Ecological Modelling 170 (2003) 333–343 Estimating plant species occurrence in MTB/64 quadrants as a function of DEM-based variables—a case study for Medvednica Nature Park, Croatia Sven D. Jelaska a,∗ , Oleg Antoni´ c b , Toni Nikoli´ c c , Vladimir Hršak c , Miško Plazibat c , Josip Križan a a Oikon Ltd., Vlade Prekrata 20, HR-10000 Zagreb, Croatia b Ru - der Boškovi´ c Institute, Bijeniˇ cka c. 54, HR-10000 Zagreb, Croatia c Department of Botany, Faculty of Science, Maruli´ cev trg 20, HR-10000 Zagreb, Croatia Abstract Croatia is among those European countries without an Atlas of Flora produced till today as a result of constant lack of greater number of active botanists and inconsistency in gathering data in the field. Recently, a standard for collection of data, based on the Central European MTB (abbreviation of German term “Meßtischblätter” that stands for a sheet of topographic map) grid was proposed and tested in the field on the “Medvednica Nature Park” on Medvednica mountain near the city of Zagreb. Using the data collected in 97 MTB/64 quadrants (presence/absence of plant species), we tested the potential of estimating species occurrence at the proposed grid by models in a function of the Digital Elevation Model (DEM)-based variables, namely altitude, terrain slope, terrain aspect, and flow accumulation potential. Because of significant spatial variability of environmental factors within MTB/64 quadrants, each one was represented by descriptive statistics (median, 5-, 25-, 75- and 95-percentiles) of DEM-based variables. Thirty-seven plant species were selected arbitrarily, on the basis of their frequency in the studied area (40–60% of all quadrants). Three methods for development of predictive model were used and compared: discriminant analyses, logistic regression, and classification trees. Yielded results suggest that spatial modelling could be probably applied in flora mapping, which would optimise fieldwork. However, decreasing of mapping unit area is recommended, especially for rare species. For larger areas, inclusion of other environmental predictors (macroclimatic, lithological, landuse) in models is probably needed. © 2003 Elsevier B.V. All rights reserved. Keywords: Flora mapping; GIS; Predictive models; CT; Logistic regression; Discriminant analyses 1. Introduction Croatia is a country with high biodiversity and tradition in flora and vegetation exploration (Visiani, 1842–1852; Schlosser and Vukotinovi´ c, 1869; Hirc, 1903–1912; Rossi, 1924; Hayek, 1927–1933; Degen, ∗ Corresponding author. Tel.: +385-1-6552-350; fax: +385-1-6552-385. E-mail address: sjelaska@oikon.hr (S.D. Jelaska). 1936–1938). According to number of plant species per square kilometre ratio, Croatia is at the third place in Europe in floristic richness, after Slovenia and Albania (Nikoli´ c, 2001). However, constant lack of greater number of active botanists and inconsistency in geocoding method of data gathered in the field resulted that Croatia is among those European coun- tries without an Atlas of Flora produced till today. Recently, a standard for collection of data, based on the Central European MTB (abbreviation of German 0304-3800/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0304-3800(03)00237-0