Pekka Hotanen, Jari Miina, Leila Korpela, Raisa Mäkipää. (2026). Effects of selection harvesting on the understorey vegetation in drained Norway spruce peatlands. Silva Fennica vol. 60 no. 1 article id 25061. https://doi.org/10.14214/sf.25061

Keywords: continuous cover forestry; ground vegetation; thinning from above; ANOVA; uneven-aged cutting

Highlights: The thinning intensity and time since harvest significantly affect vegetation dynamics on fertile, drained Norway spruce peatlands; Several species respond to the thinning intensity, showing a greater treatment effect with more time since thinning; Vaccinium myrtillus increases, especially on the most intensively thinned plots; Selection harvesting has a minor effect on the number of plant species in drained Norway spruce peatlands.

Abstract | Full text in HTML | Full text in PDF | Author Info

This study focused on the changes in species abundance after harvest in uneven-aged stands. Selection harvesting was performed at four sites in southern boreal vegetation zones in Finland using two thinning intensities: post-harvest basal area (G) of 17 and 12–13 m² ha^–1. The G pre-harvest and in control plots varied between 19 and 31 m² ha^–1. Vegetation was inventoried before thinning in 2016 and 2 and 6 years after thinning in 2018 and 2022. The effect of thinning intensity was significant for grasses and sedges as groups, Betula pubescens Ehrh. (height < 50 cm), Rubus idaeus L., and Trientalis europaea L., which showed increased abundance after harvest. However, T. europaea abundance turned to decline by 2022. Several species responded to the thinning intensity, showing a greater treatment effect with the more time since harvest. The abundance of Carex globularis L., Dryopteris carthusiana (Vill.) H.P. Fuchs, Epilobium angustifolium L., Vaccinium myrtillus L., V. vitis-idaea L., Linnaea borealis L. and Brachythecium spp. increased, but that of Oxalis acetosella L. decreased. For some species, only the time since harvest was significant. The abundance of Maianthemum bifolium (L.) F.W. Schmidt, Deschampsia flexuosa (L.) Trin. and Plagiothecium spp. increased, whereas that of Sphagnum girgensohnii Russow and S. russowii Warnst. decreased. The thinning intensity did not have a significant effect on the number of species, but the number of species increased slightly on the thinned plots. The effects of logging residues, strip roads, and light availability may be the major drivers of the changes in the species abundance.

Hotanen, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland E-mail: ext.juha-pekka.hotanen@luke.fi
Miina, Natural Resources Institute Finland (Luke), Yliopistokatu 6 B, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8639-4383 E-mail: jari.miina@luke.fi
Korpela, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-9900-4332 E-mail: ext.leila.korpela@luke.fi
Mäkipää, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0003-3146-4425 E-mail: raisa.makipaa@luke.fi

article id 25036, category Research article

Juha Kaitera, Tuula Piri, Minna Männistö, Sanna Vinblad, Heli Väätäjä, Kari Mäkitalo. (2026). Dogs can detect the rust fungus Cronartium pini in the forest. Silva Fennica vol. 60 no. 1 article id 25036. https://doi.org/10.14214/sf.25036

Keywords: Pinus sylvestris; Scots pine blister rust; alternate hosts; canine; resin-top disease; scent detection

Highlights: Dogs identified Cronartium pini spores, fruit bodies and young and old lesions; Dogs identified both heteroecious and autoecious Cronartium pini; Dogs identified Cronartium pini at the early epidemical stage of the disease; Dogs identified Cronartium pini from latent infections in alive shoots.

