Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2023
Abstract
Information on tree height-growth dynamics is essential for optimizing forest management and wood procurement. Although methods to derive information on height-growth information from multi-temporal laser scanning data already exist, there is no method to derive such information from data acquired at a single point in time. Drone laser scanning data (unmanned aerial vehicles, UAV-LS) allows for the efficient collection of very dense point clouds, creating new opportunities to measure tree and branch architecture. In this study, we examine if it is possible to measure the vertical positions of branch whorls, which correspond to nodes, and thus can in turn be used to trace the height growth of individual trees. We propose a method to measure the vertical positions of whorls based on a single-acquisition of UAV-LS data coupled with deep-learning techniques. First, single-tree point clouds were converted into 2D image projections, and a YOLOv5 (you-only-look-once) convolutional neural network was trained to detect whorls based on a sample of manually annotated images. Second, the trained whorl detector was applied to a set of 39 trees that were destructively sampled after the UAV-LS data acquisition. The detected whorls were then used to estimate tree-, plot- and stand-level height-growth trajectories. The results indicated that 70 per cent (i.e. precision) of the measured whorls were correctly detected and that 63 per cent (i.e. recall) of the detected whorls were true whorls. These results translated into an overall root-mean-squared error and Bias of 8 and −5 cm for the estimated mean annual height increment. The method’s performance was consistent throughout the height of the trees and independent of tree size. As a use case, we demonstrate the possibility of developing a height-age curve, such as those that could be used for forecasting site productivity. Overall, this study provides proof of concept for new methods to analyse dense aerial point clouds based on image-based deep-learning techniques and demonstrates the potential for deriving useful analytics for forest management purposes at operationally-relevant spatial-scales.
Authors
Morgane Merlin Rasmus Astrup Nicolas Cattaneo Nils Egil Søvde Barry Gardiner Tommaso LocatelliAbstract
No abstract has been registered
2022
Authors
Pedro Caldas Britto Dirk Jaeger Stephan Hoffmann Renato Cesar Goncalves Robert Alexander Christian Vibrans Alfredo Celso FantiniAbstract
No abstract has been registered
Authors
Stephan Hoffmann Marian Schönauer Joachim Heppelmann Antti Asikainen Emmanuel Cacot Benno Eberhard Hubert Hasenauer Janis Ivanovs Dirk Jaeger Andis Lazdins Sima Mohtashami Tadeusz Moskalik Tomas Nordfjell Krzysztof Stereńczak Bruce Talbot Jori Uusitalo Morgan Vuillermoz Rasmus AstrupAbstract
No abstract has been registered
Authors
Stephan Hoffmann Marian Schönauer Joachim Heppelmann Antti Asikainen Emmanuel Cacot Benno Eberhard Hubert Hasenauer Janis Ivanovs Dirk Jaeger Andis Lazdins Sima Mohtashami Tadeusz Moskalik Tomas Nordfjell Krzysztof Stereńczak Bruce Talbot Jori Uusitalo Morgan Vuillermoz Rasmus AstrupAbstract
Purpose of Review Mechanized logging operations with ground-based equipment commonly represent European production forestry but are well-known to potentially cause soil impacts through various forms of soil disturbances, especially on wet soils with low bearing capacity. In times of changing climate, with shorter periods of frozen soils, heavy rain fall events in spring and autumn and frequent needs for salvage logging, forestry stakeholders face increasingly unfavourable conditions to conduct low-impact operations. Thus, more than ever, planning tools such as trafficability maps are required to ensure efficient forest operations at reduced environmental impact. This paper aims to describe the status quo of existence and implementation of such tools applied in forest operations across Europe. In addition, focus is given to the availability and accessibility of data relevant for such predictions. Recent Findings A commonly identified method to support the planning and execution of machine-based operations is given by the prediction of areas with low bearing capacity due to wet soil conditions. Both the topographic wetness index (TWI) and the depth-to-water algorithm (DTW) are used to identify wet areas and to produce trafficability maps, based on spatial information. Summary The required input data is commonly available among governmental institutions and in some countries already further processed to have topography-derived trafficability maps and respective enabling technologies at hand. Particularly the Nordic countries are ahead within this process and currently pave the way to further transfer static trafficability maps into dynamic ones, including additional site-specific information received from detailed forest inventories. Yet, it is hoped that a broader adoption of these information by forest managers throughout Europe will take place to enhance sustainable forest operations.
