AbstractAimFunctional traits offer a window into how organisms are adapted, and might acclimate, to environmental pressures. Despite being important in ecosystem function, lichens are underrepresented in trait‐based research; understanding how lichen functional traits vary with climate and habitat availability will be useful in predicting how communities will respond to climate change, for example, in wetter and warmer boreal and arctic ecosystems. Here, we assess the influence of macroclimate and forest availability on the spatial distribution of lichen traits across Norway.LocationNorwegian mainland.TaxonLichens.MethodsWe used relative trait frequency (RTF) data from LIAS gtm, a database combining trait information from LIAS (A Global Information System for Lichenized and Non‐Lichenized Ascomycetes) and GBIF (Global Biodiversity Information Facility) species observations. The 20 traits included photobiont types, growth forms, cortical features and reproductive modes. Nonparametric multiplicative regression (NPMR) models were used to explore the relationships between the environmental predictors of precipitation, temperature and forest availability.ResultsAll traits showed significant relationships with the three environmental predictors. Photobiont type and reproductive mode traits produced the strongest models and revealed ecologically meaningful biogeographical patterns. Trebouxioid species peaked in colder, drier upland regions, while trentepohlioid lichens displayed an affinity for wetter and warmer climates and had a western and southern distribution. Cyanolichens increased with increasing precipitation and were strongly coastal. Sorediate and isidiate lichens were positively related to temperature, the former also increasing with forest cover. The above responses were consistent with the physiological and habitat requirements of the associated lichens. The remaining traits had weaker responses.Main conclusionsDiscrete traits (i.e. photobiont type and reproductive mode) with relatively low ecological plasticity reflect clear functional environmental responses at the large scale. By contrast, growth form and thallus structural features—proxies for continuous variables—are too variable within each given category to show observable distribution patterns.