# Does natural root grafting make trees better competitors?

Elodie Quer, Manon Helluy, Virginie Baldy, Annie Desrochers

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## To cite this version:

Elodie Quer, Manon Helluy, Virginie Baldy, Annie Desrochers. Does natural root grafting make trees better competitors?. Oikos, 2022, 2022 (12), 10.1111/oik.09666. hal-04043031

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12 Does natural root grafting make trees better competitors?

13 E. Quer<sup>ac*</sup>, M. Helluy<sup>b</sup>, V. Baldy<sup>a</sup> A. DesRochers<sup>c</sup>

14 (a) Aix Marseille Université, IMBE, Avignon Université, CNRS, IRD, Case 421 Avenue

15 Escadrille Normandie Niemen 13397, Marseille, France.

16 (b) INRAE, Université Aix-Marseille, UMR RECOVER, Aix-en-Provence, France.

17 (c) Université du Québec en Abitibi-Témiscamingue, IRF, 341 rue Principale Nord, J9T 2L8,

18 Amos, Québec, Canada.

19 *Corresponding author: elodie.quer@imbe.fr

20
21 Abstract

22 Natural root grafts (anastomoses) are morphological unions formed between roots of different
23 trees. Common root systems allow translocation of water, nutrients and photosynthesis products
24 between grafted trees, affecting their growth and their physiology. As carbohydrates are
25 redistributed among grafted trees, the formation of a common root system could reduce the
26 negative effect of intraspecific competition for light or soil resources within stands. The aim of
27 this study was to investigate the role of root grafting on intraspecific competition and growth
28 of balsam fir (Abies balsamea (L.) Mill). We studied inter-tree relationships in three natural
29 balsam fir stands of the boreal forest of Quebec (Canada) that contained an average 36% of
30 grafted trees. At each stand, ring width and basal area of trees were measured using
31 dendrochronology techniques. We used mixed linear models to test the effect of root grafting
32 and intraspecific competition on annual basal area increment of trees. Trees before grafting had
33 higher growth rates than trees once grafted. Thus, root grafting did not improve tree growth.
34 Growth of grafted trees was more negatively affected by intraspecific competition than growth
35 of non-grafted trees. Thus, grafted trees cannot be considered as better competitors than non-
36 grafted trees. Under high intraspecific competition, growth of larger grafted trees was less
37 affected than that of smaller trees suggesting that they were able to divert resources at their
38 advantage within a union. Our study demonstrated that grafted trees acted on each other's
39 growth and provides support for the idea that grafted trees respond to competition for resources
40 more as a community rather than as individual trees.

41 Key words: Root grafting, *Abies balsamea*, Boreal forest, Competition, Radial growth,
42 Anastomosis.

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**Introduction**

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When two roots from different trees come into contact, a morphological union can occur by the fusion of their vascular tissues to form a natural root graft (i.e. anastomosis, Graham and Bormann 1966, Mudge et al. 2009). In recent decades, underground networks created by root grafting generated interest in forest ecology as mechanisms of “resource sharing” between trees (McIntire and Fajardo 2014, 2011, Valladares et al. 2015). In addition to their role in facilitating resource acquisition and assimilation, extended common root systems of grafted trees allow resources exchange such as water, nutrients and photosynthesates (Fraser et al. 2006, O’Neal and Davis 2015, Klein et al. 2016, Bader and Leuzinger 2019). Since grafted trees may directly share substances and affect each other’s growth, ecological concepts that support the notion of plant individuality and dominance of competition for resources in plant interactions are challenged (Lortie et al. 2004, Brooker 2006, Brooker et al. 2008).

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While root grafts have been observed worldwide in more than 200 tree species, root grafting has long been considered as a rare or random event and little research has focussed on its ecological significance (La Rue 1952, Graham and Bormann 1966). The role of root grafting was first reduced to a mechanism to improve anchorage and stability in windy environments and waterlogged soils (Rigg and Harrar 1931, Keeley 1988, Basnet et al. 1993). Root grafting was also considered as a vector for diseases because pathogens translocated between grafted trees through sap flow or contact between roots (Epstein 1978, Baric et al. 2008). Over the last twenty years, interest in the role of root grafting on tree growth has grown to explain forest dynamics (Tarroux et al. 2010, McIntire and Fajardo 2011, Adonsou et al. 2016). On the one hand, Tarroux and DesRochers (2011) showed that *Pinus banksiana* radial growth was increased by intraspecific root grafting. Moreover, it was shown that radial growth of grafted *Picea mariana* or *Populus balsamifera* under insect outbreak or unfavorable climatic conditions was improved compared to growth of non-grafted trees, suggesting that root grafting could be
an ecological advantage for trees under environmental stresses (Salomón et al. 2016, Adonsou et al. 2016). These results promote the idea that common root systems improve access, redistribution and use of soil resources among grafted trees leading to better growth and survival. This implies that grafted trees do not only compete for resources but can also directly facilitate the growth of their grafted neighbors (Eis 1972, Keeley 1988, Loehle and Jones 1990, McIntire and Fajardo 2011).

Nonetheless, it was also reported that root grafting was an energetically costly process: dendrochronological analyses of root grafts correlated root grafting to a decrease in tree growth during their formation (Tarroux and DesRochers 2011). The same authors also showed that the inheritance of a root system from a removed tree, creates an imbalance between root biomass and leaf area, and thus could negatively impact growth of residual trees (generally the larger one) in thinned *Pinus banksiana* stands (Tarroux et al. 2010).

