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

Presence-absence of plant habitat specialists in 15 patches of dry calcareous grassland

Background Dry grasslands on calcareous bedrock in warm climates around the Oslo Fjord are naturally fragmented biodiversity hotspots. This habitat geographically coincides with the most densely populated area of Norway. Many habitat specialists, along with the habitat itself, are red-listed because of land-use change, forest encroachment, and invasive species that cause habitat loss and greater isolation of remaining patches. To ensure effective conservation, data on species presences and absences are necessary to quantify states, changes, and extinction risks in specific populations and habitat patches. New information We present presence-absence data of 49 vascular plant species in 15 patches of dry calcareous grassland habitat, surveyed in 2009, 2019, and in 2020. The species are considered to be habitat specialists and, thus, unlikely to occur between the patches. sampling-event, vascular plants, specialist species, presence-absence data, calcareous grassland, habitat patch, GBIFpublishedVersio

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

Point of view: error estimation in field assignment of land-cover types

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-cover-type 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. Taxonomic reference: Lid & Lid (2005) for vascular plants. Syntaxonomic reference: Halvorsen et al. (2015) for land-cover types. Abbreviations: ED = Ecological distance; GLM = Generalised linear model; LCE = Local complex environmental variable; NiN = Nature in Norway; TPI = Topographic position index