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Table 1 Overview of environmental variables used in the study and their spatial and temporal resolution

From: Assessing tick attachments to humans with citizen science data: spatio-temporal mapping in Switzerland from 2015 to 2021 using spatialMaxent

Variable name

Native spatial resolution

Temporal resolution

Data source/reference

Additional description

Digital height model

25 m

Static

Swisstopo; https://www.swisstopo.admin.ch/en/height-model-dhm25

 

Annual snow cover

1 km

Annual

EOC Geoservice; https://geoservice.dlr.de/web/

 

Swiss population data

NA

Annual

Swiss Federal Statistical Office (Bundesamt für Statistik der Schweiz; https://www.bfs.admin.ch)

Data on population count and density. Values in areas where no people reside were assigned a value of 0

Enhanced vegetation index (EVI)

30 m

Seasonal and annual

Swiss Data Cube https://www.swissdatacube.org/; 2010–2019: https://doiorg.publicaciones.saludcastillayleon.es/10/gqw3gn; 2020–2021: https://doiorg.publicaciones.saludcastillayleon.es/10/gqwwtk

Analysis-ready earth observation data for Switzerland. Seasonal median (spring, summer, autumn, and winter) or annual data

Leaf area index (LAI; Boegh et al. [53])

30 m

Seasonal and annual

Swiss Data Cube https://www.swissdatacube.org/; 2010–2019: https://doiorg.publicaciones.saludcastillayleon.es/10/gqw3gj; 2020–2021: https://doiorg.publicaciones.saludcastillayleon.es/10/gqwwtg

Analysis-ready earth observation data for Switzerland. Seasonal median (spring, summer, autumn, and winter) or annual data

Green chlorophyll index (GCI; Gitelson et al. [54])

30 m

Seasonal and annual

Swiss Data Cube https://www.swissdatacube.org/; 2010–2019: https://doiorg.publicaciones.saludcastillayleon.es/10/gqxdkd; 2020–2021: https://doiorg.publicaciones.saludcastillayleon.es/10/gqwwtf

Analysis-ready earth observation data for Switzerland. Seasonal median (spring, summer, autumn, and winter) or annual data

Worldwide population data

1 km

Annual

CIESIN [85]; https://doiorg.publicaciones.saludcastillayleon.es/10.7927/H49C6VHW

Gridded population of the world

Human footprint

1 km

Annual

Mu et al. [86]; https://doiorg.publicaciones.saludcastillayleon.es/10.6084/m9.figshare.16571064

Annual terrestrial human footprint data

Global travel time to cities

1 km

2015

Nelson et al. [87]; https://doiorg.publicaciones.saludcastillayleon.es/10.6084/m9.figshare.7638134.v3

Global accessibility indicators for travel time to cities. Pixel values indicating travel time in minutes from each pixel to the nearest settlement across different settlement classes (e.g., \(\ge\)5000 and <10,000 people)

Monthly precipitation (RhiresM)

1 km

Monthly

MeteoSwiss; https://www.meteoschweiz.admin.ch; data are not publicly accessible

 

Monthly relative sunshine duration (SrelM)

1 km

Monthly

MeteoSwiss; https://www.meteoschweiz.admin.ch; data are not publicly accessible

 

Monthly mean temperature (TabsM)

1 km

Monthly

MeteoSwiss; https://www.meteoschweiz.admin.ch; data are not publicly accessible

 

CORINE land-cover

NA

2018

European Environment Agency (EEA), 2018 [88]

44 Distinct land-cover classes for Europe as polygon data

Swiss land-cover

NA

2018

Swiss Federal Statistics Office; www.bfs.admin.ch

Contains 72 land-cover classes

Swiss forest composition

10 m

2018

Swiss federal authorities; http://data.geo.admin.ch/ch.bafu.landesforstinventar-waldmischungsgrad/Waldmischungsgrad_2018_10m_2056.tif

Proportion of deciduous trees within the forested areas

Global forest fraction

1 km

Annual

Winkler et al. [89]; https://doiorg.publicaciones.saludcastillayleon.es/10.1594/PANGAEA.921846

 

Global cropland data

1 km

Annual

Cao et al. [90]

Proportion of cropland by year

Roe deer data

1 km

2014

Alexander et al. [55]; https://doiorg.publicaciones.saludcastillayleon.es/10.6084/m9.figshare.1008335.v1

Distribution of roe deer in Europe

  1. These variables are input into the variable selection algorithm but are not necessarily all part of the final model (see Section "Modeling approach"). Globally available datasets were accessed via download links provided at https://github.com/OpenGeoHub/spatial-prediction-eml/blob/master/input/mood_layers1km.csv