Edited by: Boris Rewald, University of Natural Resources and Life Sciences, Austria
Reviewed by: David M. Eissenstat, Penn State University, USA; Agostino Sorgona, Università Mediterranea di Reggio Calabria, Italy
*Correspondence: Cornelia M. Tobner, Département des Sciences Biologiques, Université du Québec à Montréal, PO Box 8888, Centre-Ville station, Montreal, QC H3C 3P8, Canada e-mail:
This article was submitted to Frontiers in Functional Plant Ecology, a specialty of Frontiers in Plant Science.
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
Fine roots play an important role in nutrient and water absorption and hence overall tree performance. However, current understanding of the ecological role of belowground traits lags considerably behind those of aboveground traits. In this study, we used data on specific root length (SRL), fine root diameter (D) and branching intensity (BI) of two datasets to examine interspecific trait coordination as well as intraspecific trait variation across ontogenetic stage and soil conditions (i.e., plasticity). The first dataset included saplings of 12 North American temperate tree species grown in monocultures in a common garden experiment to examine interspecific trait coordination. The second dataset included adult and juvenile individuals of four species (present in both datasets) co-occurring in natural forests on contrasting soils (i.e., humid organic, mesic, and xeric podzolic).The three fine root traits investigated were strongly coordinated, with high SRL being related to low D and high BI. Fine root traits and aboveground life-strategies (i.e., relative growth rate) were weakly coordinated and never significant. Intraspecific responses to changes in ontogenetic stage or soil conditions were trait dependent. SRL was significantly higher in juveniles compared to adults for
The search to understand the effects of species on ecosystem functioning has brought forward the functional role of various traits. Functional traits have been shown to link species to the roles they play in the ecosystem. Through changes at the organismal level they not only influence individual performance but also higher organizational levels and hence drive ecosystem processes and services (Diaz et al.,
Although the physiological and ecological importance of roots is well established, the great variability of root systems, the small and varied size of fine roots and the relative inaccessibility of the belowground realm have all hampered exhaustive root research. In addition, the lack of consensus about how to classify and measure fine roots has constrained the development of a unified framework toward a root economics spectrum as was achieved for both leaves (Wright et al.,
Above- and below-ground organs share many functions, such as nutrient acquisition and transfer. Some functional coordination between above and belowground traits is therefore expected (Westoby and Wright,
Apart from mean trait values used to coordinate and characterize species, trait plasticity has gained momentum as a driver of individual fitness and consequently, community dynamics. Evidence is accumulating that through changes in realized niches, trait plasticity can be linked to a species' competitive ability and hence overall fitness (Berg and Ellers,
Probably the most studied fine root trait is SRL, the ratio between root length and weight (Zobel et al.,
Through its link to surface area and volume, fine root diameter (D) is an important trait directly linked to nutrient and water absorption. Although D has been shown to be plastic and strongly dependent on nutrient supply (Eissenstat et al.,
Lastly, branching intensity (BI, also called root tip density) is a fine root trait describing the topology of fine roots by counting the number of tips per unit root length. Changes in BI to environmental factors have been assessed in only a handful of studies, with contrasting results (Ahlström et al.,
In the present study, we examined interspecific (coordination) and intraspecific variation across contrasting soil conditions (i.e., plasticity) as well as with ontogenetic stages (i.e., adults versus juveniles) for SRL, D and BI. A first dataset (“common garden,” CG), including 12 North American temperate tree species grown in a common garden experiment was used to examine trait variation across species. We tested the hypotheses that under uniform controlled conditions:
SRL, BI and D are strongly coordinated across species of wide variation in root morphology; and Belowground fine root traits are correlated to whole-plant life-strategies, such as relative growth rate.
A second dataset (“natural forest”, NF) of four tree species (also present in the CG dataset) that included adults and juveniles co-occurring on contrasting soil conditions in natural forests was employed to examine trait variation in relation to species, ontogeny and soil conditions. More specifically, we tested the hypotheses that:
SRL and BI are greater and D smaller in juvenile compared to adult trees; SRL and BI generally increase while D decreases with decreasing soil moisture and nutrient content; Phenotypic plasticity is greater in fine root traits that are more strongly associated with resource uptake (i.e., SRL and D).
