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Article
Gap Size in Hyrcanian Forest Affects the Lignin and N
Concentrations of the Oriental Beech (Fagus orientalis Lipsky)
Fine Roots but Does Not Change Their Morphological Traits in
the Medium Term
Alireza Amoli Kondori 1, Kambiz Abrari Vajari 1, *, Mohammad Feizian 1, Antonio Montagnoli 2
and Antonino Di Iorio 2
Citation: Kondori, A.A.; Vajari, K.A.;
Feizian, M.; Montagnoli, A.; Di Iorio,
A. Gap Size in Hyrcanian Forest
Affects the Lignin and N
Concentrations of the Oriental Beech
(Fagus orientalis Lipsky) Fine Roots
but Does Not Change Their
Morphological Traits in the Medium
Term. Forests 2021,12, 137.
https://doi.org/10.3390/f12020137
Academic Editor:
Antonio Montagnoli
Received: 16 December 2020
Accepted: 21 January 2021
Published: 26 January 2021
Publisher’s Note: MDPI stays neutral
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iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Faculty of Agriculture and Natural Resource, Lorestan University, Khorramabad 6815144316, Iran;
amolikondori@gmail.com (A.A.K.); feizian.m@lu.ac.ir (M.F.)
2Department of Biotechnology and Life Science, University of Insubria, 21100 Varese, Italy;
antonio.montagnoli@uninsubria.it (A.M.); antonino.diiorio@uninsubria.it (A.D.I.)
*Correspondence: kambiz.abrari2003@yahoo.com; Tel.: +98-911-344-1571
Abstract:
Research Highlights: Fine roots play an important role in plant growth as well as in carbon
(C) and nutrient cycling in terrestrial ecosystems. Gaining a wider knowledge of their dynam-
ics under forest gap opening would improve our understanding of soil carbon input and below-
ground carbon stock accumulation. Single-tree selection is increasingly recognized as an alternative
regime of selection cutting sustaining biodiversity and carbon stock, along with timber production,
among ecosystem functions. However, the fine root response in terms of morphological and chem-
ical composition to the resulting harvest-created gaps remains unclear. Background and Objectives:
This paper investigates the effect in the medium term (i.e., 6 years after logging) of differently sized
harvest-created gaps on fine root dynamics and chemical composition. Materials and Methods: A total
of 15 differently sized gaps (86.05–350.7 m
2
) and the adjacent 20 m distant closed canopies (control)
were selected in a temperate Fagus orientalis forest (Hyrcanian region, Iran). Eight soil cores were
collected at the cardinal points of the gap edge, including four facing the gap area—the same at
the adjacent intact forest. Results: For the selected edge trees, the different size of gaps, the core
position, and the tree orientation did not affect the investigated morphological traits, except for the
slightly higher specific root length (SRL) for the larger fine root fraction (1–2 mm) in the side facing
the gap area. Differently, the investigated chemical traits such as N concentration and cellulose:lignin
ratio significantly increased with increasing gap size, the opposite for C:N ratio and lignin. More-
over, N concentration and C:N significantly decreased and increased with the fine root diameter,
respectively. Conclusions: This work highlighted that, in the medium term and within the adopted
size range, artificial gap opening derived from single-tree selection practice affected the chemistry
rather than the biomass and morphology of gap-facing fine roots of edge trees. The medium term of
six years after gap creation might have been long enough for the recovery of the fine root standing
biomass to the pre-harvest condition, particularly near the stem of edge trees. A clear size threshold
did not come out; nevertheless, 300 m
2
may be considered a possible cut-off determining a marked
change in the responses of fine roots.
Keywords:
forest gap; forest management; fine roots; morphology; lignin; carbon; nitrogen; Fagus
orientalis
1. Introduction
Fine roots (diameter <2 mm) are the most dynamic and sensitive component within
the overall root system [
1
,
2
], playing a crucial role in water and nutrient acquisition [
3
].
They have also been regarded as short-lived and recognized as the most important com-
ponent contributing to below-ground C and N fluxes in forest ecosystems [
4
,
5
]. Indeed,
Forests 2021,12, 137. https://doi.org/10.3390/f12020137 https://www.mdpi.com/journal/forests
Forests 2021,12, 137 2 of 14
estimation of fine root production accounts for as much as 33–67% of the total annual net
primary production (NPP) [
6
], although fine root biomass contributes relatively little to
total forest biomass, usually <5% [
7
]. Furthermore, fine root mortality contributes from
18 to 58% of total N to forest soils, making the root litter N addition higher than that from
above-ground litterfall in some ecosystems [4,5].
