Next Article in Journal
Specific Function and Assembly of Crucial Microbes for Dendroctonus armandi Tsai et Li
Previous Article in Journal
Age-Dependent Differences in Leaf Sulfur Assimilation and Relationship with Resistance to Air Pollutant SO2
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Decadal Changes in Ground-Layer Plant Communities Reflect Maple Dieback and Earthworm Invasion in National Forests in the Lake Superior Region, USA

Ecosystem Science Center, College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI 49931, USA
*
Author to whom correspondence should be addressed.
Forests 2025, 16(10), 1583; https://doi.org/10.3390/f16101583
Submission received: 27 August 2025 / Revised: 25 September 2025 / Accepted: 14 October 2025 / Published: 15 October 2025
(This article belongs to the Section Forest Ecology and Management)

Abstract

Northern hardwood forests of the Lake Superior region face a series of novel disturbance pressures including canopy dieback. Previous studies have linked regional sugar-maple (Acer saccharum) canopy dieback to introduced earthworms, which may have coinciding impacts on the ground-layer plant community. Dieback–earthworm interactions may lead to important longer-term changes in forest structure and function, but these relationships but have not been characterized. We sampled ground-layer plant communities in five national forest units in Michigan, Wisconsin, and Minnesota in 2010, and again just over a decade later in 2021. Non-metric multidimensional scaling ordination and indicator species analysis were used to assess relationships among ground-layer community composition and structure, functional traits, and environmental gradients including forest-floor condition and A. saccharum canopy dieback. Increases in dieback and earthworm disturbance in the decade between inventories were accompanied by a marked divergence in observed ground-layer plant community structure between national forests. Ordinations of 2021 data indicated a strengthening relationship between forest-floor condition and earthworm abundance. Our results suggest that earthworm impacts and A. saccharum dieback are driving changes in the ground layer on broad geographic and temporal scales, with short- and long-term implications for plant-community structure and function, and higher trophic levels.

1. Introduction

The ground-layer plant community of temperate forests is integral to the structure and function of these ecosystems. Ground-layer plants represent most of the botanical biodiversity in temperate forests of eastern North America [1] and serve as a “filter” for tree recruitment [2]; dynamics of the ground-layer therefore influence the composition and spatial arrangement of the future forest canopy [3]. Ground vegetation in forests is also thought to play a disproportionate role in nutrient and water cycling, as well as in the overall net productivity of forest ecosystems. Despite consistently representing less than 1% of a forest’s above-ground biomass, the ground layer can represent up to 5% of a forest’s net primary productivity [1,4].
In recent decades, it has been suggested that the ecological integrity of ground-layer plant communities in the Great Lakes region is deteriorating, with implications for landscape-level biodiversity and ecosystem functioning [5,6,7,8]. Many factors underlie the complex dynamics of plant-community structure, including environmental conditions and resource availability, competition, community history, presence of/proximity to propagules, and disturbance and land use histories [9,10,11,12,13]. Ground-layer changes in the last half-century appear to be driven by a variety of novel and chronic anthropogenic pressures, including atmospheric deposition, shifting weather patterns due to climate change, the introduction of non-endemic plant and animal species, and high deer browse pressures [14,15,16,17].
One such novel disturbance in the Great Lakes region has been the introduction of non-endemic earthworms (Lumbricidae). Since the end of the last period of Quaternary glaciation, forests of the region have established and evolved in the absence of large invertebrate decomposers such as terrestrial annelids [18]. The recognition of introduced earthworms as major drivers of change in the forest communities of the region has been relatively recent [17,19,20]. Many studies of earthworm impacts have been observational field studies, which have reported significant relationships between earthworm activity and lower-ground-layer plant species richness and degraded plant communities; researchers have found relationships between soil characteristics like pH, texture, and nutrient availability and the impacts of earthworms (e.g., [21]). Others have observed clear impacts of earthworm activity on plant growth in experimental settings (e.g., [22]), or how earthworms may influence communities on longer time scales through direct predation and translocation of seeds, and indirect mechanisms such as altered microtopography and soil moisture conditions that affect germination [23]. Earthworms have been shown to significantly impact physical and chemical properties of soil [24] and alter nutrient and carbon cycling [25], soil detritivore and arthropod community composition [26,27], and ground-layer plant-community composition [17,19,28]. Research suggests these changes may be irreversible, leading to ground-layer communities characterized by monotypic stands of graminoids, non-conservative native species, and adventives (e.g., [14]). Several studies have found significant evidence supporting earthworm invasion’s association with changes in plant-community diversity in North American forests [17,29,30]. However, the generalizability, persistence, and dynamics of these trends regionally are less well understood, especially as related to functional traits associated with system resilience to disturbances like earthworm invasion (see Supplementary Table S1 for example traits).
Earthworm invasions likely change plant competition outcomes over time as functional traits related to resource uptake from roots are impacted heavily in invaded ecosystems [31]. Furthermore, earthworms influence seed banks and germination, seedling survival, and other traits that can drive plant-community structure [32,33]. There are a number of functional traits that are important to plant-community assemblages [34]; however, changes in plant functional traits may have cascading effects on other community taxa and trophic levels that use them, such as pollinators and herbivores [30,35,36]. For example, earthworm invasion may favor abiotically pollinated ground-layer species, which may lead to changes in pollinator communities over time [37].
Acer saccharum Marsh. (sugar maple) is a foundational tree species in northern hardwood ecosystems of the Great Lakes region [38] and has long been the most economically valuable and among the most abundant timber species in the northern forests of the region [39,40]. Forests in the northern Great Lakes region dominated by A. saccharum may be particularly susceptible to deleterious changes associated with earthworm invasion, given other stressors such as climate change and historical management regimes. For example, Bal et al. [41] observed significant correlations between earthworm impacts on the forest floor, decreased herbaceous aerial cover in the forest understory, and A. saccharum crown dieback.
To assess ground-layer plant-community structural and compositional changes over time in situ, we resampled 60 forest health-monitoring plots established previously [41] in five national forest units across Michigan, Wisconsin, and Minnesota. We were particularly interested in the representation of traits involved in pollinator and wildlife resource value such as flowering phenology, diaspore type, and seed dispersal mechanisms. We hypothesized the following: (1) Earthworm impacts are unidirectional and accelerate predictably over time, and (2) the ground-layer plant community and its related traits will vary predictably with earthworm abundance and associated effects on the forest floor, and indirectly as a result of loss of canopy cover associated with dieback.

2. Materials and Methods

2.1. Study Location

A total of 60 plots were established in 2010 on public forested lands in northeastern Minnesota (Superior National Forest), northern Wisconsin (Chequamegon–Nicolet National Forest), and the Upper Peninsula of Michigan (Ottawa National Forest and Hiawatha National Forest). Despite forming part of the same national forest, plots on geographically disjunct units of the Chequamegon–Nicolet National Forest were treated separately. Ground-layer plant-community composition, including the percent cover of all ferns, forbs, graminoids, shrubs, and vines, was comprehensively assessed in 2010 and 2021. To examine the relationship between earthworm impacts, canopy dieback, and ground-layer composition, we excluded plots that were harvested between inventories as a confounding disturbance, resulting in a total of 41 plots analyzed for this study (Figure 1).
The humid continental climate of this region is characterized by cool summers and cold winters with heavy snowfall. Although variable due to modulating effects of topography and the Great Lakes, the growing season lasts approximately five to six months, from May to September, with temperatures ranging from a monthly average minimum of −1.1 °C to a monthly average maximum of 10.4 °C from the last frost in the spring until the first frost in the fall. Across the region, average annual precipitation is 81.5 cm of rain and 2.58 m of snow, although average snowfall across the study area ranges from 1.1 to 5.9 m (National Oceanic Atmospheric Administration, National Climatic Data Center, Ashville, NC, USA. http://www.ncdc.noaa.gov/, accessed on 10 January 2022; [41]).
Plots were established in A. saccharum-dominated stands, which were defined as containing at least ten A. saccharum trees at initiation (40 trees ha−1) with a diameter at breast height (DBH, 1.37 m) ≥ 10 cm. Plots were circular and measured 0.04 ha and were at least 40 m from a forest edge or road. Soils were predominately spodosols, mostly of coarse loam with a minority on sandy soils. In addition to A. saccharum, other overstory species included Acer rubrum L. (6.3%), Tilia americana L. (3%), and Betula alleghaniensis Britt. (2%). Minor canopy and mid-stratum species also included, but were not limited to, Fagus grandifolia Ehrh. (Hiawatha National Forest only), Fraxinus americana L., and Abies balsamea L.

