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. 2025 Jun 3;247(4):1572–1578. doi: 10.1111/nph.70284

What does colonisation tell us? Revisiting the functional outcomes of root colonisation by arbuscular mycorrhizal fungi

Adam Frew 1,2,3,✉
PMCID: PMC12267904  PMID: 40462534

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Arbuscular mycorrhiza refers to the symbiotic association between plants and arbuscular mycorrhizal (AM) fungi, a ubiquitous and ecologically significant interaction across terrestrial ecosystems (Powell & Rillig, 2018). In this partnership, AM fungi colonise plant roots and surrounding soil, exchanging mineral nutrients such as phosphorus for photosynthetically derived carbon from their host plants (Smith & Read, 2008). While nutrient uptake, particularly phosphorus, is often regarded as the central functional outcome of the symbiosis, AM fungi also influence a broader suite of plant traits, including phenology, drought tolerance and defence against herbivores and pathogens (Jung et al., 2012; Delavaux et al., 2017; Frew et al., 2022).

The physical interface of this exchange, the proportion of root length colonised by fungi, is frequently measured and used as a proxy for mycorrhizal function (McGonigle et al., 1990; Smith & Smith, 2011). This is logical; after all, it is within the roots that the symbiosis is established. Yet while it is broadly acknowledged that colonisation–benefit relationships are context dependent (Hoeksema et al., 2010), this nuance often fades in practice. Perhaps because assessment of colonisation has been such a foundational and longstanding focus in mycorrhizal research, do we now interpret it with implicit assumptions of function – even when empirical support is weak or absent? While some studies report clear positive linear correlations between colonisation metrics and plant growth (Fioroni et al., 2024) or phosphorus uptake (Püschel et al., 2016; Ryan et al., 2016), others show non‐linear responses (Gange & Ayres, 1999; Garrido et al., 2010; Claassens et al., 2018), or none at all (Ryan & Angus, 2003; Ryan & Kirkegaard, 2012; Leiser et al., 2016). This raises the question of whether we continue to rely on colonisation measures out of convention, without sufficiently interrogating what they actually mean in different contexts.

Interpreting measures of colonisation is further complicated by variation among AM fungal species in their foraging strategies (although see Camenzind et al., 2024) and carbon demands (Hart & Reader, 2002a,b), and also by methodological limitations. The proportion of root length colonised by AM fungi (McGonigle et al., 1990) is often measured at a single time point on a sub‐sample of roots (understandably the assessment of an entire root system is typically not feasible), which may fail to capture the dynamic turnover of fungal structures or the spatial heterogeneity in colonisation across root types or developmental zones. Arbuscules, for example, are ephemeral structures that undergo regular turnover during the symbiosis (Toth & Miller, 1984) meaning that their abundance at any single time point may not reflect cumulative exchange activity. Additionally, Kokkoris et al.'s (2019) valuable comparison of methods underscores that standard approaches can miss variation that may exist in the ‘intensity’ of colonisation – which incorporates the abundance of fungal structures in addition to their presence (Trouvelot, 1986) – potentially obscuring meaningful links to function.

Despite these limitations, such measures of colonisation remain widely used as a proxy in both research and applied contexts, likely because it is relatively easy to quantify and intuitively connected to the symbiosis. However, could it also risk narrowing our expectations of what AM fungi do? Focusing exclusively on nutrient‐related benefits risks underestimating other important functions of the AM symbiosis (Delavaux et al., 2017). One such function is the modulation of plant defence chemistry. AM fungi are known to prime host plants for enhanced resistance to herbivores and pathogens, sometimes through the accumulation of metabolites such as phenolics (Cameron et al., 2013; Pozo et al., 2013; Frew, 2020). These responses may occur with little or no corresponding change in growth or plant phosphorus (Pozo de la Hoz et al., 2021; Weinberger et al., 2025). Are all benefits of the symbiosis for plants mediated through exchange? Are all functions equally traceable to arbuscules?