Negative and positive interactions reported between grafted trees support the idea that relationships between grafted trees are non-neutral and can be summarized as: i) facilitation: moderation of biotic and abiotic stress, enrichment of resources or increased access to resources, or ii) parasitism: resources are translocated from the dominant to suppressed trees improving their survival at the expense of the growth of dominant trees. In the case of parasitism, it would also be conceivable that larger trees would take advantage of smaller trees, as larger members of a root complex may be able to, at the expenses of the less vigorous trees, establish gradients that cause water and nutrients absorbed by the communal root system to move primarily to them (Bormann 1962, Wimmler et al. 2022). Larger trees, with their larger crowns, will transpire more than suppressed trees, creating a stronger sink for water (Bader and Leuzinger 2019, Wimmler et al. 2022). However, we don't know if grafted trees are differently affected by root grafting according to their size within the union.
Competition (i.e. negative interaction between plants through direct interference or indirectly through the exploitation of common resources) is a key process to explain community structure and dynamics in forests worldwide (Kunstler et al. 2016). In forest stands, competition between trees increases with tree size, tree proximity and stand density (Lorimer 1983). Interestingly, the probability of root graft formation also increases with tree size, proximity of trees and stand density, allowing resources translocation and cooperation relationships (Fraser et al. 2005, Tarroux and DesRochers 2010, Gaspard and DesRochers 2020). A relatively high frequency of root grafting in balsam fir (Abies balsamea (L.) Mill) stands was reported (36% of grafted trees in three 50 m² stands), where root grafting increased with tree proximity and number of roots per tree (Quer et al. 2020). Balsam fir is known to be a shade tolerant species, growing for prolonged periods of time in dense understory environments without self-thinning (Burns and Honkala 1990, Ruel et al. 2003). Moreover, balsam fir maintains an abundant seedling bank on the ground leading to the formation of very dense stands after disturbances remove canopy trees (Morin and Laprise 1997). Under these conditions of high intraspecific competition for light and soil resources, root grafting might lessen competition effects in dense stands by supporting tree growth through resources sharing and translocation (Loehle and Jones 1990, Lev-Yadun 2011). We thus undertook this study in order to better understand the ecological significance of root grafting in balsam fir stands under high intraspecific competition. In order to demonstrate if root grafting could alleviate the negative effects of intraspecific competition on balsam fir tree growth, we developed mixed linear models estimating the role of root grafting and intraspecific competition on balsam fir growth. After selecting the “best” model to predict tree growth, we studied interactions between root grafting and intraspecific competition to further explore their relationships. Our main hypotheses were: (i) intraspecific root grafting improves growth of grafted balsam fir trees; (ii) intraspecific competition reduces growth of grafted balsam firs; (iii) root grafting alleviates the negative effects of intraspecific competition on
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balsam fir growth, (iv) trees are differently affected by root grafting according to their respective size within the union.

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## Material and methods

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### *Study sites*

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This study was conducted in Abitibi-Témiscamingue, north-western Quebec, in the balsam fir-white birch (*Betula papyrifera* Marsh.) bioclimatic domain of the boreal forest (Grondin et al.

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1996). The first site (S1) was located near the Lake Duparquet Research and Teaching Forest (48°52′21.6″N, 79°46′53.0″W), the second site (S2) was located near Kinojévis teaching forest

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(48°18′26.1″N, 78°84′63.7″W) and the third site (S3) was located near the Harricana teaching forest training center (48°76′27.8″N, 77°77′93.3″W).

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All sites were on heavy clayey soils (at least 60% of clay) associated to post Wisconinan glaciolacustrine deposits (Vincent and Hardy

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1977, Agriculture Canada Expert Committee on Soil Survey 1987). From 1981 to 2010, mean daily temperature in this region was 1.5 °C with a mean of 2366 degree-days above 0 °C and annual total precipitation averaged 929 mm (253 mm of snow and 675 mm of rain)

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(Environment Canada 2019). To be selected, sites had to be monospecific, naturally regenerated, mature (> 30 years old) and healthy balsam fir stands. Site areas were approximately 50 m² and included a minimum of 15 living trees. Stand density ranged from

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6000 stems ha⁻¹ to 14200 stems ha⁻¹. Prior to this study, hydraulic excavation and dendrochronological analyses of the root systems of each tree were carried out to determine frequency of root grafting, age of trees and grafts, as well as the distance between trees (see

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Quer et al. 2020 for further details). Stand age ranged from 39 to 74 years old. Percentage of grafted trees and number of grafts per tree was similar between stands, corresponding respectively to 36% (± 2.86 SE) and 1.30 (± 0.03 SE).

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Mean graft age was 13.57 years (± 0.98 SE) (Quer et al. 2020) (Table 1).

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## Tree radial growth analyses by tree ring width series measurement

Field work was performed in summer 2017. At each site, all trees were felled with a chainsaw and cross-sectional disks were collected at ground level (0 m). Cross-sectional disks were air dried and sanded (80-400 grit) to reveal growth rings. Tree ring widths series were measured on cross-sectional disks from the stem base using a Velmex “TA Unislide” measurement system with ACU-Rite linear encoder and QC10V digital readout device (Velmex, Inc., Bloomfield, New York) interfaced with Measure J2X (Version 5.0x) ring-reading software (Project J2X, Voortech Consulting, Holderness, NH). Ring-width series were measured with 0.001 mm precision along two rays per wood disk when possible (i.e. when the rings were clearly visible) and visually cross-dated. To obtain a single series per tree, chronologies were averaged for each tree when two of them were available. A total of 110 tree ring width series were obtained.

