Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2020
Forfattere
N.G. Hodgetts Lars Söderström T.L. Blockeel S. Caspari M.S. Ignatov N.A. Konstantinova N. Lockhart B. Papp C. Schröck M. Sim-Sim D. Bell N.E. Bell Hans Blom M.A. Bruggeman-Nannenga M. Brugués J. Enroth Kjell Ivar Flatberg R. Garilleti L. Hedenäs D.T. Holyoak V. Hugonnot I. Kariyawasam H. Köckinger J. Kučera F. Lara R.D. PorleySammendrag
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Forfattere
Jahn Davik Kjersti Aaby Matteo Buti Muath K Alsheikh Nada Surbanovski Stefan Martens Dag Røen Daniel James SargentSammendrag
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Forfattere
Greeley BeckSammendrag
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Forfattere
Ivan A. Paponov Vadym Budnyk Martina Paponov William Teale Klaus PalmeSammendrag
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Sammendrag
Key message This study showed that regeneration success (presence of oaks ≥ 150 cm in total height) in artificial canopy openings of a mature mixed sessile oak stand was mainly driven by initial oak seedling density. Context Small-scale harvesting methods as practiced in close-to-nature forestry may disadvantage the regeneration of more light-demanding tree species including sessile oak (Quercus petraea [Mattuschka] Liebl.) and thus cause regeneration failure. However, owing to the short-term nature of many previous studies, regeneration success of sessile oak could not be properly ascertained. Aims This study examined oak seedling development over a time period of ten growing seasons in canopy openings of 0.05 to 0.2 ha in size created through group selection harvesting in a mature mixed sessile oak forest in southwestern Germany. We tried to answer the following research questions: (i) how do initial stand conditions relate to and interact with oak seedling density and seedling height growth, and (ii) what are the driving factors of regeneration success under the encountered site conditions. Methods We evaluated the influence of solar radiation, Rubus spp. cover, initial oak seedling density, and competition from other tree species on change in density and height of oak seedlings, as well as overall regeneration success (oak seedlings ≥ 150 cm in height). Results Regeneration success increased with initial oak seedling density and solar radiation levels and decreased with early Rubus spp. cover. Density and maximum height of oak seedlings was negatively related with competition of other woody species. Conclusion Results of our longer-term study demonstrate that forest management activities to regenerate sessile oak naturally are only successful in stands (i) without advance regeneration of other woody species and without established, recalcitrant ground vegetation, (ii) with a sufficiently high initial oak seedling density in larger patches following mast years, and (iii) where periodic monitoring and control of competing woody individuals can be ensured. Our findings further corroborate the view that natural regeneration of sessile oak in small-scale canopy openings is possible in principle.
Forfattere
Sharad Mohan K. Kiran Kumar Vivek Sutar Supradip Saha Janet Rowe Keith DaviesSammendrag
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Forfattere
Ivan Paponov Martina Paponov Paolo Sambo Christof EngelsSammendrag
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Sammendrag
In the EU 2020 biodiversity strategy, maintaining and enhancing forest biodiversity is essential. Forest managers and technicians should include biodiversity monitoring as support for sustainible forest management and conservation issues, through the adoption of forest biodiversity indices. The present study investigates the potential of a new type of Structure from Motion (SfM) photogrammetry derived variables for modelling forest structure indicies, which do not require the availability of a digital terrain model (DTM) such as those obtainable from Airborne Laser Scanning (ALS) surveys. The DTM-independent variables were calculated using raw 3D UAV photogrammetric data for modeling eight forest structure indices which are commonly used for forest biodiversity monitoring, namely: basal area (G); quadratic mean diameter (DBHmean); the standard deviation of Diameter at Breast Height (DBHσ); DBH Gini coefficient (Gini); the standard deviation of tree heights (Hσ); dominant tree height (Hdom); Lorey’s height (Hl); and growing stock volume (V). The study included two mixed temperate forestsareas withadifferenttype ofmanagement, with onearea, left unmanagedfor thepast 50years while the other being actively managed. A total of 30 fieldsample plots were measured in the unmanaged forest, and 50 field plots were measured in the actively managed forest. The accuracy of UAV DTM-independent predictions was compared with a benchmark approach based on traditional explanatory variables calculated from ALS data. Finally, DTM-independent variables were used to produce wall-to-wall maps of the forest structure indices in the two test areas and to estimate the mean value and its uncertainty according to a model-assisted regression estimators. DTM-independent variables led to similar predictive accuracy in terms of root mean square error compared to ALS in both study areas for the eight structure indices (DTM-independent average RMSE% = 20.5 and ALS average RMSE% = 19.8). Moreover, we found that the model-assisted estimation, with both DTM-independet and ALS, obtained lower standar errors (SE) compared to the one obtained by modelbased estimation using only field plots. Relative efficiency coefficient (RE) revealed that ALS-based estimates were, on average, more efficient (average RE ALS = 3.7) than DTM-independent, (average RE DTM-independent = 3.3). However, the RE for the DTM-independent models was consistently larger than the one from theALSmodelsfortheDBH-relatedvariables(i.e.G,DBHmean,andDBHσ)andforV.Thishighlightsthepotential of DTM-independent variables, which not only can be used virtually on any forests (i.e., no need of a DTM), but also can produce as precise estimates as those from ALS data for key forest structural variables and substantially improve the efficiency of forest inventories.