Vannette & Hunter (2011) proposed a resource exchange model of defence induction, predicting that benefits such as enhanced resistance increase with the proportion of root length colonised to a point, but decline at higher colonisation levels due to carbon costs exceeding nutrient gains. Yet, it is also plausible that defence‐related outcomes are initiated early in colonisation of the host by the fungi, perhaps independent of arbuscule formation or nutrient exchange (Cameron et al., 2013). Defence activation from hyphal colonisation has been observed even in host species that are not arbuscular mycorrhizal (Anthony et al., 2020), likely triggered by fungal surface molecules (e.g. chitin) that activate immune responses upon contact or attempted penetration (Zhang & Zhou, 2010). Aspects of fungal colonisation can serve as cues rather than costs; if that is the case, we may be conflating structural presence and functional meaning, making it unclear what we are actually measuring.

Plant identity is another key factor shaping relationships between the proportion of root length colonised and functional outcomes. Species differ in their growth strategies, root traits and nutrient foraging behaviours, all of which can affect these colonisation‐function associations (Lekberg & Koide, 2005; Smith & Smith, 2011; Bergmann et al., 2020). C4 grasses, in particular, are often considered more responsive to AM fungi, especially in terms of phosphorus uptake (Treseder, 2013). These differences offer an opportunity to test when and where the root length colonised by the fungi serves as a meaningful proxy.

In this study, I revisit the function of colonisation metrics using a simple but structured experiment. I assessed colonisation using the McGonigle et al. (1990) intersect method and report it as the percentage of total root length colonised by fungal structures. Throughout the manuscript, I refer to the proportion of root length containing AM fungal structures (hyphae, arbuscules or vesicles) as ‘total colonisation’, and the proportion of root length colonised specifically by arbuscules as ‘arbuscular colonisation’. I measured root length colonised by AM fungi in four globally important crops (two C3 and two C4) and tested their relationships to plant biomass, phosphorus and phenolics. I hypothesised that: (1) the total colonisation and arbuscular colonisation would be positively associated with plant biomass, phosphorus and phenolic responses (responses being the change in each trait in plants with AM fungi relative to controls without AM fungi), particularly in the C4 crops; and (2) any relationships would be predominantly non‐linear, reflecting threshold or saturation dynamics.

While measures of AM fungal colonisation remain a cornerstone metric in mycorrhizal research, their interpretation is often assumed rather than explored. This study offers empirical data across different traits and species to revisit what the root length colonised can, and cannot, tell us about symbiotic outcomes. I hope this serves as a timely prompt for deeper reflection on how we use colonisation metrics, and what we expect them to mean.

Materials and Methods

I conducted a full factorial pot experiment with four plant species that are some of the most significant crops globally: wheat (Triticum aestivum L. cv ‘Yitpi’), barley (Hordeum vulgare L. cv ‘Hindmarsh’), sorghum (Sorghum bicolor L. Moench cv ‘MR Taurus’) and maize (Zea mays L. cv ‘Amadeus’). The plants were grown in 8‐l pots filled with gamma irradiated soil/sand mix (Table 1), which contained moderate to high levels of available phosphorus (46 mg kg−1 Colwell P) within or above the critical phosphorus levels for these crops (see M. J. Bell et al., 2013; R. Bell et al., 2013), consistent with high‐input crop systems. Each plant species was grown either with no AM fungi (n = 12 per species), or were inoculated (n = 24 per species) with a commercial inoculant (MicrobeSmart, Melrose Park SA) containing four species of AM fungi (Entrophospora etunicatum (Błaszk., B.T. Goto, Magurno, Niezgoda & Cabello) C. Walker & A. Schüßler, Funneliformis coronatum (Giovann.) C. Walker & A. Schüßler, F. mosseae (T. H. Nicolson & Gerd.) C. Walker & A. Schüßler and Rhizophagus irregularis (Błaszk., Wubet, Renker & Buscot) C. Walker & A. Schüßler). To encourage a broad range of fungal colonisation in roots, the AM fungal inoculant was applied at three rates – low (0.05 g kg−1 soil), medium (0.5 g kg−1) and high (2 g kg−1) – with each rate given to eight plants per species, totalling 24 AM fungal‐inoculated plants per species. These inoculation rates are roughly equivalent to 200, 2000 and 8000 spores per kg of soil, respectively, based on the average of 4000 spores per gram of inoculant. The inoculant was thoroughly mixed into the soil : sand substrate before potting to ensure even distribution. To account for any potential effects of non‐AM fungal microbes, non‐AM fungal pots were supplemented with 200 ml of microbial liquid filtrate derived from washing the AM fungal inoculum mixed with soil : sand mix filtered through sieves down to 20 μm to standardise the non‐AM fungal microbial community across all pots. Plants were grown in a glasshouse with day/night temperatures of 27 and 18°C, respectively, with a 12 h photoperiod. Watering was initially 100 ml every day for the first 3 wk, followed by 400–500 ml every 3 d. Volumes were adjusted as needed to maintain consistent soil moisture across pots, monitored every 3 d using a handheld moisture meter (PMS‐714; Lutron Electronic Enterprise; Taipei, Taiwan). Plants were harvested 55 d from germination, where all hosts were toward the latter vegetative growth stages, before booting or flowering. For each plant, from six locations distributed across the root system, 10–15 root fragments were collected from each location. These were cut into 5‐cm segments, composited and stored in 50% ethanol before mycorrhizal fungal colonisation assessment, and the remaining aboveground and belowground plant tissues were all oven‐dried at 60°C. Total biomass was recorded, and all foliar tissue was ground and homogenised before any chemical analyses.