Tree age and stem size increasing over time promotes a decline of tree ring width along cross-sectional radius. To avoid this biological trend, we converted tree ring width series into basal area increment (BAI) to calculate annual tree growth (Biondi and Qeadan 2008) following equation (1):

$$BAI_t = \pi R_t^2 - \pi R_{t-1}^2 \quad (1)$$

Where $R_t$ is the stem radius at year t and $R_{t-1}$ is the stem radius at year t-1.

In order to include a minimum of 30 tree ring width measurements per year, we used only the data of tree growth for the last 60 years. Due to the inaccuracy of tree ring width measurement during the first years of growth, we decided to not take into account the first 5 years of growth of each tree in the data analysis.

## Intraspecific competition measurements by using competition indices

Intraspecific competition between trees was estimated using distance-independent (BAL: Basal area of the Larger tree) and distance-dependent (HEG: Hegyi competition index) competition
indices. The first index (BAL) was developed by Wykoff et al. (1982) and corresponds to the sum of the basal area of neighbor trees that are larger than the subject tree:

$$BAL = \sum_{\substack{j=1 \\ j \neq i \\ R_j > R_i}}^{n} \pi R_j^2 \quad (2)$$

With Ri = Radius of the subject tree i; Rj = Radius of the competing tree j. The second index (HEG) was developed by Hegyi (1974) and corresponds to the sum of the ratios of diameters of a subject tree and its competitors, weighted by the distance from the subject tree. To integrate tree growth variability over time we replaced tree diameter by tree basal area in the next formula:

$$HEG = \sum_{j=1}^{n} \frac{BA_j}{Dist_{ij}} \quad (3)$$

Where: HEG = Hegyi competition index; BAᵢ = Basal area of the subject tree i; BAⱼ = Basal area of the competing tree j; Distᵢⱼ = distance between trees i and j; n = total number of competitors. In order to determine the radius around the subject tree in which there are potential competitors, we calculated competition indices (HEG) for 10 trees in each site for 10 years and for different values of radii (from 1 to 9 m). We then considered that each tree found in a radius of 6 m or less around the subject tree was a potential competitor (Supporting information, Figure S1). As HEG integrates basal area, it measures symmetric competition (i.e. competitors share resources in proportion to their size) and it is often associated to competition for belowground resources (Pretzsch and Biber 2010). BAL only integrates basal area of larger neighbor trees and measures symmetric and asymmetric competition (i.e. large competitors capture a disproportionate share of contested resources over smaller competitors) thus it reflects competition for belowground resources but also for light (Weiner 1990, Connolly and Wayne 1996, Freckleton and Watkinson 2001).

Statistical analyses
Statistical analyses were done using R software version 4.0.3 (R core team 2019).

Considering grafted trees, for a same tree, years of growth were annotated BG for years of growth before grafting and G for years of growth once tree was grafted; for non-grafted trees: years of growth of a non-grafted trees were annotated NG.

In order to test the effects of intraspecific competition (i.e. HEG and BAL) and root grafting status (i.e. BG, G and NG) on *Abies balsamea* tree growth (i.e. BAI), we developed linear mixed effect models (LMER, packages “lme4” and “lmerTest”, Bates et al. 2020, Kuznetsova et al. 2020). Data were log-transformed to satisfy linearity and normality of the residuals assumptions using the “LogSt” function formulated to taking into account null values (i.e. HEG, BAL, package “DescTools”, Signorell et al. 2020). Site, year and individual (i.e. tree) were considered as random factors for the intercept. The Model equation was as follows:

$$ \log (\text{BAI}_{i,t}) = \beta_0 + \beta_1 \log(\text{BA}_{i, t-1}) + \beta_2 \log(\text{CI}_{i, t}) + \beta_3 \text{Status}_{i,t} + b_1 + b_2 + b_3 + e \quad (4) $$

with BAIi,t the Basal Area Increment of tree i at year t, BAi, t-1 the Basal area of tree i at the previous year (t-1), CIi,t the Competition Index (i.e. HEG or BAL) of tree i at year t, the graft Status (i.e. BG, NG and G) of the tree i at the year t, b1, b2 and b3 the random effects estimated for the intercept with respectively trees, years and sites as grouping factors and e the residual error. β0, β1, β2, β3 were the fixed effect parameters. As tree growth is strongly influenced by their size (MacFarlane and Kobe 2006), BA was included to the model in order to integrate the effect of tree size on annual tree growth.

All combinations of random effects (trees, sites and years) on the intercepts were tested by adding or nesting them together but preliminary analysis revealed that the models better performed by integrating the three effects additionally. Models including all the possible combinations of independent variables (CI, status and BA) were compared based on the second-order Akaike Information Criterion (AICc) using the “aictab” function (package “AICcmodavg”, Mazerolle 2020). Marginal and conditional r-squared (reporting proportions
of variance explained by the fixed factor and by the fixed and the random factors, respectively)
were calculated and used to quantify model performance (function "r.squaredGLMM", package
"MuMin", Barton 2020). ANOVAs were used on the selected models to test the global effect
of the categorical variables on BAI. Interactions between competition index (i.e. HEG or BAL)
and root grafting status (i.e. NG or G) were then tested on the best performing model using the
same method. Effect plots of the selected model were represented graphically using the R
package "effects" (Fox et al. 2020). For each model, normality of the residuals and
multicollinearity of the explanatory variables were tested using Shapiro-Wilk test and the
Variance Inflation Factor. We used this modeling approach: (i) on the data from the BG and G
trees to test if root grafting improved tree growth once grafted, (ii) on data from G and NG trees
to determine if root grafting alleviated the negative effect of competition on growth.