Fine root biomass has been found to vary with forest stand characteristics, i.e.,
tree species, stand age, density, basal area, canopy openness and soil properties, or envi-
ronmental factors such as air temperature, amount of precipitation, geographical location,
and elevation. In general, changes in canopy openness resulting from differently shaped
gaps or coppice conversion to high forest highlighted a significant decrease in fine root
biomass in the exposed soil [
8
–
10
]. For both types of management practices, fine root
biomass has been found to decrease in the exposed soil surface of the gap center and
proportionally to its increasing size [
9
,
11
], and reduced basal area [
12
]. Morphological
traits related to fine root biomass also vary with gap opening since the mean diameter of the
fine root population changes with change in the soil moisture caused by the opening in the
canopy cover [
13
,
14
]. For example, under drier soil conditions, plants produce longer and
finer roots [
13
,
15
], which results in a relatively greater length per unit mass, thereby leading
to an increase in specific root length (SRL, length-to-mass ratio). Concerning the chemical
traits related to the fine root biomass, carbon and nitrogen concentrations are well known
to change with changes in diameter classes, branching order [
16
,
17
], and seasonality [
16
,
18
].
In beech forests, for example, fine root C and N concentrations show a reverse pattern
compared to each other, with the highest and lowest values for C concentration in July and
October, respectively [
18
]. However, how fine root morphological and chemical traits vary
with gap size is still poorly investigated.
Forest ecosystems are exposed to natural disturbances, which can have a serious
impact on their functioning especially in a worsening global climate scenario [
19
]. In par-
ticular, disturbances such as diseases [
20
–
22
], storm [
23
,
24
], fire [
25
] may cause injuries
to trees enough to cause the formation of forest gaps. In temperate broadleaf forests,
where large-scale disturbances are rare, natural regeneration occurs predominantly in
gaps [
26
,
27
]. Therefore, forest management that approximates nature, such as single-tree
selection practice, appears to be a flexible and useful tool to secure sustainable forest de-
velopment in terms of biodiversity [
26
,
27
] and uneven-aged forests [
28
]. This tool mimics
natural openings of various sizes that follow moderate disturbance events [
29
]. On the
other hand, both natural and artificial gaps induce the alteration of microclimate conditions
(i.e., soil moisture and temperature, irradiance) either inside or in the proximity of the
gaps [
30
], leading to below-ground responsive adjustments in terms of fine root dynamics
whose magnitude may change with the increasing size of the gap [
11
]. Therefore, unveil-
ing the threshold that could lower the impact on fine root morphological and chemical
traits of edge trees may be of interest for sustainable forest management, which would lead
to a higher amount and lasting in time below-ground carbon stock accumulation. This is
particularly relevant as no common agreement exists on the definition of the size class of the
gap; for example, the small criterion ranges from 300 [
29
], 700 [
31
,
32
] to 1250–1960 m
2
[
29
].
Differences in fine root biomass among forest stands have been modeled to change
also from stand initiation to a later stage of stand development (canopy closure) [
33
].
In particular, short-lived fine roots generally <0.5 mm in diameter [
34
,
35
] and character-
ized by higher turnover rate are predominant during the first years following thinning
operations [
36
,
37
]. For this reason, short-term (1–4 years) studies may not adequately track
the fine root fraction characterized by a higher longevity and that mostly contribute to the
standing biomass [
36
,
37
]. Thus, choosing the sampling time since the gap opening occurred
is crucial for a correct estimation of the fine root standing biomass, and medium-term
investigation may be considered a good compromise.
Fine root form and function may differ among branching orders [
38
,
39
] and the
shortcomings of the diameter-based approach are widely recognized [
40
]. Therefore, in this
study, the size class approach was maintained for a better discrimination between the
Forests 2021,12, 137 3 of 14
<0.5 mm diameter class (i.e., very fine roots), which represent the most dynamic component
of the root system, and the 0.5–1 and 1–2 mm diameter classes, which represent the more
stable and woodier portion [41–43].
Oriental (or eastern) beech (Fagus orientalis Lipsky) forests represent the most im-
portant tree cover in the temperate-broadleaved forest in northern Iran, playing a key
role in forestry activities. Caspian forests of Iran have been harvested under different
silvicultural systems, such as shelterwood cutting or single-tree selection, which leads
to different canopy openness [
19
]. Single-tree selection is increasingly recognized as an
alternative regime of selection cutting sustaining biodiversity, recruitment and carbon
stock, along with timber production, among ecosystem functions [
44
]. Many studies were
conducted about different features of F. orientalis trees, but few on the fine roots [
31
,
32
] and
their response at the morphological and chemical level to the different-sized gaps.