2.2. Field Methods

To survey the amount of canopy loss due to dieback, on each 0.04 ha plot, we tallied trees (≥10 cm DBH) by species and recorded their DBH and percent dieback (for detailed methods see Bal et al. [41]). In 2010, ground-layer plants were sampled in four 1 m2 quadrats located 12 m from plot center in the four cardinal directions. In 2021, ground-layer plants were sampled in three 1 m2 quadrats located north, southeast, and southwest from each plot center. In both periods, plants were identified to species and aerial percent cover was estimated. Quadrats were averaged for each plot. Some plants were only identified to genus or family due to similarities in morphological features, such as sedges and grasses (Cyperaceae and Poaceae), though readily identifiable species within these groups are reported. It was noted whether these were native or introduced species (e.g., all recorded Veronica species were considered non-native). Tree seedlings were not included. In 2010, overstory canopy cover was estimated with a spherical densiometer at each quadrat and averaged for each plot. In 2021, the Canopeo smartphone application was used (Oklahoma State University Department of Plant and Soil Sciences, Stillwater, OK, USA, 2015).
During both sampling periods, the forest floor was visually evaluated within each quadrat and rated according to a five-point scale [41]. A rating of 1 represents a poor forest floor with no organic humus or duff on the soil surface and evidence of earthworm activity such as worm castings and middens, while a rating of 5 corresponds to an intact forest floor with no evidence of earthworms [41]. The forest-floor rating can provide an index of disturbance severity and complement earthworm extraction techniques [21,42,43]. Mustard solution was used in 2021 to extract earthworms in an area immediately offset from the quadrats measuring 0.1 m2 [20].
Earthworm impacts on soil conditions can vary dramatically as a result of the ecological niche occupied by each species [22]. In general, lumbricid earthworms can be classified into three major categories, or “guilds,” according to different feeding behaviors, physiologies, and spatial niches occupied across soil horizons: (1) epigeic worms, which generally reside in the organic horizon on the surface of the forest floor; (2) endogeic worms, which generally create horizontal burrows in the upper 10–15 cm of soil; and (3) anecic worms, large pigmented worms, which create permanent vertical burrows 2–3 m deep [44,45]. Most worms introduced to the Upper Great Lakes region can be classified according to one of these three categories, although one species found in our network of plots, Lumbricus rubellus, is considered epi-endogeic [46,47].
Earthworms were extracted, counted, and identified by morphological features and sorted into the following ecological functional groups: epigeic (Dendrobaena octaedra, Dendrodrilus rubidium, and Eiseniella tetraedra), endogeic (Aporrectodea spp.), anecic (Lumbricus terrestris), epi-endogeic (L. rubellus), or simply Lumbricus spp. when juvenile, as the two species are indistinguishable before maturity [46].

2.3. Analytical Methods

Field measurements were summarized for each plot and national forest by year. Average species richness, evenness, and Shannon’s diversity were calculated for each plot and summarized by national forest using PC-ORD 7 (Wild Blueberry Media LLC, Corvalis, OR, USA, 2018). A. saccharum dieback and the forest-floor rating were also summarized by national forest over time.
Ground-layer community composition was analyzed using non-metric multidimensional scaling (NMS) ordination based on the mean aerial percent cover of each taxon [48,49]. Environmental variables included distance to Lake Superior, latitude, dieback, trees ha−1, canopy cover, forest-floor rating, and total abundance and abundance of earthworms by functional group. NMS ordinations were also conducted for each year based on plant trait data. This allowed us to analyze differences in plant-community structures using generalizable traits, including functional group and Raunkiær life-form. We also included plant traits with potential mechanistic relationships (e.g., [34,50]) to earthworm disturbance (i.e., seed size and dispersal mechanisms), and potentially cascading trophic effects of shifts in community composition, such as pollination mechanism and flowering phenology (Supplementary Table S1). When possible, traits were assigned in reference to the University of Wisconsin Plant Ecology Laboratory dataset and from botanical descriptions and assessments of illustrations [51,52,53]. Flowering phenology was determined primarily according to descriptions by Gleason and Cronquist [51] and assigned a simplified scheme of early season, mid-season, or late-season according to reported months of flowering. Seed sizes were classified according to average seed dimensions provided by Montgomery [54], using size thresholds reported for ingestion by L. terrestris [23].
Data from 2010 and 2021 were treated in separate ordinations due to differences in ground-layer sampling methods between study phases. Two ordinations from each study phase were conducted, one based on plant taxa (species compositions) and one based on plant traits. For taxon-based NMS ordinations, horizontal aerial cover data values were transformed to presence/absence to reduce ordination stress and improve interpretability. To reduce noise, rare taxa occurring in a single plot were removed from each matrix, resulting in 35 taxa in 2010 and 28 in 2021. A Beals smoothing function [55] was applied to the 2010 taxon data to produce a stable ordination solution. For trait-based ordinations, abundance values for each trait were determined using the sum of percent aerial cover of all taxa with a given trait, and no data transformations were necessary to produce stable solutions.
For all ordinations, Sørensen distances were used. Autopilot mode was applied with “slow and thorough” settings, which stipulate a maximum of 500 iterations, an instability criterion of 0.000001, 6 starting axes, 250 real runs, and 250 randomized runs. A random starting configuration for the ordination was used. Interpretive overlays and environmental variable biplots were created to visualize gradients present in the ordination space. All multivariate analyses, including NMS ordinations described above, were conducted using PC-Ord (Version 6. Wild Blueberry Media LLC, Corvallis, OR, USA). We interpreted the variance of community and traits composition along ordination axes, using Pearson correlation coefficients (r) and coefficients of determination (r2) [13,55].
To test for differences between different levels of A. saccharum dieback, forest-floor condition, and earthworm abundance, we created categorical variables based on those used in prior studies. For A. saccharum percentage canopy dieback, mean values were binned into severe (>20%), unhealthy (>10%), and low (<10%) per forest health thresholds suggested in prior studies [39,56]. We created categories of the forest-floor ratings based on the mean, i.e., forest-floor rating was binned into mostly intact forest floor (1 standard deviation above the mean) and poor categories (all other plots). We also tested for differences between plots based on the presence or absence of earthworm functional groups (epigeic, endogeic, epi-endogeic, and anecic). For 2021 data, we also used cluster analysis based on earthworm functional group assemblages to determine plot groupings by earthworm communities, which were then coded and included as a categorical variable for group analysis of plant-community and traits composition. To conduct cluster analysis, we used Euclidean distances and Ward’s linkage method. We used indicator species analysis to prune the dendrogram by minimizing the average observed p-values of all earthworm groups [55].
Multi-response permutation procedures (MRPPs) with pairwise comparisons were conducted to test statistical differences in community composition between different plot groupings [57,58]. We were interested in determining differences between national forests, expecting differences due to regional climactic variability and natural species composition. Although plots were located in four national forests when considered administratively, we treated plots in Chequamegon–Nicolet as two geographically separate units, for a total of five geographically distinct national forest units (Figure 1). We also tested differences between plots grouped by forest-floor rating, high/low earthworm density (by earthworm count), and A. saccharum-dieback magnitude classes, as well as by presence or absence of earthworm functional groups and earthworm assemblage based on cluster analysis.
Indicator species analysis was conducted to determine whether certain plant taxa or traits were significantly associated with environmental variables [59]. The same classes used for MRPPs were used for indicator analyses. Indicator species analysis relies on Monte Carlo simulations to evaluate statistical significance of an indicator species; p-values represent the probability that the indicator value of a species, as measured by percent of perfect indication (only and always present in plots with associated environmental variables), is the result of random processes. All multivariate analyses, including NMS ordinations, MRPPs, and indicator species analysis, were conducted using PC-Ord (Version 6. Wild Blueberry Media LLC, Corvallis, OR, USA).

3. Results

Across national forests, impacts to the forest floor due to earthworms and A. saccharum canopy dieback increased over the study period (Table 1 and Table 2). Forest-floor ratings were highly variable. Average canopy dieback of A. saccharum increased from 10.4% ± 0.7 SE to 19.1% ± 2.4 SE. Average dieback ranged between 3.6% and 25.4% in 2010 and between 1.5% and 78.6% in 2021 (Table 1). Superior National Forest in Minnesota displayed the highest percentage of canopy dieback, but not the most impacted forest-floor rating. The most impacted forest floor was observed in the Chequamegon National Forest, which, paradoxically, had the lowest level of dieback. Chequamegon and Superior National Forests exhibited the greatest decline in forest-floor rating (Table 2). Hiawatha National Forest had the most intact forest floor.
Forest-floor conditions declined across the study network, with average rating decreasing to 2.4 ± 0.2 SE (1 = many signs of earthworms; no intact duff layer) (Table 2). In 2010, twenty-nine of forty-one plots (71%) were rated a 5 on the forest-floor scale, indicating no evidence of earthworms was observed. Thirty-five plots in total (85%) were rated at 4 or above. In 2021, just five plots (12% of all plots) were rated at 5, and only ten plots (24%) were rated 4 or higher. No earthworms were extracted in the five plots with a forest-floor rating of 5. Of the four plots with worms extracted but with low impact ratings (average ≥ 4), three had only epigeic worms and one plot had only anecic worms extracted, although these four plots had less than a single worm extracted per 0.1 m2 when averaged across sampling quadrats. A total of 1175 worms were extracted across all plots during sampling in 2021.
Cluster analysis and subsequent iterative indicator species analyses of earthworm assemblages resulted in four distinct assemblages across the forty-one plots (Table 3). One group was defined by the complete absence of extracted earthworms. A second group was dominated by epigeic earthworms. The third group was characterized by a diversity of earthworm types, with nearly all plots composed of three or four species groups. The final group was dominated by juvenile Lumbricus and, for one plot, a high proportion of L. rubellus, an epi-endogeic earthworm.