To investigate if the growth of grafted trees was differently affected according to their size
within a union by root grafting and intraspecific competition, we replaced the independent
variable Status with Size in our models. The smallest trees within a union were annotated S and
the larger L.

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231 **Results**

232 *Does root grafting improve tree growth?*

233 Between the four single variable models tested, the one including BA (i.e. tree size) better
234 explained BAI (i.e. tree growth) than the one including root grafting status (68.6% of variance
235 explained for models including BA versus 10.2% for model including Status, Table 2) and the
236 two including competition indices (i.e. BAL or HEG, 17.7% and 49.7% of variance explained
237 for models including BAL and HEG respectively, Table 2). Thus, tree size better predicted tree
238 growth than root grafting and intraspecific competition. After the addition of the BA (i.e., tree
239 size) to the three previous models, the percentage of variance explained was similar between
240 models (71.1% on average, Table 2). However, when adding BA, the model selected with the
241 AICc included HEG rather than BAL (Table 2). The results showed that, considering grafted
242 and future grafted trees, a competition index reflecting only symmetric competition (i.e. HEG)
243 better explained BAI than a competition index integrating both symmetric and asymmetric
244 competition (i.e. BAL). The best model explaining BAI according to AICc included HEG
245 competition index, tree grafting status (Status) and BA (73.9% of the variance was explained,
246 Table 2). Year, site and tree random effects explained 16.7% of the remaining variance. We
247 also studied the interaction between intraspecific competition and tree root grafting status, but
248 the interaction was not significant and only the additive models were retained.

249 Tree grafting status (i.e. Status), intraspecific competition (i.e. HEG) and tree size (i.e. BA)
250 significantly affected annual radial growth of trees (i.e. BAI, LMER, P < 0.001, Table 3 and
251 Fig. 1). Grafted trees (i.e. G) exhibited 0.40 mm² lower BAI than the average BAI of future
252 grafted trees (i.e. BG, Table 3 and Fig. 1c). HEG had a negative effect on BAI (Table 3 and
253 Fig. 1a), where a 1% increase in HEG induced a 0.65% reduction in BAI. Tree growth (i.e.
254 BAI) increased with tree size (i.e. BA, Table 3). From 0 to 400 cm², tree growth (i.e. BAI)
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strongly increased with size of trees (i.e. BA) but beyond 400 cm² tree growth was only slightly affected by tree size (Table 3 and Fig. 1b).

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*Does root grafting alleviate the negative effect of intraspecific competition on annual tree growth?*

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BA (i.e. tree size) was also the best variable to explain BAI (i.e. tree growth) of grafted trees and non-grafted trees (55.7% of variance explained for the single variable model, Table 4).

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However, when adding BA, the model selected with the AICc included BAL rather than HEG (Table 4). Thus, considering grafted and non-grafted trees, a competition index integrating both symmetric and asymmetric competition (i.e. BAL) better explained BAI than a competition index reflecting only symmetric competition (i.e. HEG).

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Considering only models without interactions, the best model explaining BAI according to AIC included BAL competition index, tree grafting status (Status) and BA (68.7% of the variance was explained, Table 4). Year, site and tree random effects explained 23.2% of the remaining variance.

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After testing the interactions between the selected explanatory variables, we found that the model including an interaction between tree grafting status and BAL was considered as better than the one without interaction according to the AICc (Tables 4). Fixed effects explained 69.9% of the variance and random effects explained 22.2% of the remaining variance.

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Tree grafting status (i.e. Status), intraspecific competition (i.e. BAL) and tree size (i.e. BA) significantly affected annual radial growth of trees (i.e. BAI, LMER, P < 0.001, Table 5 and Fig. 2). Grafted trees (i.e. G) had 1.98 mm² greater BAI than the average BAI of non-grafted trees (Table 5 and Fig. 2b). BAL had a negative effect on BAI (Table 5 and Fig. 2b), where a 1% increase in BAL induced a 0.18% reduction in BAI. Tree growth (i.e. BAI) increased with tree size (i.e. BA, Table 5). From 0 to 400 cm², tree growth (i.e. BAI) strongly increased with size of trees (i.e. BA) but beyond 400 cm² tree growth was only slightly affected by tree size

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(Table 5 and Fig. 2a). Considering interactions within the model, BAL had a strong negative effect on BAI once trees were grafted (Table 5 and Fig. 2b). BAI of grafted trees was higher than BAI of non-grafted trees (i.e. BAI of G > BAI of NG) for BAL values ranging from 0 to 2000. When BAL was higher than 6000, BAI of grafted trees decreased below that of non-grafted trees (i.e. BAI of G < BAI of NG) meaning that under high BAL, BAI of grafted trees was lower than BAI of non-grafted trees.

