Simple attributes predict the value of plants as hosts to fungal and arthropod communities. Issue 4 (14th February 2022) - Bruun, Hans Henrik; Brunbjerg, Ane Kirstine; Dalby, Lars; Fløjgaard, Camilla; Frøslev, Tobias G.; Haarder, Simon; Heilmann‐Clausen, Jacob; Høye, Toke T.; Læssøe, Thomas; Ejrnæs, Rasmus
Abstract : Fungal and arthropod consumers constitute the vast majority of global terrestrial biodiversity. Yet, the link from richness and composition of producer (plant) communities to the richness of consumer communities is poorly understood. Fungal and arthropod species richness could be a simple function of producer species richness at a site. Alternatively, it could be a complex function of chemical and structural properties of the producer species making up communities. We used databases on plant–fungus and plant–arthropod trophic links to derive the richness of consumer biota per associated plant species (coined link score). We assessed how well link scores could be predicted by simple attributes of plant species. Next, we used a multi‐taxon inventory of 130 sites, representing all major habitat types in a country (Denmark), to investigate whether link scores summed over plant species in communities (coined link sum) could outperform simple plant species richness as predictor of fungal and arthropod richness at the sites. We found plant species' link scores for both fungi and arthropods to be positively related to plant size, regional occupancy, nativeness and ectomycorrhizal status. Link‐based indices generally improved the prediction of richness of fungal and arthropod communities. For fungal communities, both observed link sum (from databases) and predicted link sum (from plant attributes) had high predictive power, while plant richness alone had none. For arthropod communities, predictive performance varied between functional groups. For both fungi and arthropods, richness predictions were further improved by considering abiotic habitat conditions. Our results underline the importance of plants as niche space for the megadiverse groups of arthropods and fungi. The plant–attribute approach holds promise for predicting local and regional consumer richness in areas of the world lacking detailed plant–consumer databases.