Biogeochemical effects of a forest understory plant invasion depend more on dissimilar nutrient economies than invader biomass

Determining the impact of individual species on ecosystem functioning is a primary need in ecology. The widespread changes in the distribution and abundance of species resulting from human activities (Naeem and Wright, 2003; Hooper et al., 2005) could have substantial outcomes for biogeochemical cycling. While considerable evidence suggests the addition or loss of species can significantly alter nutrient cycling and productivity, species effects in ecosystems are often highly contingent, which hinders our ability to predict the ecosystem consequences of species gains and losses (Chapin et al., 1996; Cardinale et al., 2000; Cardinale et al., 2006; Wardle et al., 2011). It is particularly challenging to predict the impacts of nonnative species across heterogeneous environments (Strayer, 2012), where individual species can have positive, negative, or no effect on carbon (C) and nitrogen (N) cycling (Dassonville et al., 2008; Vila et al., 2011; Castro-Diez et al., 2014; Stricker et al., 2015).

Historically, the magnitude of a species’ effect (or a group of species sharing similar traits) on ecosystem processes has been predicted by its relative dominance within the community assuming its traits will exert effects proportional to its biomass: the mass ratio hypothesis (MRH; Grime, 1998; Mokany et al., 2008). While there is some evidence supporting MRH (Kramer et al., 2012; Lee et al., 2014), impacts do not always correlate with invader biomass (Peltzer et al., 2009; Sokol et al., 2017), casting doubt on the universality of this hypothesis. As an alternative, and perhaps not mutually exclusive hypothesis, a species could have its greatest effect when its nutrient acquisition strategy is most dissimilar from those of the existing species in the community: the nutrient economy dissimilarity hypothesis (NEDH; Figure 1c). While the MRH and NEDH are assumed to work together (Strayer et al., 2006), direct tests of their relative importance remain limited (Platt, 1964; Quinn and Dunham, 1983) and none have explored the hypotheses at the ecosystem scale in natural ecosystems. While there is evidence of these mechanisms acting as nonalternative hypotheses in laboratory microcosms (Kuebbing and Bradford, 2019), experiments performed in laboratories, greenhouses, and common gardens often do not scale to whole ecosystems (e.g., a forest stand; Kumschick et al., 2014; Stricker et al., 2015). This knowledge gap has hindered development of models predicting how species addition and loss influence ecosystem processes across a range of ecosystem types (Cardinale et al., 2012; Pyšek et al., 2012).

An abundance of research suggests that trees associating with arbuscular mycorrhizal fungi (AM) and ectomycorrhizal (ECM) fungi alter soil properties to confer an advantage in effectively obtaining limiting resources (Finzi et al., 1998; Read and Perez-Moreno, 2003; Talbot and Treseder, 2010; Phillips et al., 2013). Plants in AM-dominated communities usually have nutrient acquisitive traits (“fast cycling,” inorganic nutrient economy), whereas those in ECM-dominated communities have nutrient conservative traits (“slow cycling,” organic nutrient economy; McCormack et al., 2012; Chen et al., 2018; Zhang et al., 2018). As a result, forest stands dominated by trees associating with AM fungi typically have C and nutrient cycling rates that differ from plots dominated by trees that associate with ECM fungi. This has been especially well characterized in North American eastern deciduous forests. Stands with high AM-dominance tend to be characterized by litter and soils with narrow soil C:N ratios (Read, 1991; Midgley and Phillips, 2016; Jo et al., 2018; Zhu et al., 2018; Ward et al., 2021), soils of intermediate acidity (Read, 1991; Phillips et al., 2013), and fast rates of inorganic N cycling (Phillips et al., 2013; Lin et al., 2017; Craig et al., 2019), termed an inorganic nutrient economy (Figure 1a). By contrast, ECM-dominated stands are characterized by litter and soils with wide soil C:N (Read, 1991; Midgley and Phillips, 2016; Jo et al., 2018; Zhu et al., 2018), acidic soils (Read, 1991; Phillips et al., 2013), and slow rates of inorganic N cycling (Phillips et al., 2013; Lin et al., 2017; Craig et al., 2019), an organic nutrient economy (Figure 1a). Consequently, the dominant mycorrhizal association, or mycorrhizal association nutrient economy (MANE) gradient (Phillips et al., 2013), in a plot or stand may act as an integrative signal for soil nutrient cycling, microbial traits, and soil organic matter characteristics (Phillips et al., 2013; Craig et al., 2018; Craig et al., 2019). Because most plants and microbes have evolved strategies for scavenging and mining forms of nutrients that are most available (Read and Perez-Moreno, 2003), we posit that differences in forest nutrient economies represent a useful framework for predicting the biogeochemical consequences of plant invasions (Figure 1b). Despite this prediction, direct tests of the degree to which mycorrhizal dominance predicts invader effects are rare (Jo et al., 2018; Kuebbing and Bradford, 2019).

