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Table 2 Posterior mean, standard deviation, 2.5% and 97.5% quartiles for the binomial models of tick presence–absence with the data from public submissions (Dataset 2) and the combined dataset (Dataset 3)

From: Using imperfect data in predictive mapping of vectors: a regional example of Ixodes ricinus distribution

ModelFixed effectsMeanSD2.5% quartile97.5% quartile
Model 2: Presence–absence model with presence points from public submissions plus absence pointsIntercept− 6.26571.0232− 8.3326− 4.3135
NDVI Augusta0.13730.01760.10400.1732
No. days of air frost November− 0.17290.05210.2784− 0.0738
Rain April− 0.01480.0053− 0.0255− 0.0045
% cover of coniferous woodland5.19891.20153.09217.8095
% cover of moorland2.21800.56561.14993.3725
Interaction between latitude and longitude0.00530.0036− 0.00170.0123
Model 3: Presence–absence model with composite datasetIntercept− 3.47000.4771− 4.4160− 2.5424
NDVI August0.00050.00010.00040.0006
Deer density0.03360.01000.01390.0533
No. days of air frost November− 0.05270.0207− 0.0936− 0.0122
Rain April− 0.01230.0020− 0.0163− 0.0085
% cover of moorland1.39200.16401.07261.7161
% cover of deciduous woodland3.17620.67571.92034.5770
% cover of coniferous woodland2.18610.21281.77532.6100
Interaction between latitude and longitude− 0.00290.0013− 0.0054− 0.0004
  1. aThe posterior mean of NDVI was divided by 100
  2. Abbreviation: SD, standard deviation