Pedro Madeira Antunes

and 11 more

1Pedro M Antunes*, 2Sidney L. Stürmer*, 3James D. Bever, 4Pierre-Luc Chagnon, 5V. Bala Chaudhary, 10Coline Deveautour, 1Catherine Fahey, 6Vasilis Kokkoris, 7Ylva Lekberg, 8Jeff R. Powell, 9Carlos A. Aguilar-Trigueros, 8Haiyang Zhang1Biology Department, Algoma University, Sault Ste. Marie, Ontario, Canada, P6A 2G42Departamento de Ciências Naturais, Universidade Regional de Blumenau, Blumenau, SC, 89030-903, Brazil3Kansas Biological Survey and Center for Ecological Research and Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA4Institut de Recherche en Biologie Vegetale, Universite de Montreal, 4101 Sherbrooke Est, Montreal, QC, H1X2B2, Canada5Department of Environmental Studies, Dartmouth College, Hanover, New Hampshire, USA6Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Section Systems Ecology, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands7MPG Ranch & Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, Montana, USA8Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia9Institute of Biology, Freie Universität Berlin, Altensteinstrasse 6, 14195 Berlin, Germany.10 Institut Polytechnique UniLaSalle, Unité AGHYLE, Campus Rouen, 76130, Mont-Saint-Aignan, Normandie, France  *Equal contributionCorresponding: Pedro M. Antunes [pedro.antunes [at] algomau.ca] ORCID:Pedro M. Antunes: 0000-0003-3596-6983Sidney L. Stürmer: 0000-0003-3213-1841James D. Bever: 0000-0003-4068-3582Pierre-Luc Chagnon: 0000-0002-5054-5813Bala Chaudhary: 0000-0002-7232-1757Coline Deveautour: 0000-0001-6887-0414Catherine Fahey: 0000-0002-6987-0456Vasilis Kokkoris: 0000-0002-1667-0493Ylva Lekberg: 0000-0003-1033-8032 Jeff Powell: 0000-0003-1091-2452Carlos A. Aguilar-Trigueros: 0000-0003-0512-9500Haiyang Zhang 0000-0001-7951-0502AbstractArbuscular mycorrhizal (AM) fungi (phylum Glomeromycota) are obligate symbionts with plants influencing plant health, soil a(biotic) processes, and ecosystem functioning. Despite advancements in molecular techniques, understanding the role of AM fungal communities on a(biotic) processes based on AM fungal taxonomy remains challenging. This review advocates for a standardized trait-based framework to elucidate the life-history traits of AM fungi, focusing on their roles in three dimensions: host plants, soil, and AM fungal ecology. We define morphological, physiological, and genetic key traits, and propose methodologies for their consistent measurement, enabling cross-study comparisons towards improved predictability of ecological function.  We aim for this review to lay the groundwork for establishing a baseline of AM fungal trait responses under varying environmental conditions. Furthermore, we emphasize the need to include underrepresented taxa in research and utilize advances in machine learning and microphotography for data standardization.  Keywords: symbiosis; trait-based ecology; ecosystem processes; standardization; functional diversity; environmental adaptation. The problem: identifying and associating AM fungal traits with functional outcomes            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. 2023b). 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 fungi colonize both roots and soils in a network, predicting the functional outcomes (e.g., host growth, plant community diversity, changes in soil processes) 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 relationships between AM fungal taxa and/or genotypes (i.e., accounting for within species variability) 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; Corradi et al. 2024). However, it is important to go beyond taxonomy and morphological characteristics, incorporating physiological and genetic traits. This work is needed due to the complex associations that exist between AM fungi and various functional outcomes for hosts (e.g., plant growth and fitness, nutrient uptake and stress tolerance) and soil processes (e.g., carbon storage, aggregate stability, biotic diversity), all of which currently appear 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, which leads to the 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 (arguably more quickly if they are structurally simpler), which itself could be an adaptive response to the likelihood of unpredictable soil disturbance (e.g., caused by soil animals or 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). Measuring traits like spore size, spore production rates, and their ability to resist or respond to environmental disturbances can help to disentangle different hypotheses about how these traits contribute to AM fungal success and distribution.  Another example to illustrate the complexity of associating traits with function is the variation in rooting depth among plants in a community, which 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. As such, plants and fungal traits cannot be considered in isolation.  