In this study, the two-fold hypothesis was that, in the medium term, gap openings
might: (i) induce a reduction in fine root biomass greater than in length and, consequently,
increase the specific root length (SRL), and (ii) increase the metabolism of fine roots leading
to a higher N concentration. These variations would be of greater magnitude with the
increasing gap size. To test these hypotheses, for trees positioned at the edge of different-
sized gaps, fine root biomass, length, and tissue density were measured together with C,
N, lignin, and cellulose concentrations. This approach was intended to use the F. orientalis
tree fine root morpho-chemical traits as indicators of a threshold gap size above which
a significant influence on tree ecophysiology may occur.
2. Materials and Methods
2.1. Study Area
To study the effects of gap size on fine roots properties, a broadleaved Fagus orientalis
L. forest, covering an area of 40.4 ha, was selected in the Caspian area (Mazandaran
province), northern Iran (36
◦
12
0
N,53
◦
24
0
E). The general characteristics of this area were
already described in a previous work carried out on the same site [
45
]. Briefly, the study
site is located at an elevation of 1000–1200 m a.s.l., on a north-facing slope of 0–30%.
The climate is humid with a mean annual temperature of 10.5
◦
C and a mean annual
precipitation of 858 mm. The pseudogleyic and gley are the dominant soil types. The shade-
adapted and broadleaved F. orientalis trees occupy all canopy layers, from overtopped to
dominant ones, and other tree species including hornbeam (Carpinus betulus), alder (Alnus
subcordata), and maple (Acer velutinum) are also present. The oriental beech stand in
the study site is multi-layered, uneven-aged, and developed from natural regeneration.
At the time of fine root sampling, the stand density was 178 trees ha
−1
, with a mean
tree height and diameter at breast height (DBH) of 30.95
±
0.79 m (mean
±
SE) and
58.83 ±2.37 cm
, respectively. No natural disturbance regime, such as storm, heavy snow
or fire, is recorded in the forestry plan. The silvicultural practice historically adopted is
the single-tree selection, which produced different-sized artificial gaps depending on the
crown size of the harvested tree.
2.2. Experimental Design
In 2011, 45 gaps were randomly opened on the stand by felling different-sized trees.
A 50 m buffer of trees was maintained between all gaps, equal to twice the diameter of the
largest gap. Forest harvesting operations were conducted to prevent soil disturbance as
much as possible within the stand. In total, 15 elliptical different-sized gaps ranging from
86.05 to 350.7 m
2
were selected for this study. Detailed information on gap and related tree
sizes are reported in Table S1. Each single gap was considered as the experimental unit,
making this experimental design a point comparison approach rather than a replicated
experiment on the ecosystem scale. The gap area was measured using the formula for an
ellipse: A= (
π
LW)/4, where Land W(m) are the longest and the largest perpendicular
to L distances within the gap, respectively (Figure 1). These distances were measured
between stems of the edge trees. All gaps were oriented with the short distance W always
Forests 2021,12, 137 4 of 14
parallel to the north direction. To compare with undisturbed forest, the adjacent 20 m
distant closed-canopy clustered trees (uncut control) were selected for each gap size.
Forests 2021, 12, x FOR PEER REVIEW 4 of 15
experiment on the ecosystem scale. The gap area was measured using the formula for an
ellipse: A = (πLW)/4, where L and W (m) are the longest and the largest perpendicular to
L distances within the gap, respectively (Figure 1). These distances were measured be-
tween stems of the edge trees. All gaps were oriented with the short distance W always
parallel to the north direction. To compare with undisturbed forest, the adjacent 20 m
distant closed-canopy clustered trees (uncut control) were selected for each gap size.
2.3. Fine Root Sampling
Field sampling of fine roots was carried out late in the growing season in October
2017 in all 15 artificial gaps and adjacent intact forest, i.e., 6 years after gap creation. Soil
samples were collected by hand soil corer (Root Auger 80 mm inner diameter, ELE Inter-
national, Bedfordshire, UK) to 20 cm soil depth at 1 m distance from the trunk. The sam-
pling protocol followed the scheme reported in Figure 1 [41]. For each gap, eight soil cores
were collected at the cardinal points of the gap border, and eight at the adjacent intact
forest at 20 m from the gap. Of the eight cores, four were sampled in the side facing the
gap area (front) and four on the opposite side (back). Core samples were stored in plastic
bags in a commercial cool box (mod. 9315, Gio Style Spa, Italy) including ordinary freezer
packs, transported to the laboratory, and kept at 4 °C until processed.