3.1. Community Composition: 2010

The 2010 plant taxa ordination converged after applying a Beals smoothing function. The resulting three-dimensional ordination cumulatively explained 92.3% of the variation in community composition (r2 = 0.923, p = 0.004), with axes 1, 2, and 3 explaining 50.6%, 25.8%, and 15.9% of plant-community composition, respectively. The ordination had a final stress of 11.93, an instability of less than 0.00001, and converged after 82 iterations (Figure 2). A positive correlation was observed between axis 1 and forest-floor rating (Table 4). The strongest four positive species correlations with axis 1 were Rubus strigosus, Athyrium filix-femina, Aralia nudicaulis, and Asarum canadense (Table 4). The four taxa with the strongest negative correlations with axis 1 were Cornus alternifolia, Mitchella repens, Pyrola spp., and Rubus canadensis (Table 4). Axis 2 was most strongly correlated with latitude and distance to Lake Superior (Table 4).
The trait-based ordination converged, without transformation, into a two-dimensional solution after 83 iterations (Figure 2a). This ordination had a cumulative r2 of 0.899 (p = 0.004) and a final stress of 10.384, with axes 1 and 2 explaining 62.8% and 27.1% of the variance, respectively. No particularly strong environmental correlations (r > 0.4) were observed (Table 5). Strongly correlated along axis 1 were abundances of forbs, geophytes, plants with vertebrate-dispersed seeds, and plants with early and mid-season flowering phenology (Table 5). Abiotic pollination and graminoids were strongly correlated with axis 2 (Table 5).

3.2. Community Composition: 2021

Ordination by taxa resulted in a three-dimensional solution after 133 iterations (cumulative r2 = 0.797, p = 0.016). Final stress for the ordination was 13.714 with an instability of zero (Figure 3). The three axes explained 43.9%, 22.9%, and 12.9% of variation in plant-community composition, respectively.
Latitude and the density of L. rubellus worms were positively correlated with axis 1 (Table 5). The density of endogeic earthworms was negatively correlated. Among plant taxa, Clintonia borealis and Trientalis borealis (syn. Lysimachia borealis) were strongly positively correlated with axis 1, while sedges and mosses were strongly negatively correlated (Figure 3). Juvenile Lumbricus spp. were strongly negatively correlated with axis 2. The forest-floor rating was strongly positively correlated with axis 2, but, due to its inverse scaling, severity of earthworm impact is negatively associated with this axis. Therefore, negative values along axis 2 appear to be associated with more degraded forest floors and positive values with more intact forest floors. Taxa associated with high earthworm impacts along axis 2 include Maianthemum canadense, Anemone quinquefolia, and Athyrium filix-femina, whereas Lycopodiaceae spp. were associated with low impacts.
The 2021 trait ordination resulted in a three-dimensional solution after 77 iterations (cumulative r2 = 0.925, p = 0.004) (Figure 2). The three axes explained 61.5%, 20.4%, and 10.6% of the variance, respectively. The final stress of the ordination was 7.638, with an instability of zero. In addition to geographic variables, such as latitude, overstory canopy variables were strongly correlated with ordination axes. In addition, correlations were observed relating to earthworms (Table 5). Particularly strong negative correlations with axis 1 were biotic pollination, early and mid-season flowering plant abundance, and native plant abundance (Table 5, Figure 2b). Notable environmental correlations with axis 2 included tree density and proportion of epi-endogeic earthworms (Table 5). Forbs and large seeds were positively correlated with axis 2. Negatively correlated with axis 2 were hemicryptophytes, abiotically dispersed plants, and abiotically pollinated plants (Table 5).

3.3. Group Analysis

MRPPs of plots grouped by A. saccharum canopy dieback and forest-floor rating in 2010 found no significant differences (p > 0.05) between group taxon composition nor traits. When grouped by national forest, we found significant differences in composition for pairwise comparisons (p ≤ 0.013, average mean effect size A = 0.0785) except for those between Chequamegon, Nicolet, and Ottawa. The MRPPs using plant traits revealed significant differences between national forests in two of ten pairwise comparisons: Ottawa vs. Superior (p = 0.031, A = 0.053) and Nicolet vs. Superior (p = 0.018, A = 0.102).
For 2021, we also grouped plots by earthworm assemblage (Table 3). Significant differences in species composition were observed between plots with no worms and plots defined by worm communities dominated by juvenile Lumbricus (p = 0.050, A = 0.058). Significant differences in species composition were also observed between plots with low and high forest-floor ratings (p = 0.009, A = 0.039) and between plots with low and severe canopy dieback (p = 0.028, A = 0.018) (Figure 3). National forest pairwise comparisons were the same in 2021 as 2010. Significant differences in trait composition were found in pairwise comparisons in half of all pairs when comparing between national forest units (p < 0.05 for five of ten pairwise comparisons). No significant differences in trait composition were found when comparing between forest-floor ratings nor by earthworm assemblage. Significant differences in plant trait composition were observed between plots with unhealthy and severe levels of A. saccharum canopy dieback (p = 0.024, A = 0.032) and between low and severe levels (p = 0.028, A = 0.041).

3.4. Indicator Species Analysis

Several plant taxa emerged as indicators of high A. saccharum canopy dieback and poor forest-floor condition in 2010, but no indicators were detected for low canopy dieback nor intact forest floor (Table 6 and Table 7). Several taxa were also significant indicators of specific national forest units (Table 6). Phegopteris connectilis, Athyrium filix-femina, Rubus strigosus, and Clintonia borealis were indicators of high levels of canopy dieback, while grasses, mosses, Caulophyllum thalictroides, and Ranunculus and Ribes species were indicators of poor forest-floor condition due to earthworms.
In 2021, several taxa emerged as significant indicators of varying levels of forest-floor rating, worm number or presence/absence, earthworm assemblages (Table 3), and the presence of the anecic earthworm, Lumbricus terrestris (Table 7). A. filix-femina, Phegopteris connectilis, Trillium spp., and Veronica spp. were significantly associated with plots with poor forest-floor condition. A. filix-femina also emerged as an indicator of the diverse earthworm assemblage. Four taxa were found to be significant indicators of intact forest floors and/or earthworm absence: Dryopteris spp., Lycopodium spp., and Maianthemum racemosum. Four taxa were significantly associated with high earthworm abundance as determined by extraction count, i.e., Aster spp., Bryophyta spp., Poaceae spp., and Trillium spp., while two others were associated specifically with the presence of anecic L. terrestris earthworms: Carex spp. and non-native Veronica. Finally, Clintonia borealis was found to be a significant indicator of the earthworm assemblage dominated by juvenile Lumbricus.

4. Discussion

Ground-layer community composition and structure were associated with forest-floor condition and overstory canopy dieback. These factors appear to be associated with exotic earthworm impacts in national forests across the region. Our results also suggest that declining forest-floor condition and associated shifts in plant communities are becoming more geographically widespread and may be accelerating.

4.1. Plant-Community Composition

Plant communities were strongly correlated with changes in the forest floor associated with earthworm activity and assemblages, corresponding to much literature on northern hardwood forests finding similarly impacted plant-community diversity with earthworm invasions [19,60,61]. L. rubellus has been posited as being particularly destructive to forest ground-layer communities and one of the most impactful of all invasive earthworms found in the Upper Great Lakes region due to its generalist feeding behaviors and rapid and substantial impact to the rhizosphere [19,25].
Species and traits associated with flowering and dispersal, and their relationships to forest-floor condition were idiosyncratic, suggesting changes over time as earthworm invasions proceed. For example, in 2010 Clintonia borealis was associated with more intact forest floors. However, in 2021 it had only a very weak association with intact forest floors and strong associations with several earthworm functional groups and one earthworm community assemblage. This may suggest that previously intact forest floors are increasingly becoming impacted by earthworms and that associations between species and forest-floor conditions are not static.
It is interesting that certain species associated with forest-floor conditions were not more consistent between the time periods. In 2010, our ordination results suggested that plant species were sorted out along a gradient of forest-floor conditions. For example, Ribes spp., Rubus canadensis, Mitchella repens, Hieracium spp., and Cornus alternifolia were associated with sites with higher earthworm impacts. At least initially, Athyrium filix-femina was associated with more intact forest floors, suggesting less tolerance. Surprisingly, in ordinations from 2021, while forest-floor condition still represented a strong gradient, different species compositions emerged. One possible explanation for this result may be related to the worsening condition of forest floors over time. The signal is changing as sites that were initially associated with intact forest-floor conditions are changing. The timing of earthworm impacts as invasion fronts move through an area with different species assemblages is also varied [62,63]. Essentially, changes to community composition are complex as these are slow-moving invasion fronts.
Changes in indicator species and their associated traits between the time periods may also reveal long-term trends as the disturbance dynamics continue. For example, sedges, A. filix-femina, and non-native Veronica species were associated with the presence of anecic worms, and A. filix-femina was also associated with diverse earthworm assemblages. It has been suggested that more diverse assemblages of earthworms are typically indicative of longer histories of earthworm activity in a site (e.g., [62,64,65]). The establishment of endogeic Aporrectodea species or anecic L. terrestris can be facilitated by prior establishment and activity of epigeic and endogeic earthworms [19]. It is likely that our results show plant-community responses to earthworm activity at different stages of invasion. Our results, like others’ [30,66], may suggest a longer-term trend toward more graminoids and non-native plants in areas with more earthworms and a potential corresponding decrease in plants that provide resources up trophic levels, such as to pollinators and wildlife. These observed changes in species composition appear to reflect shifts in underlying functional traits associated with earthworm-driven disturbance, which we explore in more detail in the following section.