Table 1.

Analysis of nutrient availability and pH of the soil substrate in which plants were grown

Nutrient (units)
Ammonium nitrogen (mg kg−1) 22.5 ± 2.1
Nitrate nitrogen (mg kg−1) 29.2 ± 2.9
Phosphorus Colwell (mg kg−1) 46.5 ± 1.3
pH 5.94 ± 0.11
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Analysis by CSBP Soil & Plant Analysis Laboratory, WA, Australia. Data shown are mean ± SE.

Phosphorus (P) concentrations in plants were assessed via inductively coupled plasma spectroscopy following digestions with nitric acid (Zarcinas et al., 1987). Total foliar phenolics were determined as described in Salminen & Karonen (2011), in technical triplicates, using a Folin–Ciocalteu assay with gallic acid monohydrate (Sigma‐Aldrich, St Louis, MO, USA) as the quantification standard. For assessing root colonisation by AM fungi, and to confirm the absence of any root colonisation by AM fungi in the control plants, ethanol‐stored root samples were placed into histology cassettes, then cleared with 10% potassium hydroxide (KOH) at 90°C for 10 min, stained with 5% ink‐vinegar (using Quink ink; Parker Nantes, France) at 90°C for 15 min (Vierheilig et al., 1998). Root fragments of 5 cm each were mounted on glass slides with glycerin under a coverslip. For each plant, 30 root fragments were assessed in total, representing 150 cm of root length. The percentage of root length colonised by any AM fungal structure (total colonisation), as well as the percentage of root length colonised by arbuscules (arbuscular colonisation), and vesicles (vesicular colonisation) were examined microscopically using the intersect method at ×200 magnification for at least 100 intersections per plant (McGonigle et al., 1990). The McGonigle et al. (1990) intersect method was used as it remains the most widely applied approach (Füzy et al., 2015), allowing comparability across the literature, despite the availability of alternative methods that may offer greater sensitivity (e.g. Trouvelot, 1986; Kokkoris et al., 2019).

To examine the relationship between root length colonised (total colonisation and arbuscular colonisation) and plant outcomes, plant mycorrhizal responses were calculated as ((plant response − mean plant responses with no AM fungi)/mean plant responses with no AM fungi) × 100, where the plant response was either the total biomass, P concentration, or phenolic concentration. These provided the mycorrhizal growth responses (MGR), mycorrhizal phosphorus responses (MPR) and the mycorrhizal phenolic responses (MPhenR). Due to very low vesicular colonisation across samples, vesicles were not included in the main analyses; however, these data are provided in the Supporting Information (Fig. S1c).