*Does tree size within a union modify the effect of root grafting and competition on annual tree growth?*

Considering grafted trees, the best model explaining BAI according to AIC included BA and the interaction between size of trees within a union (Size) and BAL competition index (69.8% of the variance explained, Table 6). Year, site and tree random effects explained 24.1% of the remaining variance. BAL had a strong negative effect on BAI of grafted trees but this effect was modulated according to size of trees within unions (Table 7 and Fig. 3b). BAI of smallest grafted trees was higher than BAI of largest grafted trees (i.e. BAI of S > BAI of B) for BAL values ranging from 0 to 1000. When BAL was higher than 4000, BAI of smallest grafted trees decreased below that of largest grafted trees (i.e. BAI of S < BAI of B) meaning that under high BAL, BAI of smallest grafted trees was lower than BAI of largest grafted trees.

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298 Discussion

This study is the first to evaluate the interaction effect between root grafting and intraspecific competition on tree growth. Our results showed that intraspecific competition decreased tree growth, and that growth reduction was more pronounced for grafted trees. We thus reject our hypothesis that root grafting makes trees better competitors than non-grafted trees.

Future grafted trees had better growth rate than trees that would never form root grafts, suggesting that they were the most productive trees within a stand (Table 3, Figure S2). Several
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studies have shown that root grafting primarily occurs between larger trees within a stand
(Gaspard and DesRochers 2020, Tarroux and DesRochers 2010). To explain this effect, it had
been suggested that roots of larger trees have more chance to cross and fuse (Armson and Van
Den Driessche 1959, Reynolds and Bloomberg 1982).

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Moreover, common root systems established between grafted trees are known to increase the coverage area of roots, thus increasing stand efficiency to exploit soil resources and increase growth rates of trees (Bormann 1966, Loehle and Jones 1990, Basnet et al. 1993, Tarroux and DesRochers, 2011). However, we showed that once trees grafted, their growth decreased (Fig. 2c). Tarroux and DesRochers (2011) demonstrated that growth of *Pinus banksiana* trees decreased during the time that root grafts were forming, suggesting that root grafting is an energetically costly process (Bormann, 1966; Loehle and Jones, 1990). However, reduction in Jack pine growth lasted from 5 to 10 years after graft formation (Tarroux and DesRochers, 2011) while we observed a much longer reduction in growth once our trees grafted (mean graft age was 14 in the studied stands [Quer et al. 2020]). It would be relevant to study older stands to test if this growth reduction persists over time (e.g. after 10, 20 or 30 years of root grafting).

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We showed that once trees grafted, there was a negative effect of root grafting with intraspecific competition, while non-grafted trees were less affected by intraspecific competition (Fig. 2b).

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Considering models on grafted and non-grafted trees, the better performance of BAL competition index in our model reflected that both asymmetric (i.e. competition for light) and symmetric competition (i.e. competition for soil resources, Wykoff et al. 1982, Schwinning and Weiner 1998) negatively affected balsam fir growth (Tables 5, Fig. 2b) even if (i) balsam fir is a shade tolerant species with a strong crown morphological plasticity adapted to dark environments (Baker 1949, Duchesneau et al. 2001) and (ii) soil resources could be directly redistributed among trees through root grafting. The Hegyi competition index was nevertheless selected as the best predictor of BAL for the single variable models (Table 4). The BAL

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331 competition index was then selected as the best predictor of BAI for the two or three variables
332 models (Table 4). Once basal area of trees was included into the models, the BAL competition
333 index performed better than the Hegyi competition index to explain BAI (Table 4), suggesting
334 that the part of model variance explained by Hegyi competition index was mainly due to the
335 fact that it integrated tree size. As the Hegyi competition index also includes distance between
336 trees, our results suggest that tree proximity was not an important predictor of tree growth and
337 intraspecific competition. This was confirmed by the fact that the best model selected to explain
338 tree growth included BAL, a distance-independent competition index. This suggests that
339 competition between trees was more driven by tree size than by tree proximity. As distance-
340 dependent indices include spatial arrangement of trees, they are often more efficient for
341 describing the effects of competition on tree growth in natural and heterogenous stands
342 (Prevosto 2005, Contreras 2011). However, several studies, including ours, showed that
343 distance-independent indices performed universally better for tree growth modelling (Biging
344 and Dobbertin 1995, Stadt et al. 2007, Helluy et al. 2020).

345 The significant interaction between BAL competition index and root grafting status indicates
346 that effect of root grafting on growth was related to intraspecific competition. However, the
347 interaction between BAL and root grafting status showed that at low to moderate intraspecific
348 competition, growth of grafted trees was greater than growth of non-grafted trees while it was
349 the reverse at high levels of intraspecific competition (Table 5 and Fig. 2b). Above the value of
350 5000 BAL, corresponding approximatively to a stand density of 12500 stems ha⁻¹, growth of
351 grafted tree was lower than growth of non-grafted trees (Tables 5, Fig. 2b).