4.2. Plant Traits

Few studies have directly or widely examined relationships between plant traits and functional groups impacted directly by earthworm invasions, yet evidence is emerging that shows a marked decrease in plant functional diversity with potential cascading effects on ecosystem functioning [30]. In our study, graminoids were found to be indicators of either poor forest-floor condition or earthworm presence in both time periods (Table 6). The positive association between earthworms and graminoids has been widely studied and reported, particularly in agricultural contexts or other regions [30,66]. More recently, similar trends have been reported in northern hardwood forests [64]. Grasses and sedges are generally non-mycorrhizal and may be more resistant to soil disturbance caused by earthworm bioturbation, particularly if able to spread vegetatively, as they are more tolerant of drought conditions and root herbivory [17,64]. The relationship between non-native plants and non-native earthworms has also been reported and may result from earthworms providing soil conditions advantageous to introduced plants, many of which co-evolved with earthworms in their habitats of provenance (e.g., [67,68,69,70]). The presence of non-native Veronica species as indicators of poor forest-floor condition, anecic presence, and earthworm presence is consistent with others reporting increases in non-native species with earthworm invasions. Other non-native plants observed in our plots were Epipactis helleborine, Myosotis sylvatica, and Trifolium spp., all of which are native to Europe and have co-evolved with many species of earthworms introduced to North America. These three species were not observed in 2010 but were in 2021 (Supplemental Table S1).
Bryophytes, like grasses, were consistently associated with poor forest-floor conditions in both 2010 and 2021. Several moss species, such as those in the genus Polytrichum, benefit from disturbance to the forest floor and exposed mineral soil [71]. Soil-dwelling mosses may, in this case, benefit from altered soil conditions provided by earthworm activity. It may be useful to include mosses in further detail in future earthworm-monitoring and impact studies.
Studies have reported positive relationships between earthworm activity and the success of some ferns [22,72]. Ferns, like grasses, are largely non-mycorrhizal. Some, like G. dryopteris, are also known not to be overly sensitive to root disturbance and easily transplantable [73]. Similarly, A. filix-femina is a rhizomatous fern known to be very resistant to root disturbance [74,75]. This may mean that some fern species are more tolerant or less sensitive to earthworm-driven soil disturbance in the Great Lakes region. By contrast, although G. dryopteris and A. filix-femina were indicators of poor forest-floor rating (high earthworm impact) and high earthworm abundance, traits-based analysis shows that ferns as a functional group were negatively associated with axis 2, while epi-endogeic proportions were positively associated with axis 2 (Table 5). This group of plants was largely driven by Dryopteris species cover, which were among the most encountered taxons (in 26 plots) and by far the most abundant when compared to other ferns (G. dryopteris, A. filix-femina, Phegopteris connectilis, Pteridium aquilinum, and Matteuccia struthiopteris). This corresponds to research reported by Drouin et al. [60], who reported a decline in Dryopteris species and increases in graminoid cover linked with earthworm invasion.
Across the network, several indicators were consistent with previous studies in the region. Intact forest floors and low earthworm abundance were associated with lycopods [72,76,77] and Trientalis borealis [19,72,76]. For poor forest floors or high diverse earthworm assemblages, the ferns A. filix-femina and G. dryopteris were noted [72]. Trends of other species were also consistent, such as Polygonatum pubescens with intact forest floors [19,72,76], and Ribes species with poor forest floors in 2010 [72]. Other species, such as Maianthemum racemosum, which was a significant indicator of earthworm absence and low impact, were found to be in concordance with Hale et al. [19] but in contrast with Holdsworth et al. [76] and Corio et al. [72]. These differences may be due to differences in study methodologies, particularly in earthworm-abundance metrics, specific site characteristics, or timing since earthworm introductions. Examining change over long time periods could help elucidate differences between these studies.

4.3. Potential Influence of Sites

Superior National Forest had the highest levels of canopy dieback and some of the poorest forest-floor conditions that worsened between time periods. Superior is near the northern limit of A. saccharum’s range. While climate forecasts and species modeling predict A. saccharum may benefit at its northern range (e.g., [78]), trees growing at the limit of the species’ northern range may be more likely to have been exposed to sporadic thaw–freeze events in the spring and frost damage to crowns in recent decades; such events have been linked to severe dieback episodes in northern hardwood forests [79,80].
An abundance of plant traits were associated with an apparent gradient of A. saccharum dieback in 2021. This suggests an initial broad release of many plant functional groups in response to reduced canopy cover. It may be expected that plants such as Rubus strigosus respond positively to the increased light availability under canopy dieback. Others have observed similar trends and reported positive impacts of greater light on understory flower and fruit resources and on pollinator activity in canopy gaps created by timber harvesting [37,81].
Some of the species associations we observed are likely due to variable progression of earthworm communities in different national forests. In other words, some plants may present as indicators of high earthworm impact initially simply because they are in areas where earthworm impacts have been present for decades. Others, like Clintonia borealis in Superior, are present in sites being rapidly changed by earthworm invasion. The persistence of these plant species through time is less clear. Additionally, due to the sub-boreal location of Superior National Forest, the ground-layer communities are characteristically different than those found at the other national forests. C. borealis was a prominent member of the ground-layer communities assessed in Superior National Forest. Interestingly, as is common for members of Liliaceae, C. borealis consistently forms mycorrhizal associations [82]. It has been suggested that mycorrhizal obligates tend to decline with invasions of exotic earthworms in A. saccharum forests, while facultative or non-mycorrhizal herbs such as graminoids benefit [31,83]. C. borealis may be an indicator of earthworm abundance only because it is currently in plots seeing rapid change in earthworms. It just happens to be in the wrong place at the right time. Further observation would be necessary to determine whether C. borealis will remain as poor forest-floor conditions persist or continue to degrade.
To support monitoring of disturbance-driven shifts in northern hardwood forests, we suggest two actionable measures. First, simple field-based assessments of the forest-floor condition—such as the presence of intact litter versus exposed mineral soil—can serve as rapid indicators of earthworm activity, documenting presence and associated changes. Second, monitoring shifts in specific functional traits of understory vegetation (e.g., clonal growth, early season phenology, or mycorrhizal association) may offer insight into subtle but ecologically meaningful community transitions. Integrating these indicators into existing monitoring programs may help managers with decision making and identify emerging ecosystem changes before they become widespread or irreversible.

5. Conclusions

This study provides further evidence for the driving influence of invasive earthworms on shifting plant-community composition in northern hardwood understories, with implications for forest ecosystems writ large. Over the past decade, we observed a directional change toward communities dominated by disturbance-adapted graminoids and non-native species, accompanied by declines in mesic forest herbs and mycorrhizal-dependent taxa. These changes were strongly associated with earthworms and A. saccharum canopy dieback. These decadal shifts observed across a broad geographical scale in national forests of the Lake Superior region highlight the many challenges faced by managers and the importance of documenting earthworm spread. The convergence of soil disturbance and overstory stress is altering key functional traits in the ground layer, with likely consequences for regeneration dynamics, biodiversity, and ecosystem resilience. Causal linkages should be further investigated to better explain differences in responses among plant traits and potentially conduct management to mitigate impacts to ecosystem function. Continued research should include long-term monitoring to determine how understories may or may not recover and ascertain the feasibility or effectiveness of active restoration of forest ground-layer diversity.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/f16101583/s1. Table S1. Species found in 41 plots in five national forest units of the Lake Superior region, and assigned traits used for non-metric multidimensional scaling (NMS) ordination. Life cycle: P (perennial), A (annual). Seed dispersal and pollination: B (biotic), A (abiotic).

Author Contributions

Conceptualization, T.L.B. and M.E.A.; methodology, T.L.B., M.E.A. and C.R.W.; formal analysis, M.E.A., T.L.B. and C.R.W.; investigation, M.E.A. and M.E.B.; resources, T.L.B.; data curation, M.E.A.; writing—original draft preparation, M.E.A., T.L.B., J.I.B. and C.R.W.; writing—review and editing, T.L.B., M.E.B., J.I.B. and C.R.W.; visualization, M.E.A.; supervision, T.L.B.; project administration, T.L.B.; funding acquisition, T.L.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the USDA Forest Service Forest Health Protection, Evaluation Monitoring Grant Program #20-DG-11094200-21. Support was also provided by the Ecosystem Science Center at Michigan Technological University.

Data Availability Statement

Data is available on request from the corresponding author.

