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.
2022
Authors
Katrin ZimmerAbstract
No abstract has been registered
Authors
Emily Lines Matthew Allen Carlos Cabo Kim Calders Amandine Debus Stuart Grieve Milto Miltiadou Adam Noach Harry JF Owen Stefano PulitiAbstract
With the rise in high resolution remote sensing technologies there has been an explosion in the amount of data available for forest monitoring, and an accompanying growth in artificial intelligence applications to automatically derive forest properties of interest from these datasets. Many studies use their own data at small spatio-temporal scales, and demonstrate an application of an existing or adapted data science method for a particular task. This approach often involves intensive and time-consuming data collection and processing, but generates results restricted to specific ecosystems and sensor types. There is a lack of widespread acknowledgement of how the types and structures of data used affects performance and accuracy of analysis algorithms. To accelerate progress in the field more efficiently, benchmarking datasets upon which methods can be tested and compared are sorely needed.Here, we discuss how lack of standardisation impacts confidence in estimation of key forest properties, and how considerations of data collection need to be accounted for in assessing method performance. We present pragmatic requirements and considerations for the creation of rigorous, useful benchmarking datasets for forest monitoring applications, and discuss how tools from modern data science can improve use of existing data. We list a set of example large-scale datasets that could contribute to benchmarking, and present a vision for how community-driven, representative benchmarking initiatives could benefit the field.
Abstract
UAV, drone, ortho photo, image analysis, deep learning, wheel rut, monitoring, GIS, method
Authors
Jingjing Liang Javier G. P. Gamarra Nicolas Picard Mo Zhou Bryan Pijanowski Douglass F. Jacobs Peter B. Reich Thomas W. Crowther Gert-Jan Nabuurs Sergio de-Miguel Jingyun Fang Christopher W. Woodall Jens-Christian Svenning Tommaso Jucker Jean-Francois Bastin Susan K. Wiser Ferry Slik Bruno Hérault Giorgio Alberti Gunnar Keppel Geerten M. Hengeveld Pierre L. Ibisch Carlos A. Silva Hans ter Steege Pablo L. Peri David A. Coomes Eric B. Searle Klaus von Gadow Bogdan Jaroszewicz Akane O. Abbasi Meinrad Abegg Yves C. Adou Yao Jesús Aguirre-Gutiérrez Angelica M. Almeyda Zambrano Jan Altman Esteban Alvarez-Dávila Juan Gabriel Álvarez-González Luciana F. Alves Bienvenu H. K. Amani Christian A. Amani Christian Ammer Bhely Angoboy Ilondea Clara Antón Fernández Valerio Avitabile Gerardo A. Aymard Akomian F. Azihou Johan A. Baard Timothy R. Baker Radomir Balazy Meredith L. Bastian Rodrigue Batumike Marijn Bauters Hans Beeckman Nithanel Mikael Hendrik Benu Robert Bitariho Pascal Boeckx Jan Bogaert Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Francis Q. Brearley Jaime Briseno-Reyes Eben N. Broadbent Helge Bruelheide Erwin Bulte Ann Christine Catlin Roberto Cazzolla Gatti Ricardo G. César Han Y. H. Chen Chelsea Chisholm Emil Cienciala Gabriel D. Colletta José Javier Corral-Rivas Anibal Cuchietti Aida Cuni-Sanchez Javid A. Dar Selvadurai Dayanandan Thales de Haulleville Mathieu Decuyper Sylvain Delabye Géraldine Derroire Ben DeVries John Diisi Tran Van Do Jiri Dolezal Aurélie Dourdain Graham P. Durrheim Nestor Laurier Engone Obiang Corneille E. N. Ewango Teresa J. Eyre Tom M. Fayle Lethicia Flavine N. Feunang Leena Finér Markus Fischer Jonas Fridman Lorenzo Frizzera André L. de Gasper Damiano Gianelle Henry B. Glick Maria Socorro Gonzalez-Elizondo Lev Gorenstein Richard Habonayo Olivier J. Hardy David J. Harris Andrew Hector Andreas Hemp Martin Herold Annika Hillers Wannes Hubau Thomas Ibanez Nobuo Imai Gerard Imani Andrzej M. Jagodzinski Stepan Janecek Vivian Kvist Johannsen Carlos A. Joly Blaise Jumbam Banoho L. P. R. Kabelong Goytom Abraha Kahsay Viktor Karminov Kuswata Kartawinata Justin N. Kassi Elizabeth Kearsley Deborah K. Kennard Sebastian Kepfer-Rojas Mohammed Latif Khan John N. Kigomo Hyun Seok Kim Carine Klauberg Yannick Klomberg Henn Korjus Subashree Kothandaraman Florian Kraxner Amit Kumar Relawan Kuswandi Mait Lang Michael J. Lawes Rodrigo V. Leite Geoffrey Lentner Simon L. Lewis Moses B. Libalah Janvier Lisingo Pablito Marcelo López-Serrano Huicui Lu Natalia V. Lukina Anne Mette Lykke Vincent Maicher Brian S. Maitner Eric Marcon Andrew R. Marshall Emanuel H. Martin Olga Martynenko Faustin M. Mbayu Musingo T. E. Mbuvi Jorge A. Meave Cory Merow Stanislaw Miscicki Vanessa S. Moreno Albert Morera Sharif A. Mukul Jörg C. Müller Agustinus Murdjoko Maria Guadalupe Nava-Miranda Litonga Elias Ndive Victor J. Neldner Radovan V. Nevenic Louis N. Nforbelie Michael L. Ngoh Anny E. N’Guessan Michael R. Ngugi Alain S. K. Ngute Emile Narcisse N. Njila Melanie C. Nyako Thomas O. Ochuodho Jacek Oleksyn Alain Paquette Elena I. Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Sebastian Pfautsch Oliver L. Phillips Maria T. F. Piedade Daniel Piotto Martina Pollastrini Lourens Poorter John R. Poulsen Axel Dalberg Poulsen Hans Pretzsch Mirco Rodeghiero Samir G. Rolim Francesco Rovero Ervan Rutishauser Khosro Sagheb-Talebi Purabi Saikia Moses Nsanyi Sainge Christian Salas-Eljatib Antonello Salis Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Vladimír Šebeň Giacomo Sellan Federico Selvi Josep M. Serra-Diaz Douglas Sheil Anatoly Z. Shvidenko Plinio Sist Alexandre F. Souza Krzysztof J. Stereńczak Martin J. P. Sullivan Somaiah Sundarapandian Miroslav Svoboda Mike D. Swaine Natalia Targhetta Nadja Tchebakova Liam A. Trethowan Robert Tropek John Tshibamba Mukendi Peter Mbanda Umunay Vladimir A. Usoltsev Gaia Vaglio Laurin Riccardo Valentini Fernando Valladares Fons van der Plas Daniel José Vega-Nieva Hans Verbeeck Helder Viana Alexander C. Vibrans Simone A. Vieira Jason Vleminckx Catherine E. Waite Hua-Feng Wang Eric Katembo Wasingya Chemuku Wekesa Bertil Westerlund Florian Wittmann Verginia Wortel Tomasz Zawiła-Niedźwiecki Chunyu Zhang Xiuhai Zhao Jun Zhu Xiao Zhu Zhi-Xin Zhu Irie C. Zo-Bi Cang HuiAbstract
The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.
Abstract
No abstract has been registered
Authors
Svein Eilertsen Mattias Olsson Andreas Seiler Carolin Berndt Manisha Bhardwaj Aina Iren WinsvoldAbstract
No abstract has been registered
Authors
Manisha Bhardwaj Denice Lodnert Mattias Olsson Aina Iren Winsvold Svein Eilertsen Petter Kjellander Andreas SeilerAbstract
Prey species may display anti-predatory behavior, i.e., flight, increased vigilance, and decreased feeding, in response to the true presence of a predator or to the implied presence of a predator through, e.g., acoustic cues. In this study, we investigated the anti-predatory reactions of moose (Alces alces) to acoustic stimuli related to hunting, at saltlick stones, a known attractant. In before-during-after-control-impact experiments, we compared the behavioral responses of individuals to: (i) two hunting-related acoustic stimuli—hunting dog barking and human speaking; (ii) nonpredatory acoustic stimuli—bird sounds and; and (iii) no acoustic stimulus (control). We asked: (1) How does the probability of moose leaving the site differ depending on the stimulus they are exposed to?; (2) What affect do the acoustic stimuli have on the amount of time moose spend vigilant, feeding, or away from the site?; and (3) What affect do the stimuli have on the time between events at a site? We found that when exposed to the human stimulus, moose left the sites in 75% of the events, which was significantly more often compared to the dog (39%), bird (24%), or silent (11%) events. If moose did not leave the site, they spent more time vigilant, and less time feeding, particularly when exposed to a dog or human stimulus. Furthermore, moose spent the most time away from the site and took the longest to visit the site again after a human stimulus. Moose were also more likely to leave the site when exposed to the bird stimulus than during silent controls. Those that remained spent more time vigilant, but their behaviors returned to baseline after the bird stimulus ended. These findings suggest that acoustic stimuli can be used to modify the behavior of moose; however, reactions towards presumably threatening and nonthreatening stimuli were not as distinct as we had expected.
Abstract
No abstract has been registered
Authors
Camilla Risvoll Diego Galafassi Siri Veland Mats Pavall Tom Lifjell Aase-Kristine Aasen Lundberg Svein EilertsenAbstract
The categories and concepts in the existing official land-use maps have been under improvements over recent years; however, this study from Nordland, northern Norway, shows that they continue to pose several dilemmas when aiming to better capture the impacts of multiple land uses on reindeer herding. While these developments have done much to better communicate the presence of reindeer herding to developers and planners, there remain significant challenges to achieve best practices. In particular, the confluence of multiple landscape features, for instance, roads, farmland, ecoregions, tenure, pastures, tourism paths and cabins, may have interactions that create cumulative impacts that do not “add up” neatly across map layers. Migration routes, herding routes, and resting areas have been introduced in these maps. In collaboration with reindeer herders, this article analyses how to enrich mapping practices by for example including bottlenecks, parallel to increased attention to influence zones and avoidance zones, as important emergent impacts of multiple interacting features of the landscape. Our research reveals how local knowledge developed by herders through their “presence in the landscape” is better capable of accounting for interactions and cumulative dimensions of landscape features. Through our participatory mapping approach with Sámi reindeer herders, we focus on ways of combining reindeer herders’ knowledge and GIS maps and demonstrate the potential in collaborative work between herders and policymakers in generating a richer understanding of land-use change. We conclude that the practical knowledge of people inhabiting and living with the landscape and its changing character generates a rich understanding of cumulative impacts and can be harnessed for improved land-use mapping and multi-level governance.
Authors
Birgitta Åhman Minna Turunen Jouko Kumpula Camilla Risvoll Tim Horstkotte Élise Lépy Svein EilertsenAbstract
No abstract has been registered