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
Forfattere
Eli Knispel Rueness Maria Gulbrandsen Asmyhr Dean Basic Katrine Eldegard Andrew M. Janczak Hans Christian Pedersen Bjørnar Ytrehus Angelika Agdestein Paul Ragnar Berg Anders Bryn Sonya Rita Geange Kjetil Hindar Lars Robert Hole Lawrence R. Kirkendall Anders Nielsen Erlend Birkeland Nilsen Brett Sandercock Eva Bonsak Thorstad Gaute VelleSammendrag
Source at https://vkm.no/.
Forfattere
Bjørnar Ytrehus Jan Ove Bustnes Bård-Jørgen Bårdsen Katrine Eldegard Kyrre Kausrud Brett Sandercock Paul Ragnar Berg Anders Bryn Sonya Rita Geange Erik Georg Bø-Granquist Kjetil Hindar Lars Robert Hole Johanna Järnegren Lawrence R. Kirkendall Anders Nielsen Erlend Birkeland Nilsen Gaute VelleSammendrag
Background Spring hunting for ducks (Lodden in Northern Sami) is part of the Sami hunting and trapping culture. In Norway, this traditional hunting has been permitted in Kautokeino Municipality in accordance with the exception provision in the Wildlife Act Section 15, with quotas for males of several duck species. However, hunting in the spring may be in conflict with the Nature Diversity Act's principle for species management, saying (quote from Section 15): “Unnecessary harm and suffering caused to animals occurring in the wild and their nests, lairs and burrows shall be avoided. Likewise, unnecessary pursuing of wildlife shall be avoided.” Furthermore, in accordance with international legislation and agreements, the Wildlife Act (Section 9) states that the hunting season should not be set to the nesting and breeding season for the species in question. The Norwegian Environment Agency (NEA) asked VKM to (1) assess risk and risk-reducing measures on biodiversity and animal welfare when conducting spring hunting of ducks. The terms of reference were additionally clarified by the NEA to include assessments of the risks associated with hunting quotas of up to 150, 300, and 500 male individuals, on the populations of mallard (Anas platyrhynchos), tufted duck (Aythya fuligula), velvet scoter (Melanitta fusca), common scoter (Melanitta nigra), long-tailed duck (Clangula hyemalis), and red-breasted merganser (Mergus serrator). VKM was furthermore asked to (2) point out risk-reducing measures in scenarios with hunting bags corresponding to the mentioned quotas of all the six species. Method VKM appointed a project group to answer the request from NEA and assess the risks to biodiversity and animal welfare posed by spring hunting for adult male ducks. The project group narrowed down the scope of the biodiversity risk assessment to encompass risks for local populations of six target species: mallard, tufted duck, velvet scoter, common scoter, long-tailed duck, and red-breasted merganser, and non-target migratory waterbirds. Negative impacts on biodiversity was defined as negative effects on population viability. The VKM project group gathered data from publications retrieved from literature searches and reports from Kautokeino municipality to the Finnmark Estate (Finnmarkseiendommen), which were made available to the group by the Norwegian Environment Agency. Hunting statistics were acquired from Statistics Norway (Statistisk sentralbyrå; SSB). During the assessment, several critical knowledge gaps and uncertainties were identified. The main obstacle for assessment of the impact of spring hunting on viability of local populations in Kautokeino, is the lack of data on relevant population sizes and demographic rates for the six target species. The available population estimates are partly based on almost 30-year-old bird counts. In addition, knowledge about spatial and temporal distributions of each species, combined with local or remote-sensed data on ice breakup, is needed to estimate the proportion of the population being effectively hunted in early spring when ducks are congregating on available ice-free waters. Such knowledge, combined with information about where, when, how and by how many hunters the hunting is performed, is also critical for sound assessments of risk to biodiversity and harm to bird welfare. Improved data on hunting bags (reliable, spatially explicit, and detailed) and frequency of wounding and crippling is also needed to provide accurate assessments. The project group performed modelling of harvest scenarios for a range of conditions (e.g., number of birds harvested, reduced breeding success caused by indirect effects of disturbance, environmental stochasticity, and spatial variation in habitat) to assess how sensitive the populations are to different parameters and model assumptions. ..............................