Acknowledgments

The authors would like to thank the field technicians who collected data used for this study in both phases, with special mention to Shelby Nicole Lane-Clark in 2021.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Gilliam, F.S. The Ecological Significance of the Herbaceous Layer in Temperate Forest Ecosystems. BioScience 2007, 57, 845–858. [Google Scholar] [CrossRef]
  2. George, L.O.; Bazzaz, F.A. The Herbaceous Layer as a Filter Determining Spatial Pattern in Forest Tree Regeneration. In The Herbaceous Layer in Forests of Eastern North America; Gilliam, F., Ed.; Oxford University Press: New York, NY, USA, 2014; pp. 340–355. [Google Scholar]
  3. Royo, A.A.; Carson, W.P. On the formation of dense understory layers in forests worldwide: Consequences and implications for forest dynamics, biodiversity, and succession. Can. J. For. Res. 2006, 36, 1345–1362. [Google Scholar] [CrossRef]
  4. Neufeld, H.S.; Young, D.R. Ecophysiology of the Herbaceous Layer in Temperate Deciduous Forests. In The Herbaceous Layer in Forests of Eastern North America; Gilliam, F., Ed.; Oxford University Press: New York, NY, USA, 2014; pp. 340–355. [Google Scholar] [CrossRef]
  5. Kwiatkowska, A.J. Changes in the species richness, spatial pattern and species frequency associated with the decline of oak forest. Vegetatio 1994, 112, 171–180. [Google Scholar] [CrossRef]
  6. Robinson, D. The responses of plants to non-uniform supplies of nutrients. New Phytol. 1994, 127, 635–674. [Google Scholar] [CrossRef]
  7. Woods, K.D.; Hicks, D.J.; Schultz, J. Losses in understory diversity over three decades in an old-growth cool-temperate forest in Michigan, USA. Can. J. For. Res. 2012, 42, 532–549. [Google Scholar] [CrossRef]
  8. Webster, C.R.; Dickinson, Y.L.; Burton, J.I.; Frelich, L.E.; Jenkins, M.A.; Kern, C.C.; Raymond, P.; Saunders, M.; Walters, M.B.; Willis, J.L. Promoting and maintaining diversity in contemporary hardwood forests: Confronting contemporary drivers of change and the loss of ecological memory. For. Ecol. Manag. 2018, 421, 98–108. [Google Scholar] [CrossRef]
  9. Grime, J.P. Primary strategies in plants. Trans. Bot. Soc. Edinb. 1979, 43, 151–160. [Google Scholar] [CrossRef]
  10. Foster, D.R. Land-Use History (1730–1990) and Vegetation Dynamics in Central New England, USA. J. Ecol. 1992, 80, 753–771. [Google Scholar] [CrossRef]
  11. Davis, M.A.; Wrage, K.J.; Reich, P.B. Competition between tree seedlings and herbaceous vegetation: Support for a theory of resource supply and demand. J. Ecol. 1998, 86, 652–661. [Google Scholar] [CrossRef]
  12. Tanentzap, A.J.; Bazely, D.R. Propagule pressure and resource availability determine plant community invisibility in a temperate forest understory. Oikos 2009, 118, 300–308. [Google Scholar] [CrossRef]
  13. Burton, J.I.; Mladenoff, D.J.; Clayton, M.K.; Forrester, J.A. The roles of environmental filtering and colonization in the fine-scale patterning of ground-layer plant communities in north temperate deciduous forests. J. Ecol. 2011, 99, 764–776. [Google Scholar] [CrossRef]
  14. Rooney, T.P.; Wiegmann, S.M.; Rogers, D.A.; Waller, D.M. Biotic Impoverishment and Homogenization in Unfragmented Forest Understory Communities. Conserv. Biol. 2004, 18, 787–798. [Google Scholar] [CrossRef]
  15. Wiegmann, S.M.; Waller, D.M. Fifty years of change in northern upland forest understories: Identity and traits of “winner” and “loser” plant species. Biol. Conserv. 2006, 129, 109–123. [Google Scholar] [CrossRef]
  16. Frerker, K.; Sabo, A.; Waller, D. Long-term regional shifts in plant community composition are largely explained by local deer impact experiments. PLoS ONE 2014, 9, e115843. [Google Scholar] [CrossRef]
  17. Craven, D.; Thakur, M.P.; Cameron, E.K.; Frelich, L.E.; Beauséjour, R.; Blair, R.B.; Blossey, B.; Burtis, J.; Choi, A.; Dávalos, A.; et al. The unseen invaders: Introduced earthworms as drivers of change in plant communities in North American forests (a meta-analysis). Glob. Change Biol. 2017, 23, 1065–1074. [Google Scholar] [CrossRef] [PubMed]
  18. Hendrix, P.F.; Bohlen, P.J. Exotic earthworm invasions in North America: Ecological and policy implications. BioScience 2002, 52, 801–811. [Google Scholar] [CrossRef]
  19. Hale, C.M.; Frelich, L.E.; Reich, P.B. Changes in hardwood forest understory plant communities in response to European earthworm invasions. Ecology 2006, 87, 1637–1649. [Google Scholar] [CrossRef] [PubMed]
  20. Bohlen, P.J.; Groffman, P.M.; Fahey, T.J.; Fisk, M.C.; Suarez, E.; Pelletier, D.M.; Fahey, R.T. Ecosystem consequences of exotic earthworm invasion of north temperate forests. Ecosystems 2004, 7, 1–12. [Google Scholar] [CrossRef]
  21. Fisichelli, N.A.; Frelich, L.E.; Reich, P.B.; Eisenhauer, N. Linking direct and indirect pathways mediating earthworms, deer, and understory composition in Great Lakes forests. Biol. Invasions 2013, 15, 1057–1066. [Google Scholar] [CrossRef]
  22. Bowe, A.; Dobson, A.; Blossey, B. Impacts of invasive earthworms and deer on native ferns in forests of northeastern North America. Biol. Invasions 2020, 22, 1431–1445. [Google Scholar] [CrossRef]
  23. Forey, E.; Barot, S.; Decaëns, T.; Langlois, E.; Laossi, K.R.; Margerie, P.; Scheu, S.; Eisenhauer, N. Importance of earthworm–seed interactions for the composition and structure of plant communities: A review. Acta Oecologica 2011, 37, 594–603. [Google Scholar] [CrossRef]
  24. Alban, D.H.; Berry, E.C. Effects of earthworm invasion on morphology, carbon, and nitrogen of a forest soil. Appl. Soil Ecol. 1994, 1, 243–249. [Google Scholar] [CrossRef]
  25. Hale, C.M.; Frelich, L.E.; Reich, P.B.; Pastor, J. Exotic earthworm effects on hardwood forest floor, nutrient availability and native plants: A mesocosm study. Oecologia 2008, 155, 509–518. [Google Scholar] [CrossRef]
  26. Groffman, P.M.; Bohlen, P.J.; Fisk, M.C.; Fahey, T.J. Exotic earthworm invasion and microbial biomass in temperate forest soils. Ecosystems 2004, 7, 45–54. [Google Scholar] [CrossRef]
  27. McLean, M.A.; Parkinson, D. Impacts of the epigeic earthworm Dendrobaena octaedra on oribatid mite community diversity and microarthropod abundances in pine forest floor: A mesocosm study. Appl. Soil Ecol. 1998, 7, 125–136. [Google Scholar] [CrossRef]
  28. Nuzzo, V.A.; Maerz, J.C.; Blossey, B. Earthworm invasion as the driving force behind plant invasion and community change in northeastern North American forests. Conserv. Biol. 2009, 23, 966–974. [Google Scholar] [CrossRef] [PubMed]
  29. Cameron, E.K.; Vilà, M.; Cabeza, M. Global meta-analysis of the impacts of terrestrial invertebrate invaders on species, communities and ecosystems. Glob. Ecol. Biogeogr. 2016, 25, 596–606. [Google Scholar] [CrossRef]
  30. Thouvenot, L.; Ferlian, O.; Craven, D.; Johnson, E.A.; Köhler, J.; Lochner, A.; Quosh, J.; Zeuner, A.; Eisenhauer, N. Invasive earthworms can change understory plant community traits and reduce plant functional diversity. Iscience 2024, 27, 109036. [Google Scholar] [CrossRef] [PubMed]
  31. Thouvenot, L.; Ferlian, O.; Beugnon, R.; Künne, T.; Lochner, A.; Thakur, M.P.; Türke, M.; Eisenhauer, N. Do invasive earthworms affect the functional traits of native plants? Front. Plant Sci. 2021, 12, 627573. [Google Scholar] [CrossRef]
  32. Eisenhauer, N.; Butenschoen, O.; Radsick, S.; Scheu, S. Earthworms as seedling predators: Importance of seeds and seedlings for earthworm nutrition. Soil Biol. Biochem. 2010, 42, 1245–1252. [Google Scholar] [CrossRef]
  33. Cassin, C.M.; Kotanen, P.M. Invasive earthworms as seed predators of temperate forest plants. Biol. Invasions 2016, 18, 1567–1580. [Google Scholar] [CrossRef]
  34. Burton, J.I.; Perakis, S.S.; Brooks, J.R.; Puettmann, K.J. Trait integration and functional differentiation among co-existing plant species. Am. J. Bot. 2020, 107, 628–638. [Google Scholar] [CrossRef]
  35. Greenop, A.; Woodcock, B.A.; Pywell, R.F. Using functional traits to predict pollination services: A review. J. Pollinat. Ecol. 2023, 35, 194–206. [Google Scholar] [CrossRef]
  36. Schwarz, R.; Eisenhauer, N.; Ferlian, O.; Maestre, F.T.; Rosenbaum, B.; Uthe, H.; Thouvenot, L. Invasive earthworms modulate native plant trait expression and competition. Oikos 2023, 2024, e10008. [Google Scholar] [CrossRef]