Given these complexities, we consider the development of a robust, universally applicable trait-based framework towards predicting key AM fungal functional outcomes a priority. To achieve this objective, first we must identify AM fungal traits that can be measured not only at morphological levels of organization but also at physiological, and genetic levels. Second, considering the important roles of AM fungi in ecosystems, affecting host plants, soil processes, 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 nutrient limitations, pathogens, heavy metals, salinity, drought, etc. (Delavaux et al. 2017; Wehner et al. 2010). Within the soil environment, AM fungal effects on soil structure (Rillig and Mummey 2006), nutrient cycling, carbon storage, and other members of the soil food-web are relevant (Antunes and Koyama 2016; Frew et al. 2021; Horsch et al. 2023a). Regarding the fungal organism itself, 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; Chaudhary et al. 2020; Deveautour et al. 2020). Connecting traits to functional outcomes 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. For example, small spore size and high spore production rates can serve as proxies for functional traits such as effective dispersal in face of disturbance. Hyphal growth rate and branching pattern can serve as proxies for resource foraging efficiency. Third, we need to evaluate existing standardized methods and experimental designs, or develop new ones, to measure such relevant (soft) traits, as it 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 eventually 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 (Butler et al. 2017). Here, we aim to:   To comprehensively catalog and define AM fungal functional traits (morphological, physiological/phenological, and genetic) while avoiding redundancy. To elucidate the relationships between these traits and their functional outcomes for host plants, soil environments, and the AM fungi themselves. To critically review the historical methods and experimental designs employed in measuring AM fungal traits, highlighting their strengths and limitations. To propose standardized methodologies and protocols for measuring AM fungal traits. To explore the integration of AM fungal trait information into ecological models to potentially enhance ecosystem processes’ predictability.  Historical perspective of trait-based approaches The scientific literature on the life-history traits of AM fungi (i.e., the biological characteristics and features that influence their growth, reproduction, and survival) has predominantly centered on aspects related to plant growth and nutrition, largely through an agronomic lens. Although not explicitly reported as such, early studies employing experimental approaches to assess, for example, AM fungal root colonization, abundance of external hyphae, and spore counts for specific species under certain experimental conditions have yielded insights into AM fungal trait variation (Abbott 1982; Reich 1988; Jakobsen et al. 1992a; Gazey et al. 1992; Bever et al. 1996). Given the wide variation observed, these and other seminal studies provided a foundation for further inquiry into the complex dynamics of AM fungal life-history traits and their broader implications to the AM symbiosis.Studies of distinct traits within a taxonomic framework started with the comparison of mycelium form and function, and root colonization strategies among major families of the Glomeromycota. For example, Dodd et al. (2000) compared the morphology and mycelial architecture of different AM fungal genera, discussing form and function. In a comparative study of 21 AM fungal isolates (i.e., defined as an AM fungus isolated in the laboratory into pure culture but without genetic characterization, at which point it becomes a certified strain with a collection number) spanning 16 species from North America, Hart and Reader (2002a) showed that the isolates of the Glomeraceae family, on average, colonized roots before those of Acaulosporaceae and Gigasporaceae families. Additionally, the proportion of fungal biomass in roots versus soil also diverged, on average, among isolates of those families. Those in the Glomeraceae exhibited high root colonization but low soil colonization, Gigasporaceae tended to have low root colonization but high soil colonization, and Acaulosporaceae displayed low colonization in both roots and soil. These findings revealed a strong association between AM fungal morphological characteristics and taxonomy for these fungi, as isolates from the main families could be differentiated based on colonization rate, biomass allocation, and the onset of sporulation. These observations were corroborated by subsequent studies, albeit using AM fungi from the same community and, possibly, the same isolates (Hart and Reader 2002a, 