Figure 1. Sketch of location of the sampling points in the gap (white area) and adjacent intact forest
(light green area). Large black circles indicate the sampled trees, small brown circles the soil core
position, in the front and back of the selected trees. Dashed L and W lines indicate the distances
among stems used for ellipse calculation. All gaps were oriented with the short distance of the el-
lipse always parallel to the north direction.
2.4. Morphological Features of Fine Roots
In the laboratory, all soil samples were washed on a sieve (1 mm mesh size) to remove
the soil. Soil freed fine roots were further cleaned from soil residues under a stereo-micro-
scope, and beech fine roots were distinguished from other understory roots by morpho-
logical characteristics. Beech fine roots appear reddish and stiffer than the understorey
roots; these morphological characteristics were previously established from samples dug
near the tree. Fine root samples were then scanned at a resolution of 500 dpi with a cali-
brated flatbed scanner coupled to a lighting system (Expression 10,000 XL, Epson America
Inc., Long Beach, CA, USA). The resulting images were analyzed with WinRhizo Pro V.
2007d software (Regent Instruments Inc., Quebec, QC, Canada), which, setting the diam-
eter classes with different colors, made it possible to group with high accuracy the root
axes in three diameter classes (<0.5; 0.5–1.0; 1.0–2.0 mm); root axes were separated from
each other where necessary with scissors or scalpels. The morphometric measurements as
length and mean diameter were performed. Successively, fine-roots belonging to each di-
ameter class were grouped, oven-dried at 70 °C (48 h), and weighed for dry mass meas-
urements. Morphometric data, together with dry weight data, were also used to calculate
Figure 1.
Sketch of location of the sampling points in the gap (white area) and adjacent intact forest
(light green area). Large black circles indicate the sampled trees, small brown circles the soil core
position, in the front and back of the selected trees. Dashed L and W lines indicate the distances
among stems used for ellipse calculation. All gaps were oriented with the short distance of the ellipse
always parallel to the north direction.
2.3. Fine Root Sampling
Field sampling of fine roots was carried out late in the growing season in October 2017
in all 15 artificial gaps and adjacent intact forest, i.e., 6 years after gap creation. Soil samples
were collected by hand soil corer (Root Auger 80 mm inner diameter, ELE International,
Bedfordshire, UK) to 20 cm soil depth at 1 m distance from the trunk. The sampling
protocol followed the scheme reported in Figure 1[
41
]. For each gap, eight soil cores were
collected at the cardinal points of the gap border, and eight at the adjacent intact forest at
20 m from the gap. Of the eight cores, four were sampled in the side facing the gap area
(front) and four on the opposite side (back). Core samples were stored in plastic bags in
a commercial cool box (mod. 9315, Gio Style Spa, Italy) including ordinary freezer packs,
transported to the laboratory, and kept at 4 ◦C until processed.
2.4. Morphological Features of Fine Roots
In the laboratory, all soil samples were washed on a sieve (1 mm mesh size) to
remove the soil. Soil freed fine roots were further cleaned from soil residues under a
stereo-microscope, and beech fine roots were distinguished from other understory roots
by morphological characteristics. Beech fine roots appear reddish and stiffer than the
understorey roots; these morphological characteristics were previously established from
samples dug near the tree. Fine root samples were then scanned at a resolution of 500 dpi
with a calibrated flatbed scanner coupled to a lighting system (Expression 10,000 XL,
Epson America Inc., Long Beach, CA, USA). The resulting images were analyzed with
WinRhizo Pro V. 2007d software (Regent Instruments Inc., Quebec, QC, Canada), which,
setting the diameter classes with different colors, made it possible to group with high
accuracy the root axes in three diameter classes (<0.5; 0.5–1.0; 1.0–2.0 mm); root axes were
separated from each other where necessary with scissors or scalpels. The morphometric
measurements as length and mean diameter were performed. Successively, fine-roots
belonging to each diameter class were grouped, oven-dried at 70
◦
C (48 h), and weighed
for dry mass measurements. Morphometric data, together with dry weight data, were also
used to calculate the relative morphological traits specific root length (SRL, m g
−1
) and
root tissue density (RTD, g cm−3).
Forests 2021,12, 137 5 of 14
2.5. Chemical Composition of Fine Roots
In our samples, as the dry weight per core sample for the three fine root diameter
classes ranged from 0.05 to 0.87 g, the amount was not sufficient for testing the chemical
properties, particularly for very fine roots. Then, in the laboratory, for each diameter class,
all eight cores for each gap size were pooled together, the same for the closed canopy,
resulting in one sample per diameter class per gap size, i.e., 15 per diameter class in
total. Successively, only 9 gap sizes were selected by eliminating the even values from
the series of 15 gaps (2, 4, 6
. . .
sample). In detail, every even sample was equally split,
one half pooled with the previous sample and the second half with the successive one.
