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

Semi-natural grasslands in Southeastern Norway: Investigating the land cover contents of Naturbase localities

In the past century, the agricultural landscape in Norway, and Europe, has changed drastically. Artificial fertilizer, electricity and modern machinery has contributed to the development of the industrialization of the modern agricultural landscape. The once so abundant semi-natural grasslands have declined considerable in this period, either due to intensification or abandonment, and remaining areas are often small and peripheral. The fragmentation of these habitats poses challenges for semi-natural grassland specialist species, of which many are threatened and in decline. Since the late 1990’s, efforts have been made to map remaining localities of semi-natural hay meadows and pastures, by use of the land cover mapping system Handbook 13. The results are stored in the digital access portal Naturbase and are important for area planning and biodiversity conservation. However, the localities have been criticized for being inaccurate and of varying quality, particularly the earlier mapped areas. The aim of this thesis is to describe the land cover contents of these localities and to describe the condition of semi-natural grasslands in terms of the current agricultural land use intensity and regrowth succession. Land cover mapping was conducted in 60 sampled Naturbase localities of the types Semi-natural hay meadow and Semi-natural pasture in Southeastern Norway, by use of the Nature in Norway (NiN) land cover mapping system. A sampling scheme based on perpendicular transects was used to sample a number of semi-random points within each locality, depending on locality area. Area statistics was obtained by calculating Voronoi polygons based on the sampled points. Land cover content and condition variables were tested with Generalized Linear Models against multiple explanatory variables representing information available from Naturbase, AR5 area resource maps, local ecological conditions, topographical, geographical and bioclimatic information, and other descriptive variables from the NiN system. The investigated localities covered in total 1002 daa. The land cover type Semi-natural grassland covered 47 % of the total area, while Fertilized grasslands and Intensively managed agricultural areas with appearance of semi-natural grassland covered 19 % and 17 %, respectively. The remaining area was represented by 15 land cover types, being mostly forest-types and intensively modified non-agricultural types. The Semi-natural grassland areas were for the most part managed at a land use intensity sufficient to maintain semi-natural grassland characteristics (79 %), although some of the area was managed by a regime unfavorable for semi-natural grassland species. A smaller percentage of the Semi-natural grassland area was not affected by regrowth succession (64 %), thus some areas were managed at appropriate intensity, but showed signs of a recent period of abandonment. Locality size, vegetation zone and mapper ID were among the significant variables in predicting the number of major types in the localities, while registration year, locality size and lime-richness were significant predictors of the proportion of Semi-natural grassland in the localities. The condition of Semi-natural grasslands was related to variation in the canopy cover and measures of area accessibility, while variables derived from Naturbase where not found significant