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Abstract
Trait-based frameworks are promising tools to understand the functional consequences of community shifts in response to environmental change. The applicability of these tools to soil microbes is limited by a lack of functional trait data and a focus on categorical traits. To address this gap for an important group of soil microorganisms, we identify trade-offs underlying a fungal economics spectrum based on a large trait collection in 28 saprobic fungal isolates, derived from a common grassland soil and grown in culture plates. In this dataset, ecologically relevant trait variation is best captured by a three-dimensional fungal economics space. The primary explanatory axis represents a dense-fast continuum, resembling dominant life-history trade-offs in other taxa. A second significant axis reflects mycelial flexibility, and a third one carbon acquisition traits. All three axes correlate with traits involved in soil carbon cycling. Since stress tolerance and fundamental niche gradients are primarily related to the dense-fast continuum, traits of the 2nd (carbon-use efficiency) and especially the 3rd (decomposition) orthogonal axes are independent of tested environmental stressors. These findings suggest a fungal economics space which can now be tested at broader scales.
Challenges in obtaining empirical trait data hinder the development of trait-based frameworks for soil microbes. Here, the authors analyse traits of saprobic fungal isolates from a grassland site to propose a fungal economics spectrum, suggesting a general trait framework for soil fungi.
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1 Freie Universität Berlin, Institute of Biology, Berlin, Germany (GRID:grid.14095.39) (ISNI:0000 0000 9116 4836); Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany (GRID:grid.452299.1)
2 Western Sydney University, Hawkesbury Institute for the Environment, Penrith, Australia (GRID:grid.1029.a) (ISNI:0000 0000 9939 5719); University of Jyväskylä, P.O. Box 35, Department of Biological and Environmental Science, Jyväskylä, Finland (GRID:grid.9681.6) (ISNI:0000 0001 1013 7965)
3 Helmholtz Zentrum München, Research Unit Comparative Microbiome Analysis, Neuherberg, Germany (GRID:grid.4567.0) (ISNI:0000 0004 0483 2525)
4 Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany (GRID:grid.433014.1)
5 University of Hohenheim, Institute of Soil Science and Land Evaluation, Soil Biology department, Stuttgart, Germany (GRID:grid.9464.f) (ISNI:0000 0001 2290 1502)
6 Western Sydney University, Hawkesbury Institute for the Environment, Penrith, Australia (GRID:grid.1029.a) (ISNI:0000 0000 9939 5719)
7 Sun Yat-sen University, State Key Laboratory of Biocontrol, School of Ecology, Shenzhen, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X)
8 Peking University Shenzhen Institute, Marine Institute for Bioresources and Environment, Shenzhen, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319)