In this way, the critical amount of 2–3 g per sample has been achieved, totaling 18 samples
corresponding to 9 gaps and 9 closed canopies for each diameter class (54 in total). Each of
the 54 samples was ground in liquid nitrogen with mortar and pestle and milled to pass a
40-mesh (37
µ
m mesh opening) screen; the powder was used for carbon, nitrogen, lignin,
cellulose, and phosphorus concentrations measurement.
2.5.1. Carbon and Nitrogen
C and N concentrations were measured with a CHN analyzer (NA-2000 N-Protein;
Fisons Instruments S.p.A., Rodano [MI], Italy). The analyzer was calibrated with an
atropine standard (Sigma-Aldrich, A-0132, St. Louis, Missouri, MO, USA) and every 10th
sample with an atropine sample. The mean total N and C recovery rate for nutrient analysis
of atropine was 100.28 ±0.59% and 100.62 ±0.22%, respectively.
2.5.2. Cellulose and Lignin
The method used to measure total cellulose content was based on that developed by
Leavitt and Danzer [
46
,
47
] and consisted of removing as many non-cellulosic compounds
as possible from the root material. The first compounds to be removed were lipids (waxes,
oils, and resins). Each sample was poured into a Teflon sachet (no. 11803, pore size 1.2
µ
m)
and in groups of nine placed into a soxhlet extractor (50 mm i.d., 200 mL capacity to siphon
top, mod. 64826, Supelco|Sigma-Aldrich) equipped with a flask containing a 700 mL
mixture of toluene 99%–ethanol 96% (2–1; v/v) heated until boiling point. After 24 h of
extraction, the extractor solution was replaced with 700 mL of ethanol heated to the same
temperature. After 24 h, the samples were removed from the soxhlet and immersed in
distilled water heated to 100
◦
C for 6 h. This process removes hydrosoluble molecules from
the sample. The second compounds to be removed were lignin. All samples were placed
in a 250 mL beaker containing 160 mL of distilled water, 1.5 g of sodium chlorite (NaClO
2
),
and 0.5 mL of acetic acid. The sample and solution were shaken using a magnetic stirrer
and heated to 70–80
◦
C for 1 h (this procedure was repeated three times, 3 h in total).
After the flask was cooled to a constant temperature, the sample was removed and filtered
using a filter flask and washed with distilled water until it was free from acid. The samples
were dried at ambient temperature during 12 h and weighed. The percentage of cellulose
was evaluated by calculating the relative difference in the initial and final weight of each
sample (0.5 g).
Lignin content was measured according to a previous protocol [
48
], with minor modifi-
cations. For lignin extraction, 1 g of powdered sample was poured in a 15 mL plastic falcon
and boiled with 2 mL ethanol for 30 min and left overnight on a tilting plate. After centrifu-
gation, Falcons were centrifuged at 10,000
×
gfor 15 min at 25
◦
C, the supernatant removed
and the pellet homogenized in 10 mL of extraction buffer (50 mM Tris–HCl, 0.01% Triton X-
100 (10 g L
−1
), 1 M NaCl, pH 8.3). The suspension was stirred, centrifuged at 10,000
×
gfor
10 min, washed twice with 4 mL of extraction buffer, twice with 2 mL of 80% (v/v) acetone,
and twice with 2 mL of acetone, and then dried in a concentrator. Each pellet was then
treated with 0.4 mL of thioglycolic acid and 2 mL of 2 M HCl, for 4 h, at 95
◦
C, centrifuged
at 15,000
×
gfor 10 min and washed three times with distilled water. Lignothioglycolic
acid from each pellet was then extracted with 2 mL of 0.5 M NaOH, under stirring for 16 h,
at 25
◦
C. The supernatant was acidified with 0.4 mL of 37% (v/v) HCl in proportion 1:5 to
Forests 2021,12, 137 6 of 14
the sample volume. Lignothioglycolic acid was then precipitated at 4
◦
C, for 4 h, recovered
by centrifugation at 15,000
×
gfor 20 min, and dissolved in 1 mL of 0.5 M NaOH. The lignin
amount within each sample was calculated by measuring the absorbance at 280 nm, us-
ing a specific absorbance coefficient of 6.0 L g
−1
cm
−1
. Because this specific absorbance
coefficient provides only an approximate conversion (the absorbance of lignothioglycolic
acid from different sources can vary considerably; see Doster and Bostock [
48
]), all readings
were normalized to the specimen with the highest lignin content [49].