352 Slower growth indicates a reduced vigor and a greater sensitivity to disturbances in grafted trees
353 under high intraspecific competition. We showed that our trees were differentially affected by
354 root grafting and intraspecific competition depending on their size within the union (Fig. 3b).
355 Within two grafted trees, the one with the larger crown and higher evapotranspiration rate
probably has a greater ability to divert resources from the communal root system; hence under
intraspecific competition, the translocation of resources to smaller trees might be very limited
or null (Bormann and Graham 1959, Eis 1972, Loehle and Jones 1990). Sharing a common root
system may thus be a constraint to tree growth under highly stressful conditions, especially for
the smaller members of a union (Eis 1972). Within grafted trees, when intraspecific competition
is low, the smallest trees may benefit from resources through root grafting, but when
competition intensifies, these resources are no longer redistributed and this affects growth of
the smallest trees. At early stages of balsam fir stand development, tree size and growth are
constrained, and they release later when canopy gaps arise (Morin and Laprise 1997, Ruel et al.
2003). As intraspecific competition among balsam fir stands was mainly driven by tree size,
greater competition pressure might occur later when trees are larger. Thus, under moderate
intraspecific competition, delayed root grafting might partially explain the delayed self-thinning
of balsam fir stands under high-density of trees. Since root grafts allow the translocation of
substances through the phloem (Graham 1960), phytohormones implicated in apical dominance
may be translocated between interconnected trees (Schier 1972). Larger trees may thus send
signals to smaller trees, reducing growth and stimulating the self-thinning of stands as the
proportion of root-grafted trees increases with stand development. This hypothesis is supported
by the fact that when the trees were independent (i.e. BG), their growth was greater but once
they were grafted the negative effect of competition on growth was rapid and marked (Fig. 2b).
A parallel can be drawn with suckering trembling aspen (Populus tremuloides) stands, that are
initially very dense with stems that are closely interconnected through parental roots
(DesRochers and Lieffers 2001, Jelinkova et al. 2009); These stands usually undergo a very
rapid and heavy self-thinning (Brown and DeByle 1989). At graft initiation, balsam fir trees
were 38 years old on average (Quer et al. 2020), which might explain why the effect of
380

competition occurred later in stand development compared to aspen stands where trees are interconnected right from stand initiation (Schier 1972).

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In conclusion, this study is the first to demonstrate that root grafting decreased tree growth with increasing intraspecific competition. These results support the idea that root grafting allows trees to respond (and compete) as a group rather than as individual stems and forces us to reconsider traditional forest stand dynamics concepts such as competition, dominance and succession. This is important not only for the fundamental science aspect of it, but also because these findings influence the way that the forest should be managed. As intraspecific competition was mainly driven by tree size and root grafting that occurred tardily in balsam fir stand development, we suggest that apical dominance may be implicated in this effect and that it could explain the delayed self-thinning of balsam fir stands. Further studies on phytohormone translocation between grafted trees could help us better understand the ecological significance of root grafting in forest stands dynamics.

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## Speculations

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Since root grafting is of common occurrence in balsam fir stands, there are likely other benefits to being grafted to a neighbor, that may not be directly reflected in individual tree growth. These benefits are probably the evolutionary agents that lead to the selection for the enhanced formation of root grafts (Keeley 1988). We assumed that the ecological significance of root grafting was based on resource translocation between trees but it could also be based on its structural role by improving mechanical support for trees and their root systems (Dosen and Iyer 1979, Stokes et al. 1995). Balsam fir is the main host of spruce budworm (Choristoneura fumiferana Clem.; Morin et al. 1993), and outbreaks promote higher rates of wind-related mortality by increasing wind penetration in the stand (Taylor and MacLean 2009). Thus, in post
404

outbreak stands root grafting may increase tree stability and constitute a benefit to being grafted
to a neighbor.

405

406

Root grafting could also help trees indirectly “control” their environment by maintaining
neighboring trees through root grafts; when suppressed trees die, canopy gaps occur and other
opportunistic species could take the available space such as following severe and repeated
spruce budworm outbreaks where the canopy becomes sparse. A change in the direction of
succession may occur and lead to the dominance of other tree species if they successfully
establish in the open spaces left by dead balsam fir trees (Bouchard et al. 2006, Sainte-Marie et
al. 2014). However, when dominant trees are grafted to suppressed neighbors or to live stumps,
their root systems continue to occupy the soil leaving no space for invasion (Loehle and Jones
1990). Root grafting may thus reduce inter-specific competition for water, minerals or light if
other trees species are not able to establish (Lev-Yadun 2011). This could be seen as a
cooperative relationship to ensure that soil resources of a site remain within the species (Tarroux
and DesRochers 2010).

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418
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<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Predicted effects of: a) Hegyi competition index, b) Basal Area (BA) and c) graft status (Status) on *Abies balsamea* annual Basal Area Increment (BAI). BG: Before Grafting tree, G: Grafted. 95% confidence intervals are highlighted in grey. Black straight lines are data and N = 39.</figcaption></figure>
639

<figure><img src="image_4.png" /></figure>

640

<figure><img src="image_5.png" /></figure>

641 **Fig. 2.** Predicted effects of: a) Basal Area (BA), b) the interaction between Basal area of the

642 larger tree (BAL) and graft status (Status) on *Abies balsamea* annual Basal Area Increment

643 (BAI). G: Grafted, NG: Non-grafted. 95% confidence intervals are highlighted in grey. Black

644 straight lines are data and N = 110.
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Predicted effects of: a) Basal Area (BA), b) the interaction between Basal area of the larger tree (BAL) and the size of grafted tree within the unions (Size) on *Abies balsamea* annual Basal Area Increment (BAI). L: Larger tree, S: Smallest tree. 95% confidence intervals are highlighted in grey. Black straight lines are data and N = 37.</figcaption></figure>
651 **Table 1:** Root grafting occurrence and site characteristics of the three *Abies balsamea*

652 excavated stands (according to Quer et al. 2020).

