Composition and spatial structure of dwarf shrub heath in Norway

Aune-Lundberg, Linda; Strand, Geir-Harald

doi:10.1080/00291951.2017.1291536

Cited by 7 publications

(9 citation statements)

References 38 publications

(35 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our results show that VTs with broad distributions along spatial, climatic and environmental gradients are over‐represented among poorly predicted types. This is in accordance with results of previous studies, showing that some of these VTs are very broadly defined, with large intra‐type variation, actually comprising several subtypes (Aune‐Lundberg & Strand, ). An example from our study of such an ambiguous VT associated with a model of poor predictive power is Dwarf shrub/alpine Calluna heath (2ef), which comprises at least four sub‐types (Aune‐Lundberg & Strand, ).…”

Section: Discussionsupporting

confidence: 93%

“…No EV is able to separate presences clearly from absences in such cases. Modelling of separate subtype entities is recommended (Aune‐Lundberg & Strand, ). Furthermore, this (and other) VTs that occupy suitable habitats in the middle parts of gradients (i.e., avoiding extremes) will be poorly predicted by explanatory variables that are linearly related to the underlying environmental gradients as long as non‐linear transformations of these variables are not used in the modelling.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Distribution modelling of vegetation types based on area frame survey data

Horvath

Halvorsen

Stordal

et al. 2019

Applied Vegetation Science

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Distribution modelling of vegetation types based on area frame survey data

Horvath

Halvorsen

Stordal

et al. 2019

Applied Vegetation Science

View full text Add to dashboard Cite

show abstract

“…However, our results also contain examples of confusion of units from different groups, e.g. the NIBIO units “dwarf shrub heath” and “bog” (Aune‐Lundberg & Strand, ). This is not unexpected since groups share borders with other groups, both in the field and in ecological theory.…”

Section: Discussionmentioning

confidence: 63%

Consistency in land‐cover mapping: Influence of field workers, spatial scale and classification system

Ullerud

Bryn

Halvorsen

et al. 2018

Applied Vegetation Science

View full text Add to dashboard Cite

| INTRODUC TI ONIn a rapidly changing world with increasing pressure on natural resources, land-cover maps are of utmost importance for area planning and resource management (Fuchs, Herold, Verburg, Clevers, & Eberle, 2015). Land-cover maps depict the physical cover of the surface of the Earth. Vegetation, for example the plant species composition (Box & Fujiwara, 2005), is the physical cover most often used for land-cover mapping because plants are easy to observe and vegetation types can be identified using a wide variety of methods. The plant species composition reflects variation along important environmental complex gradients (Whittaker, 1967), thus vegetation-based land-cover maps can also be used as a proxy for the ecosystem, i.e. all species present at a site, the environmental conditions and the processes and mechanisms by which the environment influences the species (cf. Tansley, 1935). Lakes, rock outcrops and vast areas of constructed sites and land otherwise heavily modified by man do, however, lack natural vegetation and hence are 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. K E Y W O R D S delineation, ecosystem mapping, ecosystem types, GIS, map quality, precision, repeatability, vegetation mapping, vegetation types SUPPORTING INFORMATION Additional Supporting Information may be found online in the supporting information tab for this article. APPENDIX S1 Details of the aerial photos APPENDIX S2 Details of the NiN system, and the update from the preliminary system to the revised system APPENDIX S3 Method for and res...

show abstract

“…The results of both N50 and AR18X18 are therefore probably restricted by the defined minimum polygon sizes. The 10 Secondary Statistical Unit (SSU) points gathered within each of the 1081 PSUs can be used to test such issues, but that is beyond the scope of this article (for an example of such an analysis see Aune-Lundberg & Strand 2017).…”

Section: Implications Of New Land Cover Statistics: the Case Of Wetlandsmentioning

confidence: 99%

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

Bryn

Strand

Angeloff

et al. 2018

Norsk Geografisk Tidsskrift - Norwegian Journal of Geography

Self Cite

View full text Add to dashboard Cite

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 km 2 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.

show abstract

Composition and spatial structure of dwarf shrub heath in Norway

Cited by 7 publications

References 38 publications

Distribution modelling of vegetation types based on area frame survey data

Distribution modelling of vegetation types based on area frame survey data

Consistency in land‐cover mapping: Influence of field workers, spatial scale and classification system

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

Contact Info

Product

Resources

About