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.
2019
Abstract
Aim: Many countries lack informative, high‐resolution, wall‐to‐wall vegetation or land cover maps. Such maps are useful for land use and nature management, and for input to regional climate and hydrological models. Land cover maps based on remote sensing data typically lack the required ecological information, whereas traditional field‐based mapping is too expensive to be carried out over large areas. In this study, we therefore explore the extent to which distribution modelling (DM) methods are useful for predicting the current distribution of vegetation types (VT) on a national scale. Location: Mainland Norway, covering ca. 324,000 km2. Methods: We used presence/absence data for 31 different VTs, mapped wall‐to‐wall in an area frame survey with 1081 rectangular plots of 0.9 km2. Distribution models for each VT were obtained by logistic generalised linear modelling, using stepwise forward selection with an F‐ratio test. A total of 116 explanatory variables, recorded in 100 m × 100 m grid cells, were used. The 31 models were evaluated by applying the AUC criterion to an independent evaluation dataset. Results: Twenty‐one of the 31 models had AUC values higher than 0.8. The highest AUC value (0.989) was obtained for Poor/rich broadleaf deciduous forest, whereas the lowest AUC (0.671) was obtained for Lichen and heather spruce forest. Overall, we found that rare VTs are predicted better than common ones, and coastal VTs are predicted better than inland ones. Conclusions: Our study establishes DM as a viable tool for spatial prediction of aggregated species‐based entities such as VTs on a regional scale and at a fine (100 m) spatial resolution, provided relevant predictor variables are available. We discuss the potential uses of distribution models in utilizing large‐scale international vegetation surveys. We also argue that predictions from such models may improve parameterisation of vegetation distribution in earth system models.
2018
Abstract
The Norwegian area frame survey of land cover and outfield land resources (AR18X18), completed in 2014, provided unbiased statistics of land cover in Norway. The article reports the new statistics, discusses implications of the data set, and provides potential value in terms of research, management, and monitoring. A gridded sampling design for 1081 primary statistical units of 0.9 km2 at 18 km intervals was implemented in the survey. The plots were mapped in situ, aided by aerial photos, and all areas were coded following a vegetation type system. The results provide new insights into the cover and distribution of vegetation and land cover types. The statistic for mire and wetlands, which previously covered 5.8%, has since been corrected to 8.9%. The survey results can be used for environmental and agricultural management, and the data can be stratified for regional analyses. The survey data can also serve as training data for remote sensing and distribution modelling. Finally, the survey data can be used to calibrate vegetation perturbations in climate change research that focuses on atmospheric–vegetation feedback. The survey documented novel land cover statistics and revealed that the national cover of wetlands had previously been underestimated.
Authors
Finn-Arne HaugenAbstract
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Finn-Arne HaugenAbstract
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Nina SvartedalAbstract
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Nina SvartedalAbstract
No abstract has been registered
Abstract
Questions : Land-cover maps are used for nature management, but can they be trusted? This study addresses three questions: (1) what is the magnitude of between field worker inconsistencies in land-cover maps and what may cause such inconsistencies; (2) in which ways and to what extent do spatial scale and mapping system influence inconsistencies between maps; and (3) are some biomes mapped more consistently than others, and if so, why? Location : Gravfjellet, Øystre Slidre municipality, southern Norway. Methods : Two different mapping systems, designed for mapping at different spatial scales, were used for parallel mapping by three different field workers, giving a total of six maps for the study area. Spatial consistency of the resulting maps was compared at two hierarchical levels for both systems. Results : The average pair-wise spatial consistency at the highest hierarchical level was 83% for both systems, while the average pair-wise spatial consistency at the lowest hierarchical level was 60.3% for the coarse system and 43.8% for the detailed system. Inconsistencies between maps were partly caused by the use of different land- cover units and partly by spatial displacement. Conclusions : Field workers made different maps despite using the same mapping systems, materials and methods. The differences were larger at lower hierarchical levels in the mapping systems and increased strongly with system complexity. Consistency among field workers should be estimated as a standard quality indicator in all field-based mapping programmes.
Abstract
Purpose Treelines and forest lines (TFLs) have received growing interest in recent decades, due to their potential role as indicators of climate change. However, the understanding of TFL dynamics is challenged by the complex interactions of factors that control TFLs. The review aims to provide an overview over the trends in the elevational dynamics of TFLs in Norway since the beginning of the 20th century, to identify main challenges to explain temporal and spatial patterns in TFL dynamics, and to identify important domains for future research. Method A systematic search was performed using international and Norwegian search engines for peer-reviewed articles, scientific reports, and MA and PhD theses concerning TFL changes. Results Most articles indicate TFL rise, but with high variability. Single factors that have an impact on TFL dynamics are well understood, but knowledge gaps exist with regard to interactions and feedbacks, especially those leading to distributional time lags. Extracting the most relevant factors for TFL changes, especially with regard to climate versus land-use changes, requires more research. Conclusions Existing data on TFL dynamics provide a broad overview of past and current changes, but estimations of reliable TFL changes for Norway as a whole is impossible. The main challenges in future empirically-based predictions of TFLs are to understand causes of time lags, separate effects of contemporary processes, and make progress on the impacts of feedback and interactions. Remapping needs to be continued, but combined with both the establishment of representative TFL monitoring sites and field experiments.
Abstract
The long history of human land use have had a strong influence on ecosystems and landscapes in the boreal forest region of Northern Europe and created semi-natural habitats of high conservation value. In this study, we quantify land-cover change and loss of semi-natural grassland in an agricultural landscape (6.2 km2 ) in the boreal region of Norway from 1960 to 2015, and document a 49.1% loss of area that was seminatural grassland in 1960. The remaining semi-natural grasslands became smaller and the connectivity between them decreased. Intensification and abandonment of agricultural land use were of approximately equal importance for the loss of semi-natural grassland although the relative contribution of these processes depended on the topography and distance to farmsteads. The study provides an example of how change in land cover can be estimated and key drivers identified on a scale that is relevant for implementation of management and conservation measures.