<table><thead><tr><th>Site</th><th>S1</th><th>S2</th><th>S3</th><th>Mean</th><th>Total</th></tr></thead><tbody><tr><td>Stand age (years)</td><td>36</td><td>51</td><td>74</td><td>54</td><td>—</td></tr><tr><td>Density (stems ha<sup>-1</sup>)</td><td>14 200</td><td>4800</td><td>6000</td><td>8 333</td><td>—</td></tr><tr><td>Number of excavated trees</td><td>71</td><td>24</td><td>30</td><td>—</td><td>125</td></tr><tr><td>Percentage of grafted trees (%) ± SE</td><td>32.4</td><td>41.7</td><td>40.0</td><td>36.0 ± 2.86</td><td>—</td></tr><tr><td>Mean number of grafts per grafted tree</td><td>1.3</td><td>1.2</td><td>1.3</td><td>1.3 ± 0.03</td><td>—</td></tr><tr><td>Mean graft age (years) ± SE</td><td>11.7 ± 1.1</td><td>11.5 ± 1.3</td><td>19.4 ± 2.5</td><td>13.6 ± 1.0</td><td>—</td></tr><tr><td>Mean Basal Area of the Larger trees index (BAL)</td><td>5691.7 ± 209.6</td><td>3258.7 ± 235.5</td><td>3649.5 ± 328.8</td><td>4659.9 ± 185.1</td><td>—</td></tr></tbody></table>

653
**Table 2:** Linear mixed-effects models tested to describe the annual Basal Area Increment (BAI) of future and grafted *Abies balsamea* according to the competition indexes (HEG and BAL), the Basal Area of the previous year (BA) and the graft presence (Status). Trees, sites and years were set as random effects.

<table><thead><tr><th>Models tested</th><th>Marginal R<sup>2</sup></th><th>Conditional R<sup>2</sup></th><th>AICc</th></tr></thead><tbody><tr><td>log(BAI) ~ Status</td><td>0.102</td><td>0.603</td><td>4737.42</td></tr><tr><td>log(BAI) ~ log(BAL)</td><td>0.177</td><td>0.723</td><td>4606.04</td></tr><tr><td>log(BAI) ~ log(HEG)</td><td>0.497</td><td>0.808</td><td>4234.51</td></tr><tr><td>Log(BAI)~log(BA)</td><td>0.686</td><td>0.917</td><td>3115.59</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA)</td><td>0.704</td><td>0.910</td><td>3093.26</td></tr><tr><td>log(BAI) ~ log(HEG) + log(BA)</td><td>0.726</td><td>0.914</td><td>3058.97</td></tr><tr><td>log(BAI) ~ Status + log(BA)</td><td>0.704</td><td>0.903</td><td>3053.69</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA) + Status</td><td>0.719</td><td>0.899</td><td>3033.33</td></tr><tr><td><strong>log(BAI) ~ log(HEG) + log(BA) + Status</strong></td><td><strong>0.739</strong></td><td><strong>0.906</strong></td><td><strong>3004.26</strong></td></tr></tbody></table>

Note: Best model selected is in bold. Values of marginal R² and conditional R² of the models tested are shown accounting for fixed and random effects. AICc : Second-order Akaike Information Criterion.
<table><caption>**Table 3:** Output of the linear mixed-effects model testing the effect of the Basal Area (BA), the competition index (HEG) and graft status (Status) on the annual Basal Area Increment (BAI) of grafted and future grafted *Abies balsamea*. Trees, sites and years were fixed as random effects.</caption><thead><tr><th rowspan="2">Parameters</th><th colspan="3">Basal area increment</th></tr><tr><th>Estimates</th><th>Std. Errors</th><th>P value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>3.887</td><td>0.310</td><td>***</td></tr><tr><td>Status (G)</td><td>-0.397</td><td>0.050</td><td>***</td></tr><tr><td>HEG</td><td>-0.652</td><td>0.088</td><td>***</td></tr><tr><td>BA</td><td>0.750</td><td>0.017</td><td>***</td></tr></tbody></table>

Note: Parameters, estimated coefficient, standard errors (Std. Errors) and P values of the model are shown. (P values = ***: P < 0.001).

659

660

661

662

663
<table><caption>**Table 4:** Linear mixed-effects models tested to describe the annual Basal Area Increment (BAI) of grafted and non-grafted *Abies balsamea* according to the competition indexes (HEG and BAL), the Basal Area of the previous year (BA) and the graft presence (Status). Trees, sites and years were set as random effects.</caption><thead><tr><th>Models tested</th><th>Marginal R<sup>2</sup></th><th>Conditional R<sup>2</sup></th><th>AICc</th></tr></thead><tbody><tr><td>log(BAI) ~ Status</td><td>0.029</td><td>0.849</td><td>6387.10</td></tr><tr><td>log(BAI) ~ log(BAL)</td><td>0.063</td><td>0.853</td><td>6226.78</td></tr><tr><td>log(BAI) ~ log(HEG)</td><td>0.249</td><td>0.839</td><td>6060.71</td></tr><tr><td>Log(BAI) ~log(BA)</td><td>0.557</td><td>0.895</td><td>5731.52</td></tr><tr><td>log(BAI) ~ Status + log(BA)</td><td>0.677</td><td>0.919</td><td>4632.29</td></tr><tr><td>log(BAI) ~ log(HEG) + log(BA)</td><td>0.673</td><td>0.916</td><td>4631.92</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA)</td><td>0.679</td><td>0.916</td><td>4611.80</td></tr><tr><td>log(BAI) ~ log(HEG) + log(BA) + Status</td><td>0.681</td><td>0.918</td><td>4632.71</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA) + Status</td><td>0.687</td><td>0.919</td><td>4612.52</td></tr><tr><td>log(BAI) ~ log(HEG) × Status + log(BA)</td><td>0.693</td><td>0.918</td><td>4618.56</td></tr><tr><td><strong>log(BAI) ~ log(BAL) × Status + log(BA)</strong></td><td><strong>0.699</strong></td><td><strong>0.921</strong></td><td><strong>4593.91</strong></td></tr></tbody></table>