2.6. Statistical Analyses
To compare the different gap sizes and the difference between the fine roots facing
the gap and those facing the opposite side for each cardinal point, 15 artificial gaps of
increasing size and 15 adjacent 20 m distant uncut control plots were established. In this
work, no a priori subjective thresholds, such as small, medium and large sizes, have been
adopted within the considered gap size range (86.05–350.70 m
2
), so gap size was used as a
covariate in the analysis of covariance (ANCOVA). Two-way ANCOVA was performed to
evaluate the effects of the fixed factor core position (front, back) and edge tree orientation (N,
S, E, W), as well as their interaction, and the covariate gap size on several morphological
traits of fine roots with diameters of <0.5, 0.5–1.0 and 1.0–2.0 mm. For chemical traits
(Section 2.4), as fine root samples were pooled, a one-way ANCOVA was performed with
the diameter classes as a fixed factor and the gap size as a covariate. All uncut control data
were pooled as one and treated as a control.
Data were square-root or log-transformed where necessary to meet normality and
homoscedasticity assumptions. Data given in figures are not transformed; pand R
2
values
of regression analysis refer to data transformed where necessary. All statistical analyses
were performed with SPSS version 20.0 (IBM, Armonk, NY, USA) software and were
performed with a 5% rejection level.
3. Results and Discussion
3.1. Morphological Traits
For the edge trees, the different size of gaps did not affect the investigated morpholog-
ical traits, neither the core position nor the tree orientation (Table 1). If pooled, the mean
values of all morphological traits did not differ from those of the uncut control (closed
canopy), independently from the size of gaps (Figure 2); some deviations either above or
below the control mean occurred in the center-left of the distribution, i.e., for the smaller
gap sizes. The only exception was the slightly higher SRL for the larger fine root frac-
tion (
1–2 mm
) in the side facing the gap area (Figure 3), which marginally missed the
significance (core position p= 0.071; Table 1).
Table 1.
F and pvalues of ANCOVA (General Linear Model) for the effects of core position and orientation on morphological fine root
traits divided by diameter classes. Gap sizes were used as covariates. Interactions were not significant and therefore excluded from
the model.
Fine Root Trait Diameter
(mm)
Core Position Orientation Gap Size (c)
(df = 1) (df = 3) (df = 1)
FpFpFp
Length (m m−2)
0.5 0.125 0.724 0.343 0.794 0.087 0.768
0.5–1 0.054 0.817 0.031 0.993 0.152 0.697
1–2 0.274 0.601 0.163 0.921 0.510 0.476
Dry mass (g m−2)
0.5 0.009 0.924 0.329 0.805 0.007 0.935
0.5–1 0.067 0.796 0.338 0.798 0.030 0.862
1–2 0.843 0.360 0.207 0.891 0.253 0.616
RTD (g cm−3)
0.5 0.405 0.525 0.387 0.762 0.137 0.712
0.5–1 0.096 0.756 1.220 0.303 1.387 0.240
1–2 1.082 0.299 0.822 0.483 0.844 0.359
SRL (m g−1)
0.5 0.687 0.408 0.434 0.729 0.804 0.371
0.5–1 0.001 0.998 0.671 0.571 0.659 0.418
1–2 3.296 0.071 1.230 0.299 0.135 0.714
RTD, Root Tissue Density; SRL, Specific Root Length; (c), covariate
Forests 2021,12, 137 7 of 14
Forests 2021, 12, x FOR PEER REVIEW 8 of 15
Figure 2. Fine root length, dry mass, root tissue density (RTD), and specific root length (SRL) (columns), according to three
diameter classes (<0.5, 0.5–1, and 1–2 mm) (rows), in relation to gap size. Each point represents the mean of 8 replicates
(front and back position and orientation pooled together) ± SE. The uncut control was conventionally assigned the gap
size value of 1 m2 and was the mean of 120 replicates (front and back position, orientation, and 15 gap size pooled together).
If not reported, the scale for a given variable is the same for all the three panels.
Ø <0.5 0.5 <Ø <1.0 1.0 <Ø <2.0
SRL (m g−1) RTD (g cm−3) Dry mass (g m−2)
Gap size (m
2
)
Diameter class (mm)
4003002001000
Length (m m−2)
1800
1600
1400
1200
1000
800
600
400
200
400
350
300
250
200
150
100
120
100
80
60
40
20
40030020010004003002001000
1
0
08
0
6
0
4
0
2
0
0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
50
40
30
20
10
8
6
4
2
0
2.0
1.5
1.0
0.5
0.0
Figure 2.
