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        <gco:CharacterString>The database compiled for the Braun-Blanquet project is a compilation of various national and regional vegetation databases. The maintenance of these databases is in principle in the hands of the custodians. However, before uploading the databases into Braun-Blanquet database a quality check is performed by Alterra and Masaryk University. If possible, detected errors are corrected and reported back to the data provider. For the modelling of the habitat suitability map the Maxent software is used (http://www.cs.princeton.edu/~schapire/maxent/). The grid values in the map represent the probability (ranging from 0-1) that the cell is suitable for the habitat.
The grid file represents the habitat suitability of the EUNIS type. For the modelling the widely used software Maxent for maximum entropy modelling of species’ geographic distributions was used. Maxent is a general-purpose machine-learning method with a simple and precise mathematical formulation, and has a number of aspects that make it well-suited for species distribution modelling when only presence (occurrence) data but not absence data are available (Philips et al. 2006). Because EUNIS habitats have a particular species composition, they are assumed to respond to specific ecological requirements, allowing us to generate correlative estimates of geographic distributions. Modelling habitats that have been floristically defined is a well-known procedure for ecological modelling at local scales, and a promising technique to be applied also at the continental level. 
                The Maxent method considers presence data (known observations of a given entity) and the so-called background data. Background data comprise a set of points used to describe the environmental variation of the study area according to the available environmental layers. It is assumed that these layers represent well the most important ecological gradients on a European scale. As layers the following environmental parameters have been used: Potential Evapotranspiration, Topsoil pH, Solar radiation, Temperature Seasonality (standard deviation *100), Mean Temperature of Wettest Quarter, Annual Precipitation, Precipitation Seasonality (Coefficient of Variation), Precipitation of Warmest Quarter &amp; Distance to water (rivers, lakes, sea).
Statistical output of the model:
#Training samples: 1070
Regularized training gain: 1.3458
Unregularized training gain: 1.4095
Iterations: 500
Training AUC: 0.901
#Test samples: 118
Test gain: 1.2721
Test AUC: 0.8861
AUC Standard Deviation: 0.0075
#Background points: 6070
bio_12_etrs2_ras contribution: 33.5265
bio_15_etrs2_ras contribution: 0.1903
bio_18_etrs2_ras contribution: 9.6382
bio_4_etrs2_ras contribution: 1.0636
bio_8_etrs2_ras contribution: 0.5933
bld_m_sd1_1km_eu_ll contribution: 2.8496
cecsum_m_sd1_1km_eu_ll contribution: 0.6751
clyppt_m_sd1_1km_eu_ll contribution: 1.2887
crfvol_m_sd1_1km_eu_ll contribution: 18.1061
dist2water1km contribution: 0
orcdrc_m_sd1_1km_eu_ll contribution: 11.4909
pet_he_yr contribution: 3.6068
phihox_m_sd1_1km_eu_ll contribution: 0.1302
sltppt_m_sd1_1km_eu_ll contribution: 1.8458
sndppt_m_sd1_1km_eu_ll contribution: 0.6931
solar_1km contribution: 14.3018
bio_12_etrs2_ras permutation importance: 1.0794
bio_15_etrs2_ras permutation importance: 0.6918
bio_18_etrs2_ras permutation importance: 7.8141
bio_4_etrs2_ras permutation importance: 6.4946
bio_8_etrs2_ras permutation importance: 0.9379
bld_m_sd1_1km_eu_ll permutation importance: 0.5402
cecsum_m_sd1_1km_eu_ll permutation importance: 4.6098
clyppt_m_sd1_1km_eu_ll permutation importance: 5.4915
crfvol_m_sd1_1km_eu_ll permutation importance: 56.308
dist2water1km permutation importance: 0
orcdrc_m_sd1_1km_eu_ll permutation importance: 2.8099
pet_he_yr permutation importance: 10.1387
phihox_m_sd1_1km_eu_ll permutation importance: 0.3418
sltppt_m_sd1_1km_eu_ll permutation importance: 0.5011
sndppt_m_sd1_1km_eu_ll permutation importance: 1.1682
solar_1km permutation importance: 1.0731
Entropy: 7.3657
Prevalence (average of logistic output over background sites): 0.1264