Generalised additive models (GAMs) were fitted for each plant species separately. These models were initially fitted for each response variable using the mgcv package in R (Wood, 2003). Inoculation rates were used to generate variation in colonisation and were not included in GAMs as plant responses were analysed in relation to root length colonised, the biologically relevant predictor for the hypotheses. GAMs were chosen for their flexibility in capturing both linear and nonlinear trends without assuming a predefined functional form. Smooth terms were fitted using the default basis dimension (k = 10) in the mgcv package, the suitability of the k value was confirmed using diagnostic checks with the gam.check function. Model smoothness was determined using generalised cross‐validation, and the effective degrees of freedom (edf) of the smooth term were examined to assess the shape of the relationship. Where the GAM indicated a significant relationship and edf was close to 1 (suggesting an approximately linear trend), a linear model (LM) was fitted and model selection was confirmed using Akaike Information Criterion (AIC). If a GAM indicated a significant relationship that was nonlinear (edf > 1.8), a nonlinear asymptotic model was tested using nonlinear least squares (NLS). The asymptotic model followed the self‐starting asymptotic function SSasymp in R. Model parameters were tested for significance, and AIC values were used to confirm the best model fit. Where a GAM showed no significant relationship (P > 0.05 for the smooth term), no further modelling was conducted, and the response variable was considered to be independent of root length colonised. GAM fits were used to visualise relationships and the statistical outputs of the best fitting models (GAM, LM, or NLS) were reported on plots (Fig. 1). Predictions were obtained using the predict function over an evenly spaced sequence of colonisation values. Confidence intervals (95%) were generated from the GAM or LM and displayed as shaded regions in all plots. Where GAMs yielded non‐significant relationships, no trend lines or confidence intervals were displayed in the plots. Model assumptions were checked via residual diagnostics (using the gam.check function for GAMs, Shapiro–Wilk tests for normality in LMs, and parameter stability checks for NLS models). Model selection was confirmed based on AIC comparisons and significance testing of fitted parameters. Statistical analyses were performed in R (v.4.3.3) using the mgcv (Wood, 2003), ggeffects (Lüdecke, 2018) and nlme packages (Pinheiro & Bates, 2000).

Fig. 1.

Fig. 1

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Figure showing plant responses to arbuscular mycorrhizal colonisation across four plant species. Relationships between plant mycorrhizal growth response (MGR), mycorrhizal phosphorus response (MPR) and mycorrhizal phenolic response (MPhenR) and either percentage of total root length colonised (total colonisation) or percentage of root length colonised by arbuscules (arbuscular colonisation) in (a, b) wheat (Triticum aestivum), (c, d) barley (Hordeum vulgare), (e, f) sorghum (Sorghum bicolor) and (g, h) maize (Zea mays). Data are shown separately for each crop species. Model fits and 95% confidence intervals are based on generalised additive models (GAMs). Solid lines represent significant relationships. For significant GAMs, the effective degrees of freedom (edf) and coefficient of determination (R 2) are reported. Where a linear model (LM) was selected as the best fit, the R 2 and P‐value from the LM are shown. For relationships best described by non‐linear least squares (NLS), asymptote estimates (Asym) and associated P‐values are provided to indicate asymptotic trends. ns, not significant.

Results and Discussion

Measuring the proportion of root length colonised by AM fungi offers a logical proxy for inferring the functional outcomes of the symbiosis. Yet this study adds to others that demonstrate that the relationship between colonisation and benefit is far from straightforward. It varies across traits, species and colonisation types – and, critically, not all functional outcomes appear to scale with the proportion of root length colonised in the same way.

Among all plant responses measured, the clearest and most consistent pattern emerged in relation to plant defence chemistry. In all four plant species, the total colonisation was strongly and non‐linearly associated with increases in mycorrhizal phenolic responses (MPhenR), with each exhibiting an asymptotic relationship (Table S1; Fig. 1). In all species, GAMs were significant (P ≤ 0.01), with effective degrees of freedom (edf) ranging from 1.75 in maize to 7.56 in wheat, and high explanatory power (R 2 ranging from 0.32 to 0.86). These patterns were best described by NLS models supporting my second hypothesis that colonisation–response relationships would often be non‐linear, and (in part) my first, which predicted positive associations between total colonisation and phenolics.

As total colonisation increased, plant phenolic responses rose sharply at low to moderate levels, before reaching a plateau. This may suggest that phenolic defence responses are triggered by the plant signalling associated with the presence of fungi within the root (Jung et al., 2012) rather than arbuscule development, and that these responses do not necessarily continue to rise in proportion to the percentage of root length colonised. That this pattern held consistently across both C3 and C4 crops did not support my first hypothesis that anticipated C4 hosts would be more responsive.