The study site for the first dataset was located at Ste-Anne-de-Bellevue, near Montreal, Québec, Canada (45°26'N, Long 73°56'W, 39 m.s.l). Mean annual temperature is 6.2°C with a mean annual precipitation of 963 mm (climate.weatheroffice.gc.ca). On this former agricultural field that has been managed for several decades (Marc Samoisette, personal communication, October 2011), monocultures of twelve North American temperate forest species were established in spring 2009 with seedlings of 1 (broadleaf) or 2 (conifer) years of age. These monocultures are part of an ongoing experiment on biodiversity and ecosystem functioning with trees (Tobner et al., submitted). Within the objectives of this biodiversity experiment, the 12 species were selected to cover a wide range of functional traits, including angio- and gymnosperms, and early and late successional species:
Each species was planted in a square plot of eight by eight individuals (50 × 50 cm). Plots were replicated four times within an area of ~0.6 ha. Plots were weeded manually and a fence was installed to protect against ungulate herbivory.
Traits were measured in September 2011. From each plot, two individuals were selected that were growing in the outer rows (to minimize impacts on the ongoing experiment). This was repeated for each of the four replicate blocks resulting in eight individuals sampled per species. Following the main axis (i.e., stem), a root that grew toward the inside of the plot was detected and followed until it branched off into roots <2 mm. Roots were excavated and placed in a cooler for transport. Roots were then stored at 4°C until processing that occurred no later than 2 weeks after sampling.
Roots were carefully washed and separated into segments of the first three orders. This classification approach (i.e., 1st to 3rd order roots) was chosen following Guo et al. (
The study site for the second dataset was situated at the Station de biologie des Laurentides of Université de Montréal in St-Hippolyte, Québec, Canada (Lat 45°59'N, Long 73°59'W, 366 m.s.l.). The research station consists of an area of about 16 km2 of forest and lakes dedicated to research and has been protected from other human activities since 1963. Birch (
Four forest species, also present in the CG dataset, co-occur in the forests of the research station on contrasting soil conditions: Humisols with standing water level between 10 to 20 cm belowground and Orthic humoferric podzols (Courchesne and Hendershot, Orthic humoferric podzols with good drainage, nil to very gentle slope and
For each soil type, three plots covering at least 200 m2 were established. Plots were located under closed canopy, with no recent sign of perturbation and at least four adult and four juvenile individuals of the target species. Exceptions were
At the center of each plot, one soil sample was taken at 20 cm depth on August 22, 2011. The average daily temperature in the 2 weeks preceding soil sampling was 17.5°C. Precipitation for the same period amounted to 46 mm distributed over 6 days with 15 mm being the strongest precipitation event for 1 day.
Soil samples were placed in resealable plastic bags and immediately stored at −18°C before further processing that occurred no later than 1 week after collection. Samples were then oven-dried at 65°C until they reached constant weight and sieved through a 2 mm mesh prior to soil analyses. Soil moisture was the difference in sample weight before and after drying. Soil pH was measured in water in a ratio of one part soil (10 mg) to two parts water for mineral soil and one part soil (4 mg) to five parts water for organic soils (Canadian Society of Soil Sciences,
HO | 85.2 ± 1.8 | 4.88 ± 1.1 | 1.9 ± 1.1 | 95.9 ± 3.4 | 5.9 ± 2 | 14.85 ± 2.6 | 7.1 ± 0.4 | 6.3 ± 3.5 | 8.0 ± 4.2 |
MP | 30.7 ± 3.0 | 5.05 ± 0.0 | 0.6 ± 0.2 | 29.9 ± 16.2 | 7.2 ± 3 | 4.7 ± 0.4 | 23 ± 14.1 | 9.5 ± 5.6 | |
XP | 19.2 ± 7.2 | 4.70 ± 0.3 | 0.5 ± 0.1 | 19.1 ± 4.7 | 6.0 ± 3.4 | 10.1 ± 5.6 | 4.0 ± 2.9 | 6.7 ± 3.0 | 11.6 ± 14.0 |
On each plot, species and DBH of all adult trees (i.e., DBH >10 cm) were recorded to calculate basal area (Table
For the four target species, at least four adult and four juvenile individuals were sampled (i.e., total of 12 adults and 12 juveniles per soil condition). For each adult tree, two root samples were collected in opposite directions from each other. From the stem, roots were excavated and followed until they branched off into fine roots (<2 mm diameter). Roots of adult individuals were excavated from the mineral or organic soil horizons, never from the humus or litter layers. Furthermore, for each adult individual, at least three of the highest branches were harvested with the help of a professional tree climber to obtain sun leaves. For juveniles, the entire plant was excavated for root samples and at least three leaves or 20 needles were collected.