Sammendrag
The alpine treeline ecotone is expected to move upwards in elevation with global warming. Thus, mapping treeline ecotones is crucial in monitoring potential changes. Previous remote sensing studies have focused on the usage of satellites and aircrafts for mapping the treeline ecotone. However, treeline ecotones can be highly heterogenous, and thus the use of imagery with higher spatial resolution should be investigated. We evaluate the potential of using unmanned aerial vehicles (UAVs) for the collection of ultra-high spatial resolution imagery for mapping treeline ecotone land covers. We acquired imagery and field reference data from 32 treeline ecotone sites along a 1100 km latitudinal gradient in Norway (60–69°N). Before classification, we performed a superpixel segmentation of the UAV-derived orthomosaics and assigned land cover classes to segments: rock, water, snow, shadow, wetland, tree-covered area and five classes within the ridge-snowbed gradient. We calculated features providing spectral, textural, three-dimensional vegetation structure, topographical and shape information for the classification. To evaluate the influence of acquisition time during the growing season and geographical variations, we performed four sets of classifications: global, seasonal-based, geographical regional-based and seasonal-regional-based. We found no differences in overall accuracy (OA) between the different classifications, and the global model with observations irrespective of data acquisition timing and geographical region had an OA of 73%. When accounting for similarities between closely related classes along the ridge-snowbed gradient, the accuracy increased to 92.6%. We found spectral features related to visible, red-edge and near-infrared bands to be the most important to predict treeline ecotone land cover classes. Our results show that the use of UAVs is efficient in mapping treeline ecotones, and that data can be acquired irrespective of timing within a growing season and geographical region to get accurate land cover maps. This can overcome constraints of a short field-season or low-resolution remote sensing data.
2021
Forfattere
Peter Horvath Hui Tang Rune Halvorsen Frode Stordal Lena M. Tallaksen Terje Koren Berntsen Anders BrynSammendrag
Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.
Sammendrag
Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved. area frame survey, assembly strategies, distribution modeling, spatial probabilities, vegetation mapping, vegetation types
Sammendrag
Information about the distribution of a study object (e.g., species or habitat) is essential in face of increasing pressure from land or sea use, and climate change. Distribution models are instrumental for acquiring such information, but also encumbered by uncertainties caused by different sources of error, bias and inaccuracy that need to be dealt with. In this paper we identify the most common sources of uncertainties and link them to different phases in the modeling process. Our aim is to outline the implications of these uncertainties for the reliability of distribution models and to summarize the precautions needed to be taken. We performed a step-by-step assessment of errors, biases and inaccuracies related to the five main steps in a standard distribution modeling process: (1) ecological understanding, assumptions and problem formulation; (2) data collection and preparation; (3) choice of modeling method, model tuning and parameterization; (4) evaluation of models; and, finally, (5) implementation and use. Our synthesis highlights the need to consider the entire distribution modeling process when the reliability and applicability of the models are assessed. A key recommendation is to evaluate the model properly by use of a dataset that is collected independently of the training data. We support initiatives to establish international protocols and open geodatabases for distribution models.
Sammendrag
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Sammendrag
Abandonment of agricultural land is a process described from different regions of many industrialized countries. Given the current focus on land use, land use change and food security, it appears highly relevant to develop improved tools to identify and monitor the dynamics of agricultural land abandonment. In particular, the temporal aspect of abandonment needs to be assessed and discussed. In this study, we used the detailed information available through the Norwegian subsidy claim database and analyzed the history of use of unique land parcels through a fourteen-year period. We developed and tested five different statistics identifying these land parcels, their temporal dynamics and the extent of occurrence. What became apparent was that a large number of land parcels existing in the database as agricultural land were taken out of production, but then entered into production again at a later stage. We believe that this approach to describe the temporal dynamics of land abandonment, including how it can be measured and mapped, may contribute to the understanding of the dynamics in land abandonment, and thus also contribute to an improved understanding of the food production system.
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Forfattere
Anders Bryn Thea Grobstok Dalen Eirik Aasmo Finne Hanne Heiberg Lasse Torben Keetz Irene Brox Nilsen Frans-Jan W. Parmentier Christine Snekkenes Frode Stordal Kjetil Schanke Aas Dag Olav Hessen Inge Althuizen Liss Marie Andreassen Dag-Inge Bakke Terje Koren Berntsen Jarle W. Bjerke Ryan Bright Anita Verpe Dyrrdal Sonya Rita Geange Peter Horvath Thomas Opel Norbert Pirk Oskar Puschmann Kjersti Strass Lena M. Tallaksen Hui Tang Michal Torma Ane Vollsnes Sebastian Westermann Yeliz A. YilmazSammendrag
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