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Additional file 6: Figure S5. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on environmental data.

Additional file 4: Figure S4. The relative contributions of the explanatory variables in the data set of (a) host only, (b) environment only based on the mean ensemble model.

Additional file 7: Figure S6. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on host data.

Additional file 5: Table S1. The number of times each model contributed to the final ensemble in different data sets.

Additional file 3: Figure S3. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. persulcatus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.

Additional file 8: Figure S7. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus based on combined host and environmental data, and habitat suitability data for the other tick species.

Additional file 2: Figure S2. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. ricinus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.

Additional file 1: Figure S1. (a) The sampling strategy for new collections in 2021 was created based on the following criteria. Subdivisions of landscape areas (Area1–Area4), CORINE land cover 2018, a 5-km buffer around existing I. persulcatus occurrences (grey circles), and a 500-m buffer around roads were used to delimit the four sampling areas (light grey lines). For each sampling area, a random sample of 25 collection locations was created depending on the relative shares of forest and meadow categories in each area. (b) The map showing the 2021 results indicates the locations where I. ricinus was found with B. burgdorferi (s.l.)-positive locations.

Additional file 1: Text S1. Additional laboratory protocols. Table S1. Primers and probes used in tick-borne pathogen screening and sequencing. Table S2. Mastermix contents for qPCR analyses of tick-borne pathogens.: Text S1. Additional laboratory protocols. Table S1. Primers and probes used in tick-borne pathogen screening and sequencing. Table S2. Mastermix contents for qPCR analyses of tick-borne pathogens.

Additional file 5: Table S6. Comparative analysis of Borrelia flagellin sequences from I. persulcatus adults from the Bothnian Bay coast (samples labeled BothnianB), I. ricinus nymphs from Helsinki (Helsinki) and reference sequences downloaded from GenBank (with accession numbers). Numbers in brackets signify the count of unique, identical sequences. Geneious version 2020.0 created by Biomatters. Available from https://www.geneious.com .

Additional file 4: Table S5. Data on pathogen infections summarised per area and stage (adults vs nymphs).

A national crowdsourcing-based tick collection campaign was organized in 2015 with the objective of producing novel data on tick distribution and tick-borne pathogens in Finland. Nearly 20 000 Ixodes ticks were collected. The collected material revealed the nationwide distribution of I. persulcatus for the first time and a shift northwards in the distribution of I. ricinus in Finland. A subset of 2038 tick samples containing both species was screened for Borrelia burgdorferi sensu lato (the prevalence was 14.2% for I. ricinus and 19.8% for I. persulcatus), B. miyamotoi (0.2% and 0.4%, respectively) and tick-borne encephalitis virus (TBEV; 0.2% and 3.0%, respectively). We also report new risk areas for TBEV in Finland and, for the first time, the presence of B. miyamotoi in ticks from mainland Finland. Most importantly, our study demonstrates the overwhelming power of citizen science in accomplishing a collection effort that would have been impossible with the scientific community alone.