A comparison of three ways to assemble wall-to-wall maps from distribution models of vegetation types

References

• Alexander, R., and A. C. Millington. 2000. “Vegetation Mapping from Ground, Air and Space - Competitive or Complementary Techniques?” In Vegetation Mapping: From Patch to Planet, edited by R. Alexander and A. C. Millington, 1–21. Chichester: John Wiley & Sons.
   Google Scholar
• Almås, R., B. Gjerdåker, K. Lunden, B. Myhre, and I. Øye. 2004. Norwegian Agricultural History. Trondheim: Tapir.
   Google Scholar
• Araújo, M. B., R. P. Anderson, A. Márcia Barbosa, C. M. Beale, C. F. Dormann, R. A. G. Reagen Early, et al. 2019. “Standards for Distribution Models in Biodiversity Assessments.” Science Advances 5 (1): 1–11. doi:https://doi.org/10.1126/sciadv.aat4858.
   Google Scholar
• Assal, T. J., P. J. Anderson, and J. Sibold. 2015. “Mapping Forest Functional Type in a Forest-Shrubland Ecotone Using SPOT Imagery and Predictive Habitat Distribution Modelling.” Remote Sensing Letters 6 (10): 755–764. doi:https://doi.org/10.1080/2150704x.2015.1072289.
   Web of Science ®Google Scholar
• Bakkestuen, V., L. Erikstad, and R. Halvorsen. 2008. “Step‐Less Models for Regional Environmental Variation in Norway.” Journal of Biogeography 35 (10): 1906–1922. doi:https://doi.org/10.1111/j.1365-2699.2008.01941.x.
   Web of Science ®Google Scholar
• Bryn, A., G.-H. Strand, M. Angeloff, and Y. Rekdal. 2018. “Land Cover in Norway Based on an Area Arame Survey of Vegetation Types.” Norsk Geografisk Tidsskrift–Norwegian Journal of Geography 72 (3): 1–15. doi:https://doi.org/10.1080/00291951.2018.1468356.
   Web of Science ®Google Scholar
• Brzeziecki, B., F. Kienast, and O. Wildi. 1993. “A Simulated Map of the Potential Natural Forest Vegetation of Switzerland.” Journal of Vegetation Science 4 (4): 499–508. https://doi.org/10.2307/3236077.
   Google Scholar
• Cawsey, E. M., M. P. Austin, and B. L. Baker. 2002. “Regional Vegetation Mapping in Australia: A Case Study in the Practical Use of Statistical Modelling.” Biodiversity & Conservation 11 (12): 2239–2274. doi:https://doi.org/10.1023/A:1021350813586.
   Web of Science ®Google Scholar
• Czekanowski, J. 1909. Zur Differentialdiagnose Der Neandertalgruppe:Korrespbl. dt. Ges. Anthrop. 40: 44–47.
   Google Scholar
• D’Amen, M., C. Rahbek, N. E. Zimmermann, and A. Guisan. 2017. “Spatial Predictions at the Community Level: From Current Approaches to Future Frameworks.” Biological Reviews 92 (1): 169–187. doi:https://doi.org/10.1111/brv.12222.
   PubMed Web of Science ®Google Scholar
• Eriksen, E. L., H. A. Ullerud, R. Halvorsen, S. Aune, H. Bratli, P. Horvath, K. V. Inger, K. W. Anders, and A. Bryn. 2018. “Point of View: Error Estimation in Field Assignment of Land-Cover Types.” Phytocoenologia 49 (2): 135–148. doi:https://doi.org/10.1127/phyto/2018/0293.
   Web of Science ®Google Scholar
• Eurostat. 2003. The LUCAS Survey: European Statisticians Monitor Territory. Luxembourg: Office for Official Publications of the European Communities.
   Google Scholar
• Feranec, J. 2016. “Project CORINE Land Cover.” In European Landscape Dynamics: Corine Land Cover Data, edited by J. Feranec, T. Soukup, G. Hazeu, and G. Jaffrain, 9–14. Boca Raton, FL: CRC-Press.