  37. Neill, A.R.; Puettmann, K.J. Managing for adaptive capacity: Thinning improves food availability for wildlife and insect pollinators under climate change conditions. Can. J. For. Res. 2013, 43, 428–440. [Google Scholar] [CrossRef]
  38. Horsley, S.B.; Long, R.P. Sugar Maple Ecology and Health. In Proceedings of the International Symposium, Warren, PA, USA, 2–4 June 1998; Gen Tech Rep NE-261, 1999. United States Department of Agriculture (USDA) Forest Service, Northeastern Research Station: Radnor, PA, USA, 1999. [Google Scholar]
  39. Godman, R.M.; Mendel, J.J. Economic Values for Growth and Grade Changes of Sugar Maple in the Lake States; Res. Pap. MC-155, 1978; United States Department of Agriculture (USDA) Forest Service, North Central Forest Experiment Station: St. Paul, MN, USA, 1978; 16p.
  40. Webster, C.R.; Reed, D.D.; Orr, B.D.; Schmierer, J.M.; Pickens, J.B. Expected rates of value growth for individual sugar maple crop trees in the Great Lakes Region. North. J. Appl. For. 2009, 26, 133–140. [Google Scholar] [CrossRef]
  41. Bal, T.L.; Storer, A.J.; Jurgensen, M.F. Evidence of damage from exotic invasive earthworm activity was highly correlated to sugar maple dieback in the Upper Great Lakes region. Biol. Invasions 2018, 20, 151–164. [Google Scholar] [CrossRef]
  42. Edwards, C.A. The assessment of populations of soil-inhabiting invertebrates. Agric. Ecosyst. Environ. 1991, 34, 145–176. [Google Scholar] [CrossRef]
  43. Loss, S.R.; Hueffmeier, R.M.; Hale, C.M.; Host, G.E.; Sjerven, G.; Frelich, L.E. Earthworm Invasions in Northern Hardwood Forests: A Rapid Assessment Method. Nat. Areas J. 2013, 33, 21–30. [Google Scholar] [CrossRef]
  44. Bouché, M.B. Strategies lombriciennes. Ecol. Bull. 1977, 25, 122–132. [Google Scholar]
  45. Edwards, C.A.; Arancon, N.Q. Earthworm Ecology: Communities. In Biology and Ecology of Earthworms; Edwards, C.A., Arancon, N.Q., Eds.; Springer: New York, NY, USA, 2022; pp. 151–190. [Google Scholar] [CrossRef]
  46. Hale, C. Earthworms of the Great Lakes; Kollath + Stensaas: Duluth, MN, USA, 2013. [Google Scholar]
  47. Brady, M.E. Decadal Reevaluation of Sugar Maple Dieback Etiology Across the Upper Great Lakes Region. Master’s Thesis, Michigan Technological University, Houghton, MI, USA, 2022. [Google Scholar] [CrossRef]
  48. Kruskal, J.B. Nonmetric multidimensional scaling: A numerical method. Psychometrika 1964, 29, 115–129. [Google Scholar] [CrossRef]
  49. Mather, P.M. Computational Methods of Multivariate Analysis in Physical Geography; J. Wiley & Sons: London, UK, 1976; Available online: https://cir.nii.ac.jp/crid/1130000794145289728 (accessed on 10 January 2022).
  50. Burton, J.I.; Mladenoff, D.J.; Forrester, J.A.; Clayton, M.K. Experimentally linking disturbance, resources and productivity to diversity in forest ground-layer plant communities. J. Ecol. 2014, 102, 1634–1648. [Google Scholar] [CrossRef]
  51. Gleason, H.A.; Cronquist, A. Manual of Vascular Plants of Northeastern United States and Adjacent Canada; New York Botanical Garden: New York, NY, USA, 1991. [Google Scholar]
  52. Holmgren, N.H.; Holmgren, P.K. Illustrated Companion to Gleason and Cronquist’s Manual: Illustrations of the Vascular Plants of Northeastern United States and Adjacent Canada; New York Botanical Garden: New York, NY, USA, 1998. [Google Scholar]
  53. Waller, D.; Paulson, A.K.; Richards, J.; Alverson, W.S.; Bai, C.; Amatangelo, K.L.; Johnson, S.E.; Li, D.; Sonnier, G.; Toczydlowski, R.H. Functional trait data for vascular plant species from eastern North America. Ecology 2021, 103, e03527. [Google Scholar] [CrossRef]
  54. Montgomery, F.H. Seeds and Fruits of Plants of Eastern Canada and Northeastern United States; University of Toronto Press: Toronto, ON, Canada, 1977. [Google Scholar] [CrossRef]
  55. McCune, B.; Grace, J.B. Analysis of Ecological Communities; MjM Software Design: Gleneden Beach, OR, USA, 2002. [Google Scholar]
  56. Allen, D.C.; Barnett, C.J.; Millers, I.; Lachance, D. Temporal change (1988–1990) in sugar maple health, and factors associated with crown condition. Can. J. For. Res. 1992, 22, 1776–1784. [Google Scholar] [CrossRef]
  57. Mielke, P.W.; Berry, K.J. Permutation Methods: A Distance Function Approach, 2nd ed.; Springer: New York, NY, USA, 2007. [Google Scholar] [CrossRef]
  58. Biondini, M.E.; Bonham, C.D.; Redente, E.F. Secondary successional patterns in a sagebrush (Artemisia tridentata) community as they relate to soil disturbance and soil biological activity. Vegetatio 1985, 60, 25–36. [Google Scholar] [CrossRef]
  59. Dufrêne, M.; Legendre, P. Species assemblages and indicator species: The need for a flexible asymmetrical approach. Ecol. Monogr. 1997, 67, 345–366. [Google Scholar] [CrossRef]
  60. Drouin, M.; Bradley, R.; Lapointe, L. Linkage between exotic earthworms, understory vegetation and soil properties in sugar maple forests. For. Ecol. Manag. 2016, 364, 113–121. [Google Scholar] [CrossRef]
  61. Hopfensperger, K.N.; Leighton, G.M.; Fahey, T.J. Influence of invasive earthworms on above and belowground vegetation in a northern hardwood forest. Am. Midl. Nat. 2011, 166, 53–62. [Google Scholar] [CrossRef]
  62. Hale, C.M.; Frelich, L.E.; Reich, P.B. Exotic European earthworm invasion dynamics in northern hardwood forests of Minnesota, USA. Ecol. Appl. 2005, 15, 848–860. [Google Scholar] [CrossRef]
  63. Beauséjour, R.; Handa, I.T.; Lechowicz, M.J.; Gilbert, B.; Vellend, M. Historical anthropogenic disturbances influence patterns of non-native earthworm and plant invasions in a temperate primary forest. Biol. Invasions 2015, 17, 1267–1281. [Google Scholar] [CrossRef]
  64. Alexander, G.; Almendinger, J.; White, P. The long-term effects of invasive earthworms on plant community composition and diversity in a hardwood forest in northern Minnesota. Plant-Environ. Interact. 2022, 3, 89–102. [Google Scholar] [CrossRef] [PubMed]
  65. Mathieu, J.; Reynolds, J.W.; Fragoso, C.; Hadly, E. Multiple invasion routes have led to the pervasive introduction of earthworms in North America. Nat. Ecol. Evol. 2024, 8, 489–499. [Google Scholar] [CrossRef]
  66. Scheu, S. Effects of earthworms on plant growth: Patterns and perspectives. Pedobiologia 2003, 47, 846–856. [Google Scholar] [CrossRef]
  67. Madritch, M.D.; Lindroth, R.L. Removal of invasive shrubs reduces exotic earthworm populations. Biol. Invasions 2009, 11, 663–671. [Google Scholar] [CrossRef]
  68. Whitfeld, T.J.; Roth, A.M.; Lodge, A.G.; Eisenhauer, N.; Frelich, L.E.; Reich, P.B. Resident plant diversity and introduced earthworms have contrasting effects on the success of invasive plants. Biol. Invasions 2014, 16, 2181–2193. [Google Scholar] [CrossRef]
  69. Dávalos, A.; Nuzzo, V.; Blossey, B. Single and interactive effects of deer and earthworms on non-native plants. For. Ecol. Manag. 2015, 351, 28–35. [Google Scholar] [CrossRef]
  70. Clause, J.; Forey, E.; Lortie, C.J.; Lambert, A.M.; Barot, S. Non-native earthworms promote plant invasion by ingesting seeds and modifying soil properties. Acta Oecologica 2015, 64, 10–20. [Google Scholar] [CrossRef]
  71. Kimmerer, R.W. Patterns of dispersal and establishment of bryophytes colonizing natural and experimental treefall mounds in northern hardwood forests. Bryologist 2005, 108, 391–401. [Google Scholar] [CrossRef]
  72. Corio, K.; Wolf, A.; Draney, M.; Fewless, G. Exotic earthworms of great lakes forests: A search for indicator plant species in maple forests. For. Ecol. Manag. 2009, 258, 1059–1066. [Google Scholar] [CrossRef]
  73. Snyder, S.A. Gymnocarpium dryopteris. In Fire Effects Information System [Online]; United States Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory: Missoula, MT, USA, 1993. Available online: www.fs.usda.gov/database/feis//plants/fern/gymdry/all.html (accessed on 1 March 2022).
  74. Adams, A.B.; Dale, V.H.; Kruckeberg, A.R. Plant survival, growth form and regeneration following the 18 May eruption of Mount St. Helens, Washington. Northwest Sci. 1987, 61, 160–170. [Google Scholar]
  75. Walkup, C.J. Athyrium filix-femina. In Fire Effects Information System [Online]; United States Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory: Missoula, MT, USA, 1991. Available online: https://www.fs.usda.gov/database/feis/plants/fern/athfil/all.html#1 (accessed on 1 March 2022).