Abstract | Full text in HTML | Full text in PDF | Author Info

Cronartium pini (Willd.) Jørst. is a major rust pathogen that kills especially Scots pine (Pinus sylvestris L.). Early diagnosis of the pathogen would reduce significant losses in managed forest productivity. Dogs (Canis lupus familiaris L.) with their accurate sense of smell have potential to detect forest pathogens at an early stage before they cause significant losses in forests. In this study, we tested in northern Finland whether trained volunteer dog-handler teams could identify infected wood, fruit bodies, spores or mycelia of C. pini in vitro and in vivo to facilitate early disease diagnosis. Volunteer dog-handler teams were able to indicate C. pini spores, fruit bodies and both fresh and old rust lesions on Scots pine including alive shoots, where the rust was present yet as latent. Five dogs out of five detected in vitro C. pini (both life-cycle forms), with 51% mean sensitivity and 58% mean precision. Four dogs out of four detected in vivo the autoecious life-cycle form of C. pini, with 95% mean sensitivity and 89% mean precision. In in vivo detection of the heteroecious life cycle form on pine, two dogs out of two performed with 78% mean sensitivity (100% precision). For identifying C. pini on alternate hosts in vivo, the mean sensitivity was 58% (precision 100%). Trained dog-handler pairs show promise as an aid in searching for C. pini especially in Scots pine stands at their early epidemical stage, but further testing is needed.

Kaitera, Natural Resources Institute Finland (Luke), Paavo Havaksen tie 3, FI-90570 Oulu, Finland https://orcid.org/0000-0003-2549-7001 E-mail: juha.kaitera@luke.fi
Piri, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-8690-3726 E-mail: tuula.piri@luke.fi
Männistö, Natural Resources Institute Finland (Luke), Ounasjoentie 6, FI-96200 Rovaniemi, Finland https://orcid.org/0000-0001-9390-1104 E-mail: minna.mannisto@luke.fi
Vinblad, Lapland University of Applied Sciences, Jokiväylä 11 C, FI-96300 Rovaniemi, Finland https://orcid.org/0009-0009-1131-6143 E-mail: sanna.vinblad@lapinamk.fi
Väätäjä, Lapland University of Applied Sciences, Jokiväylä 11 C, FI-96300 Rovaniemi, Finland https://orcid.org/0000-0003-3324-9497 E-mail: heli.vaataja@lapinamk.fi
Mäkitalo, Natural Resources Institute Finland (Luke), Ounasjoentie 6, FI-96200 Rovaniemi, Finland E-mail: kari.makitalo@luke.fi

article id 25022, category Research article

Reetta Kangaslampi, Olli-Pekka Tikkanen. (2026). Training and utilizing scent detection dogs in the identification of the European spruce bark beetle Ips typographus. Silva Fennica vol. 60 no. 1 article id 25022. https://doi.org/10.14214/sf.25022

Keywords: Ips typographus; conservation detection dog; scent detection dog; spruce bark beetle, wildlife detection dog

Highlights: Scent detection dogs can identify a small sample of live European spruce bark beetles with a 98% sensitivity in the laboratory; Training a scent detection dog to detect bark beetles is relatively time-efficient; Early intervention strategies may benefit from inclusion of scent detection dogs in the management process.

Abstract | Full text in HTML | Full text in PDF | Author Info

The European spruce bark beetle (Ips typographus L.) thrives in weakened mature spruce (Picea abies (L.) H. Karst.) stands, causing massive destruction and becoming more abundant in Europe since the late 2010s. Early identification of new outbreaks is essential to ensure timely logging of infested trees to control the bark beetle population. Scent detection dogs (Canis lupus familiaris L.) are being used to identify illegal substances, diseases, and animal scat. In this study, the use of scent detection dogs in the identification of the European spruce bark beetle was tested. The main objective was to examine whether a dog could be trained to reliably identify the scent of a small group of live bark beetles. In this study we carried out comprehensive testing of the accuracy of the method in the laboratory and performed a small-scale functionality study in a field setting. The study was conducted by training two scent detection dogs to identify live bark beetles from empty samples and interference samples. This study differs from previous publications regarding spruce bark beetle detection, as our dogs were trained on live beetles. We concluded that, after a relatively short training period (23 days within eight weeks), scent detection dogs can identify a small sample of live European spruce bark beetles with a 98% sensitivity in the laboratory. The sensitivity was remarkably high and gave positive indications of the method’s functionality and usability in the future also in field conditions. The use of a scent detection dog can be a welcome and effective way to identify bark beetle damage.