2005; Maherali and Klironomos 2007; Powell et al. 2009; Sikes et al. 2009). In fact, using the same data, Aguilar-Trigueros et al. (2019) showed that large-spore species produced, on average, fewer spores than small-spore species, suggesting that AM fungi experience similar resource allocation constraints during reproduction as plants seeds (Moles et al. 2005). However, to what extent plant trait-frameworks may be applicable to AM fungi is unknown. At present, evidence suggest differences between Glomeraceae and Gigasporaceae concerning life-history traits and their relationship with host benefits. However, new comparative studies that include more fungal species isolated from other ecological contexts are necessary to confirm these differences. More recently, a distinction between ‘edaphophilic’ and ‘rhizophilic’ life-history strategies has been introduced to categorize AM fungi that allocate more biomass to growth within roots versus soil (Weber et al. 2019), and data show that long-term P enrichment in subtropical forests shifts AM fungal communities toward edaphophilic guilds (Wang et al. 2023). The patterns described above demonstrate the utility of employing a comparative framework to test hypotheses concerning AM fungal function by examining trait expression. For instance, based on soil mycelium production, Gigasporaceae would be expected to outperform Glomeraceae in nutrient uptake (Maherali and Klironomos, 2007). Alternatively, if early or extensive root colonization (with abundant coils/arbuscules) is more important for nutrient delivery to the host, then Glomeraceae could be more beneficial partners under nutrient limiting conditions (e.g., (Horsch et al. 2023b). Despite inconsistencies among studies, which may to some extent be explained by variability in mycorrhizal dependency among hosts (Pringle and Bever 2008; Sikes et al. 2009), a meta-analysis (Yang et al. 2017) suggested that, on average, fungi of the familiy Glomeraceae were better at acquiring P and reducing pathogen growth compared to other AM fungal families. It is also of interest, that this family also appears to be the most abundant in many locations (Öpik et al. 2010). Despite these advances towards better consistency in predicting functional outcomes from morphological and taxonomy data, we argue that only a robust database integrating morphological, physiological, and genetic trait variation under different environmental conditions can establish a basis for more accurately predicting the functions of these fungi.Previous studies lacked a comprehensive environmental perspective. For instance, considering diverse environmental conditions, such as varying soil types or climatic factors, could unveil how AM fungal traits respond and adapt. Currently, most data reporting the impact of different AM fungi on their host originate from short-term experiments, using fungal taxa that readily sporulate and are easily amenable to pure cultures (Ohsowski et al. 2014). This may not reflect the reality in natural environments. Both the study by Sikes et al. (2009) investigating differences in plant pathogen protection between AM fungal taxa, as well as that of (Lerat et al. 2003) on C-sink strength among different AM fungal families suggest that certain functional outcomes resulting from the symbiosis depend on the combination of plant and fungal traits (Johnson et al. 1997). As such, considering fungal traits alone (i.e., in absence of plant and soil characteristics) may limit predictions of functional outcomes of the symbiosis (see Chaudhary et al. 2022). This brings an additional layer of complexity to the study of AM fungal ecophysiology and trait-based ecology, as intricate relationships between fungal and plant traits are to be expected (Chagnon et al. 2013).  Proposed trait-based frameworks for AM fungi Van Der Heijden and Scheublin (2007) conducted the first comprehensive review of AM fungal traits to predict plant growth and ecosystem functioning. The authors provided a list of 13 AM fungal functional traits, which they categorized into morphological traits (e.g., hyphal length, rate and extent of root colonization, spore production) and physiological traits (e.g., fungal carbon acquisition, host preference, nutrient uptake efficiency, exudation of compounds into the hyphosphere). Subsequently, Behm and Kiers (2014) noted substantial intraspecific trait variation among AM fungal species (also see Koch et al. 2017), complicating the characterization of traits and their incorporation into functional trait models. To address this issue, they proposed a five-part framework for characterizing intraspecific trait variation of AM fungal species within the context of nutrient cycling, based on experimental design and trait measurement considerations. According to Behm and Kiers (2014), AM fungal genetic units should be subjected to