The problem
A trait is an attribute influencing an organism’s performance within its environment, encompassing morphological, genetic and physiological characteristics measured at the individual or population levels (Salguero-Gómez et al. , 2018; Zhang et al. , 2023a). Understanding the ecology of species using a trait-based approach can contribute to a mechanistic explanation of processes mediated by microbes, including those that affect ecosystem functioning (Romero-Olivares et al. , 2021). This approach holds particular significance for arbuscular mycorrhizal (AM) fungi - Phylum Glomeromycota. As obligate symbionts of plants, where multiple species colonize both roots and soils in a network, predicting the functional outcomes (e.g., host growth, plant community diversity, soil characteristics) of individual AM fungal genotypes and communities within ecosystems remains challenging, despite major developments in molecular methods in the last two decades (Tisserant et al. , 2013; Montoliu-Nerin et al. , 2021). Indeed, establishing connections between AM fungal taxa and/or genotypes (e.g., within species) and their functional roles is a laborious process, which is expected to continue in the foreseeable future (Serghi et al. , 2021; Manley et al. , 2023). This is needed due to the complex links between AM fungi and functional outcomes for both hosts (e.g. , plant growth and fitness, nutrient uptake and stress tolerance) and soil functions/properties (e.g. , carbon storage, aggregate stability, biotic diversity), which appear to be highly context dependent and relatively poorly predicted by taxonomy alone (Munkvold et al. , 2004; Koch et al. , 2017; Yang et al. , 2017; Qiu et al. , 2021). However, this effort is also required because AM fungal traits have not been systematically assessed alongside with hypotheses of adaptation or with specific mechanisms in mind. For example, small-spored AM fungi may be dispersed longer distances by wind than large-spored AM fungi. It is then a reasonable hypothesis that small spore size is an adaptation for wind dispersal. One could empirically observe that small-spored AM fungi are geographically more widespread than large-spored fungi and this potential result could be viewed as evidence in support of this hypothesis. However, this finding would not necessarily prove that such dispersal difference has “functional” or “adaptive” value. Alternatively, producing small spores is a correlated response to producing many spores quickly, which itself could be an adaptive response to the likelihood of unpredictable soil disturbance such as from tillage. In this scenario, the adaptation and/or function is the production of many spores quickly to confer resistance to disturbance and then, after soil disturbance with wind erosion, small spores may also be blown farther (which may or may not improve fitness). Another example, variation in rooting depth among plants in a community may contribute to resource partitioning. But the mechanism (differential resource depletion with depth) still needs to be demonstrated separately from the trait evidence. AM fungi could contribute to equalize resource partitioning if plants with short roots associate with AM fungi that form more extensive extra-radical mycelium and vice-versa. Given these complexities, we consider the development of a robust, universally applicable trait-based framework for predicting key AM fungal functional outcomes a priority. To achieve this objective, first we must identify AM fungal traits that can be measured at morphological, physiological, and genetic levels. Second, considering the important roles of AM fungi in ecosystems, affecting host plants, soil, and the AM fungi themselves, we need to discern/hypothesize how measuring AM fungal traits impacts each of these components. For the host plant, it is crucial to consider nutrition, biomass, fitness, and survival in face of pathogens, heavy metals, salinity, drought, etc. (Delavaux et al. , 2017; Wehneret al. ). Within the soil environment, AM fungal effects on soil structure (Rillig & Mummey, 2006), nutrient cycling, carbon storage, and other members of the soil food-web are paramount (Antunes & Koyama, 2016; Frew et al. , 2021; Horsch et al. , 2023a). Regarding the fungal organism, we should focus on key aspects of their life-history strategies; reproduction and fitness, survival, dispersal, competitive ability, infectivity and abundance both within the host and soil environments (Aguilar-Trigueros et al. , 2019; Chaudharyet al. , 2020; Deveautour et al. , 2020). This requires identifying relevant proxies (sometimes termed “soft traits” in the plant ecophysiology literature) to provide easy-to-measure quantitative metrics for such complex facets of fungal life-history that can be measured across several species. Third, we need to evaluate existing standardized methods and experimental designs, or develop new ones, to measure such relevant (soft) traits, as has been done in plant ecophysiology (Pérez-Harguindeguy et al. , 2013). Measurement standardization and relevant metadata for hypothesis-driven analysis and interpretation is essential if we are to aggregate trait information from different studies into a public database, facilitating their incorporation into earth system models (e.g., (Fry et al. , 2019) and enhancing the predictability of functional processes and/or adaptations associated with AM fungi. Analogous libraries on plant traits (Kattge et al. , 2020) have proved useful to better understand trait variation along global climatic gradients (Butleret al. , 2017). Here, we aim to:
  1. To comprehensively catalog and define AM fungal functional traits (morphological, physiological/phenological, and genetic) while avoiding redundancy.
  2. To elucidate the relationships between these traits and their functional outcomes for host plants, soil environments, and the AM fungi themselves.
  3. To critically review the historical methods and experimental designs employed in measuring AM fungal traits, highlighting their strengths and limitations.
  4. To propose standardized methodologies and protocols for measuring AM fungal traits.
  5. To explore the integration of AM fungal trait information into ecological models to enhance ecosystem processes’ predictability.