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.
2022
Sammendrag
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Forfattere
Diogo N. Cosenza Petteri Packalén Matti Maltamo Petri Varvia Janne Räty Paula Soares Margarida Tomé Jacob L. Strunk Lauri KorhonenSammendrag
Semi- and nonparametric models are popular in the area-based approach (ABA) using airborne laser scanning. It is unclear, however, how many predictors and training plots are needed to provide accurate predictions without overfitting. This work aims to explore these limits for various approaches: ordinary least squares regression (OLS), generalized additive models (GAM), least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine (SVM), and Gaussian process regression (GPR). We modeled timber volume (m3·ha–1) for four boreal sites using ABA with 2–39 predictors and 20–500 training plots. OLS, GAM, LASSO, and SVM overfitted as the number of predictors approached the number of training plots. They required ≥15 plots per predictor to provide accurate predictions (RMSE ≤30%). GAM required ≥250 plots regardless of the number of predictors. The number of predictors only mildly affected RF and GPR, but they required ≥200 and ≥250 training plots, respectively. RF did not overfit in any circumstances, whereas GPR overfit even with 500 training plots. Overall, using up to 39 predictors did not generally result in overfit, and for most model types, it resulted in better accuracy for sufficiently large datasets (≥250 plots).
Forfattere
Ida Marie Luna Fløystad Paul Eric Aspholm Per John Aslaksen Anti Ann Maret Eira Mahtte Ailu Utsi Gaup Aslak Ole Eira Trond-Erik Markussen Geir-Arne Evanger Tor-Einar Bones Torfinn Strømseth Christina Martin Stig Ronald Sletten Gina Uthus Ingrid Helle Søvik Ane-Sofie B. Hansen Oda Rustad Snorre Hagen Hans Geir EikenSammendrag
Hår fra brunbjørn ble samlet inn i hårfeller med luktstoff i et 1075 km2 stort område i Karasjok kommune og i et 525 km2 stort område i indre Troms (Troms og Finnmark fylke) i løpet av 2 måneder fra juni til august i 2021. Det ble brukt et 5 x 5 km rutesystem med én hårfelle i hver rute, og der hårfellen ble flyttet etter én måned til en annen lokalitet i samme rute. Hårrøttene ble DNA-analysert med 8 genetiske markører. I Karasjok var området utvidet med studieområdet i Valjohka til totalt 43 hårfeller i år mot 16 feller i tidligere år. Her ble det samlet inn 178 hårprøver (i tillegg til 5 ekskrementprøver), og 106 (60%) var positive for brunbjørn. Det ble påvist 11 ulike bjørner (6 hannbjørn og 5 hunnbjørn) i det sammenhengende området Karasjok/Valjohka. Av disse 11 bjørnene var kun 2 bjørner (en hann og en hunn) nye i år. Utvidet DNA-familieanalyse med 12 genetiske markører påviste mulige lokale foreldre for begge de nye bjørnene. Sentralt i Karasjok (16 feller) ble prosjektet utført i samme område og tidsrom som i 2019 (9 ind.) og 2020 (8 ind.), og viser i år en liten nedgang i antallet bjørn (6 ind.) og bjørnetetthet (0,15 bjørn/10km2 mot hhv 0.23 og 0.20 bjørn/10km2). Tidsmessig informasjon viste at flest bjørner ble påvist i begynnelsen av august, mens kun én bjørn ble påvist i juni. For første gang ble det satt ut hårfeller for brunbjørn i indre Troms, med 21 hårfeller i 3 mindre områder. DNA- analysen viste at 2 av de 16 innsamlede hårprøvene (13 %) og 2 av de 4 ekrementprøvene var positive for brunbjørn, og det ble påvist 2 ulike bjørner (bjørnetetthet på 0,04 bjørn/10 km2). Begge var tidligere kjente bjørner som kun er påvist i dette området i indre Troms. Hårfellemetoden med DNA- analyse av hårrøtter gir unik geografisk og tidsmessig informasjon om brunbjørn, og fremtidige prosjekter bør derfor utføres i større sammenhengende områder i flere påfølgende år slik som i Karasjok for å oppnå sikre resultater.
