Data: Ecological dimensions of the <i>fungal economics spectrum</i> in soil saprobic fungi

This data file contains functional trait data of saprobic fungi, published in the manuscript "<b>Ecological dimensions of the </b><b><i>fungal economics spectrum</i></b><b> in soil saprobic fungi</b>"<br>Abstract: Soil microbial community composition commonly shifts in response to environmental change, but the functional consequences remain unknown. To understand and predict them, trait-based frameworks are the most promising tool. Their applicability, though, is currently limited by a lack of functional trait data informing microbial life-history trade-offs, and a focus on categorical frameworks. To close this gap for an important group of soil microorganisms, we established a fungal economics spectrum in saprobic fungi based on an unprecedented trait collection for 28 isolates from a grassland soil. Ecologically relevant trait variation was best captured by a three-dimensional fungal economics spectrum: The primary explanatory axis represented a <i>dense-fast</i> continuum, resembling dominant life-history trade-offs in other organism groups. A second significant axis reflected mycelial flexibility, and a third one carbon acquisition traits. All three axes correlated with traits involved in soil processes, i.e., soil aggregation ability and melanin contents (1^st axis), carbon-use efficiency (2^nd) and litter decomposition (3^rd). Since stress tolerance and fundamental niche gradients were primarily related to the <i>dense-fast </i>continuum, carbon cycling traits of the 2^nd and especially 3^rd (orthogonal) axes were independent of environmental stressors, contradicting current theoretical life-history frameworks applied to soil. In conclusion, the use of novel fungal traits not only allowed to describe a fungal economics spectrum, which can be tested at broader scales. In an ecological context, trait correlations further revealed a novel mechanism of resilience in soil processes, while the rich trait collection used here highlighted the diversity and uniqueness of individual functional trait spaces.