Fixed cumulative value 1 cumulative threshold: 1
Fixed cumulative value 1 logistic threshold: 0.0349
Fixed cumulative value 1 area: 0.3572
Fixed cumulative value 1 training omission: 0.0047
Fixed cumulative value 1 test omission: 0.0169
Fixed cumulative value 1 binomial probability: 5.36E-46
Fixed cumulative value 5 cumulative threshold: 5
Fixed cumulative value 5 logistic threshold: 0.1584
Fixed cumulative value 5 area: 0.2453
Fixed cumulative value 5 training omission: 0.0234
Fixed cumulative value 5 test omission: 0.0593
Fixed cumulative value 5 binomial probability: 0.00E+00
Fixed cumulative value 10 cumulative threshold: 10
Fixed cumulative value 10 logistic threshold: 0.2848
Fixed cumulative value 10 area: 0.199
Fixed cumulative value 10 training omission: 0.0561
Fixed cumulative value 10 test omission: 0.0932
Fixed cumulative value 10 binomial probability: 0.00E+00
Minimum training presence cumulative threshold: 0.1003
Minimum training presence logistic threshold: 0.002
Minimum training presence area: 0.6049
Minimum training presence training omission: 0
Minimum training presence test omission: 0
Minimum training presence binomial probability: 8.29E-19
10 percentile training presence cumulative threshold: 13.5366
10 percentile training presence logistic threshold: 0.3562
10 percentile training presence area: 0.1797
10 percentile training presence training omission: 0.1
10 percentile training presence test omission: 0.1441
10 percentile training presence binomial probability: 0.00E+00
Equal training sensitivity and specificity cumulative threshold: 18.1358
Equal training sensitivity and specificity logistic threshold: 0.435
Equal training sensitivity and specificity area: 0.1616
Equal training sensitivity and specificity training omission: 0.1617
Equal training sensitivity and specificity test omission: 0.2119
Equal training sensitivity and specificity binomial probability: 0.00E+00
Maximum training sensitivity plus specificity cumulative threshold: 8.2314
Maximum training sensitivity plus specificity logistic threshold: 0.2444
Maximum training sensitivity plus specificity area: 0.2117
Maximum training sensitivity plus specificity training omission: 0.0411
Maximum training sensitivity plus specificity test omission: 0.0847
Maximum training sensitivity plus specificity binomial probability: 0.00E+00
Equal test sensitivity and specificity cumulative threshold: 14.1477
Equal test sensitivity and specificity logistic threshold: 0.3691
Equal test sensitivity and specificity area: 0.1769
Equal test sensitivity and specificity training omission: 0.1075
Equal test sensitivity and specificity test omission: 0.178
Equal test sensitivity and specificity binomial probability: 0.00E+00
Maximum test sensitivity plus specificity cumulative threshold: 6.807
Maximum test sensitivity plus specificity logistic threshold: 0.2098
Maximum test sensitivity plus specificity area: 0.2242
Maximum test sensitivity plus specificity training omission: 0.0299
Maximum test sensitivity plus specificity test omission: 0.0593
Maximum test sensitivity plus specificity binomial probability: 0.00E+00
Balance training omission, predicted area and threshold value cumulative threshold: 1.5235
Balance training omission, predicted area and threshold value logistic threshold: 0.0551
Balance training omission, predicted area and threshold value area: 0.3278
Balance training omission, predicted area and threshold value training omission: 0.0056
Balance training omission, predicted area and threshold value test omission: 0.0254
Balance training omission, predicted area and threshold value binomial probability: 6.14E-51
Equate entropy of thresholded and original distributions cumulative threshold: 4.0404
Equate entropy of thresholded and original distributions logistic threshold: 0.1289
Equate entropy of thresholded and original distributions area: 0.2603
Equate entropy of thresholded and original distributions training omission: 0.0187
Equate entropy of thresholded and original distributions test omission: 0.0508
Equate entropy of thresholded and original distributions binomial probability: 0.00E+00</gco:CharacterString>
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