Forfattere
Ilaria Piccoli Till Seehusen Jenny Bussell Olga Vizitu Irina Calciu Antonio Berti Gunnar Börjesson Holger Kirchmann Thomas Kätterer Felice Sartori Chris Stoate Felicity Crotty Ioanna S. Panagea Abdallah Alaoui Martin A. BolinderSammendrag
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Forfattere
Pia Heltoft ThomsenSammendrag
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Sammendrag
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Forfattere
Kannan Mohan Durairaj Karthick Rajan Thirunavukkarasu Muralisankar Abirami Ramu Ganesan Palanivel Sathishkumar Nagarajan RevathiSammendrag
Aquaculture industry is one of the world’s fastest and largest growing food producing sector. Most importantly, the usage of fish meal in aquaculture has been replaced with alternate protein sources due to their production cost, demand of raw materials and various environmental issues. The insect black soldier fly (Hermetia illucens) larval (BSFL) meal is being recognized as a feed ingredient in aquafeeds for their protein rich content similar to fish meal (FM). BSFL meal has been utilized as a fish meal or soy meal substitution in aquaculture to improve the nutrition. The culture of H. illucens larvae can be achieved using various biodegradable wastes and converted into a valuable biomass. In addition, the proximate analysis of H. illucens has been analyzed for its multifaceted role in poultry, cattle feed preparation and human consumption. The effectiveness of BSFL diet was analyzed for final body weight (FBW), specific growth rate (SGR), feed conversion ratio (FCR), feed intake (FI), feed efficiency (FE) and survival (SUR) of different fish and shrimp used as an experimental models with FM as the control diet. However, there is no comprehensive review available on the BSFL as an alternate protein source in aquaculture till date. Hence, the present review aimed to evaluate the feasible role of BSFL in feed, its sustainable production and challenges of BSFL meal in aquaculture sector along with their merits and demerits.
Sammendrag
In total, 154 wild raspberry samples were collected from 26 localities representing a large area in Norway (21 localities) and a narrowly defined region of the Giant Mountains in the northern parts of the Czech Republic (5 localities). The samples were characterized for genetic diversity and population differentiation as well as for their potential use in crop breeding. Choice of plant material was based on the biogeographical similarity between the Giant Mountains and relevant areas in Norway, where plant communities may have evolved in parallel since the ice ages. The overall level of genetic diversity ĥ = 0.786, I = 2.153 was high. Numerous rare alleles were found for raspberries originating especially from the East Giant Mountains populations Jeleni louky and Krakonosuv lom. The overall degree of population subdivision measured by Wright’s fixation index (FST) was of a moderate level of 0.28. The highest level 0.33 was found between populations in Northern Norway and 0.31 between populations in the Giant Mountains. The genetic structure was evaluated using Bayesian analyses as implemented using STRUCTURE software. According to the ΔK value, eight clusters (K8) were identified among all the analysed samples. The results of the analysis of molecular variance (AMOVA) indicated that 79.7% of the total variation could be attributed to differences among individuals within populations, 15.3% was credited to differences among populations within regions, and only 5.0% was attributed to differences among regions. We concluded based on the results that Czech and Norwegian raspberry (R. idaeus) populations growing in natural high altitude and northern ecosystems are important genetic resources and represent a valuable source of genes and unique allele compositions for in situ and ex situ conservation and future raspberry breeding programmes.
Forfattere
Pavel Raška Nejc Bezak Carla S.S. Ferreira Zahra Kalantari Kazimierz Banasik Miriam Bertola Mary Bourke Artemi Cerdà Peter Davids Mariana Madruga de Brito Rhys Evans David C. Finger Rares Halbac-Cotoara-Zamfir Mashor Housh Artan Hysa Jiří Jakubínský Marijana Kapović Solomun Maria Kaufmann Saskia Keesstra Emine Keles Silvia Kohnová Michele Pezzagno Kristina Potočki Samuel Rufat Samaneh Seifollahi-Aghmiuni Arthur Schindelegger Mojca Šraj Gintautas Stankunavicius Jannes Stolte Ružica Stričević Jan Szolgay Vesna Zupanc Lenka Slavikova Thomas HartmannSammendrag
The major event that hit Europe in summer 2021 reminds society that floods are recurrent and among the costliest and deadliest natural hazards. The long-term flood risk management (FRM) efforts preferring sole technical measures to prevent and mitigate floods have shown to be not sufficiently effective and sensitive to the environment. Nature-Based Solutions (NBS) mark a recent paradigm shift of FRM towards solutions that use nature-derived features, processes and management options to improve water retention and mitigate floods. Yet, the empirical evidence on the effects of NBS across various settings remains fragmented and their implementation faces a series of institutional barriers. In this paper, we adopt a community expert perspective drawing upon LAND4FLOOD Natural flood retention on private land network (https://www.land4flood.eu) in order to identify a set of barriers and their cascading and compound interactions relevant to individual NBS. The experts identified a comprehensive set of 17 barriers affecting the implementation of 12 groups of NBS in both urban and rural settings in five European regional environmental domains (i.e., Boreal, Atlantic, Continental, Alpine-Carpathian, and Mediterranean). Based on the results, we define avenues for further research, connecting hydrology and soil science, on the one hand, and land use planning, social geography and economics, on the other. Our suggestions ultimately call for a transdisciplinary turn in the research of NBS in FRM.
Sammendrag
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