Leaf and root samples were immediately put into sealed plastic bags, labeled and stored at about 4°C until further processing, occurring no later than 6 weeks after sampling. For each individual, 3–5 leaves were punched with a hollow metal pin, yielding leaf samples of a standard surface area. A minimum of 20 needles of the previous year of growth were plucked off the branch and scanned. Samples were then oven-dried to constant weight to calculate SLA (foliage area/foliage weight, mm mg−1).
Root samples (<2 mm) of each individual were carefully washed and scanned and analyzed in an identical fashion to the CG dataset. Once the complete sample was scanned, parts of the image containing first to third order roots were selected and re-analyzed. For these subsamples, average diameter, total length and number of tips were calculated. In addition, root diameter was assessed following the handbook of trait measurements (Cornelissen et al.,
Hereafter for both datasets, traits measured on complete root samples (roots <2 mm) are noted using the subscript “c” (e.g., Dc), while results for fine roots defined as first to third order roots are noted with subscript “3” (e.g., D3). Diameter measured on first order roots is noted as “D1”.
The total phenotypic variability of a population is the result of genetic and environmental sources and their interaction (Hartl and Clark,
In a second step, for each trait and species we calculated an index of the variability which is due solely to variation in the environment, the phenotypic plasticity index (PI). Determining the contribution of the environmental source of variability is essential in assessing a population's potential to adapt to heterogeneous or changing environments (Byers, [max(trait mean among soil conditions) − min(trait mean among soil conditions)]/max[trait mean among soil conditions]
Finally, to compare the phenotypic plasticity with the overall phenotypic variability, we computed a ratio of PI to CV (PI:CV) as an expression of how much of the overall phenotypic variability is due to plastic responses to the environment. Both CV and PI vary between zero and one. Hence, a PI:CV of zero would indicate no environmental source of variability, whereas a PI:CV of one would indicate that the overall phenotypic variability is completely due to acclimations to the environment. Although the literature on trait variation and plasticity is rich, we are not aware of other studies using PI:CV to explore differences in relative plasticity between species and traits.
For both datasets, traits were tested for normality with the Shapiro test and transformations were applied where needed to correct for deviations. To test for species differences within the CG dataset, a One-Way ANOVA with subsequent Tukey HSD test was performed. Trait correlations were assessed using the Pearson correlation coefficient.
To test for effects of soil condition and ontogenetic stage on fine root traits in the NF dataset, linear mixed effect models (REML) with site (random effect) as well as the interaction of plot and ontogenetic stage nested within soil condition were applied for each species. The asymptotic inference test for coefficients of variation as described in Miller and Feltz (
In the common garden, fine root traits were highly coordinated across species, especially SRL3 and D3 (Table
SRL3 | |||
BI3 | |||
RGR | 0.05 | 0.07 | 0.07 |
In the natural forest, fine root diameter in woody (i.e., Dc and D3) as well as non-woody roots (i.e., D1) was generally greater in humid organic than in mesic and xeric podzol conditions. However, differences were only significant for
Soil | 0.07 |
< |
0.95 | 0.67 | 0.17 | 0.47 | ||
OS | 0.12 | 0.30 | 0.58 | 0.44 | ||||
Soil+OS | 0.72 | 0.43 | 0.20 | 0.71 | 0.98 | 0.96 | 0.34 | |
Soil | 0.09 |
0.22 | 0.77 | 0.60 | 0.66 | |||
OS | 0.09 |
0.72 | 0.21 | 0.71 | ||||
Soil+OS | 0.71 | 0.95 | 0.67 | 0.51 | 0.66 | 0.59 | 0.42 | |
Soil | 0.13 | 0.76 | 0.14 | 0.55 | 0.11 | 0.10 | 0.09 |
|
OS | 0.63 | 0.13 | ||||||
Soil+OS | 0.99 | 0.33 | 0.53 | 0.75 | 0.33 | 0.47 | ||