   Google Scholar
• Ferrier, S., and A. Guisan. 2006. “Spatial Modelling of Biodiversity at the Community Level.” Journal of Applied Ecology 43 (3): 393–404. doi:https://doi.org/10.1111/j.1365-2664.2006.01149.x.
   Web of Science ®Google Scholar
• Fielding, A. H., and J. F. Bell. 1997. “A Review of Methods for the Assessment of Prediction Errors in Conservation Presence/Absence Models.” Environmental Conservation 24 (1): 38–49. doi:https://doi.org/10.1017/S0376892997000088.
   Web of Science ®Google Scholar
• Fratte, D., G. B. Michele, and B. E. L. Cerabolini. 2019. “A Low-Cost and Repeatable Procedure for Modelling the Regional Distribution of Natura 2000 Terrestrial Habitats.” Journal of Maps 15 (2): 79–88. doi:https://doi.org/10.1080/17445647.2018.1546625.
   Web of Science ®Google Scholar
• Fuller, R. M., G. M. Smith, and B. J. Devereux. 2003. “The Characterisation and Measurement of Land Cover Change through Remote Sensing: Problems in Operational Applications?” International Journal of Applied Earth Observation and Geoinformation 4 (3): 243–253. doi:https://doi.org/10.1016/S0303-2434(03)00004-7.
   Google Scholar
• Guillera-Arroita, G., J. J. Lahoz-Monfort, J. Elith, A. Gordon, P. E. Heini Kujala, M. A. M. Lentini, R. Tingley, and B. A. Wintle. 2015. “Is My Species Distribution Model Fit for Purpose? Matching Data and Models to Applications.” Global Ecology and Biogeography 24 (3): 276–292. doi:https://doi.org/10.1111/geb.12268.
   Web of Science ®Google Scholar
• ’
   Google Scholar
• Guisan, A., W. Thuiller, and N. E. Zimmermann. 2017. Habitat Suitability and Distribution Models: With Applications in R. London: Cambridge University Press.
   Google Scholar
• Hagen‐Zanker, A. 2009. “An Improved Fuzzy Kappa Statistic that Accounts for Spatial Autocorrelation.” International Journal of Geographical Information Science 23 (1): 61–73. doi:https://doi.org/10.1080/13658810802570317.
   Web of Science ®Google Scholar
• Halvorsen, R. 2012. “A Gradient Analytic Perspective on Distribution Modelling.” Sommerfeltia 35 (1): 1–165. doi:https://doi.org/10.2478/v10208-011-0015-3.
   Google Scholar
• Halvorsen, R., O. Skarpaas, A. Bryn, H. Bratli, L. Erikstad, T. Simensen, and E. Lieungh. 2020. “Towards a Systematics of Ecodiversity: The EcoSyst Framework.” Global Ecology and Biogeography 29 (11): 1887–1906. doi:https://doi.org/10.1111/geb.13164.
   Web of Science ®Google Scholar
• Halvorsen, R., S. Mazzoni, A. Bryn, and V. Bakkestuen. 2015. “Opportunities for Improved Distribution Modelling Practice via a Strict Maximum Likelihood Interpretation of MaxEnt.” Ecography 38 (2): 172–183. doi:https://doi.org/10.1111/ecog.00565.
   Web of Science ®Google Scholar
• Hartley, A. J., N. MacBean, G. Georgievski, and S. Bontemps. 2017. “Uncertainty in Plant Functional Type Distributions and Its Impact on Land Surface Models.” Remote Sensing of Environment 203: 71–89. doi:https://doi.org/10.1016/j.rse.2017.07.037.
   Web of Science ®Google Scholar
• Heggem, E., S. Flo, H. Mathisen, and J. Frydenlund. 2019. AR50 – Arealressurskart I Målestokk 1: 50 000: Et Heldekkende Arealressurskart for Jord- Og Skogbruk. NIBIO Rapport 5 (118). Ås: NIBIO.