Strikingly, no significant relationships were observed between arbuscular colonisation and MPhenR in any species (GAM P > 0.05; edf ≈ 1; R 2 < 0.1; Table S1; Fig. 1). While some models propose that arbuscule‐mediated nutrient exchange enhances defence by enabling greater resource allocation (Pozo & Azcón‐Aguilar, 2007; Vannette & Hunter, 2011), others have demonstrated that defence responses can be activated upon fungal entry, independent of arbuscule formation or nutritional benefit (Cameron et al., 2013; Anthony et al., 2020; Pozo de la Hoz et al., 2021). This decoupling suggests that phenolic responses are not mediated by the arbuscules themselves – despite their role as the primary interface for carbon and nutrient exchange. Arbuscular colonisation can sometimes have weak or inconsistent associations with plant traits due to the ephemeral nature of arbuscules, yet the consistent absence of any relationship across all hosts was unexpected, particularly when compared to the consistent relationship plant phenolic responses had with the total root length colonised. Rather than reflecting methodological noise due to inaccuracies of relying on measurements of the ephemeral arbuscules, this pattern may point to a biological disconnect: phenolic responses could be triggered by fungal presence more broadly, not by arbuscular function per se.

This distinction is important when viewed in light of the resource exchange model of plant defence from Vannette & Hunter (2011), which posited that defence benefits from AM fungi initially increase with colonisation but may diminish at higher fungal densities due to rising carbon costs and diminishing nutrient returns. By contrast, the patterns observed here – consistent defence responses even in the absence of growth or phosphorus benefits – suggest that the phenolic responses are not closely linked to carbon‐for‐nutrient exchange per se, as they occur even in the absence of proportional growth or phosphorus responses and are not predicted by arbuscule abundance. Rather than supporting a strict cost–benefit trade‐off model, the findings here align with the understanding of a mycorrhiza‐induced resistance which can be primed through early‐stage fungal signalling, such as root penetration or other pre‐exchange cues, independent of extensive resource exchange (Cameron et al., 2013; Anthony et al., 2020; Weinberger et al., 2025).

The saturation of the plant phenolic responses may reflect an upper threshold of defence activation, beyond which either host regulation downregulates further metabolic investment, or fungal suppression of host defence limits further accumulation. The absence of a corresponding relationship with arbuscular colonisation does challenge the idea that nutrient exchange is required for downstream defence benefits. Instead, it suggests a broader role for colonisation as a signalling event, a cue which may then trigger systemic resistance.

Together, these findings suggest that AM fungi can modulate plant phenotype in ways that are independent of resource acquisition. Smith & Smith (2011) noted that P uptake via the AM fungal pathway can occur without observable growth responses, particularly in non‐responsive species or under high‐P conditions. Similarly, the patterns reported here imply that AM fungi may confer consistent defence‐related benefits even when classical markers of mutualism (mycorrhizal growth and P responses) show little change.

In contrast to the strong phenolic patterns, and contradicting my first hypothesis, no significant associations were observed between colonisation (total or arbuscular) and MGR across any crop species (GAM P > 0.05; R 2 ≤ 0.12). The plants in my study were grown in soil with high P availability (c. 46 mg kg−1 Colwell P), which probably affected the likelihood of observing such effects. Nonetheless, this P level falls within the critical range reported for these crops (typically 22–48 mg kg−1 depending on soil type and pH), and thus the soil P here would somewhat reflect conditions typical of high‐input agricultural systems in which these crops are bred and grown. Additionally, while plant root growth was largely unrestricted, minor root binding was observed in a few sorghum replicates with particularly high root biomass – an occasional artefact of pot experiments that may influence root development or function. Although limited, such constraints could have modestly contributed to the absence of stronger growth–colonisation links. Nonetheless, average MGRs were positive across all species, with sorghum exhibiting the strongest response.