Fine root length, dry mass, root tissue density (RTD), and specific root length (SRL) (columns), according to three
diameter classes (<0.5, 0.5–1, and 1–2 mm) (rows), in relation to gap size. Each point represents the mean of 8 replicates
(front and back position and orientation pooled together)
±
SE. The uncut control was conventionally assigned the gap size
value of 1 m
2
and was the mean of 120 replicates (front and back position, orientation, and 15 gap size pooled together).
If not reported, the scale for a given variable is the same for all the three panels.
Forests 2021,12, 137 8 of 14
Forests 2021, 12, x FOR PEER REVIEW 9 of 15
Figure 3. Relationship between specific root length (SRL) and mean diameter (MD) of the 1–2 mm
diameter fine root class according to the front (filled circle) and back (empty circle) core positions.
Each point represents the mean of 4 replicates ± SE. Continuous and dashed lines represent front
and back linear interpolations, respectively.
3.2. Chemical Traits
Interestingly, N concentration significantly (p < 0.001) increased with increasing size
of gaps and significantly (p < 0.001) decreased with increasing fine root diameter (Table 2;
Figure 4). C concentration did not show any trend in response to the different sizes of the
gap, whereas it marginally decreased (p = 0.096) with increasing root diameter (Table 2;
Figure 4). C:N ratio marginally decreased (p = 0.087) with increasing gap size, whereas it
significantly (p < 0.001) increased with increasing fine root diameter (Table 2, Figure 4). It
is noteworthy that having pooled the samples did not withhold the clear trend obtained
for N concentration.
Table 2. F and p values of ANCOVA (General Linear Model) for the effects of diameter classes on
chemical fine root traits. Gap size was used as a covariate. Interactions were not significant and
therefore excluded from the model. Boldface p values are significant at a probability level of p < 0.05.
Chemical Trait Diam Class (df = 2) Gap size (c) (df = 1)
F
p F p
C 2.598 0.096 1.596 0.219
N 43.73 <0.001 25.28
<0.001
C:N 20.89 <0.001 3.05 0.087
Cellulose 0.374 0.692 0.024 0.879
Lignin 1.747 0.197 9.371
0.006
Cellulose:Lignin 2.299 0.123 13.442
0.001
Lignin: N 3.209 0.059 14.54 0.001
(c), covariate.
These findings are in accordance with the literature which reports a strong inverse
correlation between N concentration and root diameter with the highest concentrations in
the thinnest root portions [17,34], whereas no consistency emerges on the relationship be-
tween C concentration and root diameter [34,52] and references therein. Differently, a lack
of consistency persists about the possible N concentration increase in fine roots in re-
sponse to gap opening [30], particularly when consequent to artificial gap formation. Most
of the studies had focused on alteration on soil processes such as nutrient release during
litter decomposition [53,54], microbial activity [45,54], net mineralization and nitrification
MD (mm)
SRL (m g
-1
)
1.51.41.31.21.1
2.5
2.0
1.5
1.0
0.5
front
P= 0.001
R
2
= 0.185
back
P= 0.008
R
2
= 0.117
Figure 3.
Relationship between specific root length (SRL) and mean diameter (MD) of the 1–2 mm
diameter fine root class according to the front (filled circle) and back (empty circle) core positions.
Each point represents the mean of 4 replicates
±
SE. Continuous and dashed lines represent front
and back linear interpolations, respectively.
The mean diameter (MD) (Figure 3) rather than the RTD (data not shown) contributed
to this slightly higher gap facing, 1–2 mm in diameter SRL, as the relationship was stronger
for the gap-facing side. Moreover, the average diameter slightly increased with increasing
gap size (Figure S1). Therefore, this result does not support the first hypothesis except for
the slightly higher SRL of the larger fine root fraction (1–2 mm).
Unfortunately, no data in the short-term have been collected, making any considera-
tion on fine root dynamics over time merely speculative. Nevertheless, the decrease in fine
root biomass following gap openings is supported by other short-term experiments [
8
,
9
]
(6 and 11 months after logging, respectively), which found a consistent decrease at the gap
edge, and almost no growth in the center of the gap compared to the adjacent intact forest.
