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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

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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. ..............................

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Background Since the late 1800s, an unknown number of common pheasants and grey partridges from captive bred stocks have been released in Norwegian nature. The birds are released to be used for training of pointing dogs. The import, keeping and release of gamebirds, as well as the management of release sites, have been largely unregulated. The consequences to biodiversity, animal health and welfare have not been investigated. The Norwegian Environment Agency (NEA) and the Norwegian Food Safety Authority (NFSA) have jointly requested the Norwegian Scientific Committee for Food and Environment (VKM) for a scientific opinion on the release of common pheasants and grey partridges for pointing dog training regarding consequences for biodiversity, animal welfare of the released birds and health of the released birds as well as wild birds to which pathogens may be transmitted. VKM was further asked to suggest risk reducing measures for biodiversity and animal welfare. Methods VKM established a project group with expertise within avian ecology, landscape ecology, population biology, wildlife veterinary medicine and animal welfare. The group conducted systematic literature searches, scrutinized the resulting literature, and supplemented by other relevant articles and reports. In the absence of Norwegian studies, VKM used literature from other countries where common pheasants and grey partridges (and in some cases other gamebirds), are released, as references. The project group applied observation data of common pheasants and grey partridges in Norway for the period 2000-2022, presented by the Norwegian Biodiversity Information Centre (NBIC). In the assessments, VKM assumed that the release of birds will be in the same order of magnitude as in previous years (a few thousand birds annually on a national level). The number of release sites and the density of released birds per site are unknown. Increasing the number and density of birds would also increase the probability of negative effects and the severity of the consequences. VKM assessed the impacts of released common pheasants and grey partridges on competition, predation, hybridization, transmission of disease, herbivory and indirect impacts through interactions with other species (predator abundance and pathogen-mediated competition). VKM also assessed the impact on biodiversity in a 50-year perspective. Furthermore, VKM discusses how the birds’ welfare might be impacted by rearing, transport, release and exposure to pointing dogs. Finally, VKM provides a list of relevant diseases and assessed their potential impact on animal health during transport, rearing and release. Results and conclusions VKMs assessment show that there are several risks to biodiversity, animal health, and animal welfare from the release of captive bred common pheasants and grey partridges in Norway. The risk of increased competition for food, particularly in winter, with birds with similar niches as common pheasants and grey partridges, is low on a national scale and moderat on a local scale. This is particularly so for yellowhammer, Emberiza citronella, a species categorized as vulnerable on the national red list due to its progressive population decline caused by reduced availability of food during winter. There is a moderate risk for predation on invertebrates and negative impacts on flora. Indirectly, activities connected to the release of birds may lead to moderate risks of altered predator abundance and disease-mediated competition. VKM concludes that the ecological impacts will be more severe for redlisted species present within the release areas for common pheasants and grey partridges. Repeated release of common pheasants and grey partridges can lead to high risk of disease transmission to wild birds. .............

2021

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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.

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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

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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.

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Aim Many thematic land cover maps, such as maps of vegetation types, are based on field inventories. Studies show inconsistencies among field workers in such maps, explained by inter-observer variation in classification and/or spatial delineation of polygons. In this study, we have tested a new method to assess the accuracy of these two components independently. Location Four study sites dominated by different ecosystems in southeast Norway. Methods We have used a vegetation-based land cover classification system adapted to a map scale of 1:5,000. First, a consensus map, a map that can be considered an approximation of a flawless map, was established. Secondly, the consensus map was adapted to test the accuracy of classification and polygon delineation independently. We used 10 field workers to generate a consensus map, and 14 new field workers (in pairs) to test the accuracy (n = 7). Results The results show that the accuracy of polygon delineation is lower than that of land cover classification. This is in contrast with previous studies, but previous research designs have not enabled a separation of the two accuracy components. Conclusion We recommend strengthening the training and harmonization of field workers in general, and increasing the emphasis on polygon delineation.

Sammendrag

Om lag 5 % av landarealet i Norge er bebygd eller opparbeidet areal. De resterende 95 % er utmark. Fotosyntesebasert verdiskaping i utmark skjer i form av skogbruk, utmarksbeite, reindrift og en rekke former for høstingsbruk. Rapporten gir en overordnet beskrivelse av status og muligheter med hensyn til denne verdiskapingen. Rapporten tar også for seg arealbruks- og målkonflikter som kan oppstå når utmarka tas i bruk.