Kangaslampi, University of Eastern Finland; Faculty of Science, Forestry and Technology; P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0009-0001-2965-3369 E-mail: reetta.kangaslampi@uef.fi
Tikkanen, University of Eastern Finland; Faculty of Science, Forestry and Technology; P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-3875-2772 E-mail: olli-pekka.tikkanen@uef.fi

article id 25018, category Research article

Erik Arvidsson, Anders Rowell, Linnea Hansson, Håkan Lideskog, Mikael Rönnqvist. (2026). Comparison of manual and automated coverage path planning for mechanized forest regeneration. Silva Fennica vol. 60 no. 1 article id 25018. https://doi.org/10.14214/sf.25018

Keywords: site preparation; planting; mechanization; automation; precision forestry; routing

Highlights: Automated coverage path planners TerraTrail and Pathfinder outperform manual operators driving the PlantMax planting machine in coverage across all test sites; Pathfinder demonstrated the shortest path lengths, especially in constrained environments, with up to 14% shorter paths compared to manual planning; The study emphasizes the potential of autonomous path planning systems to reduce labor dependency, enhance sustainability, and improve the efficiency of forest regeneration operations; The automated planners effectively accounted for vehicle constraints such as terrain and soil moisture conditions, optimizing routes for more efficient regeneration.

Abstract | Full text in HTML | Full text in PDF | Author Info

In Finland and Scandinavia, even-aged forest management predominates, often including mechanical site preparation and manual planting. Growing labor shortages and increased demand for sustainability have driven interest in mechanized and autonomous planting systems. This study evaluates two automated Coverage Path Planners (CPP), Pathfinder and TerraTrail, developed to optimize planting routes for mechanized forest regeneration. Their performance is compared to the routes of the manually operated mechanized planting machine, PlantMax. Three operational sites in Sweden, representing varied terrain and hydrological conditions are evaluated. The evaluation focuses on coverage, Euclidean and Dubins path lengths. Both CPPs incorporate Digital Elevation Models (DEM), Depth-to-Water (DTW) maps and vehicle-specific kinematics to generate planting routes. Two scenarios are evaluated: one where the CPPs neglect the DTW map, and another where the CPPs are constrained to avoid DTW values below 0.3 m. Results show that automated CPPs achieve 15–19% higher coverage than manual planning on average. Pathfinder showed similar normalized path lengths in an unconstrained scenario as the manual operator, but 14% shorter in the constrained environment. TerraTrail shows 7% longer normalized path lengths in an unconstrained scenario, while the constrained scenario shows similar path lengths as the manual operator. These findings emphasize the potential of deploying automated CPP systems to enhance precision, sustainability, and labor efficiency of silvicultural operations. The CPPs support both autonomous deployment and decision support tool for operators. Further refinement, including combining both CPPs to leverage the best functions of each, along with reversible path planning, could enhance their value in forestry practices.

Arvidsson, Luleå University of Technology (LTU), SE-971 87 Luleå, Sweden https://orcid.org/0000-0001-7679-0203 E-mail: erik.arvidsson@ltu.se
Rowell, Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden https://orcid.org/0009-0000-2810-1434 E-mail: anders.rowell@skogforsk.se
Hansson, Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden https://orcid.org/0000-0002-9788-1734 E-mail: linnea.hansson@skogforsk.se
Lideskog, Luleå University of Technology (LTU), SE-971 87 Luleå, Sweden https://orcid.org/0000-0002-9862-828X E-mail: hakan.lideskog@ltu.se
Rönnqvist, Université Laval, 1065, avenue de la Médecine, Local 1504, Québec G1V 0A6, Canada https://orcid.org/0000-0002-1940-6129 E-mail: mikael.ronnqvist@gmc.ulaval.ca

article id 25012, category Research article

Heikki Astola, Annika Kangas, Francesco Minunno, Matti Mõttus. (2026). Emulating a forest growth and productivity model with deep learning. Silva Fennica vol. 60 no. 1 article id 25012. https://doi.org/10.14214/sf.25012