Japanese stiltgrass, Microstegium vimineum, a plant invasive to eastern North American forest understories, is well suited to be a model species for exploring whether proxies for MRH and NEDH predict invader impacts on soils. Japanese stiltgrass can form sparse to dense populations in forest understories (Flory, 2010; Warren et al., 2011; Craig and Fraterrigo, 2017; Sokol et al., 2017) dominated by a range of forest types. Both greenhouse (Kramer et al., 2012; Fraterrigo et al., 2014; Lee et al., 2014; Craig et al., 2015) and field (Phillips lab unpublished data) studies have reported that M. vimineum associates with AM fungi, suggesting M. vimineum has nutrient acquisition strategies most similar with those observed in AM-dominated stands. Microstegium vimineum has well-documented effects on soil biogeochemical cycling consistent with those observed in AM-dominated forest stands and inorganic nutrient economies (Figure 1a). Soils under M. vimineum tend to be wetter (Ehrenfeld et al., 2001; Fraterrigo et al., 2014), have higher pH (Kourtev et al., 1999), narrow soil C:N (Ehrenfeld et al., 2001; Craig and Fraterrigo, 2017), and higher rates of inorganic N cycling than uninvaded areas (Lee et al., 2014; Craig et al., 2019). Previous work suggests M. vimineum may become dominant in both inorganic, that is, AM dominated forest stands (Adams and Engelhardt, 2009) and organic nutrient economies, that is, ECM dominated forest stands (Kourtev et al., 2002); though invasive plants might be more likely to invade AM-dominated forest stands as has been observed for understory invasive plants generally across eastern North American forests (Jo et al., 2018). Therefore, we expect greater M. vimineum biomass in inorganic nutrient economies. However, evidence suggests both invader biomass and nutrient availability can predict M. vimineum effects on soil independently and collectively (Lee et al., 2014; Craig et al., 2015; Kuebbing and Bradford, 2019), making it well suited for exploring MRH and NEDH as alternative and nonalternative hypotheses.

In this study, we evaluated the degree to which impacts of M. vimineum on various soil properties were explained by the dominant mycorrhizal association (i.e., supporting the NEDH), its biomass (i.e., supporting the MRH), or both (supporting NEDH and MRH as nonalternative hypotheses). We measured soil characteristics in forest stands without (reference) and with M. vimineum (invaded) present in their understories across a gradient of AM- to ECM-dominated forest types (Figure 1a) and determined whether M. vimineum biomass differed in AM- and ECM-dominated forest stands. We used the ECM-dominance gradient as a natural experiment, estimating the invader effect as the difference between invaded and reference conditions (Figure 1b). We then ask whether ECM-dominance, M. vimineum (as proxies for NEDH and MRH), or both best explain invasion effects on soil nutrient cycling (Figure 1c). Lastly, to evaluate if patterns are generalizable, we replicated the study at 3 locations (Indiana, North Carolina, and Georgia) across the invaded range of M. vimineum in the eastern North American deciduous forests.