Phosphorus responses (MPR) showed clearer patterns, particularly in the C4 crops. In sorghum, MPR was significantly and non‐linearly associated with total colonisation (GAM edf = 1.86, R 2 = 0.49, P < 0.001), and best fit by an NLS model. In maize, the relationship was linear (R 2 = 0.35, P = 0.001). These findings are consistent with my first and second hypotheses and align with previous work suggesting that C4 species often derive P benefits from the symbiosis in ways more tightly linked to the proportion of root length colonised (Treseder, 2013). The asymptotic shape of the MPR response in sorghum may suggest early saturation of P benefit, while maize's linear pattern could reflect a more gradual uptake curve. These contrasting responses could challenge assumptions that P benefit may always saturate at high colonisation. Interestingly, barley showed a significant linear relationship between arbuscular colonisation and MPR (R 2 = 0.41, P = 0.002), a result not predicted by my first or second hypothesis in that I expected the root length colonised in C4 plants to have stronger relationship with MPR than in C3 plants, and that this relationship would be non‐linear.

Overall, the results of this study would suggest that phenolic responses may be among the most consistent outcomes of AM fungal colonisation in high‐input systems, and that these may occur independently of traditional growth or nutrient‐associated benefit metrics. Here I did not test whether the phenolics did confer increased resistance to pathogens or insect herbivores. This would have given a stronger basis for a functional interpretation of the MPhenR across the plant hosts.

Researchers of arbuscular mycorrhizas are well acquainted with context dependency, and the caveats here are no exception. While this study draws on data from four globally important crops, the relationships observed are likely to vary with crop variety, AM fungal identity, and environmental conditions. Rather than proposing these patterns as universal, I offer them as a prompt to revisit how we assess AM symbiosis function. This may be particularly valuable in agricultural systems, where high nutrient availability can mute growth and P mycorrhizal benefit (Ryan & Kirkegaard, 2012).

While this study aimed to interrogate the functional meaning of colonisation metrics as they are commonly used, it is clear that methodological constraints remain a barrier to deeper understanding. Traditional staining‐based techniques, including the one used here, do not discriminate between living and dead fungal structures and could conflate functional colonisation with fungal necromass. Moreover, colonisation was assessed at a single endpoint, limiting insight into the temporal dynamics of the symbiosis. Recent advances, including live‐imaging techniques such as AMSlides (McGaley et al., 2025) or genetically modified hosts that report arbuscule formation through anthocyanin expression (Kumar et al., 2022), offer new tools to monitor colonisation over time. Similarly, molecular approaches (Bodenhausen et al., 2021) targeting mitochondrial or nuclear markers could be used, and perhaps could help, to quantify metabolically active fungal tissue, while image‐based analyses could allow more nuanced trait‐based characterisation of intraradical structures, including potentially important distinctions in fungal morphology across host species. These emerging methods offer valuable opportunities to move beyond static, aggregate colonisation measures and to refine how we detect, interpret and ultimately understand the ecological and functional roles of AM fungal colonisation.

Finally, while the proportion of root‐length colonised and similar measures remain useful and easily obtained metrics, I hope this Letter encourages careful interpretation. Indeed, the positive associations observed here between total colonisation and plant phenolics (in all four species), and between arbuscular colonisation and foliar phosphorus in three species, reinforce its utility as an informative, albeit context‐dependent, indicator of symbiotic outcomes. Assessing colonisation remains fundamental to the study of the AM symbiosis; the presence of AM fungi inside the root is a prerequisite for the symbiosis itself. Yet, as we continue to rely on colonisation metrics to understand symbiotic function, we must ask not only what it measures, but what assumptions we carry with it. If we are to better understand the role of AM fungi in shaping plant traits and ecosystem processes, we must also sharpen how we interpret the most fundamental measures of the symbiosis.

Supporting information

Fig. S1 Plant responses and root length colonised across plant species and treatments.

Table S1 Outputs from generalised additive models.

Please note: Wiley is not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

NPH-247-1572-s001.pdf (826.2KB, pdf)

Acknowledgements

This work was supported by an Australian Research Council Discovery Early Career Researcher Award (DE220100479) awarded to AF. Open access publishing facilitated by Western Sydney University, as part of the Wiley ‐ Western Sydney University agreement via the Council of Australian University Librarians.

Data availability

Data that support this study are openly available from the figshare repository at the following doi: 10.6084/m9.figshare.28645046.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Fig. S1 Plant responses and root length colonised across plant species and treatments.

Table S1 Outputs from generalised additive models.

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NPH-247-1572-s001.pdf (826.2KB, pdf)

Data Availability Statement

Data that support this study are openly available from the figshare repository at the following doi: 10.6084/m9.figshare.28645046.

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