Climate and tree seed production predict the abundance of the European Lyme disease vector over a 15-year period

Parasites & Vectors

Table 1 Model selection results for the linear models of the log₁₀-transformed cumulative nymphal density

Rank	Model structure	df	logLik	AIC	ΔAIC	Weight1	Weight2	r²
1	log₁₀(CND) ~ S+Y+B+RH2	7	33.0	− 48.7	0.0	76.0	76.0	73.2
2	log₁₀(CND) ~ S+Y+B+RH2+S:Y	9	33.6	− 43.6	5.2	6.0	82.0	72.4
3	log₁₀(CND) ~ S+Y+B+SD2	7	30.4	− 43.5	5.3	5.0	87.0	69.7
4	log₁₀(CND) ~ S+Y+B+T2	7	30.4	− 43.4	5.3	5.0	92.0	69.6
5	log₁₀(CND) ~ S+Y+B+RH2_y-1	7	29.4	− 41.4	7.3	2.0	94.0	68.1
6	log₁₀(CND) ~ S+Y+B+SD2_y-1	7	29.1	− 40.8	7.9	1.0	95.0	67.7

Notes: Model selection results are shown for the linear models with normal errors of the log₁₀-transformed CND response variable. The explanatory variables were elevation site, year, beech masting 2 years prior, and the climate variables from the field and the Climap-net database. The models are ranked according to their Akaike Information Criterion (AIC). Of the 52 models in the set, only the 6 top models are shown for which the cumulative support (Weight 2) is 95%. Shown for each model are the model rank (Rank), model structure (see below for explanation of variable acronyms), model degrees of freedom (Df), log-likelihood (logLik), Akaike information criterion (AIC), difference in the AIC value from the top model (ΔAIC), model weight (Weight1), cumulative model weight (Weight2), and adjusted r-squared value (r²). Additional file 1: Section 6 shows the results from the full model selection. The acronyms for the explanatory variables are as follows: S, site; Y, year; B, beech mast score 2 years prior; S:Y, interaction between site and year; RH2, mean annual relative humidity from the field data in the same year; SD2, mean annual saturation deficit from the field data in the same year; T2, mean annual temperature from the field data in the same year; RH2_y-1, mean annual relative humidity from the field data in the previous year (y-1); SD2_y-1, mean annual saturation deficit from the field data in the previous year (y-1)

ISSN: 1756-3305