We selected 3 study locations across the distribution of invasive M. vimineum in the eastern North America (Figure S1), including Moore’s Creek Research and Teaching Preserve (IN; Bloomington, IN), Duke Forest (NC; Durham, NC), and Whitehall Forest (GA; Athens, GA). At each of the 3 locations, we established 9–11 uninvaded plots (hereafter “reference plots”) and 9–11 M. vimineum invaded plots (Figure S2) within mature forest stands (>70 years old; Table 1). The plots represented a mycorrhizal dominance gradient (i.e., shifts in the relative abundance of AM vs. ECM tree basal area; Phillips et al., 2013) to capture a range of nutrient economies.

We established 60 plots total (IN = 18, NC = 22, and GA = 20; Figure S2), with an equal number of reference and M. vimineum invaded plots at each location. Each plot consisted of 3 adjacent subplots (10 m radius) within a single contiguous patch of M. vimineum and 3 subplots (10 m radius) located nearby (i.e., within 40 m) that lacked M. vimineum but were otherwise similar in slope, canopy coverage, and overstory and understory plant communities. Subplots were established to capture spatial heterogeneity in soils across stands within a forest. Within each subplot, we recorded the diameter at breast height and species (or genus) of all trees (≥5 cm DBH, 4.5 ft above average ground level) to attribute a previously known mycorrhizal association to the tree community (Wang and Qiu, 2006; Phillips et al., 2013). At each plot, overstory ECM tree dominance (ECM dominance) was calculated as a percentage of the total basal area within a subplot (Phillips et al., 2013) and then averaged across subplots to estimate ECM dominance for invaded and reference. Although “time-since-invasion” can mediate invasion effects (Strayer et al., 2006; Flory et al., 2013; Stricker et al., 2016), our primary goal was to investigate invasion impacts across the forest nutrient economy gradient. We captured a range of “time-since-invasion” at each location, while within location opted to capture the nutrient economy gradient rather than controlling for invasion age. More detailed information regarding “time-since-invasion” for these locations is published in Craig et al. (2019).

We collected soil and understory vegetation samples from invaded and reference subplots for 3 growing seasons from 2014 to 2016. All samples were collected during the time of peak biomass for M. vimineum (August in IN, and September in NC and GA). We collected soil cores using a slide hammer soil corer (5 cm in diameter) from each subplot, removing litter layers, and collecting topsoil (0–5 cm depth including thin O-horizons where present) and 5–15 cm depths. O-horizons are not consistently present in forests experiencing similar climatic conditions (Keller et al., 2021; Craig et al., 2022) and had little influence on our data. We saw minor differences between the 0–5 and 5–15 cm depths in soil moisture, soil pH, and nitrification rates (Figure S3), suggesting any influence of the presence of a thin O-horizon is weaker than other factors of interest in this study, that is, invasion status and forest stand. We thus focus on 0–5 cm samples for determining the differences between reference and invaded conditions and include both depths in general models. Cores collected from the 3 invaded and 3 reference subplots were composited at the plot level, totaling 30 invaded and 30 reference samples for each sampling year.

Samples were stored on ice, transported back to the lab, and sieved to 2 mm to homogenate soils and remove rocks and coarse roots. Fine roots were picked from the samples, and after sieving, subsamples were reserved at 4°C for chemical assays and air-dried for total elemental analyses. At peak biomass, we also collected understory vegetation in subplots adjacent the soil samples by hand-clipping samples using 0.0625 m² quadrats to quantify aboveground M. vimineum biomass on a grams per square meter basis (Figure S2). Vegetation samples were sorted into M. vimineum and non-M. vimineum biomass. Non-M. vimineum biomass was sorted by groups into forbs, graminoids, woody species (including trees, shrubs, and vines), leaf litter, and finally into woody debris and seeds (Figure S4). The sorted understory vegetation was oven dried at 55°C for at least 48 h before being weighed. Aboveground biomass was averaged across subplots for comparison to the composited soil samples.