Keywords: carbon balance; simulation; machine learning; climate scenarios; digital twins; forest variables; time series prediction

Highlights: Emulating the operation of analytical forest growth models is feasible using state-of-the-art machine learning methods; Long term prediction of forest growth and carbon balance variables were produced with low bias accumulation when compared to the reference model; The methods tested offer means for long time span simulations of large areas with a high spatial resolution.

Abstract | Full text in HTML | Full text in PDF | Author Info

We studied the possibility of replacing a complex forest growth and productivity model with a deep learning model with sufficient accuracy. We used three different neural network architectures for emulating the prediction task of the PREBASSO (Mäkelä 1997; Minunno et al. 2016) forest growth model: 1) Recurrent Neural Network (RNN) Encoder-decoder network, 2) RNN encoder network, and 3) Transformer encoder network. The PREBASSO forest growth model was used to produce 25-year predictions for forest variables: tree height, stem diameter, basal area, and the carbon balance variables: net primary production (NPP), gross primary production per tree layer (GPP), net ecosystem exchange (NEE) and gross growth (GGR) to train the machine learning models. The Finnish Forest Centre provided the data for 29 619 field inventory plots in continental Finland that were used as the initial state of the forest sites to be simulated. Climate data downloaded from Copernicus Climate Data Store were used to provide realistic climate scenarios. We emphasized the importance of low bias in long term predictions and set the goal for the emulator prediction relative bias to be within ±2%. The RNN encoder model produced the best results with the mean of the yearly bias values within the specified ±2% limit over the 25-year prediction period. The study shows that emulating the operation of analytical forest growth models is feasible using state-of-the-art machine learning methods and indicates the potential of using such emulators for producing long time span simulations for e.g. digital twins.

Astola, VTT Technical Research Centre of Finland, Tekniikantie 1, 02150 Espoo, Finland https://orcid.org/0000-0003-4989-9910 E-mail: heikki.astola@gmail.com
Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Yliopistokatu 6, 80100 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
Minunno, Yucatrote, Rua António Gavina L49, 8600-214 Luz, Lagos, Portugal https://orcid.org/0000-0002-7658-6402 E-mail: francesco.minunno@helsinki.fi
Mõttus, VTT Technical Research Centre of Finland, Tekniikantie 1, 02150 Espoo, Finland https://orcid.org/0000-0002-2745-1966 E-mail: Matti.Mottus@vtt.fi

article id 25010, category Research article

Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic, Erik Næsset, Terje Gobakken. (2026). Semantic segmentation of forest stands using deep learning. Silva Fennica vol. 60 no. 1 article id 25010. https://doi.org/10.14214/sf.25010

Keywords: forest management; image segmentation; remote sensing; stand delineation; U-Net

Highlights: Deep learning enables automated stand delineation that closely replicates expert human interpretation; The proposed approach has the potential to reduce time and cost required for operational stand delineation; Performance declines in highly complex forest environments, highlighting the need for further refinement.

