Anders Bryn

Research Scientist

(+47) 930 39 782
anders.bryn@nibio.no

Place
Ås O43

Visiting address
Oluf Thesens vei 43, 1433 Ås

Biography

I work as a researcher in a 20 % position in the Department of Land Resource Surveys, Division of Survey and Statistics.

My work is primarily related to vegetation mapping, the project Arealregnskap i utmark (AR18X18), mountain farming and contributions to other departments (applications, articles, dissemination, etc.). I also generally contribute to the development, research and dissemination of methodology for mapping of outfield lands.

My subject areas are:
- vegetation mapping
- distribution modelling
- tree- and forest lines
- ecological climatology
- citizen science
- land use

I have a Master degree in vegetation ecology from the University of Oslo and a PhD in biogeography from the University of Bergen.

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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 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.

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During recent decades, forests have expanded into new areas throughout the whole of Norway. The processes explained as causing the forest expansion have focused mainly on climate or land use changes. To enable a spatially explicit separation of the effects following these two main drivers behind forest expansion, the authors set out to model the potential for natural forest regeneration following land use abandonment, given the present climatic conditions. The present forest distribution, a number of high-resolution land cover maps, and GIS methods were used to model the potential for natural forest regeneration. Furthermore, the results were tested with independent local models, explanatory variables and predictive modelling. The modelling results show that land use abandonment, in a long-term perspective, has the climatic and edaphic potential to cause natural forest regeneration of 48,800 km2, or 15.9% of mainland Norway. The future natural forest regeneration following land use change or abandonment can now be spatially separated from the effects of climate changes. The different independent model tests support the main findings, but small fractions of the modelled potential natural forest regeneration will probably be caused by other processes than land use abandonment.

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Didemnum vexillum is colonial sea squirt, a marine species which originates from the northwest Pacific; it was first recorded in Norway in November 2020. Didemnum vexillum is an alien species, meaning that it is a species that has been transferred from its original region to other regions of the world through human activity, and it had not previously been recorded in Norwegian waters. The species is regarded as having great invasive potential and having strong negative ecological effects on biodiversity. It is also considered to pose a risk to marine industries such as shipping and aquaculture, with possible major negative economic impacts.

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VKM has evaluated the risk to biodiversity from allowing private import and keeping of the Northern Cardinal as a caged bird in Norway, for birds acquired through the bird trade. VKM has reviewed the invasion ecology of non-native birds in general and of the Northern Cardinal specifically. The assessment includes evaluation of various mechanisms that invasive birds generally have a negative impact through, and includes competition, hybridization, spread of pathogens and interactions with other alien species in Norway. VKM has also evaluated two different scenarios establishment and how climate change can influence both the negative impact and the likelihood of establishment. Overall, VKM finds that there is low risk in regards negative effects on biodiversity in Norway in regard to import and keeping of the Northern Cardinal.

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VKM has evaluated to what extent keeping of cats pose a risk to biodiversity in Norway. Risks were assessed separately for threats to biodiversity from direct predation, indirect (non-lethal) effects, competition with other wildlife and spread of infectious organisms. VKM also assessed the risk of reduced animal welfare related to the keeping of domestic cats, both for the cats and their prey. In addition, VKM has assessed a range of risk-reducing measures aimed at minimizing the risk for negative impacts on biodiversity and animal welfare. Overall, VKM find that the risk of negative impact on vulnerable birds and red-listed mammalian species are high under certain conditions. VKM also find that there is a considerable risk associated with increased spread of infectious organisms from cats to wildlife and other domestic species. Some of these infectious organisms may also infect humans. With respect to mitigation measures, VKM concludes that measures focused on limiting cats’ access to prey populations are likely to yield the most positive outcomes in terms of mitigating the adverse impact on biodiversity.