Note: Best model selected is in bold. Values of marginal R² and conditional R² of the models tested are shown accounting for fixed and random effects. AICc : Second-order Akaike Information Criterion.
669

670

671

672

**Table 5:** Output of the linear mixed-effects model testing the effect of the Basal Area (BA) and the interaction between competition index (BAL) and graft status (Status) on the annual Basal Area Increment (BAI) of grafted and ungrafted *Abies balsamea*. Trees, sites and years were fixed as random effects.

<table><thead><tr><th rowspan="2">Parameters</th><th colspan="3">Basal area increment</th></tr><tr><th>Estimates</th><th>Std. Errors</th><th>P value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>3.062</td><td>0.240</td><td>***</td></tr><tr><td>Status (G)</td><td>1.975</td><td>0.430</td><td>***</td></tr><tr><td>BAL</td><td>-0.175</td><td>0.042</td><td>***</td></tr><tr><td>BA</td><td>0.802</td><td>0.017</td><td>***</td></tr><tr><td>BAL × Status (G)</td><td>-0.529</td><td>0.116</td><td>***</td></tr></tbody></table>

Note: Parameters, estimated coefficient, standard errors (Std. Errors) and P values of the model are shown. (P values = ***: P < 0.001).

673

674
**Table 6:** Linear mixed-effects models tested to describe the annual Basal Area Increment (BAI) of grafted *Abies balsamea* according to the competition indexes (HEG and BAL), the Basal Area of the previous year (BA) and the size of trees within unions (Size). Trees, sites and years were set as random effects.

<table><thead><tr><th>Models tested</th><th>Marginal R<sup>2</sup></th><th>Conditional R<sup>2</sup></th><th>AICc</th></tr></thead><tbody><tr><td>log(BAI) ~ log(HEG)</td><td>0.138</td><td>0.918</td><td>899.49</td></tr><tr><td>log(BAI) ~ Size</td><td>0.146</td><td>0.92</td><td>893.63</td></tr><tr><td>log(BAI) ~ BA</td><td>0.418</td><td>0.92</td><td>795.39</td></tr><tr><td>log(BAI) ~ Size + log(BA)</td><td>0.499</td><td>0.922</td><td>791.31</td></tr><tr><td>log(BAI) ~ log(HEG) + log(BA)</td><td>0.705</td><td>0.94</td><td>718.78</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA)</td><td>0.698</td><td>0.94</td><td>717.15</td></tr><tr><td>log(BAI) ~ log(BAL)</td><td>0.756</td><td>0.957</td><td>667.24</td></tr><tr><td>log(BAI) ~ log(HEG) + log(BA) + Size</td><td>0.746</td><td>0.957</td><td>662.18</td></tr><tr><td>log(BAI) ~ log(BAL) + log(BA) + Size</td><td>0.723</td><td>0.957</td><td>660.92</td></tr><tr><td>log(BAI) ~ log(HEG) × Size + log(BA)</td><td>0.751</td><td>0.957</td><td>660.82</td></tr><tr><td><strong>log(BAI) ~ log(BAL) × Size + log(BA)</strong></td><td><strong>0.698</strong></td><td><strong>0.939</strong></td><td><strong>646.21</strong></td></tr></tbody></table>

Note: Best model selected is in bold. Values of marginal R² and conditional R² of the models tested are shown accounting for fixed and random effects. AICc : Second-order Akaike Information Criterion.

679
**Table 7:** Output of the linear mixed-effects model testing the effect of the Basal Area (BA) and the interaction between competition index (BAL) and size of grafted tree (Size) on the annual Basal Area Increment (BAI) of grafted *Abies balsamea*. Trees, sites and years were fixed as random effects.

<table><thead><tr><th rowspan="2">Parameters</th><th colspan="3">Basal area increment</th></tr><tr><th>Estimates</th><th>Std. Errors</th><th>P value</th></tr></thead><tbody><tr><td>(Intercept)</td><td>5.046</td><td>0.240</td><td>***</td></tr><tr><td>Size (S)</td><td>4.364</td><td>0.529</td><td>***</td></tr><tr><td>BAL</td><td>-0.709</td><td>0.155</td><td>**</td></tr><tr><td>BA</td><td>0.767</td><td>0.043</td><td>***</td></tr><tr><td>BAL × Size (S)</td><td>-1.336</td><td>0.150</td><td>***</td></tr></tbody></table>

Note: Parameters, estimated coefficient, standard errors (Std. Errors) and P values of the model are shown. (P values = ***: P < 0.001 ; **: P < 0.01).