Soil | 0.15 | 0.54 | 0.10 | 0.15 | 0.50 | 0.65 | 0.77 |
A | HO | 0.62/0.11 | 11.7/0.31 | 2.3/0.33 | 2.1/0.39 | |||
MP | 0.46/0.23 | 10.7/0.17 | 2.7/0.22 | 2.7/0.23 | ||||
XP | 0.55/0.15 | 11.0/0.24 | 2.4/0.18 | 2.0/0.30 | ||||
All sites | 0.59/0.14 | 0.55/0.20 | 0.47/0.20 | 11.1/0.25 |
2.5/0.25 |
2.3/0.32 | ||
J | HO | 0.55/0.19 | 15.0/0.41 | 2.2/0.27 | 2.2/0.34 | |||
MP | 0.47/0.15 | 17.0/0.49 | 2.5/0.32 | 2.8/0.22 | ||||
XP | 0.50/0.13 | 14.4/0.32 | 2.2/0.38 | 2.2/0.28 | ||||
All sites | 0.55/0.16 | 0.51/0.17 | 0.42/0.14 | 15.5/0.42 |
2.3/0.32 |
2.4/0.29 | ||
A | HO | 0.64/0.14 | 13.1/0.19 | 1.8/0.34 | 1.4/0.24 | |||
XP | 0.56/0.14 | 14.0/0.15 | 1.9/0.34 | 1.3/0.24 | ||||
All sites | 0.60/0.15 | 0.60/0.18 | 0.55/0.14 | 13.6/0.17 |
1.8/0.33 |
1.3/0.24 | ||
J | HO | 0.59/0.13 | 12.9/0.25 | 1.5/0.31 | 1.6/0.37 | |||
XP | 0.50/0.16 | 14.7/0.21 | 1.7/0.49 | 1.4/0.42 | ||||
All sites | 0.55/0.17 | 0.52/0.16 | 0.46/0.18 | 13.8/0.24 |
1.6/0.43 |
1.5/0.39 | ||
A | HO | 0.45/0.14 | 0.40/0.14 | 0.42/0.13 | 24.6/0.27 | 2.9/0.11 | 3.6/0.21 | |
MP | 0.39/0.13 | 0.36/0.17 | 0.36/0.19 | 24.9/0.31 | 2.8/0.16 | 3.6/0.24 | ||
XP | 0.40/0.14 | 0.39/0.17 | 0.36/0.14 | 26.6/0.23 | 2.6/0.17 | 3.1/0.28 | ||
All sites | 0.41/0.15 | 0.39/0.16 | 0.38/0.17 | 25.4/0.26 |
2.8/0.15 |
3.4/0.25 | ||
J | HO | 0.41/0.14 | 0.32/0.18 | 0.36/0.11 | 28.2/0.18 | 3.0/0.22 | 3.0/0.23 | |
MP | 0.36/0.15 | 0.33/0.14 | 0.31/0.15 | 33.4/0.36 | 3.3/0.16 | 3.5/0.21 | ||
XP | 0.36/0.12 | 0.35/0.13 | 0.34/0.14 | 33.1/0.22 | 2.4/0.12 | 2.7/0.25 | ||
All sites | 0.38/0.15 | 0.33/0.15 | 0.34/0.14 | 31.3/0.28 |
3.0/0.21 |
3.1/0.24 | ||
A | HO | 0.37/0.20 | 0.29/0.32 | 0.30/0.16 |
24.9/0.43 | 3.1/0.13 | 3.7/0.29 | |
MP | 0.40/0.06 | 0.26/0.35 | 0.22/0.26 |
17.3/0.40 | 3.5/0.09 | 3.8/0.20 | ||
XP | 0.34/0.14 | 0.26/0.21 | 0.23/0.17 |
28.0/0.17 | 3.1/0.22 | 4.1/0.23 | ||
All sites | 0.36/0.16 | 0.27/0.29 | 0.25/0.24 | 23.2/0.38 |
3.2/0.17 |
3.9/0.24 |
SRLc never varied significantly across soil conditions but was significantly greater for juveniles compared to adults in
PI was greatest in Dc except for
As expected, SLA was significantly higher in shade-grown leaves of juveniles compared to sun leaves of adults (Table
Although fine root classification based on root orders did not uniformly reduce variation (i.e., CV) compared to fine root classification based on size (Table
The observed belowground trait correlations across various taxa indicate strong coordination among fine root morphological traits supporting the idea of a generalized tree root syndrome (Holdaway et al.,
As root diameter and root mass density constitute the two components of SRL, the strong negative correlation between SRL and D was expected (Fahey and Hughes,
Although evidence is still sketchy, root syndromes are based on a trade-off between life-history strategies (e.g., RGR) and tissue longevity. Thus, roots with high SRL, thin D and low tissue density are generally associated with greater root proliferation, greater RGR and shorter overall longevity (Eissenstat,
In the present study, no significant relationships were found between fine root traits and RGR based on volume, height or diameter (only volume is reported). Here, the two species with highest SRL were also the species with the highest and lowest RGR (
Trait responses to ontogenetic stage were trait dependent. Similar trends of decreasing SRL with age as shown in our study have been reported in the literature for Japanese cedar (
Two possible mechanisms may explain differences in root morphology with age. On the one hand, higher SRL and lower D in juveniles could be an artifact of differences in root orders measured as it is likely that juvenile root samples <2 mm contain fewer root orders than their conspecific adults. For a multitude of species, SRL and D have been shown to significantly change with root order (Pregitzer et al.,