   Google Scholar
• Hijmans, R. J. 2019. Raster: “Geographic Data Analysis and Modeling.” R package version 2.8-19. https://rspatial.org/raster
   Google Scholar
• Horvath, P., R. Halvorsen, F. Stordal, L. M. Tallaksen, H. Tang, and A. Bryn. 2019. “Distribution Modelling of Vegetation Types Based on Area Frame Survey Data.” Applied Vegetation Science 22 (4): 547–560. doi:https://doi.org/10.1111/avsc.12451.
   Web of Science ®Google Scholar
• Horvath, P. H., T. R. Halvorsen, F. Stordal, L. M. Tallaksen, T. K. Berntsen, and A. Bryn. 2021. “Improving the Representation of High-Latitude Vegetation Distribution in Dynamic Global Vegetation Models.” Biogeosciences 18 (1): 95–112. doi:https://doi.org/10.5194/bg-18-95-2021.
   Web of Science ®Google Scholar
• Jiménez-Alfaro, B., S. Suárez-Seoane, S. M. Milan Chytrý, W. W. Hennekens, M. Hájek, E. Agrillo, et al. 2018. “Modelling the Distribution and Compositional Variation of Plant Communities at the Continental Scale.” Diversity and Distributions 24 (7): 978–990. doi:https://doi.org/10.1111/ddi.12736.
   Web of Science ®Google Scholar
• Jr, P., R. Gilmore, and M. Millones. 2011. “Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment.” International Journal of Remote Sensing 32 (15): 4407–4429. doi:https://doi.org/10.1080/01431161.2011.552923.
   Web of Science ®Google Scholar
• Merow, C., M. J. Smith, T. C. Edwards, S. M. M. Antoine Guisan, S. Normand, W. Thuiller, R. O. Wüest, N. E. Zimmermann, and J. Elith. 2014. “What Do We Gain from Simplicity versus Complexity in Species Distribution Models?” Ecography 37 (12): 1267–1281. doi:https://doi.org/10.1111/ecog.00845.
   Web of Science ®Google Scholar
• Mikolajczak, A., D. Marechal, T. Sanz, M. Iseninann, V. Thierion, and S. Luque. 2015. “Modelling Ecologically-Consistent Species Assemblages.” Ecological Informatics 30: 196–202. doi:https://doi.org/10.1016/j.ecoinf.2015.09.005.
   Web of Science ®Google Scholar
• MNHN-EEA (Muséum national d’Histoire naturelle and European Environment Agency). 2014. Terrestrial Habitat Mapping in Europe: An Overview. EEA Technical Report No. 1/2014. Luxembourg: Publications Office of the European Union.
   Google Scholar
• Monserud, R. A., and R. Leemans. 1992. “Comparing Global Vegetation Maps with the Kappa Statistic.” Ecological Modelling 62 (4): 275–293. doi:https://doi.org/10.1016/0304-3800(92)90003-W.
   Web of Science ®Google Scholar
• Mucina, L. J., S. Rodwell, J. H. J. Schaminée, and H. Dierschke. 1993. “European Vegetation Survey: Current State of Some National Programmes.” Journal of Vegetation Science 4 (3): 429–438. doi:https://doi.org/10.2307/3235603.
   Web of Science ®Google Scholar
• Myers-Smith, I. H., J. T. Kerby, G. K. Phoenix, J. W. Bjerke, H. E. Epstein, J. J. Assmann, C. John, et al. 2020. “Complexity Revealed in the Greening of the Arctic.” Nature Climate Change 10 (2): 106–117. doi:https://doi.org/10.1038/s41558-019-0688-1.
   Web of Science ®Google Scholar
• Nelson, M. D., J. D. Garner, B. G. Tavernia, S. V. Stehman, R. I. Riemann, A. J. Lister, and C. H. Perry. 2021. “Assessing Map Accuracy from a Suite of Site-Specific, Non-Site Specific, and Spatial Distribution Approaches.” Remote Sensing of Environment 260 (Article): 112442. doi:https://doi.org/10.1016/j.rse.2021.112442.
   Web of Science ®Google Scholar
• Norberg, A., N. Abrego, F. G. Blanchet, F. R. Adler, B. J. Anderson, J. Anttila, M. B. Araujo, et al. 2019. “A Comprehensive Evaluation of Predictive Performance of 33 Species Distribution Models at Species and Community Levels.” Ecological Monographs 89 (3): 24. doi:https://doi.org/10.1002/ecm.1370.