  76. Holdsworth, A.R.; Frelich, L.E.; Reich, P.B. Effects of earthworm invasion on plant species richness in northern hardwood forests. Conserv. Biol. 2007, 21, 997–1008. [Google Scholar] [CrossRef]
  77. Loss, S.R.; Blair, R.B. Earthworm invasions and the decline of clubmosses (Lycopodium spp.) that enhance nest survival rates of a ground-nesting songbird. For. Ecol. Manag. 2014, 324, 64–71. [Google Scholar] [CrossRef]
  78. Jain, P.; Khare, S.; Sylvain, J.D.; Raymond, P.; Rossi, S. Predicting the location of maple habitat under warming scenarios in two regions at the northern range in Canada. For. Sci. 2021, 67, 446–456. [Google Scholar] [CrossRef]
  79. Auclair, A.N.D.; Lill, J.T.; Revenga, C. The role of climate variability and global warming in the dieback of Northern Hardwoods. Water Air Soil Pollut. 1996, 91, 163–186. [Google Scholar] [CrossRef]
  80. Burton, J.I.; Zenner, E.K.; Frelich, L.E. Frost crack incidence in northern hardwood forests of the southern boreal-north temperate transition zone. J. Appl. For. 2008, 25, 133–138. [Google Scholar] [CrossRef]
  81. Proctor, E.; Nol, E.; Burke, D.; Crins, W.J. Responses of insect pollinators and understory plants to silviculture in northern hardwood forests. Biodivers. Conserv. 2012, 21, 1703–1740. [Google Scholar] [CrossRef]
  82. Malloch, D.; Malloch, B. The mycorrhizal status of boreal plants: Species from northeastern Ontario. Can. J. Bot. 1981, 59, 2167–2172. [Google Scholar] [CrossRef]
  83. Paudel, S.; Longcore, T.; MacDonald, B.; McCormick, M.K.; Szlavecz, K.; Wilson, G.W.T.; Loss, S.R. Belowground interactions with aboveground consequences: Invasive earthworms and arbuscular mycorrhizal fungi. Ecology 2016, 97, 605–614. [Google Scholar] [CrossRef]
Figure 1. Map of plots assessed for A. saccharum canopy dieback, earthworm impacts, and ground-layer plant-community composition in 2010 and 2021. Gray areas labeled by name are national forest units found in the Lake Superior region in Michigan, northeastern Minnesota, and northern Wisconsin, and black dots are plot locations.
Figure 1. Map of plots assessed for A. saccharum canopy dieback, earthworm impacts, and ground-layer plant-community composition in 2010 and 2021. Gray areas labeled by name are national forest units found in the Lake Superior region in Michigan, northeastern Minnesota, and northern Wisconsin, and black dots are plot locations.
Forests 16 01583 g001
Figure 2. NMS ordinations showing traits in 2010 (a) and in 2021 (b) in two-dimensional ordination space. Environmental variables (EVs) strongly correlated with axes 1 and/or 2 (r > 0.35) are shown as vectors. EVs are plotted in ordination space using Pearson correlation coefficients corresponding to each axis.
Figure 2. NMS ordinations showing traits in 2010 (a) and in 2021 (b) in two-dimensional ordination space. Environmental variables (EVs) strongly correlated with axes 1 and/or 2 (r > 0.35) are shown as vectors. EVs are plotted in ordination space using Pearson correlation coefficients corresponding to each axis.
Forests 16 01583 g002
Figure 3. Plot of a non-metric multidimensional scaling (NMS) ordination of 38 ground-layer taxa sampled across the network of 41 national forest plots in 2021. Each point represents a taxon. Vectors represent environmental variables with r2 values > 0.2, and environmental variable labels are in text boxes. Vectors are plotted in ordination space using Pearson correlation coefficients corresponding to each axis, and taxa near and in the direction of each vector are associated with the environmental trait represented by the given vector.
Figure 3. Plot of a non-metric multidimensional scaling (NMS) ordination of 38 ground-layer taxa sampled across the network of 41 national forest plots in 2021. Each point represents a taxon. Vectors represent environmental variables with r2 values > 0.2, and environmental variable labels are in text boxes. Vectors are plotted in ordination space using Pearson correlation coefficients corresponding to each axis, and taxa near and in the direction of each vector are associated with the environmental trait represented by the given vector.
Forests 16 01583 g003
Table 1. Summary of 41 plots in national forest units remeasured in 2021. Values are averages unless indicated, parentheses are minimum-max, SE, or SE alone. Positive sign of Δ dieback percentage indicates increased percentage of crown dieback between 2010 and 2021.
Table 1. Summary of 41 plots in national forest units remeasured in 2021. Values are averages unless indicated, parentheses are minimum-max, SE, or SE alone. Positive sign of Δ dieback percentage indicates increased percentage of crown dieback between 2010 and 2021.
SUCHNIOTHI
N plots658175
A. saccharum canopy dieback (% per tree)42.2
(21.0–78.5, 8.1)
12.4
(3.1–34.1, 5.5)
16.7
(1.5–34.5, 4.1)
15.0
(2.9–37.5, 2.8)
15.9
(10.0–25.3, 4.6)
Δ from 2010+26.8 (6.8)+2.42 (5.3)+4.9 (4.7)+5.8 (2.3)+7.9 (3.2)
Distance from Lake Superior (km)8.8590.1196.6831.589.44
Ground-layer plant taxon richness (S) (species per m2)15.3 (0.96)16.2 (0.74)13.25 (1.01)16.12 (0.73)13.2 (0.53)
Evenness (H/ln(S))0.87 (0.02)0.92 (0.01)0.85 (0.03)0.90 (0.01)0.92 (0.03)
Ground-layer Shannon’s diversity index (H)2.38 (0.07)2.57 (0.03)2.17 (0.1)2.47 (0.05)2.36 (0.11)
Canopy density
(% closure)
72
(38–88, 8)
93
(91–95, 1)
90
(81–95, 2)
88
(61–94, 2)
86
(76–95, 3)
Note: SU = Superior, CH = Chequamegon, NI = Nicolet, OT = Ottawa, HI = Hiawatha National Forests.
Table 2. Summary of forest-floor rating and density metrics for 41 plots in national forest units remeasured in 2021. Values are means unless indicated, parentheses are minimum-max, SE, or SE alone. Negative sign on Δ forest-floor rating corresponds to a decrease in condition of the forest floor between 2010 and 2021. Values for “All worms” and each ecological guild are proportions of plots in which each guild was found (i.e., value of 1 = 100% of plots in the national forest unit).
Table 2. Summary of forest-floor rating and density metrics for 41 plots in national forest units remeasured in 2021. Values are means unless indicated, parentheses are minimum-max, SE, or SE alone. Negative sign on Δ forest-floor rating corresponds to a decrease in condition of the forest floor between 2010 and 2021. Values for “All worms” and each ecological guild are proportions of plots in which each guild was found (i.e., value of 1 = 100% of plots in the national forest unit).
SUCHNIOTHI
N plots658175
Forest-floor rating (1–5)1.33
(1.0–2.0, 0.17)
1.0
(1.0–1.0, 0)
2.25
(1.0–3.0, 0.25)
2.78
(1.0–5.0, 0.37)
4.6
(3.5–5.0, 0.29)
Δ from 2010−3.67 (0.17)−3.8 (0.2)−1.59 (0.26)−1.66 (0.36)−0.35 (0.31)
Earthworms (presence/absence)1 (0)1 (0)1 (0)0.82 (0.09)0.4 (0.12)
Juvenile Lumbricus0.83 (0.15)1 (0)0.88 (0.12)0.53 (0.12)0 (0)
Epigeic0.83 (0.15)1 (0)1 (0) 0.76 (0.10)0.2 (0.10)
Endogeic0.17 (0.15)1 (0)1 (0)0.24 (0.10)0.2 (0.10)
Epi-endogeic0.83 (0.15)0 (0)0.13 (0.12)0.12 (0.08)0 (0)
Anecic0.17 (0.15)0.4 (0.22)0.63 (0.17)0.24 (0.10)0.4 (0.12)
Note: SU = Superior, CH = Chequamegon, NI = Nicolet, OT = Ottawa, HI = Hiawatha National Forests.
Table 3. Plot groupings by earthworm assemblages found across 41 plots in five national forest units of the Lake Superior region. Groups were determined by cluster analysis. Iterative indicator species analyses of earthworm assemblages were used to prune the resulting dendrogram by minimizing the average p value.
Table 3. Plot groupings by earthworm assemblages found across 41 plots in five national forest units of the Lake Superior region. Groups were determined by cluster analysis. Iterative indicator species analyses of earthworm assemblages were used to prune the resulting dendrogram by minimizing the average p value.
Group Characterizationn
1No earthworms6
2Epigeic-dominated21
3High earthworm diversity11
4Juvenile Lumbricus/L. rubellus3
Table 4. Pearson correlation coefficients for species taxa (from main matrices) and for environmental variables (from secondary matrices) with NMS ordination axes for each of the two ordinations based on ground-layer plant composition in 2010 and 2021. Only coefficients corresponding to an r > 0.35 (r2 > 0.12) for either axes 1 or 2 are shown, all of which are significant correlations (p < 0.05). The strongest correlations for each are in bold.