Authors
Katrin ZimmerAbstract
No abstract has been registered
Authors
Katrin ZimmerAbstract
No abstract has been registered
Authors
Marta Vergarechea Rasmus Astrup Carolin Fischer Knut Øistad Clemens Blattert Markus Hartikainen Kyle Eyvindson Fulvio Di Fulvio Nicklas Forsell Daniel Burgas Astor Toraño-Caicoya Mikko Mönkkönen Clara Antón FernándezAbstract
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving mitigation targets and at the same time meet nationally determined targets for other FES. Using data from the Norwegian national forest inventory (NFI) we simulated the development of Norwegian forests under different management regimes and defined different forest policy scenarios, according to the most relevant forest policies in Norway: national forest policy (NFS), biodiversity policy (BIOS), and bioeconomy policy (BIES). Finally, through multi-objective optimization, we identified the combination of management regimes matching best with each policy scenario. The results for all scenarios indicated that Norway will be able to satisfy wood demands of up to 17 million m3 in 2093. However, the policy objectives for FES under each scenario caused substantial differences in terms of the management regimes selected. We observed that BIES and NFS resulted in very similar forest management programs in Norway, with a dominance of extensive management regimes. In BIOS there was an increase of set aside areas and continuous cover forestry, which made it more compatible with biodiversity indicators. We also found multiple synergies and trade-offs between the FES, likely influenced by the definition of the policy targets at the national scale.
Abstract
No abstract has been registered
2021
Authors
Ingmar R. Staude Henrique M. Pereira Gergana N. Daskalova Markus Bernhardt-Römermann Martin Diekmann Harald Pauli Hans Van Calster Mark Vellend Anne D. Bjorkman Jörg Brunet Pieter De Frenne Radim Hédl Ute Jandt Jonathan Lenoir Isla H. Myers-Smith Kris Verheyen Sonja Wipf Monika Wulf Christopher Andrews Peter Barančok Elena Barni José-Luis Benito-Alonso Jonathan Bennie Imre Berki Volker Blüml Markéta Chudomelová Guillaume Decocq Jan Dick Thomas Dirnböck Tomasz Durak Ove Eriksson Brigitta Erschbamer Bente Jessen Graae Thilo Heinken Fride Høistad Schei Bogdan Jaroszewicz Martin Kopecký Thomas Kudernatsch Martin Macek Marek Malicki František Máliš Ottar Michelsen Tobias Naaf Thomas A. Nagel Adrian C. Newton Lena Nicklas Ludovica Oddi Adrienne Ortmann-Ajkai Andrej Palaj Alessandro Petraglia Petr Petřík Remigiusz Pielech Francesco Porro Mihai Puşcaş Kamila Reczyńska Christian Rixen Wolfgang Schmidt Tibor Standovár Klaus Steinbauer Krzysztof Świerkosz Balázs Teleki Jean-Paul Theurillat Pavel Dan Turtureanu Tudor-Mihai Ursu Thomas Vanneste Philippine Vergeer Ondřej Vild Luis Villar Pascal Vittoz Manuela Winkler Lander BaetenAbstract
Species turnover is ubiquitous. However, it remains unknown whether certain types of species are consistently gained or lost across different habitats. Here, we analysed the trajectories of 1827 plant species over time intervals of up to 78 years at 141 sites across mountain summits, forests, and lowland grasslands in Europe. We found, albeit with relatively small effect sizes, displacements of smaller- by larger-ranged species across habitats. Communities shifted in parallel towards more nutrient-demanding species, with species from nutrient-rich habitats having larger ranges. Because these species are typically strong competitors, declines of smaller-ranged species could reflect not only abiotic drivers of global change, but also biotic pressure from increased competition. The ubiquitous component of turnover based on species range size we found here may partially reconcile findings of no net loss in local diversity with global species loss, and link community-scale turnover to macroecological processes such as biotic homogenisation.