   Web of Science ®Google Scholar
• Oksanen, J. F., G. Blanchet, M. Friendly, R. Kindt, P. Legendre, P. R. M. Dan Mcglinn, et al. 2019. “Vegan: Community Ecology Package.” R package version 2.5-4. https://github.com/vegandevs/vegan
   Google Scholar
• Olofsson, P., G. M. Foody, S. V. Martin Herold, C. E. W. Stehman, and M. A. Wulder. 2014. “Good Practices for Estimating Area and Assessing Accuracy of Land Change.” Remote Sensing of Environment 148: 42–57. doi:https://doi.org/10.1016/j.rse.2014.02.015.
   Web of Science ®Google Scholar
• Ovaskainen, O., G. Tikhonov, F. Anna Norberg, G. Blanchet, L. Duan, D. Dunson, T. Roslin, N. Abrego, and J. Chave. 2017. “How to Make More Out of Community Data? A Conceptual Framework and Its Implementation as Models and Software.” Ecology Letters 20 (5): 561–576. https://doi.org/https://doi.org/10.1111/ele.12757.
   PubMed Web of Science ®Google Scholar
• Ovaskainen, O., and N. Abrego. 2020. Joint Species Distribution Modelling with Applications in R. Cambridge: Cambridge University Press.
   Google Scholar
• Pebesma, E. J., and R. S. Bivand. 2005. “Classes and Methods for Spatial Data in R.” R News 5 (2): 9–13.
   Google Scholar
• Pontius, J., R. Gilmore, and A. Santacruz. 2019. “Package ‘Differ’: Metrics of Difference for Comparing Pairs of Maps or Pairs of Variables.” R package version 0.0-6. https://github.com/amsantac/diffeR
   Google Scholar
• Poulter, B., N. MacBean, A. Hartley, I. Khlystova, O. Arino, R. Betts, S. Bontemps, et al. 2015. “Plant Functional Type Classification for Earth System Models: Results from the European Space Agency’s Land Cover Climate Change Initiative.” Geoscientific Model Development 8 (7): 2315–2328. doi:https://doi.org/10.5194/gmd-8-2315-2015.
   Web of Science ®Google Scholar
• QGIS Development Team. 2009. QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.org
   Google Scholar
• R Core Team. 2020. R: A Language and Environment for Statistical Computing 3.4.3. Vienna: R Foundation for Statistical Computing. https://www.R-project.org/
   Google Scholar
• Ramberg, I. B., I. Bryhni, A. Nøttvedt, and K. Rangnes. 2008. The Making of a Land: Geology of Norway. Trondheim: Geographical Society of Norway.
   Google Scholar
• Landis, J. R., and G. G. Koch. 1977. “The Measurement of Observer Agreement for Categorical Data.” Biometrics 33 (1): 159–174. doi:https://doi.org/10.2307/2529310.
   PubMed Web of Science ®Google Scholar
• Rocchini, D. 2010. “While Boolean Sets Non-Gently Rip: A Theoretical Framework on Fuzzy Sets for Mapping Landscape Patterns.” Ecological Complexity 7 (1): 125–129. doi:https://doi.org/10.1016/j.ecocom.2009.08.002.
   Web of Science ®Google Scholar
• Rodwell, J. S. 2018. “The UK National Vegetation Classification.” Phytocoenologia 48 (2): 133–140. doi:https://doi.org/10.1127/phyto/2017/0179.
   Web of Science ®Google Scholar
• Rossiter, D. G. 2004. Technical Note: Statistical Methods for Accuracy Assessment of Classified Thematic Maps. Department of Earth Systems Analysis. Enschede: International Institute for Geo-information Science & Earth Observation (ITC).