It appears thus more likely, that the observed changes in root morphology with ontogenetic stage may be an adaptation to rooting depth. In most of the above-mentioned studies examining the effect of tree age on root morphology, including the present study, soil depth was not accounted for. However, changes in SRL and diameter with soil depth have been reported in other studies (Wang et al.,
It was surprising that BI never changed significantly with ontogenetic stage. In fact, BI also never changed significantly with soil condition, pointing toward a rather conservative trait and fine root topology.
As shown above with ontogenetic stages, fine root responses to soil conditions were also trait specific. Despite the large gradient in soil nutrients and water (Table
SRL has been studied extensively and it was often associated with root proliferation in response to nutrient heterogeneity (Hodge,
As mentioned earlier, SRL has two components: diameter and root mass density. While SRL did not change significantly with soil conditions, D was higher in humid organic conditions compared to mesic and xeric podzolic conditions implying a possible inverse response of root mass density that could explain the lost signal in SRL. In grasses, decreases in nitrogen and phosphorus have been shown to decrease root diameter and increase tissue mass density (Ryser and Lambers,
A limited number of studies have examined responses of BI to soil nutrition, reporting mostly non-significant changes (George et al.,
From the three fine root traits assessed in the present study, D clearly showed the greatest plasticity (PI) and was also the trait where phenotypic plasticity contributed the most to total phenotypic variability (highest PI:CV). This coincides with it being the most responsive trait to soil conditions (Tables
Variability of BI was highly species specific. In adults and juveniles, CV for BIc was similar to those of Dc for the two angiosperm species and significantly higher for the two gymnosperm species. In addition, CV was generally higher in juveniles compared to adults. This trend is reversed in many cases when measured on D3, D1, or BI3 (Table
Fine root morphological traits were found to be strongly coordinated across species, but further work is needed to test for general patterns across ecosystems and biomes. Above- and below-ground traits and whole-plant-strategies may not be as coordinated as previously thought once other factors such as site productivity are accounted for or controlled as we have done in this study for the common garden experiment. For the natural forest experiment, fine root traits responded differently to soil conditions within species, with fine root diameter being the most responsive. Diameter showed the least total variation yet much of it was explained by changes in the environment. Consequently, D may be the most suitable trait for evaluating plasticity to soil nutrition for the rhizosphere.
Lastly, the present study underscores the need for a unified framework of fine root classification and stronger control for the many possible confounding factors in root studies. Although a functional classification of fine roots managed to reduce variance in a limited number of cases, it improved estimator evaluation in at least one species. Most importantly, a unified framework would greatly facilitate the comparison of studies and therefore increase current understanding of the functional ecology of roots.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We greatly appreciated the support of the entire staff of the Station de biologie des Laurentides (Université de Montréal) and of Nicolas Bélanger (TÉLUQ, Université du Québec) for his advice on and help with soil analyses. We'd also like to express our thankfulness to Marc Samoisette (McGill University) and François Courchesne (Université de Montréal) for their valuable information about the study sites as well as to the many people handling roots or climbing trees. The authors also thank Dylan Craven for editing and improving the manuscript. Funding for this project was provided by a NSERC RDC grant to Christian Messier and a FQRNT scholarship to Cornelia M. Tobner.