Gravimetric soil moisture content was determined by oven drying samples (105ºC) for 24 h. Soil pH was determined by measuring a 1:8 wet soil to 0.01 M calcium chloride (CaCl₂) extract on a bench-top meter (VWR symphony pH meter; VWR international, West Chester, PA, USA). To quantify total soil C and N content, air-dried soils were ground to a homogenous powder and combusted on a Costech Elemental Analyzer 4010 (Costech Analytical Technologies Inc.; Valencia, CA, USA). Inorganic N concentrations were determined using potassium chloride extractions (KCl extractable N) and net nitrification potential (nitrification) was quantified as the change in KCl extractable nitrate after 14-day aerobic incubations at 23°C. Extractions were done in a 1:2.5 wet soil to a 2 M potassium chloride (KCl) solution on 2-mm sieved soils, performed as soon as possible after collection (within 48 h, where field sites were easily accessible and within a week when travel was required). Extracts were quantified for inorganic N, ammonium and nitrate + nitrite (henceforth described as nitrate), using salicylate and cadmium column reduction methods, respectively, on a Lachat QuikChem 8500 series 2 autoanalyzer (Lachat; Hach, Loveland, CO, USA).

In the summer 2016, bulk soils from the 0–15 cm were collected using a slide hammer soil corer for bulk density and texture analyses. Soil bulk density and texture samples were split into 0–5 cm and 5–15 cm depths, oven dried at 110°C, sieved into the greater than and less than 2 mm fraction, and weighed to determine soil bulk densities (Brady et al., 2008). The sieved and dried 5–15 cm depths were used to determine soil texture using standard hydrometer procedures (Ulmer et al., 1994).

To determine the role of invasion status, location, and position along the nutrient economy gradient on soil properties and nitrification, we fit linear mixed effects models to our data with the following fixed effects: invasion status (invaded, reference), forest (IN, GA, and NC), ECM dominance, and their interactions. Response variables included soil pH, moisture (%), nitrification (ug NO_x−N g⁻¹ d⁻¹), and soil C:N. Since we are interested in the effect of invasion status across spatially heterogeneous forest stands, we included year (including 3 samples 2014, 2015, and 2016) and sampling depth (0–5 cm and 5–15 cm) as random effects. We included the plot as a random effect to account for repeated sampling of the same plots in consecutive years. The distribution of nitrification rates was slightly skewed toward zero and was thus natural log transformed to improve normality, while no transformation was necessary for soil moisture, pH, and C:N (Figure S5). To determine if M. vimineum differentially established across the ECM-dominance gradient, we test their correlation with Pearson’s r test.

To estimate the impact of invasion on soil properties and nitrification, we used the ECM-dominance gradient as a natural experiment and proxy for expected soil conditions, over which M. vimineum is layered, which we used to evaluate potential invader effects on soils. We had designed the experiment with the hope of using a paired plot modeling approach, whereby plot pairs differed only by the presence and absence of M. vimineum. However, we found that the ECM-dominance of invaded areas did not strongly correlate with those in nearby reference areas (Figure S6), making a paired plot modeling approach infeasible. Thus, we used data from the reference plots to establish a baseline relationship between ECM dominance and soil response variables at each location. To ensure the assumptions of normality were met, we performed a Shapiro–Wilk test (Shapiro and Wilk, 1965) and assessed heteroscedasticity visually (nitrification was log transformed to meet assumptions). Then, we used this relationship to predict soil responses for all invaded areas (based on their ECM dominance) and estimated the invasion impact by subtracting the predicted values from the expected values in each plot (Figure 1b). Each impact estimate is also accompanied by 95% prediction intervals to show the level of uncertainty associated with these estimates (Figure S7). Although we acknowledge that we did not directly measure invader effects (e.g., a common garden) and did not manipulate the system, the natural experimental gradient we set up and our modeling approach provide a critical insight into putative drivers. Using a well-established natural gradient as a hypothesis for expected soil conditions provides an informed prediction against which we can compare conditions under invasion, offering an alternative approach to estimate invader impacts that incorporates quantitative estimates of the ecological context.