   Google Scholar
• Rowlingson, B., R. Bivand, and T. Keitt. 2019. “Rgdal: Bindings for the ‘Geospatial’ Data Abstraction Library.” R package version 1.4-8. http://rgdal.r-forge.r-project.org
   Google Scholar
• Simensen, T., L. Erikstad, and R. Halvorsen. 2021. “Diversity and Distribution of Landscape Types in Norway.” Norsk Geografisk Tidsskrift–Norwegian Journal of Geography 75 (2): 79–100. doi:https://doi.org/10.1080/00291951.2021.1892177.
   Web of Science ®Google Scholar
• Simensen, T., P. Horvath, L. Erikstad, A. Bryn, J. Vollering, and R. Halvorsen. 2020. “Composite Landscape Predictors Improve Distribution Models of Ecosystem Types.” Diversity and Distributions 26: 928–943. doi:https://doi.org/10.1111/ddi.13060.
   Web of Science ®Google Scholar
• Sofaer, H. R., C. S. Jarnevich, I. S. Pearse, R. L. Smyth, G. L. Stephanie Auer, T. C. Cook, E. Jr, et al. 2019. “Development and Delivery of Species Distribution Models to Inform Decision-Making.” Bioscience 69 (7): 544–557. doi:https://doi.org/10.1093/biosci/biz045.
   Web of Science ®Google Scholar
• Strand, G.-H. 2013. “The Norwegian Area Frame Survey of Land Cover and Outfield Land Resources.” Norsk Geografisk Tidsskrift–Norwegian Journal of Geography 67 (1): 24–35. doi:https://doi.org/10.1080/00291951.2012.760001.
   Web of Science ®Google Scholar
• Tang, G., S. L. Shafer, P. J. Bartlein, and J. O. Holman. 2009. “Effects of Experimental Protocol on Global Vegetation Model Accuracy: A Comparison of Simulated and Observed Vegetation Patterns for Asia.” Ecological Modelling 220 (12): 1481–1491. doi:https://doi.org/10.1016/j.ecolmodel.2009.03.021.
   Web of Science ®Google Scholar
• Ullerud, H. A., A. Bryn, K. Klanderud, and J. Paruelo. 2016. “Distribution Modelling of Vegetation Types in the Boreal–alpine Ecotone.” Applied Vegetation Science 19 (3): 528–540. doi:https://doi.org/10.1111/avsc.12236.
   Web of Science ®Google Scholar
• Van Vliet, J., A. Hagen-Zanker, J. Hurkens, and H. Van Delden. 2013. “A Fuzzy Set Approach to Assess the Predictive Accuracy of Land Use Simulations.” Ecological Modelling 261–262: 32–42. doi:https://doi.org/10.1016/j.ecolmodel.2013.03.019.
   Web of Science ®Google Scholar
• Van Vliet, J., A. K. Bregt, and A. Hagen-Zanker. 2011. “Revisiting Kappa to Account for Change in the Accuracy Assessment of Land-Use Change Models.” Ecological Modelling 222 (8): 1367–1375. doi:https://doi.org/10.1016/j.ecolmodel.2011.01.017.
   Web of Science ®Google Scholar
• Wickham, H. 2016. Ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag. https://ggplot2.tidyverse.org
   Google Scholar
• Wickham, J., S. V. Stehman, J. A. Leila Gass, D. G. Dewitz, B. J. Sorenson, R. V. P. Granneman, and L. A. Baer. 2017. “Thematic Accuracy Assessment of the 2011 National Land Cover Database (NLCD).” Remote Sensing of Environment 191: 328–341. doi:https://doi.org/10.1016/j.rse.2016.12.026.
   PubMed Web of Science ®Google Scholar
• Yoshioka, P. M. 2008. “Misidentification of the Bray-Curtis Similarity Index.” Marine Ecology Progress Series 368: 309–310. doi:https://doi.org/10.3354/meps07728.
   Web of Science ®Google Scholar
• Zhang, H., A. Eziz, J. Xiao, S. L. Tao, S. P. Wang, Z. Y. Tang, J. L. Zhu, and J. Y. Fang. 2019. “High-Resolution Vegetation Mapping Using eXtreme Gradient Boosting Based on Extensive Features”. Remote Sensing 11(12). Article 1505. doi:https://doi.org/10.3390/rs11121505.
   Google Scholar