Abstract | Full text in HTML | Full text in PDF | Author Info

Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the past two decades, stand borders have typically been delineated through manual interpretation of stereographic aerial images. This is a time-consuming and subjective process, which limits operational efficiency and introduces inconsistencies. Substantial effort has been devoted to automating the process, using various algorithms together with aerial images and canopy height models constructed from airborne laser scanning (ALS) data, but the manual interpretation remains the preferred method. Deep learning (DL) methods have demonstrated great potential in computer vision, yet their application to forest stand delineation remains unexplored in published research. This study presents a novel approach, framing stand delineation as a multiclass segmentation problem and applying U-Net-based DL-framework. The model was trained and evaluated using multispectral images, ALS data, and an existing stand map created by an expert interpreter. Performance was assessed on independent data using overall accuracy, a standard metric for classification tasks that measures the proportions of correctly classified pixels. The model achieved a pixel-level overall accuracy of 0.72. These results demonstrate the strong potential for DL-based stand delineation to be faster and more objective than manual methods. However, a few key challenges were noted, especially for complex forest environments. In these environments, model predictions showed over-segmentation and complex, irregular stand boundaries.

Sandum, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0009-0001-5764-2544 E-mail: hakon.nass.sandum@nmbu.no
Ørka, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0002-7492-8608 E-mail: hans.ole.orka@nmbu.no
Tomic, Faculty of Science and Technology, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0003-1595-9962 E-mail: oliver.tomic@nmbu.no
Næsset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no
Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway https://orcid.org/0000-0001-5534-049X E-mail: terje.gobakken@nmbu.no

article id 25001, category Research article

Katri Rusanen, Teppo Hujala, Jouni Pykäläinen. (2026). “We are already in the frontline” – Sustainable value creation and entrepreneurial orientation in forest-based small and medium-sized enterprises. Silva Fennica vol. 60 no. 1 article id 25001. https://doi.org/10.14214/sf.25001

Keywords: forest-based sector; sustainability transition; sustainable business model; sustainable entrepreneurship; value creation

Highlights: Sustainability transitions call for new types of businesses and value creation; Sustainability-oriented forest-based SMEs providing various services were studied; Operating environment and entrepreneurial orientation of companies shape how sustainable value is created with and for stakeholders; There is resistance from the operating environment towards sustainability-oriented businesses; System-level changes and sustainability-oriented entrepreneurship are interconnected and support each other.

Abstract | Full text in HTML | Full text in PDF | Author Info

Sustainability challenges such as climate change and biodiversity loss have a great impact on the operating environment of companies. Business actors have increasingly sought answers to these challenges. A range of innovations, technologies and business models have been developed. Little is however known about those companies and entrepreneurs that strive for solving sustainability challenges. Sustainability-oriented entrepreneurship has interested researchers for a while. Nevertheless, studies have not thoroughly focused on forest-based services and related business models and value creation. This multiple case study investigates how the operating environment and entrepreneurial orientation are entailed in sustainability-pursuant value creation. We interviewed nine sustainability-oriented small and medium-sized enterprises providing forest-based services. The results indicate that the companies feature several entrepreneurial capabilities that enable them creating sustainable value. They are positively oriented towards future and consider their business as a solution to focal sustainability challenges. The companies’ operating environment can support the emergence and long-term development of sustainability-oriented businesses and innovations, and hence collaboration with stakeholders is essential for sustainable value creation. However, the established forest-based sector and existing support system have created tensions for the development of the sustainability-oriented businesses. The companies strive actively for making an impact on their operating environment to create sustainable value with and for their stakeholders. This study advances empirical research on sustainable value creation and entrepreneurship. Overall, this paper suggests that sustainability-oriented entrepreneurs need more collaboration and support for scaling up the solving of sustainability challenges.

Rusanen, School of Forest Sciences, Faculty of Science, Forestry and Technology, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0003-1705-5561 E-mail: katri.rusanen@uef.fi
Hujala, School of Forest Sciences, Faculty of Science, Forestry and Technology, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-7905-7602 E-mail: teppo.hujala@uef.fi
Pykäläinen, School of Forest Sciences, Faculty of Science, Forestry and Technology, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0003-3427-9954 E-mail: jouni.pykalainen@uef.fi