diverse environmental conditions (e.g., host plants, soil nutrient concentrations). Subsequent measurements would encompass the degree of variation, trait reversibility, relationships among traits, the adaptive nature of variation, and the potential for variation to evolve. Through these five dimensions, researchers could map traits onto an evolutionary tree and incorporate them into functional models for predicting nutrient cycling dynamics. Chaudhary et al. (2022) highlighted the challenges in defining traits for organismal networks such as fungi that establish mycorrhizal symbioses. They proposed a unified trait framework, complemented by a standardized vocabulary, with the objective of establishing a clear connection between trait-based mycorrhizal ecology, AM fungal niches and community assembly rules. The authors categorized traits into three main groups: morphological, physiological, and phenological. Within each of these categories, they pinpointed distinctive mycorrhizal traits specific to both the host plant (e.g., root:shoot ratio, growth form, photosynthetic pathways) and the fungal partner (e.g., spore size, hyphal length, and melanin content). Beyond these bifurcated traits by plant or fungal traits, Chaudhary et al. (2022) introduced the concept of mycorrhizal traits. These are unique attributes that emerge during symbiosis and are co-dependent on both partners. They encompass aspects such as root colonization-induced structures, plant mycorrhizal response, and resource exchange rates. This novel framework provides an enriched understanding of mycorrhizal ecology and serves as a basis for the empirical framework proposed here. Chagnon et al. (2013) put forth an AM fungal trait-based framework building on Grime's CSR (competitive, stress-tolerant, ruderal) framework - which identifies stress, disturbance and competition as the major filters driving trait selection and evolution in plant natural communities. By allowing speculative connections to be made regarding potential linkages between fungal traits (e.g., hyphal fusion, sporulation phenology, carbon sink strength, growth rates) and environmental filters (e.g., soil disturbances, scarce C transfer from host, low soil pH), this framework could tentatively identify priority traits for measurement, and combinations of host and fungal traits that may lead to the highest mutual benefits. Building on the apparent family-level conservatism of many traits or responses to environmental filters, parallels were drawn between AM fungal major families and C, S and R strategies. However, as stressed by Chagnon et al. (2013), this family-to-strategy association is simplistic and struggles to predict AM fungal responses in complex multi-stress scenarios (Heuck et al. 2024). In addition, it fails to consider several AM fungal families (e.g., Pacisporaceae, Entrophosporaceae, Diversisporaceae, or more basal lineages like Paraglomeraceae, Archaeosporaceae, and Ambisporaceae). It also fails to consider the relative distribution of different AM fungal families in certain biomes or at certain latitudes. For example, Acaulospora is a common genus in the tropics, where it can be dominant both in natural forests and under intensive land-use where ruderal traits are crucial (e.g., González-Cortés et al. 2012). The primary significance of the CSR framework in AM fungal trait-based ecology should not be considered merely as a framework for associating families with strategies. Instead, it should be recognized as a tool for leveraging well-established life-history trade-offs in plant ecology to pinpoint pertinent fungal traits that should be incorporated into our research agenda. We build upon prior frameworks, emphasizing two significant barriers to achieving a more predictive understanding of AM fungal ecology. First, discrepancies among studies often arise due to non-standardized experimental approaches. Second, the absence of a comprehensive database on AM fungal traits further complicates progress in this field. Moreover, the validity and relevance of the isolates and species employed in these studies are reliant on the taxa available in culture collections or from a few natural communities. A deliberate inclusion of numerous uncultured taxa, or other taxa hitherto overlooked fungal mutualisms in conjunction with AM fungi, such as Mucoromycotina, as suggested by Hoysted et al. (2023), remains an important task. Given the existing data showing large variability in plant and soil responses to the AM symbiosis both among and within AM fungal species, we must address these issues to assess if, and to what extent, AM fungal traits determine plant growth responses or effects on ecosystems.  