We used multiple linear regression models with ECM dominance, M. vimineum biomass, and their interaction to explain Δ in soil conditions (i.e., the difference in soil characteristics between invaded and uninvaded reference plots across the mycorrhizal gradient; Figure 1c). Results from the previous model showed soil conditions and the baseline relationship between soil conditions and ECM dominance differed by location. For this reason, we fit separate models for each location. For each Δ soil property (Δ soil moisture, Δ pH, Δ soil C:N, Δ nitrification), we fit a linear regression with ECM dominance, M. vimineum biomass, and their interaction as predictors. We ensured the assumptions of linear models were met using a Shapiro–Wilk test (Shapiro and Wilk, 1965) and heteroscedasticity visually. We standardized M. vimineum biomass values by dividing by 100, so values were in a comparable range as ECM dominance. We partition the variation in our main effects (ECM dominance and M. vimineum biomass) and their interaction by calculating eta squared, η², to determine whether NEDH (approximated using ECM dominance), MRH (described by M. vimineum biomass), or both explained the most variation in Δ soil property. All statistical analyses were performed in R Version 3.4.1 (R Core Team, 2017) and visualization of regression models were made in R package “visreg” (Breheny and Burchett, 2017). Linear mixed effect models were fit, and tests were performed using the R packages “lme4” and “lmerTest” (Bates et al., 2015; Kuznetsova et al., 2017).

Whitehall Forest had the highest N availability and more intermediate acidity, in comparison to Moore’s Creek and Duke Forest. Locations differed in mean bulk density, texture, inorganic N, and soil pH. Whitehall Forest had the highest mean KCl extractable nitrate and ammonium concentrations, as well as highest mean pH. Mean bulk density, percent clay, percent sand, and inorganic N were similar between reference and invaded conditions within location (Table S2).

We confirmed the presence of the nutrient economy gradient in reference plots at all 3 locations, but the magnitude of the relationship between ECM dominance and soil moisture, pH, and nitrification changed between forests (Table 2, “ECM: Forest”). Overall, we observed negative relationships between ECM dominance and pH (Figure 2f), soil moisture (Figure 2e), and nitrification (Figure 2h); soil C:N increased with greater ECM dominance (Figure 2c and g). Locations differed in their reference soil conditions; however, the magnitude of the relationship between ECM-dominance and soil C:N was consistent across the varying soil types (Table 1) at all 3 locations (Table 2, Figure 2c). The magnitude of the relationship between soil moisture (Figure 2a), pH (Figure 2b), nitrification (Figure 2d), and ECM dominance was steepest at Whitehall Forest, where inorganic N and pH were the highest (Table S2). At Duke Forest and Moore’s Creek, the magnitude of the relationship between ECM dominance and soil pH (Figure 2b) and nitrification rates (Figure 2d) was similar. At Moore’s Creek, the relationship between moisture and ECM-dominance was weakest (Figure 2a).

Microstegium vimineum invaded forest stands across the ECM-dominance gradient, but it was not more likely to invade nutrient economies with similar conditions to those it promotes (Figure S8). ECM dominance and M. vimineum biomass were not correlated (Pearson’s r = −0.18, t [0.05, 87] = −1.7, P = 0.09). The relative contribution of other understory plants was comparable between reference and invaded plots (Figure S4, “treatment panel”). Overall, the largest differences between reference and invaded understory communities were the biomass of M. vimineum, which was higher in invaded plots, and the amount of decaying plant material, which was highest in reference plots (Table 1, Figure S4).