Category : Discussion article

article id 26001, category Discussion article

Hanne K. Sjølie, Brett J. Butler, Francisco X. Aguilar, Isabella Hallberg-Sramek, Veera Tahvanainen, Anniina Kietäväinen, Matti Maltamo, Silvia M. Korth, Dohun Kim, Lucas Nahuel Lopez, Ane C. Tange, Lisa Ockier. (2026). A call for improving forest socioeconomic data with inspiration from national forest inventories. Silva Fennica vol. 60 no. 1 article id 26001. https://doi.org/10.14214/sf.26001

Keywords: biophysical information; data integration; forest ownership survey; forest product survey

Abstract | Full text in HTML | Full text in PDF | Author Info

National forest inventories have long and strong traditions in many countries and they can offer a wealth of information about the biophysical aspects of forests such as tree growth, carbon fluxes and biodiversity. However, these are in most cases not paralleled by data representing the socioeconomic dimensions of forests. Integration of socioeconomic and biophysical data has the potential to better unveil interactions between human and natural resources and can therefore better support policy. Climate change has multiple impacts on forest resources. Policies to support sustainable forestry, the bioeconomy, and climate change mitigation and adaptation are constantly developing. At the same time, forest owners’ attitudes and forest markets are evolving. More data is needed to advance the understanding of the links between the human and biophysical factors and the relationship between these factors and the complex objectives of forests. We compared the national forest inventories, national forest owner surveys, and national forest product surveys across Argentina, Finland, Norway, Sweden and the USA. The national forest inventories in all selected countries are built on solid methodological grounds and have strong institutional support and funding. However, the consistency of methods, frequency of implementation, and institutional support for forest owner and forest product surveys are in many cases lacking. There is also a lack of integration between biophysical and socioeconomic data. The USA was the only studied country with integrated biophysical and socioeconomic data. We suggest that this approach reflects the needs of data integration and can serve as a reference for other countries.

Sjølie, Department of Forestry and Wildlife Management, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, University of Inland Norway, Elverum, Norway https://orcid.org/0000-0001-8099-3521 E-mail: hanne.sjolie@inn.no
Butler, USDA Forest Service, Northern Research Station, Amherst, MA, USA https://orcid.org/0000-0002-2465-7993 E-mail: –
Aguilar, Department of Forest Economics, Swedish University of Agricultural Sciences, Umeå, Sweden https://orcid.org/0000-0003-0226-4467 E-mail: francisco.aguilar@slu.se
Hallberg-Sramek, Department of Forest Resource Management, Swedish University of Agricultural Science, Umeå, Sweden https://orcid.org/0000-0002-9645-9208 E-mail: isabella.hallberg.sramek@slu.se
Tahvanainen, School of Forest Sciences, University of Eastern Finland, Joensuu, Finland https://orcid.org/0009-0004-4527-992X E-mail: –
Kietäväinen, Department of Forest Economics, Swedish University of Agricultural Sciences, Umeå, Sweden https://orcid.org/0009-0001-9435-1519 E-mail: anniina.kietavainen@slu.se
Maltamo, School of Forest Sciences, University of Eastern Finland, Joensuu, Finland https://orcid.org/0000-0002-9904-3371 E-mail: matti.maltamo@uef.fi
Korth, Universidad Nacional de Misiones, Posadas, Misiones, Argentina https://orcid.org/0009-0007-3261-8234 E-mail: –
Kim, Department of Forest Economics, Swedish University of Agricultural Sciences, Umeå, Sweden https://orcid.org/0000-0002-1919-3346 E-mail: dohun.kim@slu.se
Lopez, Department of Forestry and Wildlife Management, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, University of Inland Norway, Elverum, Norway https://orcid.org/0009-0006-6860-3408 E-mail: lucas.lopez@inn.no
Tange, Department of Forestry and Wildlife Management, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, University of Inland Norway, Elverum, Norway; Glommen-Mjøsen Skog SA, Elverum, Norway https://orcid.org/0009-0001-3145-8159 E-mail: –
Ockier, Universidad Nacional de Misiones, Posadas, Misiones, Argentina E-mail: lisa@ockier.de

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