Traits and Function Morphological and physiological traits Arbuscular mycorrhizal fungal traits, including for example hyphal length, arbuscule morphology, or the robustness of hyphal and spore walls, can modulate key functions/processes with ramifications not only to the health of the fungus itself but also the associated plant and the soil environment (see Figure 1 and Table 1 for detailed descriptions of key traits, their hypothesized function, and methods for trait measurement). Here, we define AM fungal traits primarily as “functional markers,” which serve as indicators of mycorrhizal function and depend on the morphological, physiological, or phenological characteristics of the fungal partner (Chaudhary et al. 2022). In this context, AM fungal traits are most likely instrumental in defining ecosystem resistance, resilience and adaptability to environmental fluctuations, as certain fungal isolates with specific traits may demonstrate superior robustness or flexibility under changing conditions.Conceptualizing the form and function of AM fungal traits becomes clearer when contextualized within the lifecycle of the fungal organism. We can broadly categorize the lifecycle of an AM fungus into two  phases: (1) the asymbiotic phase, in which the dispersed spores (or other propagules) are activated, germinate and explore the soil for a compatible host, and (2) the symbiotic phase, which includes four stages: a) initiation of root colonization; b) formation of structures within the root cortex; c) extension of mycelium into the soil matrix and possibly other hosts; and d) spore production and dispersal. Briefly, spores, hyphal networks, and colonized root fragments, identified as the three principal types of propagules, remain dormant until the proper abiotic/biotic conditions emerge (MacLean et al. 2017; Lanfranco et al. 2018). Hyphae emerging from these propagules identify a host root, adhere to its surface, and commence root colonization. A swollen hyphopodium forms, from which a single hypha penetrates the root epidermis to access the cortex. A series of morphogenetic and molecular processes come into play at these initial stages, enabling the plant to recognize the presence of the AM fungus (as reviewed by Bonfante and Perotto 1995; Gianinazzi-Pearson et al. 2007; Bonfante and Genre 2010; Luginbuehl and Oldroyd 2017). Upon reaching the root cortex, the fungus colonizes intercellular spaces, forming the intraradical mycelium (IRM). This mycelium then differentiates into structures such as arbuscules or coils, and, in some taxa, vesicles and intraradical spores. Upon attaining a certain threshold of root colonization, hyphae extend beyond the root system into the soil matrix, forming the extraradical mycelium (ERM), which consists of runner hyphae, branched absorbing structures (BAS), spore associated BAS, and spores. The expansive hyphal network, comprising IRM, ERM and spores, embodies the traits that underpin several ecosystem-level processes attributed to AM fungi (e.g., nutrient cycling, soil carbon sequestration, water regulation, soil formation, pathogen regulation, etc.). As we will explore next, these traits impact not just the host plants and soil environment, but also the fungal organism itself.

Lorinda Bullington

and 2 more

Plants host diverse microbial communities, but there is little consensus on how we sample and characterize these communities, and this has unknown consequences. Using root and leaf tissue from 20 showy milkweed (Asclepias speciosa) plants in the field, we compared two common sampling strategies by: 1) homogenizing after subsampling a small proportion of tissue (30 mg), and 2) homogenizing bulk tissue before subsampling 30 mg. Due to potential differences in richness and spatial distributions among microorganisms, we targeted bacteria, arbuscular mycorrhizal (AM) fungi and non-AM fungi in roots, as well as foliar fungal endophytes (FFE) in leaves. We also sampled FFE twice across the season using sampling strategy 1 to assess temporal dynamics, and we extracted DNA from all remaining homogenized bulk leaf tissues to determine the extent of potential undersampling. Bacterial richness was higher under sampling strategy 2, and all microbial groups except AM fungi differed in composition. Community overlap between the two sampling strategies increased when rare taxa were removed, but FFE and bacterial communities remained more different than alike and showed largely non-overlapping communities within individual plants. Increasing the extraction mass 10x also increased FFE richness ~10x, confirming the severe undersampling indicated in the sampling strategy comparisons. Even so, seasonal patterns in FFE communities were apparent, suggesting that strong drivers may be identified despite severe undersampling. Our findings highlight that current sampling practices poorly characterize many microbial groups and that increased sampling intensity is necessary to identify subtler patterns and to increase the reproducibility of studies.