The effects of invasion status varied across the ECM-dominance gradient. The interaction between ECM dominance and invasion status was significant in all models (Table 2), most often altering ECM-dominated soil conditions more than AM-dominated soil conditions (Figure 2e–h). Under M. vimineum invasion, the relationship between ECM dominance (Table 2, “ECM:Inv”) and soil pH, soil C:N, and nitrification rates flattened (Figure 2e–h).

Of the 2 hypotheses, ECM dominance (NEDH) explained the most variation in models predicting the difference in pH and soil C:N and at 2 sites for soil moisture and nitrification (Figure 3, Table S3). At Moore’s Creek and Duke Forest, ECM dominance consistently accounted for over 50% of the variation in the difference in soil moisture, pH, and nitrification under M. vimineum invasion, as well as soil C:N at Moore’s Creek. ECM dominance explained a plurality of the variation in the change in soil C:N at Duke Forest. At Whitehall Forest, ECM dominance explained a plurality of the variation in difference in soil C:N. The interaction between ECM dominance and M. vimineum biomass was significant for the difference in soil moisture at Moore’s Creek and nitrification at Duke Forest. Microstegium vimineum biomass is not correlated with the difference between reference and invaded soil moisture or nitrification at both locations. ECM dominance positively predicts the change in soil moisture and nitrification, representing a significant difference between the slopes (Figure S7), but not a synergistic or additive effect.

Invader biomass, often along with ECM dominance and the interaction, predicted the differences in soil conditions at one location, Whitehall Forest (Figure 3, Table S3). M. vimineum biomass positively predicted soil moisture, pH, and nitrification at Whitehall Forest (Figure S7). M. vimineum biomass explained the most variation in models of change soil moisture (η² = 0.37; Figure 3) and net nitrification (η² = 0.60; Figure 3). M. vimineum biomass interacted with ECM dominance to explain changes in soil pH at Whitehall Forest (Figure 3), with both ECM dominance and invader biomass as positive predictors (Figure S7).

We investigated whether invader biomass and ECM dominance, as proxies for MRH and NEDH, operate as alternative and nonalternative predictors of the effects of M. vimineum on soil conditions. Overall, ECM dominance, a proxy for NEDH, more often predicted differences between reference and invaded conditions (Figure 3), indicating that knowledge of the overstory nutrient economy gradient may be a useful and scalable tool for predicting where a plant invasion may have the greatest impact on soil biogeochemistry. Notably, M. vimineum invasion across the mycorrhizal gradient was associated with homogenization of the ECM-dominance gradient, altering slow cycling, organic nutrient economies more than inorganic nutrient economies (Figure 2). To the extent that the loss of heterogeneity in nutrient economies may promote a reduction in species richness (Scott and Baer, 2019), which has known effects on ecosystem functioning (Hooper et al., 2005), the longer term consequences of invasion may be greater than demonstrated here.

While it has been widely assumed that MRH and NEDH should operate additively to predict the effects of invasion (Strayer et al., 2006), we found more evidence that NEDH alone was a better predictor of invaded soil conditions. This suggests traits associated with “fast cycling,” nutrient acquisitive strategies have a strong impact on ecosystem processes. While traits associated with N fixation are most often associated with increased invader impacts (Vila et al., 2011; Pyšek et al., 2012; Lee et al., 2017), warm-season, C₄ grasses like M. vimineum that photosynthesize at faster rates, may accelerate demand for belowground resources. In soils typically dominated by “slow-cycling” C₃ trees, the addition of a warm season grass may have greater impacts by increasing the rate photosynthetic materials are added to the system both above and belowground. Studies exploring how plant community dissimilarity alter invasion effects on soil biogeochemistry often use measures of native and invasive plant height as a metric of dissimilarly (Martin et al., 2017), which are highly correlated with biomass. While it is true that MRH, by definition, incorporates some aspects of plant traits, which here we assume to exert a measurable effect on soil nutrient economies, it is surprising that nutrient economy dissimilarity (NEDH) alone more often predicted changes in invaded soil conditions. In contrast to our initial expectations, M. vimineum did not establish preferentially in plots with nutrient economies it promotes, suggesting it is equally likely to form dense stands across forest types independent of the status may promote.

The outcome of M. vimineum invading AM- and ECM-dominated stands in equal densities and NEDH driving effects appears to result more uniform soil conditions across the nutrient economy gradient. The ultimate effect homogenizes a once biogeochemically diverse landscape, making organic nutrient economies indistinguishable from an inorganic nutrient economy within each location. Our results are consistent with findings from other studies that suggest invasive plants differentially affect high and low fertility soils, resulting in a convergence of soil conditions (Dassonville et al., 2008). Invasive plants have been shown to promote the homogenization of plant communities (McKinney, 2004), and these results suggest an invasive plant can also have similar impacts on soil conditions.

Our findings suggest in forested communities understanding the overstory nutrient economy of soils may be a useful tool for predicting if and where invasion alters soil conditions. In direct tests using experimental microcosms, Kuebbing and Bradford (2019) found that biomass effects interacted with trait dissimilarity to alter C mineralization rates. The authors manipulated invader biomass by altering the percentage of invasive plant litter in mesocosms containing maple–poplar and oak–hickory litter mixes. While this manipulation provides clear evidence that MRH and NEDH can and do operate together, our observations in the field are an interesting contrast. We only found evidence of possible synergism between both mechanisms at one site for one variable. There were no live plants in the Kuebbing and Bradford (2019) lab mesocosms, while in the field in our study, plant interactions with soils and thus rhizosphere interactions were present. Roots can alter soil microbial communities in many ways, for example, by altering the quantity (Phillips et al., 2011) and quality (de Vries et al., 2019) of root exudates that, in turn, can up and down regulate soil microbial decomposition and rates of nutrient mineralization. These plant–soil interactions may mask the direct effects of aboveground biomass on belowground nutrient cycling in our observational study—perhaps making NEDH a better predictor of the differences between references and invaded conditions, as it inherently integrates both above and below ground plant–soil interactions. In a northeastern forest in Connecticut, understory shrubs associating with ericoid mycorrhizae weakened the negative relationship between soil C:N and ECM dominance in forests (Ward et al., 2021). While it is unlikely ericoid associating shrubs had similar effects in our plots given the low contribution of shrubs to reference and invaded plots (Table 1, Table S1, in fact only one site—Whitehall Forest, GA—has ericoid shrubs), the findings of Ward et al. (2021) highlight that understory plants can have disproportionately large effects on soil processes and, in some cases, modulate the impacts of ECM dominance, MANE gradients (Phillips et al., 2013). While the timing of sampling my also moderate whether understory plants effect soil nutrient cycling, whether other understory plants—invasive or native—can have such effects warrants further study in forests with denser understory cover.

While soil conditions predicted by overstory plant communities may help explain when MRH and NEDH drive invasion effects, site conditions also explained where biomass or ECM dominance explained invasion effects on soils. We observed nutrient economy gradients that were consistent with the predictions based on ECM-dominance of the overstory trees across all 3 locations; however, in GA, soil pH and inorganic N were elevated in both reference and invaded plots relative to conditions observed NC and IN forest stands. This result may explain, in part, why Whitehall Forest, GA, was most sensitive to invader-induced changes in nitrification. In reference plots in GA, for example, we observed soil pH consistently above 4.75, which are conditions already favorable for nitrifying bacteria (Vitousek et al., 1982; Mushinski et al., 2019). Given that high M. vimineum biomass can increase pH (Ehrenfeld et al., 2001; Kourtev et al., 2002; Lee et al., 2014), inorganic N availability (Craig and Fraterrigo, 2017), and moisture (Fraterrigo et al., 2014), all of which are drivers of nitrification, the conditions in invaded plots may have become even more favorable for nitrification. This result could be due to increases in other potentially limiting substrates because of invasion, such as organic matter, which was significantly higher in invaded plots in GA (Table S2). Conversely, in landscapes with lower available N and greater soil acidity, which are strong limiters of nitrification rates and thus N cycling, the nutrient economy dissimilarity gradient was of greater importance for determining where the invader had the greatest effects on biogeochemical cycling. This result is in line with previous findings from European grasslands, where the effect of multiple invasive plants on soil conditions was greatest in sites with low soil fertility and high acidity prior to invasion (Dassonville et al., 2008). Nitrification and soil moisture change on a faster temporal scale (days or months) in comparison to pH and soil C:N (years or decades). The temporal scale may make moisture and nitrification more responsive to inputs from an annual invasive plant.

The disproportionate effect of M. vimineum on soils of ECM compared to AM dominated stands could have broad implications for soil nutrient cycling. Greater demand for inorganic N in soils that, under uninvaded conditions, would have contained high quantities of accessible carbon could stimulate the breakdown of unprotected carbon pools (Craig et al., 2019; Kumar et al., 2019). There is evidence of this phenomenon in soils from IN, where in ECM-dominated plots, the increased respiration from soils was perhaps due to greater demand for N (Kumar et al., 2019). We also observed changes in the composition of soil organic matter pools in ECM-dominated plots across all locations in this study, while concentrations in AM-dominated plots were relatively unchanged (Craig et al., 2019). The potential to release stored, but unprotected, soil organic matter from ECM-dominated soils, and alter the form of stored carbon in soils, provides further evidence in support of preventing M. vimineum establishment in ecosystems dominated by ECM-associating trees (Craig et al., 2019; Kumar et al., 2019).

Of MRH and NEDH, our data suggest NEDH (approximated by ECM-dominance) most often predicts M. vimineum impacts on soils. Under this mechanism, ECM-dominated forest stands are ultimately most at risk of ecosystem impacts due to M. vimineum invasion, where positive feedbacks on soil creates a fast cycling inorganic nutrient economy. The ultimate result may be to homogenize soils across forests that would under uninvaded conditions promote diverse biogeochemical cycling. There are now maps of mycorrhizal dominance for the entire United States (Jo et al., 2019), which could make our findings scalable to the landscape level. In the few instances where MRH best explained changes in soil conditions, reference soils were more fertile (higher inorganic N) with intermediate acidity, suggesting, as others have demonstrated for multiple invasive plants (Dassonville et al., 2008), understanding ecological context is of the utmost importance for predicting spatial impacts of plant invasion. Our work elucidates where impacts of an invasive plant on biogeochemical cycling may be idiosyncratic or unidirectional, with potential to be both predictive and scalable for other invasive species.

The authors confirm that the data associated with this study are available within the supplemental materials.

The supplemental files for this article can be found as follows:

Figures S1–S8. Tables S1–S3. Docx

MvSupplementalData.csv

Funding was provided by National Science Foundation ecosystem studies program (DEB 1353296, DEB 1354879, and DEB 1353211).

The authors declare no conflict of interest.

Conceived of and designed this study: ML, CF, JW, SLF, RPP.

Executed this study: LYP, ML, CF.

Analyzed the data: LYP, ML.

Wrote the manuscript, with all coauthors providing editorial advice: LYP.

How to cite this article: Podzikowski, LY, Lee, M, Fahey, C, Wright, J, Flory, SL, Phillips, RP. 2023. Biogeochemical effects of a forest understory plant invasion depend more on dissimilar nutrient economies than invader biomass. Elementa: Science of the Anthropocene 11(1). DOI: https://doi.org/10.1525/elementa.2023.00007

Domain Editor-in-Chief: Steven Allison, University of California Irvine, Irvine, CA, USA

Associate Editor: Rebecca Ryals, University of California Merced, Merced, CA, USA

Knowledge Domain: Ecology and Earth Systems