Table 4. Pearson correlation coefficients for species taxa (from main matrices) and for environmental variables (from secondary matrices) with NMS ordination axes for each of the two ordinations based on ground-layer plant composition in 2010 and 2021. Only coefficients corresponding to an r > 0.35 (r2 > 0.12) for either axes 1 or 2 are shown, all of which are significant correlations (p < 0.05). The strongest correlations for each are in bold.
Axis 1Axis 2Axis 3
2010Aralia nudicaulis0.566−0.3050.258
Arisaema triphyllum−0.654−0.175−0.082
Asarum canadense0.5180.443−0.041
Aster spp.0.5130.338−0.46
Athyrium filix-femina0.6180.027−0.117
Caulophyllum thalictroides−0.615−0.006−0.442
Circaea alpina−0.034−0.5660.044
Clintonia borealis0.410.5410.033
Coptis trifolia0.362−0.4650.295
Cornus alternifolia−0.8660.007−0.052
Cornus foemina0.301−0.742−0.337
Dryopteris spp.−0.2220.509−0.494
Galium spp.0.228−0.763−0.022
Poaceae spp.−0.122−0.787−0.022
Hepatica americana0.11−0.6290.097
Hieracium spp.−0.848−0.001−0.015
Impatiens capensis0.044−0.690.082
Laportea canadensis−0.8390.125−0.003
Lonicera canadensis−0.7670.2180.041
Mitella nuda−0.041−0.5490.191
Mitchella repens−0.8660.007−0.052
Bryophyta spp.−0.597−0.240.28
Osmunda claytoniana0.318−0.514−0.522
Pyrola spp.−0.8660.007−0.052
Ranunculus spp.−0.680.007−0.507
Ribes spp.−0.842−0.1060.069
Rubus canadensis−0.8660.007−0.052
Rubus strigosus0.6080.073−0.252
Sanguinaria canadensis0.044−0.690.082
Carex spp.−0.228−0.765−0.234
Trillium spp.0.163−0.5450.17
Forest-floor rating0.5170.3750.171
Distance to L. Superior0.023−0.5830.171
Latitude0.1390.546−0.059
2021Anemone quinquefolia0.052−0.4120.155
Athyrium filix-femina0.125−0.40.337
Clintonia borealis0.7020.057−0.22
Lycopodiaceae spp.0.2150.680.157
Maianthemum canadense0.098−0.5190.201
Bryophyta spp.−0.698−0.077−0.434
Phegopteris connectilis0.389−0.259−0.202
Ribes spp.−0.017−0.3940.422
Carex spp.−0.69−0.024−0.217
Trientalis borealis0.590.037−0.38
Trillium spp.−0.207−0.388−0.153
Forest-floor rating−0.050.5970.157
Lumbricus rubellus0.4760.185−0.065
Juvenile Lumbricus−0.052−0.44−0.028
Epi-endogeic worms0.4890.178−0.053
Epi-endogeic, proportion0.5380.044−0.012
Latitude0.5990.082−0.121
Distance to L. Superior−0.42−0.264−0.145
Table 5. Pearson correlation coefficients for community traits (from main matrices) and environmental variables (from secondary matrices) with NMS ordination axes for each of the two ordinations based on ground-layer plant traits in 2010 and 2021. Only coefficients corresponding to an r > 0.35 (r2 > 0.12) for either axes 1 or 2 are shown, all of which are significant correlations (p < 0.05). The strongest correlations for each are in bold.
Table 5. Pearson correlation coefficients for community traits (from main matrices) and environmental variables (from secondary matrices) with NMS ordination axes for each of the two ordinations based on ground-layer plant traits in 2010 and 2021. Only coefficients corresponding to an r > 0.35 (r2 > 0.12) for either axes 1 or 2 are shown, all of which are significant correlations (p < 0.05). The strongest correlations for each are in bold.
Axis 1Axis 2Axis 3
2010Graminoids−0.2680.619
Forbs−0.724−0.4
Ferns−0.3870.331-
Perennials−0.7560.48-
Geophytes−0.679−0.218-
Abiotic seed dispersal−0.4890.298-
Biotic seed dispersal−0.679−0.415-
Vertebrate seed dispersal−0.651−0.45-
Large seeds−0.563−0.245-
Early flowering−0.744−0.385-
Mid-flowering−0.702−0.425-
Abiotic pollination−0.4470.778-
Biotic pollination−0.746−0.42-
2021Forbs−0.6670.4760.084
Shrubs−0.5120.057−0.069
Ferns−0.373−0.666−0.335
Hemicryptophytes−0.331−0.628−0.353
Geophytes−0.6450.302−0.158
Abiotic seed dispersal−0.483−0.6120.025
Biotic seed dispersal−0.5790.2270.016
Vertebrate seed dispersal−0.6850.346−0.046
Large seeds−0.6140.445−0.127
Early flowering−0.7820.3730
Mid-flowering−0.7720.3440.007
Abiotic pollination−0.375−0.6180.492
Biotic pollination−0.7970.3740.013
Native−0.764−0.188−0.318
A. saccharum dieback−0.4230.099−0.157
Tree density (trees/area)−0.1120.4450.1
Epi-endogeic, proportion−0.2530.406−0.108
Latitude−0.4280.152−0.222
Table 6. Results of indicator species analysis for ground-layer community data collected in two study periods from a network of 41 national forest plots. p-values are listed for traits in sample plots with strong associations (p < 0.1) with categorical variables. Significant Monte Carlo permutation test results (p < 0.05) are in bold.
Table 6. Results of indicator species analysis for ground-layer community data collected in two study periods from a network of 41 national forest plots. p-values are listed for traits in sample plots with strong associations (p < 0.1) with categorical variables. Significant Monte Carlo permutation test results (p < 0.05) are in bold.
Taxon20102021
Forest-Floor RatingForest-Floor RatingEarthworm AbundanceEarthworm AssemblageAnecic Presence
Poor (>20%)IntactPoorAbsencePresenceHighDiverseJuvenile Lumbricus
Aster spp. 0.036
Athyrium filix-femina 0.024 0.046 0.082
Bryophyta (s. str.)0.032 0.017
Carex spp. 0.088 0.01
Caulophyllum thalictroides0.032
Clintonia borealis 0.002
Dryopteris spp. 0.045
Gymnocarpium dryopteris 0.085
Lycopodiaceae spp. 0.002 < 0.001
Maianthemum racemosum 0.027 0.041
Phegopteris connectilis 0.038
Poaceae spp. 0.033 0.049
Polygonatum pubescens 0.052
Ranunculus spp.0.033
Ribes spp.0.025
Trientalis borealis 0.0892
Trillium spp. 0.029 0.013
Veronica spp. 0.026 0.059 0.035
Table 7. Results of indicator species analysis for ground-layer community data and earthworm variables collected in two study periods from a network of 41 national forest plots. p-values are listed for traits in sample plots with strong associations (p < 0.1) with categorical variables. Significant Monte Carlo permutation test results (p < 0.05) are in bold.
Table 7. Results of indicator species analysis for ground-layer community data and earthworm variables collected in two study periods from a network of 41 national forest plots. p-values are listed for traits in sample plots with strong associations (p < 0.1) with categorical variables. Significant Monte Carlo permutation test results (p < 0.05) are in bold.
Taxon20102021
National ForestA. saccharum canopy diebackNational ForestA. saccharum canopy dieback
Severe (>20%)Low (<10%)Severe (>20%)
Aster spp. SU 0.013
Athyrium filix-femina 0.041
Carex spp. NI 0.02
Clintonia borealis SU < 0.0010.008SU < 0.001 <0.001
Dryopteris spp. HI 0.066
Lycopodiaceae spp. HI 0.005
Maianthemum canadense CH 0.0080.068
Phegopteris connectilis SU 0.011 0.026
Poaceae spp. CH 0.03 0.088
Rubus strigosus 0.019
Trientalis borealis 0.096
Trillium spp.CH 0.019 CH 0.059
Note: SU = Superior, CH = Chequamegon, HI = Hiawatha, NI = Nicolet National Forests.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Bal, T.L.; Anderson, M.E.; Brady, M.E.; Burton, J.I.; Webster, C.R. Decadal Changes in Ground-Layer Plant Communities Reflect Maple Dieback and Earthworm Invasion in National Forests in the Lake Superior Region, USA. Forests 2025, 16, 1583. https://doi.org/10.3390/f16101583

AMA Style

Bal TL, Anderson ME, Brady ME, Burton JI, Webster CR. Decadal Changes in Ground-Layer Plant Communities Reflect Maple Dieback and Earthworm Invasion in National Forests in the Lake Superior Region, USA. Forests. 2025; 16(10):1583. https://doi.org/10.3390/f16101583

Chicago/Turabian Style

Bal, Tara L., Manuel E. Anderson, Mattison E. Brady, Julia I. Burton, and Christopher R. Webster. 2025. "Decadal Changes in Ground-Layer Plant Communities Reflect Maple Dieback and Earthworm Invasion in National Forests in the Lake Superior Region, USA" Forests 16, no. 10: 1583. https://doi.org/10.3390/f16101583

APA Style

Bal, T. L., Anderson, M. E., Brady, M. E., Burton, J. I., & Webster, C. R. (2025). Decadal Changes in Ground-Layer Plant Communities Reflect Maple Dieback and Earthworm Invasion in National Forests in the Lake Superior Region, USA. Forests, 16(10), 1583. https://doi.org/10.3390/f16101583

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop