Michael J. Gundale’s research while affiliated with Swedish University of Agricultural Sciences and other places

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Publications (143)


Figure 1. Neighbor-joining tree of representative sequences from obtained clusters and reference sequences belonging to lichens (Lecanoromycetes -Ascomycota) found across all samples. Three orders are present across all samples, each represented by a different color (light blue= Agyriales; yellow = Pertusariales; orange = Lecanorales). All branch nodes with boot-strap values of > 70 are shown with full lines indicating strong support, while those with values < 70 are shown with dashed lines, indicating weaker support. Agyriales and Pertusariales are typically associated with crustose growth forms that adhere tightly to substrate surface, and are often found on rocks, bark or soil.
Figure 2. The effects of shrub removals [shrub present (+S) or shrub absent (−S)] and moss removals [moss present (+M) or moss absent (−M)] across contrasting island size classes [Large (red), Medium (blue), and Small (green)] on the biomass of (a) lichens (% OTU corrected by PLFA), or (b) shrubs and mosses (allometric equations). Boxplots represent the central 50% of the data representing lichen or shrub + moss biomass, and the whiskers on the boxplots represent the 95% percentiles. The grey circles within each boxplot represent the mean. Island size classes topped by the same capital letter do not differ, and within island size classes removal treatments topped with the same lower case letter do not differ (Tukey's HSD test, α = 0.05); results of mixed linear model analyses for this data are given in Table 1.
Figure 3. Average relative abundance (% of total OTUs) of each lichen order (Agyriales, Pertusariales and Lecanorales) in the lichen community after shrub removals [shrub present (+S) or shrub absent (−S)] and moss removals [moss present (+M) or moss absent (−M)] across contrasting island size classes. We used Tukey's HSD test to compare the different treatments across island size classes for the orders Agyriales, Pertusariales and Lecanorales. Removal treatments with the same lowercase letter do not differ (Tukey's HSD test, α = 0.05).
Figure 4. The effects of shrub removals [shrub present (+S) or shrub absent (−S)] and moss removals [moss present (+M) or moss absent (−M)] across contrasting island size classes [Large (red), Medium (blue), and Small (green)] on (a) lichen alpha diversity (species richness), and (b) lichen beta-diversity (dissimilarity among communities). Boxplots represent the central 50% of the data representing beta-diversity (dissimilarity among contrasting lichen communities) and the whiskers on the boxplots represent the 95% percentiles. The grey circles within each boxplot represent the mean. Island size classes topped by the same capital letter do not differ, and within island size classes removal treatments topped with the same lower case letter do not differ (Tukey's HSD test, α = 0.05).
Figure 5. Non-metric multidimensional scaling (NMDS) ordination based on Bray-Curtis distances of lichen OTUs, showing the effects of shrub presence (+S; shaded ellipses) versus removal (−S; unshaded ellipses) across contrasting island size classes [Large (red), Medium (blue), and Small (green)]. Vectors represent the goodnessof-fit statistics (r 2 ) of vegetation parameters fitted to the NMDS.

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Effects of boreal ground layer shrubs and bryophytes on the diversity, biomass and composition of lichen communities across contrasting ecosystems
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April 2025

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113 Reads

Oikos

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Michael J. Gundale

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There has been much recent interest in understanding how abiotic factors such as light, nutrients, and soil moisture affect the composition and biomass of lichen communities. Meanwhile, whether and how ground layer vegetation such as bryophytes and shrubs also influence lichen communities have received much less attention, particularly regarding how these effects vary across environmental gradients. In this study, we used a long‐term (19‐year) biodiversity manipulation experiment to assess the importance of feather moss and ericaceous dwarf shrub removals on the composition and diversity (assessed via metabarcoding) and biomass (assessed via PLFA markers) of terricolous lichen communities along a 5000‐year boreal forest post‐fire chronosequence in northern Sweden. Overall, our results showed that shrub removals had a greater impact than moss removals on the biomass and composition of lichen communities. Shrub removals increased lichen alpha‐diversity while decreasing lichen beta‐diversity. This is mainly because, although the number of lichen species increased in the absence of shrubs, lichen communities were strongly dominated by Cladonia spp. However, the effects of shrub removals were context‐dependent, with greater effects observed in older ecosystems. Our results highlight that shrubs had a greater impact than moss in shaping terricolous lichen communities in boreal forests, with increasing effects from young ecosystems to older ones. We conclude that the foreseen expansion of vascular plants such as ericaceous shrubs into high latitude regions will probably have negative consequences on lichen cover, but that these effects will be dependent on the environmental context.

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The negative relationship between the leaf Amax of tree species and tree growth
Tree growth was quantified based on several metrics and values are standardized to enable comparisons among sites using the approach of the log growth ratio (positive values and negative values indicate values higher and lower than the site mean value, respectively; Methods). Results are presented by latitude class (high-latitudes sites, |latitude| ≥ 45°; intermediate sites, 23° < |latitude| < 45°; tropical sites, |latitude| ≤ 23°). A linear regression was fitted (level of confidence of the error band = 0.95) for each class (for high-latitude, intermediate and tropical sites, respectively: P = 1.7 × 10⁻⁴, P = 0.005 and P = 0.379; t = −3.79, −2.83 and 0.88; d.f. = 499, 434 and 135; n = 501, 436 and 137). ***P < 0.001; **P < 0.010; NS, not significant, P ≥ 0.100). For readability, data points are not presented together with regression lines and error bands (data points are presented class by class in Extended Data Fig. 3). Results are confirmed when presented by an independent dataset (Supplementary Methods 1).
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The influence of site productivity on growth–trait relationships
a–d, Site productivity (x axis) is the mean growth value of all tree species of a given site (in cm per year of height growth). The correlation coefficient (y axis) refers to the relationship at a given site between tree species growth and species trait value: positive y-axis values and negative y-axis values indicate a positive growth–trait correlation and a negative growth–trait correlation, respectively (Pearson method). The presented traits are as follows: wood density (a), SLA (b), leaf Amax (c) and SRL (d). Data were selected from the sites that had at least ten different tree species, which comprised all EAN sites (triangles), three TDN sites (squares) and four TED sites (diamonds). The black line represents the linear regression between the productivity and correlation r value (with the P value in parentheses). As the TDN and TED sites did not have the same number of tree species as the EAN sites, and because r values tend to increase with decreasing size of data (Methods), the TDN–TED sites were not used to fit the regressions. One TDN site had very high r values that were beyond the y-axis limit (b and c) and this was plotted in the upper part of the graph (with its r value in brackets). Two TED sites had very high site productivity and their correlation value was indicated with red arrows. Six examples of relationships between growth and trait values are presented in Extended Data Fig. 6, and these six sites are identified by the letters A–F (b). For a–d, the respective statistics were as follows: t = 2.80, 2.15, 2.02 and 2.56; d.f. = 30 and n = 32 in all cases; r = 0.45, 0.37, 0.35 and 0.42.
Source data
Growth rates according to species strategy and resource supply
a,b, The expected response of tree species to environmental conditions. The current paradigm, which is adapted from a previous study²³, with acquisitive species and conservative species representing high- and low-resource species, respectively (a), and a revised version of the paradigm (b). c,d, This revised version is supported by the results of this study of tree species growth along gradients of site productivity for young trees (c; the dataset, EAN + TDN + TED) and mature stands (d; dataset, SBD). Values were standardized to enable comparison of sites from all datasets (Methods). Growth strategies (that is, acquisitive versus conservative) were defined a priori, based on theory and trait values (leaf Amax, SLA and leaf N; Methods). Sites that included only acquisitive species, or only conservative species, were not taken into account in data analyses. Three classes of site productivity were defined based on percentiles 33% and 66%, before testing possible differences between acquisitive and conservative species (two-sided Kruskal–Wallis test). A linear regression was fitted (level of confidence of the error band = 0.95) for each growth strategy. The slope difference was tested using covariance analysis. As the number of species highly varied from site to site, values were averaged by site (that is, one acquisitive average value + one conservative average value per site) to give the same statistical weight to all sites. n was 776 and 288 for individual values, which were averaged into 92 and 150 final values for c and d. Test of slope difference: F = 16.11 and 9.48 for c and d (averaged values). The results remained unchanged if individual values were used. Similarly, the results remained statistically significant if the two outlier sites (identified in the ‘Assessment of the datasets’ section of the Methods) were included.
Source data
The effective ability of acquisitive tree species and conservative tree species to grow fast
a–d, Growth strategies (that is, acquisitive versus conservative) were defined a priori based on theory and trait values (leaf Amax, SLA and leaf N; Methods). Growth values were standardized to enable comparison of sites from all datasets (Methods). Results are presented together (a) and by latitudinal classes (high (b), intermediate (c) and tropical (d)), with 23° and 45° as limit values. The results are confirmed when presented by dataset (Supplementary Methods 2). Sites that included only acquisitive species, or only conservative species, were not taken into account in data analyses. As the number of species highly varied from site to site, values were averaged by site (that is, one acquisitive average value + one conservative average value per site) to give the same statistical weight to all sites. n was 1,159, 514, 427 and 218 for individual values, which were averaged into 256, 124, 90 and 42 final values for a–d. The box plots represent the median (centre line), the first and third quartiles (box limits) and 1.5× the interquartile range (whiskers). Different letters indicate a significant difference between the two growth strategies. Differences were tested using the two-sided Kruskal–Wallis non-parametric test. For a–d, χ² = 40.41, 32.83, 22.44 and 0.51; d.f. = 1 in all cases. The results remained unchanged if individual values were used.
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Widespread slow growth of acquisitive tree species

March 2025

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1,049 Reads

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2 Citations

Nature

Trees are an important carbon sink as they accumulate biomass through photosynthesis¹. Identifying tree species that grow fast is therefore commonly considered to be essential for effective climate change mitigation through forest planting. Although species characteristics are key information for plantation design and forest management, field studies often fail to detect clear relationships between species functional traits and tree growth². Here, by consolidating four independent datasets and classifying the acquisitive and conservative species based on their functional trait values, we show that acquisitive tree species, which are supposedly fast-growing species, generally grow slowly in field conditions. This discrepancy between the current paradigm and field observations is explained by the interactions with environmental conditions that influence growth. Acquisitive species require moist mild climates and fertile soils, conditions that are generally not met in the field. By contrast, conservative species, which are supposedly slow-growing species, show generally higher realized growth due to their ability to tolerate unfavourable environmental conditions. In general, conservative tree species grow more steadily than acquisitive tree species in non-tropical forests. We recommend planting acquisitive tree species in areas where they can realize their fast-growing potential. In other regions, where environmental stress is higher, conservative tree species have a larger potential to fix carbon in their biomass.


A map depicting two Pinus contorta native-introduced region pairs (NIRPs, panel a). The northern NIRP is represented in blue, indicating native range locations in northern British Columbia, Canada (b), and corresponding introduced populations in Sweden (c). The southern NIRP is depicted in red, indicating native range populations in the Pacific Northwest, USA (d), and corresponding introduced populations in Patagonia (e). In Patagonia, two paired stand types (i.e., plantations and invasion fronts) were sampled and represented in red and pink, respectively.
A principal coordinate analysis (PCoA) showing the results of a PERMANOVA test evaluating differences in community composition of (a) all fungi, (b, c) plant pathogens, (d) endophytes, (e) epiphytes, (f) saprotrophs, (g) “others” and (h) fungi with unknown ecology associated with Pinus contorta needles in four distinct regions (Canada, USA, Sweden, and Patagonia). Results of the PERMANOVA are reported in Table 1. The R² of post-hoc pairwise comparisons are shown on each panel, number with *, and ** indicates a significant difference at α = 0.05 and α = 0.01 respectively.
Amplicon sequence variants (ASVs) richness (a–g) and relative abundance (h) of fungal communities associated with Pinus contorta needles in two native range populations (Canada and USA) and two introduced populations (Sweden and Patagonia), respectively. Richness is presented as the average rarified richness for each sample. Results from the corresponding two-way Kruskal-Wallis test for all variables are reported in Table 1. Different letters above boxplots (a–g) or across bar segments with the same shade (h) indicate significant pairwise differences (α = 0.05) determined using nonparametric post hoc comparisons.
A principal coordinate analysis (PCoA) showing the results of a PERMANOVA test evaluating differences in community composition of (a) all fungi, (b, c) plant pathogens, (d) endophytes, (e) epiphytes, (f) saprotrophs, (g) “others” and (h) fungi with unknown ecology associated with Pinus contorta needles in introduced plantations and invasion fronts growing from plantations in Patagonia. Results of the PERMANOVA are reported in Table S5, with α = 0.05 indicating statistically significant differences.
Amplicon sequence variants (ASVs) richness (a–g) and relative abundance (h) of fungal communities associated with Pinus contorta subsp. murrayana needles in introduced plantations and invasion fronts growing from plantations in Patagonia, respectively. Richness is presented as the average rarified richness for each sample. Results from the corresponding Welch’s t or Wilcoxon rank sum tests are reported in Table S5. Different letters above boxplots (a–g) or across bar segments with the same shade (h) indicate significant differences at α = 0.05.
Distinct foliar fungal communities in Pinus contorta across native and introduced ranges: evidence for context dependency of pathogen release

March 2025

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54 Reads

Inter-continental study systems are crucial for testing ecological hypotheses, such as the widely cited Enemy Release Hypothesis (ERH), which seeks to explain the superior performance of plant species when they are introduced to new regions. Pinus contorta (lodgepole pine), native to North America, has been extensively introduced to Europe and the Southern Hemisphere, making it an ideal tree species for studying invasion hypotheses from a biogeographical perspective. We compared foliar fungal communities, especially pathogens, of P. contorta across two native–introduced region pairs (NIRPs): a northern NIRP (from Canada to Sweden) and a southern NIRP (from the USA to Patagonia), while also examining the differences between source plantations and invasion fronts within Patagonia. P. contorta underwent significant fungal community shifts and experienced pathogen release during its large-scale introduction from North America to Sweden and Patagonia. The fungal richness and relative abundance changes were more pronounced for the southern NIRP pair, where no closely related tree species to P. contorta are present in Patagonia. In Sweden, the presence of the phylogenetically related P. sylvestris and its associated local fungal community appears to play a role in influencing the foliar fungal communities associated with introduced P. contorta. In Patagonia, the incomplete co-invasion of fungal taxa from the USA emerges as a principal driver of the observed variability in fungal community composition and pathogen release following the introduction of P. contorta. In Patagonia, fungal community composition differences between source plantations and invasion fronts provided insufficient evidence that pathogen release occurs at this local scale. Integrating both biogeographical and phylogenetic perspectives, our study suggests that priority effects of local fungi appear to be a dominant community assembly process when introduction is done in a phylogenetically similar community; whereas, co-invasion of fungal communities is the dominant process in phylogenetically distant communities.



Map showing the locations of the two field sites in Sweden. Three replicate blocks are present at each site, with each block consisting of plots (0.1 ha) with monocultures of each tree species planted at the site. Tree species present at each site are listed and the number of green dots indicate the number of replicate plots of each species that are found at the site (30 plots at Svartberget and 20 in Garpenberg). Photos are one replicate plot of two species (photo source: C. Spitzer). Map source: www.vemaps.com.
Principal Component Analysis of leaf and fine root traits across all species. a Leaf trait variation only. b Fine root trait variation only. Traits corresponding to the bi-plot arrows are shown in blue font: leaf carbon content (Leaf C); leaf nitrogen content (Leaf N); specific leaf area (SLA); leaf dry matter content (LDMC); leaf carbon to nitrogen ratio (Leaf C: N); average root diameter (Root diameter); root nitrogen content (Root N); specific root area (SRA); specific root length (SRL); root carbon content (Root C); root carbon to nitrogen ratio (Root C: N), and root dry matter content (RDMC).
Principal Component Analysis of above- and belowground plant traits across all species. Traits corresponding to the bi-plot arrows are shown in blue font: leaf carbon content (Leaf C); leaf nitrogen content (Leaf N); specific leaf area (SLA); leaf dry matter content (LDMC); leaf carbon to nitrogen ratio (Leaf C: N); average root diameter (Root diameter); root nitrogen content (Root N); specific root area (SRA); specific root length (SRL); root carbon content (Root C); root carbon to nitrogen ratio (Root C: N), and root dry matter content (RDMC).
Spearman’s rank correlation matrices between fine root traits and leaf traits across all species. The six leaf traits are leaf carbon content (C); leaf nitrogen content (N); specific leaf area (SLA); leaf dry matter content (LDMC); leaf carbon to nitrogen ratio (C: N). The eight fine root traits are average fine root diameter (AD); root nitrogen content (N); specific root area (SRA); specific root length (SRL); root carbon content (C); root carbon to nitrogen ratio (C: N), and root dry matter content (RDMC). Asterisks indicate statistical significance (* indicates P ≤ 0.05; ** indicates P ≤ 0.01; *** indicates P ≤ 0.001).
Variance decomposition for each trait across all tree species. Bars are the total trait variation for each plant trait. The sub-bars shows the percentage of the total variation for each trait explained by species (purple), site (blue), variation between blocks within a site (peach) and residual variation (green). The fourteen plant traits are root carbon content (Root C); leaf carbon content (Leaf C); root carbon to nitrogen ratio (Root C: N); leaf carbon to nitrogen ratio (Leaf C: N); root nitrogen content (Root N); leaf nitrogen content (Leaf N); average fine root diameter (AD); specific leaf area (SLA); specific root length (SRL); specific root area (SRA); leaf dry matter content (LDMC), and root dry matter content (RDMC).
Aboveground and belowground trait coordination across twelve boreal forest tree species

January 2025

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69 Reads

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1 Citation

The existence of trait coordination in roots and leaves has recently been debated, with studies reaching opposing conclusions. Here, we assessed trait coordination across twelve boreal tree species. We show that there is only partial evidence for above-belowground coordination for “fast-slow” economic traits across boreal tree species, i.e., while N content in leaves and roots were positively correlated, as well as dry matter content, root dry matter content and leaf N had no significant relationship. For resource acquisition traits (i.e. related to light capture and nutrient uptake) we did not find strong evidence for trait coordination, as specific root length and specific leaf area were not positively correlated. We further show that site only explained between 0 and 7% of the total trait variation, while within-site variation contributed substantially to the total trait variation for a large number of traits (1.6–96%), and more so for morphological root traits than leaf traits. This likely influences the strength of above-belowground trait coordination found across species in our study. Understanding sources of trait variation and above-belowground trait relationships can contribute to improving global and regional C cycling models. However, fine-scale environmental variability should be accounted for given its importance for driving trait variation.


Biochar effects on soil nutrient transformations

October 2024

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202 Reads

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12 Citations

This chapter serves as a review of the general mechanisms through which biochar influences nutrient availability to plants, and provides an evaluation of the effect biochar has on nutrient cycling and specific transformations for several key plant nutrients. We explore some of the knowns and unknowns regarding how biochar influences soil nutrient transformations, which are likely to have both short- and long-term impacts on plant productivity in forest and agricultural landscapes. We specifically focus on the influence of biochar additions to soil on transformations of N, P, S, and micronutrients, Cu, Fe, Mn, and Zn. , and explore the implications for modification of these cycles in terms of plant availability of nutrients and their long-term budgets across a range of ecosystems.


Conceptual diagrams illustrating the primary drivers of plant-soil feedbacks (PSFs) and the design of PSF experiments under various environmental, experimental and intrinsic contexts. a Plants elicit changes in whole soil biota (1), including mutualists (2), pathogens (3) and decomposers, and in nutrient availability (4) and secondary chemicals (5), which in turn, independently or interactively (6), affect the performance of subsequent plants. b In the training phase, a single plant species is grown to condition the soil. The effect of changes to the soil on plant performance is assessed in a testing phase, where plants are either grown on conspecific or heterospecific soils. Individual PSFs assess a species’ performance on conspecific versus heterospecific soils, while pairwise PSFs assess the relative performance of two species relative to each other. In studies included in our meta-analysis, PSF drivers are experimentally manipulated in both conspecific and heterospecific soils, resulting in two groups: control (the absence or decreased level of a driver) and treatment (the presence or increased level of a driver). Note that we only illustrate one driver (i.e. pathogens) for clarity
Differences in the mean effect size of individual (a) and pairwise (c) plant-soil feedbacks (PSFs) between control (blue bars) and treatment (red bars) groups, and the mean effect size of different drivers (ΔPSF, green bars) on individual (b) and pairwise (d) PSFs. Positive and negative values of individual PSFs indicate that a species’ growth increases or decreases, respectively, when grown on conspecific compared to heterospecific soil. Positive and negative values of pairwise PSFs indicate potential destabilizing or stabilizing coexistence, respectively. Positive and negative values of ΔPSF [difference in PSFs between control (PSFC) and treatment (PSFT) groups] indicate positive or negative effects of PSF drivers. The numbers in brackets show the number of effect sizes. The points and shades represent the mean effect sizes and 95% confidence intervals. Confidence intervals not overlapping with the dashed line (i.e. 0) indicate statistical significance, as indicated by asterisks
Model-averaged importance of external and intrinsic contexts on the effect size of different drivers on individual (a–e) and pairwise (f–j) plant-soil feedbacks (PSFs). Importance is based on the sum of Akaike weights derived from the model selection analysis using Akaike’s information criteria. A cutoff of 0.8 (red dashed line) is set to differentiate between important and nonimportant moderators
Effects of intrinsic and external contexts on the effect size of plant-soil feedback (PSF) drivers. For individual PSF studies, the effect size of whole biota differs between different categories of plant origin (a) and testing system (b). For pairwise PSF studies, the effect size of whole biota differs between different categories of testing system (c) and the effect size of nutrient availability depends on the phylogenetic distance between species (d). Positive and negative values of ΔPSF indicate positive or negative effects of PSF drivers. The numbers in brackets show the number of effect sizes. The points and shades represent the mean effect sizes and 95% confidence intervals. Bars that do not share a letter differ significantly from one another (p < 0.05). The points in panel (d) are scaled by the inverse variance of effect sizes
Deciphering the drivers of plant-soil feedbacks and their context-dependence: A meta-analysis

August 2024

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235 Reads

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3 Citations

Plant and Soil

Background and aims Plant-soil feedbacks (PSFs) play an important role in mediating plant species coexistence, community dynamics and ecosystem functioning. Soil biota (e.g. mutualists, pathogens), nutrient availability and secondary chemicals can drive the strength and direction of PSFs, but the variations and context-dependence of their effects remain unclear. Methods We used a phylogenetically controlled meta-analysis of 57 PSF studies across 166 plant species to explore whether and how these drivers affect individual PSFs (the performance of a species on conspecific versus heterospecific soils) and pairwise PSFs (indicating whether feedbacks promote stable or unstable species coexistence) under various intrinsic, environmental and experimental contexts. Results Mutualists led to stronger positive individual and pairwise PSFs across various intrinsic and external contexts. However, PSFs became more negative when whole biota was present, with stronger negative effects on native species compared to exotic species and the most negative effects on plants experiencing interspecific competition. Manipulations of pathogens, nutrient availability and secondary chemicals had overall minimal influence on both types of PSFs, but the effect of nutrient availability on pairwise PSFs increased with increasing phylogenetic distance between species. Conclusion Our study suggests that soil biota is an important driver of PSFs and that plant origin and competitive context should be considered when predicting the role of soil biota in driving PSFs. Finally, we propose several directions for the next generation of PSF experiments towards a better understanding of the relative importance and interactions of different PSF drivers.



Number and proportion of EM fungal OTUs for each exploration type for the three depth layers (00–10 cm, 10–30 cm and 30–50 cm). The red colors represent the “short distance” exploration types (SD) and the green colors correspond to the “long distance” exploration types (LD).
Non-metric multidimensional scaling (NMDS) analysis, in the first and second dimension based on Bray–Curtis distances, of EM fungal communities based on OTUs composition depending on the tree host (square and circle for gymnosperms and angiosperms respectively) and the geographical origin of the sites (each site corresponds to a different color)
Relationships between humus index and the ratio of long distance (LD) on short distance (SD) exploratory types in three soil depths (cm): 00–10, 10–30 and 30–50. Pearson correlations were tested on data from (A) all forests; (B) recent forests (i.e. agricultural past land use); and (C) ancient forests (i.e. land use former forests). Gymnosperms (green) and angiosperms (orange) were tested separately. The Pearson correlation coefficients and P-values are shown in the same two colors for each line
Conceptual diagram showing the distribution of EM morphological traits (i.e. long vs. short exploration types) related to the humus indices and humus forms (from eumull to mor), as proxy of soil fertility. This figure was based on results obtained in gymnosperm and angiosperm stands for the three depths (00–10 cm, 10–30 cm and 30–50 cm) in the ancient forest sites (i.e. tree stands on formerly forested soils). EM: Ectomycorrhizal symbiosis. AM: Arbuscular Mycorrhizal symbiosis. LD: Long Distance hyphae. SD: Short Distance hyphae
“Ectomycorrhizal exploration type” could be a functional trait explaining the spatial distribution of tree symbiotic fungi as a function of forest humus forms

May 2024

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455 Reads

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1 Citation

Mycorrhiza

In European forests, most tree species form symbioses with ectomycorrhizal (EM) and arbuscular mycorrhizal (AM) fungi. The EM fungi are classified into different morphological types based on the development and structure of their extraradical mycelium. These structures could be root extensions that help trees to acquire nutrients. However, the relationship between these morphological traits and functions involved in soil nutrient foraging is still under debate. We described the composition of mycorrhizal fungal communities under 23 tree species in a wide range of climates and humus forms in Europe and investigated the exploratory types of EM fungi. We assessed the response of this tree extended phenotype to humus forms, as an indicator of the functioning and quality of forest soils. We found a significant relationship between the relative proportion of the two broad categories of EM exploration types (short- or long-distance) and the humus form, showing a greater proportion of long-distance types in the least dynamic soils. As past land-use and host tree species are significant factors structuring fungal communities, we showed this relationship was modulated by host trait (gymnosperms versus angiosperms), soil depth and past land use (farmland or forest). We propose that this potential functional trait of EM fungi be used in future studies to improve predictive models of forest soil functioning and tree adaptation to environmental nutrient conditions.


The left panel a depicts sample sites of native Pinus contorta in Oregon and Washington State, USA. Pinus contorta subspecies are displayed using different symbols, including contorta (orange circles), murrayana (red squares), and latifolia (blue triangle). The right panel b depicts sample sites of introduced Pinus contorta in the Patagonia region of Chile and Argentina (green downward triangles)
The upper picture a shows a Pinus contorta invasion front (foreground) stemming from a plantation (background) near Coyhaique, Chile (Photo by M. Gundale and A. Fajardo). The lower picture b shows an invasive P. contorta stand near Bariloche, Argentina (Photo by Jaime Moyano)
Results of Canonical Analysis of Principal coordinates on mean trait values a and within-stand trait co-efficient of variations b for sites of the five Pinus contorta stand categories. The analysis includes three native North American Pinus contorta sub-species, including contorta (yellow circles; C), latifolia (blue upward triangles; L), murrayana (red squares; M), and two introduced stand types, Patagonia Plantations (PP, green filled downward triangles) and Patagonia Invasion fronts (PI, green unfilled downward triangles). The δ² values on the axes indicate the strength of the association between the data cloud of mean trait values and the hypothesis of differences between the five categories. In the lower left corner of each panel, within and between group similarities (%) are listed. An asterisk next to pairwise similarity values indicate when post hoc pairwise PERMANOVA analyses showed a significant difference (p < 0.05) in trait values between the two regions
Mean trait values for five Pinus contorta stand types, including native sub-species contorta (C, yellow), latifolia (L, blue), murrayana (M, Orange), and two introduced stand types, Patagonia Plantations (PP, left green) and Patagonia Invasion fronts (PI, right green). Black dots and error bars represent mean (± SE) trait values. Only trait variables exhibiting significant difference (p value < 0.05 from univariate analyses) are depicted. Different lower case letters (a–c) above means indicant significant differences between the first four categories, and uppercase letters (A, B) indicate significant differences between the two Patagonian stand types
Within stand trait coefficients of variation (CV) values for five Pinus contorta stand types, including native sub-species contorta (C, yellow), latifolia (L, blue), murrayana (M, Orange), and two introduced stand types, Patagonia Plantations (PP, left green) and Patagonia Invaders (PI, right green). Black dots and error bars represent mean CV (± SE) trait values. Only trait variables exhibiting significant differences (p-value < 0.05 from univariate analyses) are depicted. Different lower case letters (a or b) above means indicate significant differences between the first four categories, whereas no post hoc comparisons are depicted for the two Patagonian stand categories, because no PERMANOVA difference was detected
Functional traits differ across an invasive tree species’ native, introduced, and invasive populations

May 2024

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253 Reads

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1 Citation

Biological Invasions

It is often speculated that non-native invasive species undergo rapid changes in their phenotypic properties (i.e., traits) that provide adaptive advantage in their new environment. However, few studies have directly compared traits of invasive non-native species with their native counterparts to reveal whether such phenotypic changes occur, and which stages of initial introduction and subsequent invasion contribute to these shifts. We studied trait variation of an invasive tree, Pinus contorta, which is native to northwestern North America and invasive in the Patagonia region of South America (i.e., Argentina and Chile). Commercial plantations of P. contorta were introduced extensively in Patagonia from the 1970s onward, from an unknown seed origin within the Pacific Northwest, USA, where three sub-species are found, including subsp. contorta, latifolia, and murrayana. We employed a home-versus-away study approach, where we compared mean growth, defense, and reproduction trait values, and mean within-stand trait variation (Coefficient of Variation, CV) of Patagonia plantations, with the three native sub-species. We further compared mean traits, and trait CVs between invasive P. contorta and the Patagonia plantations from which they escaped. Patagonia plantations shared the most similar mean trait values with subsp. latifolia and murrayana, suggesting possible source populations. However, both mean trait values and trait CVs of Patagonia plantations differed from all three native sub-species, indicating potential founder effects, population bottlenecks, and/or plastic responses to their new environment that occurred during or after introduction. We also found evidence for selective change during invasion; however, these differences did not suggest growth traits were prioritized over defense traits, which was inconsistent with hypotheses that invaders exhibit an evolutionary trade-off between defense traits and growth traits. Our study highlights that processes occurring both at first introduction and establishment, as well as the subsequent invasion phase can influence the phenotype of successful invaders.


Citations (77)


... Most recently, five additional papers analyzed above-belowground trait coordination with mixed results. These ranged from full support for an aligned conservation gradient for 60 woody subtropical tree species (Fan et al. 2024), to partly coupled chemical traits for 12 boreal tree species (Spitzer et al. 2025), nine desert herbs (but not shrubs, (Ma et al. 2024a)), and for community-weighted means but not species mean traits in 23 dune species , to no coordination of intraspecific trait variation in four temperate tree species (Schaffer-Morrison et al. 2024). ...

Reference:

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Aboveground and belowground trait coordination across twelve boreal forest tree species

... Similarly, increase in soil pH could have reduced sorption of available soil phosphorus. [9] reported a greater soil available P content in biochar-amended soils compared to unamended soils and attributed the improvement to biochar's capacity to retain and exchange phosphate ions due to its positively charged surface sites. ...

Biochar effects on soil nutrient transformations

... PSF refers to the process by which plants alter the physical, chemical, and biological properties of soil through their growth activities, and these altered soil properties in turn affect the growth of individual plants, population dynamics, and community structure ( Fig. 1; modified based on Cheng et al.'s work) [13][14][15][16][17]. There are positive, neutral, and negative feedbacks between plants and soils, and the ultimate effect will be determined by various factors including plant root exudates, soil microbiota such as pathogens and mutualists, litter decomposers, soil secondary chemicals, and macronutrients [14,15,18,19]. ...

Deciphering the drivers of plant-soil feedbacks and their context-dependence: A meta-analysis

Plant and Soil

... However, previous studies in nitrogen addition experiments that were harvested by clearcutting report contradicting results. While some studies found increased tree growth, needle nitrogen concentration, nitrogen mineralization, and soil inorganic nitrogen concentration in forests fertilized during the preceding rotation period (Footen et al., 2009;From et al., 2015;Högbom et al., 2001), others found no difference in seedling mortality, tree growth, needle nitrogen concentration, and understory biomass between clearcuts of fertilized and unfertilized stands (Johansson et al., 2013;Larsson et al., 2024;Sikström, 2005). ...

Diminishing legacy effects from forest fertilization on stand structure, vegetation community, and soil function

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... Soil fungal necromass concentrations may also create soil conditions where distance explorations types are favoured, resulting in a positive feedback loop. For example, studies have shown that lower fertility soil is associated with a higher relative abundance of longor medium-distance ECM exploration types (Khalfallah et al., 2024). ...

“Ectomycorrhizal exploration type” could be a functional trait explaining the spatial distribution of tree symbiotic fungi as a function of forest humus forms

Mycorrhiza

... The precise seed origin of Patagonia plantations is not known, but trait and anecdotal analysis have indicated the P. contorta subsp. murrayana population in central Oregon, USA as the origin 41 , where we distributed our native range sampling (Fig. 1). ...

Functional traits differ across an invasive tree species’ native, introduced, and invasive populations

Biological Invasions

... The recovery rate depends on factors such as soil depth 150,151 , climate 151,152 , previous land use 151 , and the species planted 153 . Moreover, it is vital to understand how SOC stocks respond to disturbances like wildfires and how long it takes for them to recover, especially as wildfire risk continues to increase in the north 154 . The relationship between the size of the SOC pool and properties like soil moisture 155 , soil Nitrogen concentrations, C:N ratios 156 , and preafforestation soil carbon 157 is complex and needs more research. ...

The biological controls of soil carbon accumulation following wildfire and harvest in boreal forests: A review

Global Change Biology

... In acidic northern forest soils, ectomycorrhizal (ECM) fungi are major players in N cycling, and ECM taxa that explore larger volumes of soil or produce organic matter depolymerizing enzymes play more prominent roles as succession advances and a larger share of soil N pool is held in less accessible organic forms (Chen et al., 2019;Hobbie et al., 2013;Leduc et al., 2013). As yet, successional interactions between soil N availability, photobiont C supply, and mycobiont enzyme production and N foraging are better characterized in boreal forest soils but are relevant to the N economy and C balance of temperate forest soils as well (Baldrian et al., 2023;Forsmark et al., 2024;Hay et al., 2015;Jörgensen et al., 2022). Research that places these biogeochemical processes in the context of aboveground ecosystem dynamics (e.g., tree community composition and canopy structure) is particularly needed to better understand succession as a whole-ecosystem process. ...

Shifts in microbial community composition and metabolism correspond with rapid soil carbon accumulation in response to 20 years of simulated nitrogen deposition

The Science of The Total Environment

... Saleh et al. (2025) Jurnal Sylva Lestari 13(1): 102-119 103 influence initial seedling survival by affecting seedling roots and soil compaction (Pradiko et al. 2016). Competitive vegetation controls such as mowing, herbicide application, and mulching have varied effects on seedling establishment (Häggström et al. 2024). As an environmentally friendly approach, mulching suppresses competition and enhances soil moisture retention and nutrient availability (Mechergui et al. 2021). ...

Environmental controls on seedling establishment in a boreal forest: implications for Scots pine regeneration in continuous cover forestry

European Journal of Forest Research

... Apart from their abundance, forests have a high potential to uptake and store carbon. Therefore, forest residues such as wood residues, present a promising alternative for sustainable bioprocesses [7]. Hence, the production of BDO from wood residues, rather than fossil resources, can offer remarkable advantageous in environmental sustainability [8]. ...

Forest inventory tree core archive reveals changes in boreal wood traits over seven decades
  • Citing Article
  • July 2023

The Science of The Total Environment