Skjøtselsplan for verneområdene i Froan

I arbeidet med forvaltningsplan for verneområdene i Froan, ble det på oppdrag fra Fylkesmannen i Sør-Trøndelag gjennomført naturfaglige registreringer i 2011, som skulle danne grunnlaget for en skjøtselsplan. Alle landarealer innen verneområdene ble vegetasjonskartlagt. Med basis i vegetasjonskartleggingen fra 2011, tidligere vegetasjonskartlegging (2007) og andre registreringer fra Froan, presenterer denne rapporten skjøtselsplanen for de terrestre arealene innen verneområdene i Froan. Sammen med skjøtselsplanen følger 5 temakart

Kartmodell viser gjengroing

Det norske landskapet gror igjen med skog og kratt. En ny kartmodell viser hvilke områder i Norge som kan gro igjen

Land cover in Norway based on an area frame survey of vegetation types

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.publishedVersio

Fritidsboliger og skoggrensen i fjellområder

Oppdragsgiver: Klima- og miljødepartementetKlima- og miljødepartementet har bestilt denne analysen som inngår i et arbeid med å vurdere behov for utbyggingsgrenser som virkemiddel for arealbruksmyndighetene. Utredningen gir i den sammenheng et faggrunnlag blant annet for vurdering av mulige statlige planretningslinjer for deler av fjellområdene. Analyseområdet i utredningen er 113 kommuner i det indre av Sør-Norge fra og med Trøndelag. Dette området benevnes Fjellkommuner og Tilliggende fjellkommuner. Verneområdene er medtatt i analyseområdet. Analyse viser utviklingen av fritidsboliger i skoggrensesonen for hele analyseområdet, og en detaljstudie av (15) utvalgte områder hvor det har vært størst utviklingsdynamikk i skog / snaufjell – grenseland

Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral- and three-dimensional information from UAV-based aerial imagery

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.publishedVersio

Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning : Average climate versus extremes

The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and processes that couple vegetation and climate. Dynamic global vegetation models (DGVMs) have been widely applied to describe the distribution of vegetation types and their future dynamics in response to climate change. As a process-based approach, it partly relies on hard-coded climate thresholds to constrain the distribution of vegetation. What thresholds to implement in DGVMs and how to replace them with more process-based descriptions remain among the major challenges. In this study, we employ machine learning using decision trees to extract large-scale relationships between the global distribution of vegetation and climatic characteristics from remotely sensed vegetation and climate data. We analyse how the dominant vegetation types are linked to climate extremes as compared to seasonally or annually averaged climatic conditions. The results show that climate extremes allow us to describe the distribution and eco-climatological space of the vegetation types more accurately than the averaged climate variables, especially those types which occupy small territories in a relatively homogeneous ecological space. Future predicted vegetation changes using both climate extremes and averaged climate variables are less prominent than that predicted by averaged climate variables and are in better agreement with those of DGVMs, further indicating the importance of climate extremes in determining geographic distributions of different vegetation types. We found that the temperature thresholds for vegetation types (e.g. grass and open shrubland) in cold environments vary with moisture conditions. The coldest daily maximum temperature (extreme cold day) is particularly important for separating many different vegetation types. These findings highlight the need for a more explicit representation of the impacts of climate extremes on vegetation in DGVMs.Peer reviewe

Naturtyperegistrering etter NIN 2.0 i landsskogtakseringen. Erfaringer og resultater fra pilotprosjekt

Denne rapporten sammenstiller erfaringer fra et pilotprosjekt der hovedmålet har vært å gjennomføre en uttesting av metodikk for innhenting av arealrepresentativ statistikk for naturtyper etter NiN-systemet, med utgangspunkt i Landsskogtakseringen. Erfaringene skal danne grunnlag for vurdering av mulighetene for en fullskala landsdekkende NiN-registrering i skog og på tresatte arealer. Delmål har vært å avklare 1) hvilke variabler i Landsskogtakseringen som kan anvendes i sin nåværende form ved registreringer etter NiN 2.0, og 2) hvilke nye registreringsvariabler, eventuelt endringer av eksisterende, som er nødvendig. To alternative registreringsopplegg ble utarbeidet og er testet ut av lagledere i Landsskogtakseringen. Disse har taksert over 350 landsskogflater i ulike landsdeler etter begge opplegg, og et utvalg av flatene (46) er også taksert av en biolog fra Naturhistorisk museum ved Universitetet i Oslo, uavhengig av Landsskogtakseringens lagledere. Resultatene viser at en ved å anvende et opplegg basert på en kombinasjon av eksisterende variabler i Landsskogtakseringen og ved å inkludere noen nye fra NiN i tillegg, vil kunne framskaffe et datagrunnlag for å beregne fordelingen av naturtyper i skogsmark og på andre tresatte arealer etter et femårig omdrev. Erfaringene fra prosjektet viser imidlertid også betydningen av å få på plass et godt opplegg for NiN-opplæring og kalibrering av laglederne. I rapporten gis det et anslag over ressursbehov knyttet til en fullskala implementering av NiN- registreringer inkludert kostnader knyttet til kursing og opplæring av inventørene. Før en kan sette i gang med registreringer over et femårig omdrev, er det behov for å avklare med oppdragsgiver hvilket omfang registreringene skal ha og hvordan registreringsopplegget for noen av variablene fra beskrivelsessystemet i NiN skal utformes

Risk assessment of the predatory mite Stratiolaelaps scimitus for biological control of varroa mites in beehives : Scientific opinion of the panel on plant health of the Norwegian scientific committee for food and environment

Source at https://vkm.no/.publishedVersio

What explains inconsistencies in field-based ecosystem mapping?

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. classification, experience, field-based mapping, GIS, inter-observer variation, land-cover mapping, landscape metrics, ordination, scale, vegetation mappingpublishedVersio

Assessment of risk and risk-reducing measures related to the introduction and dispersal of the invasive alien carpet tunicate Didemnum vexillum in Norway

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.Assessment of risk and risk-reducing measures related to the introduction and dispersal of the invasive alien carpet tunicate Didemnum vexillum in NorwaypublishedVersio