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Key words: apiculture, biological control, Norwegian Environment Agency, Norwegian Scientific Committee for Food and Environment, predatory mites, risk assessment, varroa Introduction The Norwegian Environment Agency (NEA) have asked the Norwegian Scientific Committee for Food and Environment for an assessment of adverse impacts on biodiversity concerning import and release of the predatory mite Stratiolaelaps scimitus as measure against varroa mites (Varroa destructor) in apiaries. The predatory mite is already in use in Norwegian greenhouses and polytunnels as a biological control agent against dark-winged fungus gnats in a various of plant cultures. The NEA has received an application for a new type of use: to combat varroa mites in apiaries. Background Varroa destructor (the varroa mite) is a species of parasitic mite that feeds externally on honeybees; it is considered one of the major threats to beekeeping world-wide due to its parasitic behaviour and because it acts as a vector for several viral and bacterial bee pathogens. Beekeepers in North America have begun experimenting with introducing Stratiolaelaps scimitus, a commercially available predaceous mite originally used for biocontrol in greenhouses and polytunnels, to control varroa mites, and several studies on the use of the mite in this context have been published recently. The Norwegian Environment Agency has asked VKM to assess the risk to biological diversity in Norway associated with this new use of S. scimitus, and to assess the effects of climate change on any risks that are proposed. Stratiolaelaps scimitus is a tiny (0.5 mm), soil-dwelling predaceous mite that in nature feeds on a wide variety of soil invertebrates, including fly larvae, nematodes, nymphs of thrips, potworms (oligochaetes), springtails, and other mites. For over three decades, Stratiolaelaps scimitus has been produced commercially and the species is now used globally for biological control. The mite is applied to control a wide variety of organisms harmful to food production or to the production of ornamental plants, but especially to combat infestations of fungus gnat larvae, spider mites, flower thrips, and certain plant-feeding nematodes. The species is already used as a biocontrol agent in Norway in greenhouses, open plastic polytunnels used for protecting crops, and in various indoor plantings and fungiculture. Methods VKM established a project group with expertise in entomology, invasion ecology, honeybee behaviour and ecology, and risk analysis of biological control agents. The group conducted systematic literature searches and scrutinized the relevant literature that was found. In the absence of Norwegian studies, VKM relied on literature from other countries. Results and conclusions This VKM assessment concludes with medium confidence that introducing S. scimitus for use in beehives would not significantly increase the probability of establishment and spread of S. scimitus above that of its current use. We point out that there is no evidence that continuous use of S. scimitus in Norway, over decades, has led to its establishment outside of enclosures, including open polytunnels. The optimal temperature for development and reproduction is far higher than what is normally observed in Norway (~28 °C). Although lethal temperature has been reported to be as low as –5.2 °C, we still conclude that S. scimitus would not be able to establish permanent populations in Norway, not even in the southern part of the country as such temperatures are expected to occur in some years throughout the country. Future climate change is not believed to alter this conclusion, since periods with lethally cold temperatures are expected to still occur in the future.

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Questions Field-based ecosystem mapping is prone to observer bias, typically resulting in a mismatch between maps made by different mappers, that is, inconsistency. Experimental studies testing the influence of site, mapping scale, and differences in experience level on inconsistency in field-based ecosystem mapping are lacking. Here, we study how inconsistencies in field-based ecosystem maps depend on these factors. Location Iškoras and Guollemuorsuolu, northeastern Norway, and Landsvik and Lygra, western Norway. Methods In a balanced experiment, four sites were field-mapped wall-to-wall to scales 1:5000 and 1:20,000 by 12 mappers, representing three experience levels. Thematic inconsistency was calculated by overlay analysis of map pairs from the same site, mapped to the same scale. We tested for significant differences between sites, scales, and experience-level groups. Principal components analysis was used in an analysis of additional map inconsistencies and their relationships with site, scale and differences in experience level and time consumption were analysed with redundancy analysis. Results On average, thematic inconsistency was 51%. The most important predictor for thematic inconsistency, and for all map inconsistencies, was site. Scale and its interaction with site predicted map inconsistencies, but only the latter were important for thematic inconsistency. The only experience-level group that differed significantly from the mean thematic inconsistency was that of the most experienced mappers, with nine percentage points. Experience had no significant effect on map inconsistency as a whole. Conclusion Thematic inconsistency was high for all but the dominant thematic units, with potentially adverse consequences for mapping ecosystems that are fragmented or have low coverage. Interactions between site and mapping system properties are considered the main reasons why no relationships between scale and thematic inconsistency were observed. More controlled experiments are needed to quantify the effect of other factors on inconsistency in field-based mapping.

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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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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.

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

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Abstract

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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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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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.

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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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The abstract classification system Nature in Norway (NiN) has detailed ecological definitions of a high number of ecosystem units, but its applicability in practical vegetation mapping is unknown because it was not designed with a specific mapping method in mind. To investigate this further, two methods for mapping – 3D aerial photographic interpretation of colour infrared photos and field survey – were used to map comparable neighbouring sites of 1 km2 in Hvaler Municipality, south-eastern Norway. The classification accuracy of each method was evaluated using a consensus classification of 160 randomly distributed plots within the study sites. The results showed an overall classification accuracy of 62.5% for 3D aerial photographic interpretation and 82.5% for field survey. However, the accuracy varied for the ecosystem units mapped. The classification accuracy of ecosystem units in acidic, dry and open terrain was similar for both methods, whereas classification accuracy of calcareous units was highest using field survey. The mapping progress using 3D aerial photographic interpretation was more than two times faster than that of field survey. Based on the results, the authors recommend a method combining 3D aerial photographic interpretation and field survey to achieve effectively accurate mapping in practical applications of the NiN system.

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Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves

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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.

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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.

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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.

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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.

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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.

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Questions: Substantial variation between observers has been found when comparing parallel land-cover maps, but how can we know which map is better? What magnitude of error and inter-observer variation is expected when assigning land-cover types and is this affected by the hierarchical level of the type system, observer characteristics, and ecosystem properties? Study area: Hvaler, south-east Norway. Methods: Eleven observers assigned mapping units to 120 stratified random points. At each observation point, the observers first assigned a mapping unit to the point independently. The group then decided on a ‘true’ reference mapping unit for that point. The reference was used to estimate total error. ‘Ecological distance’ to the reference was calculated to grade the errors. Results: Individual observers frequently assigned different mapping units to the same point. Deviating assignments were often ecologically close to the reference. Total error, as percentage of assignments that deviated from the reference, was 35.0% and 16.4% for low and high hierarchical levels of the land-covertype system, respectively. The corresponding figures for inter-observer variation were 42.8% and 19.4%, respectively. Observer bias was found. Particularly high error rates were found for land-cover types characterised by human disturbance. Conclusions: Access to a ‘true’ mapping unit for each observation point enabled estimation of error in addition to the inter-observer variation typically estimated by the standard pairwise comparisons method for maps and observers. Three major sources of error in the assignment of land-cover types were observed: dependence on system complexity represented by the hierarchical level of the land-cover-type system, dependence on the experience and personal characteristics of the observers, and dependence on properties of the mapped ecosystem. The results support the necessity of focusing on quality in land-cover mapping, among commissioners, practitioners and other end users.

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Abstract Questions Vegetation mapping based on field surveys is time-consuming and expensive. Distribution modelling might be used to overcome these challenges. What is the performance of distribution modelling of vegetation compared to traditional vegetation mapping when projected locally? Does the modelling performance vary among ecosystems? Does vegetation type distribution and abundance influence the modelling performance? Location Gravfjellet, Øystre Slidre commune, southern Norway. Methods Two comparable neighbouring areas, each of 4 km2, were mapped for species-defined vegetation types. One area was used for model training, the other for model projection. Maximum entropy models were run for six vegetation types, two from each of the ecosystems present in the area: forest, wetland and mountain heath- and shrublands. For each ecosystem, one locally abundant and one locally rare vegetation type were tested. AUC, the area under the receiver operating curve, was used as the model selection criterion. Environmental variables (n = 9) were selected through a backwards selection scheme, and model complexity was kept low. The models were evaluated using independent data. Results Distribution modelling of vegetation types by local projection gave high AUC values, and the results were supported by the evaluation using independent data. The modelling ability was not affected by ecosystem differences. A negative relationship between the number of points used to train the models and the AUC value before evaluation suggests that models for locally rare vegetation types had better predictive performance than the models for abundant types. This result was not significant after evaluation. Conclusion Provided that relevant explanatory variables are available at an appropriate scale, and that field-validated training points are available, distribution modelling can be used for local projection of the six tested vegetation types from the boreal–alpine ecotone.

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Expanding high elevation and high latitude forest has contrasting climate feedbacks through carbon sequestration (cooling) and reduced surface reflectance (warming), which are yet poorly quantified. Here, we present an empirically-based projection of mountain birch forest expansion in south-central Norway under climate change and absence of land use. Climate effects of carbon sequestration and albedo change are compared using four emission metrics. Forest expansion was modeled for a projected 2.6 °C increase of summer temperature in 2100, with associated reduced snow cover. We find that the current (year 2000) forest line of the region is circa 100 m lower than its climatic potential due to land use history. In the future scenarios, forest cover increased from 12 to 27% between 2000 and 2100, resulting in a 59% increase in biomass carbon storage and an albedo change from 0.46 to 0.30. Forest expansion in 2100 was behind its climatic potential, forest migration rates being the primary limiting factor. In 2100, the warming caused by lower albedo from expanding forest was 10 to 17 times stronger than the cooling effect from carbon sequestration for all emission metrics considered. Reduced snow cover further exacerbated the net warming feedback. The warming effect is considerably stronger than previously reported for boreal forest cover, because of the typically low biomass density in mountain forests and the large changes in albedo of snow-covered tundra areas. The positive climate feedback of high latitude and high elevation expanding mountain forests with seasonal snow cover exceeds those of afforestation at lower elevation, and calls for further attention of both modelers and empiricists. The inclusion and upscaling of these climate feedbacks from mountain forests into global models is warranted to assess the potential global impacts.

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During recent decades, forests have expanded into new areas throughout the whole of Norway. The processes explained as causing the forest expansion have focused mainly on climate or land use changes. To enable a spatially explicit separation of the effects following these two main drivers behind forest expansion, the authors set out to model the potential for natural forest regeneration following land use abandonment, given the present climatic conditions. The present forest distribution, a number of high-resolution land cover maps, and GIS methods were used to model the potential for natural forest regeneration. Furthermore, the results were tested with independent local models, explanatory variables and predictive modelling. The modelling results show that land use abandonment, in a long-term perspective, has the climatic and edaphic potential to cause natural forest regeneration of 48,800 km2, or 15.9% of mainland Norway. The future natural forest regeneration following land use change or abandonment can now be spatially separated from the effects of climate changes. The different independent model tests support the main findings, but small fractions of the modelled potential natural forest regeneration will probably be caused by other processes than land use abandonment.

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Pilgrims travel along the main reopened St Olav pilgrim routes in Norway and visit a variety of cultural heritage types. These routes are part of a value creation programme, in which the management authorities try to increase the numbers of pilgrims. At the same time, forest regrowth is reported to reduce the landscape experience of pilgrims and to biophysically change the cultural heritage sites. However, no studies have been reported on the spatial encroachments of forests along the pilgrim routes. The purpose of this study is to analyse where forest regrowth along the main reopened pilgrim routes in Norway will appear, given the present climatic conditions, and to assess the spatial overlap of future forest regrowth with cultural heritage sites. A potential forest model and a cultural heritage sites database were combined with several baseline geographical data layers and spatially joined in geographical information systems. The results show that most of the future forest regrowth will appear in mountainous parts of the pilgrim routes, whereas many hunting sites, tradition sites and other cultural heritage sites will be overgrown by young forests. Therefore, management efforts to keep the main pilgrim routes open need to be strengthened and directed towards future risks.

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Long-term and varied land use has had a major influence on the vegetation in rural Norway, and the traditional open landscapes are now being replaced by forests. In the present investigation, we assess and quantify structural vegetation changes caused by changes in land use and climate. Up-to-date actual vegetation maps from three rural study areas were compared with interpreted historical vegetation maps and potential natural vegetation (PNV) models. Our findings indicate that the present vegetation structure is strongly influenced by land use. In the studied sites, 56–66% of the areas presently have another vegetation type than expected from a natural state (PNV). The mean turnover of vegetation types in the study areas during the past 35–40 years was 25%. Our study highlights that the influence of land-use needs to be accounted for when considering the effects of climate change.

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The purpose of the study was to explore and compare three different methods for modelling potential natural vegetation (PNV), a hypothetic natural state of vegetation that shows nature's biotic potential in the absence of human influence and disturbance. The vegetation was mapped in a south-central Norwegian mountain region, in a 34.2 km2 area around the village of Beitostølen, in 2009. The actual vegetation map (AVM) formed the basis for the development of PNV using three different modelling methods: (1) an expert-based manual modelling (EMM), (2) rule-based envelope GIS-modelling (RBM), and (3) a statistical predictive GIS-modelling method (Maxent). The article shows that the three modelling methods have different advantages, challenges and preconditions. The findings indicate that: (1) the EMM method should preferably be used only as a supplementary method in highly disturbed areas, (2) both the RBM and the Maxent methods perform well, (3) RBM performs especially well, but also Maxent are more objective methods than EMM and they are much easier to develop and re-run after model validation, (4) Maxent probably underestimates the potential distribution of some vegetation types, whereas RBM overestimates, (5) the Maxent output is relative probabilities of distribution, giving higher model variation than RBM.

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Extensive landscape and vegetation changes are apparent within rural districts of Norway, especially as forest regrowth on abandoned agricultural land. Forest regrowth changes the landscape and vegetation heterogeneity, thus affecting management issues related to, for example, biodiversity and landscape aesthetics. By comparing up-to-date actual vegetation maps (AVMs), interpreted previous vegetation maps (IPVs), and potential natural vegetation maps (PNVs), we assess and quantify structural changes on a landscape level which are important for biological diversity and also the tourism industry. Our findings indicate that landscapes in rural districts of Norway have changed and that changes will continue in the future. The landscapediversity did not decrease from the 1970s until 2009. Further forest regrowth however, will lead to reduced landscape heterogeneity, while landscape connectivity will increase.

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The Norwegian landscape is changing as a result of forest regeneration within the cultural landscape, and forest expansion has impacts on accessibility, visibility, and landscape aesthetics, thereby affecting the country's tourism industry. This study aimed at identifying the potential areas of forest regeneration and anticipated subsequent landscape effects on different categories of tourist locations in southern Norway. Deforested areas with a potential for forest regeneration were identified from several map sources by GIS-analyses, and 180 tourist locations were randomly selected from the Norwegian national tourism database (Reiselivsbasen), and then buffered by 2 km radius for land cover classes. The findings revealed that approximately 15% of southern Norway has the climatic potential for future forest regeneration, in addition to 5% of cultivated land. Future forest regeneration will affect the landscapes surrounding the tourist locations of rural south Norway, and while the potential is nationwide, it is not uniformly distributed. Two important tourist landscape regions seem especially exposed to forest regeneration: the coastal heath region and the mountain landscapes. Large parts of these areas do not have sufficient numbers of domestic grazing animals necessary to maintain the present character of the landscape.

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Forest regrowth in rural districts of Norway is currently leading to extensive landscape changes. We aim to quantify and understand the future impact of outfield forest regrowth following land-use abandonment on red-listed vascular plant species which are supposedly threatened by regrowth in Norway, i.e. species classified to habitats within the semi-natural landscape. Vascular plant species were defined by the Norwegian Red List and presence data was downloaded from the Norwegian GBIF-node, Artskart. A newly developed spatially explicit model of deforested semi-natural heaths and meadows in Norway was used to evaluate the vulnerability of red-listed plants to future forest regrowth. The results show that some red-listed species may be greatly affected, since they have most of their known populations within the modelled areas of future forest regrowth. The study also revealed that there are many methodological challenges in using museum databases for hypothesis testing. However, the use of such databases was clearly hypothesis generating, giving us many ideas for future studies.

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Extensive landscape and vegetation changes are apparent within southern Norway, specifically the expansion of forests into new areas and to higher altitudes. Two main processes are believed to cause these changes: regrowth after abandoned human utilisation and recent climate changes. The purpose of this article is to elucidate ways of separating the effects of these two processes on spatiotemporal changes in the upper forest limits using examples from southern Norway. Examples from two spatial scales are implemented, a vegetation map study of a mountain region in south-east Norway and a national map-based study of south Norway. The findings show that multiple methods are necessary to understand the forest limit changes and that the research focus should be on the separation of potential drivers, specifically climate improvements and land-use changes.

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The conference «Mapping and Monitoring of Nordic Vegetation and Landscapes» took place in Hveragerði, Iceland from the 16th to the 18th of September 2009. The 105 participants from 15 countries contributed with 50 oral presentations and 19 posters. This special edition of «Viten», published by the Norwegian Forest and Landscape Institute, presents the conference proceedings, containing 32 articles and 13 posters. We wish to thank the participants for their contributions to both the conference and this report! .....

Abstract

For almost 40 years the Norwegian Forest and Landscape Institute (Norsk institutt for skog og landskap) has mapped vegetation in Norway. In total, just over 10 % of the country’s land area has been mapped, most of which is in the mountain regions. The resultant vegetation maps are the closest Norway has to an ecological map series. Many secondary map themes can be derived from the vegetation map and the digital format allows a wealth of both spatial and temporal GIS-analyses. Accordingly, there are many user groups and topics of interest. During 2009 the aim is to make the institute’s vegetation maps available to all via the Internet in a seamless database.

Abstract

The coastal heath region along the western coast of Norway, dominated by Calluna vulgaris, is undergoing rapid change. Vegetation changes are caused by changes in management, including reduced frequency or abandonment of periodic heath burning and reduced cutting and grazing. The islands of Froan, in the outermost part of Sør-Trøndelag County in mid-western Norway, are dominated by coastal heath in a state of recession due to reduced traditional land use. The coastal heath is acknowledged as vulnerable and valuable by national environmental authorities, and local landscape management is supported by different national subsidies. The authors mapped the vegetation on Froan and used rule-based GIS-modelling to predict the relative potential for future vegetation changes. The model was based on a range of map layers, including management themes such as history of heath burning and peat removal, current practices of sheep grazing, and also themes derived from the vegetation map, such as soil nutrients, soil moisture and present management status. The resulting model output provides relative probabilities of future changes under different land-use scenarios, and highlights where management efforts should be focused in order to maintain the traditional landscape character.

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The forest limits of south-east Norway have expanded to higher altitudes. Two main processes are believed to cause these changes; re-growth after abandonment of human utilisation and recent climate changes. This article aim at separating the effects of these two processes on the upper forest limits and recent forest expansion. The results show that raised forest limits and forest range expansion often attributed to recent climate change is rather the product of re-growth, a process that was climatically retarded from 1959 to 1995. From 1995 to 2006, the data indicate a preliminary effect of climate change escalating the re-growth and probably pushing the future forest limits to higher altitudes.