Furthermore, regarding the spatial localization of the soil sampling points for edge trees,
the adopted distances of 5 and 8 m from the trunk in the same short-term experiments [
8
,
9
]
were higher than the 1 m used in the present work, which fell under the canopy crowns
of rather tall trees (on average 31 m). In fact, previous findings on the soil characteris-
tics (moisture content, bulk density, total N, P, and soil organic carbon) from the same
experimental gaps [
45
] showed a lack of significant differences between edge and closed
canopy trees. These findings also highlighted the low impacts of the adopted manage-
ment practices on soil characteristics, which did not extend over the medium term [
50
,
51
].
This scanty soil alteration might explain the lack of significance of the orientation factor for
the edge trees, although a higher soil temperature should be expected for south-faced trees.
Therefore, the fine root biomass of edge trees might have been scarcely reduced after gap
openings, and the medium-term observation adopted in this work may have been long
enough to enable the recovery of fine root biomass to pre-harvest levels, explaining the
lack of morphological differences among the gap sizes investigated.
3.2. Chemical Traits
Interestingly, N concentration significantly (p< 0.001) increased with increasing size
of gaps and significantly (p< 0.001) decreased with increasing fine root diameter (Table 2;
Figure 4). C concentration did not show any trend in response to the different sizes of the
gap, whereas it marginally decreased (p= 0.096) with increasing root diameter (Table 2;
Figure 4). C:N ratio marginally decreased (p= 0.087) with increasing gap size, whereas it
Forests 2021,12, 137 9 of 14
significantly (p< 0.001) increased with increasing fine root diameter (Table 2, Figure 4). It is
noteworthy that having pooled the samples did not withhold the clear trend obtained for
N concentration.
Table 2.
F and pvalues of ANCOVA (General Linear Model) for the effects of diameter classes on
chemical fine root traits. Gap size was used as a covariate. Interactions were not significant and
therefore excluded from the model. Boldface pvalues are significant at a probability level of p< 0.05.
Chemical Trait Diam Class (df = 2) Gap Size (c) (df = 1)
FpFp
C 2.598 0.096 1.596 0.219
N 43.73 <0.001 25.28 <0.001
C:N 20.89 <0.001 3.05 0.087
Cellulose 0.374 0.692 0.024 0.879
Lignin 1.747 0.197 9.371 0.006
Cellulose:Lignin 2.299 0.123 13.442 0.001
Lignin: N 3.209 0.059 14.54 0.001
(c), covariate.
These findings are in accordance with the literature which reports a strong inverse
correlation between N concentration and root diameter with the highest concentrations
in the thinnest root portions [
17
,
34
], whereas no consistency emerges on the relationship
between C concentration and root diameter [
34
,
52
] and references therein. Differently,
a lack of consistency persists about the possible N concentration increase in fine roots in
response to gap opening [
30
], particularly when consequent to artificial gap formation.
Most of the studies had focused on alteration on soil processes such as nutrient release
during litter decomposition [
53
,
54
], microbial activity [
45
,
54
], net mineralization and nitrifi-
cation [
55
], but few papers concern fine roots [
8
,
9
,
11
]. Thinning operations stimulate the N
concentration increase in European beech forests in the Southern Alps, [
18
], which results
in fine roots with a shorter lifespan than those living in the forest left to grow for many
years. Findings from the present study suggest a similar response at the fine root level to
artificial gap opening derived from single-tree selection practice. Indeed, the lower C:N
ratio observed in larger gaps independently of the diameter class highlighted the lower
construction costs and, consequently, the more ephemeral nature of these fine roots [
34
].
Although not differentiated between orientation and core position, these chemical trends
would reveal the stimulation of the fine root growth with the increasing size of the gap,
with traces still present six years after gap opening.
For cell wall chemical compounds, lignin concentration did not change between
diameter classes, but significantly decreased with increasing gap size only for the larger
sub-classes, 0.5–1 and 1–2 mm (Table 2, Figure 4). Cellulose also did not differ between the
diameter classes and decreased with increasing gap size, but only for the 1–2 mm diameter
class. Interestingly, the Cellulose to lignin ratio resulted significantly higher in larger gaps
only for the 0.5–1 and 1–2 mm classes, whereas lignin to N ratio decreased significantly with
increasing gap size for the smaller <0.5 and larger 1–2 mm classes, and slightly increased
with increasing diameter (p= 0.059).
The decrease in the cellulose and lignin in the larger fraction of fine roots with in-
creasing gap size is indicative of roots with thinner secondary walls, and the finding of the
slightly higher SRL and lower mean diameter in gap facing 1–2 mm fine roots (
Figure 3
)
fits to this explanation. Moreover, the increasing trend of the cellulose:lignin ratio with
increasing gap size is indicative of a lignin reduction proportionally higher than that
of cellulose; the latter, in particular, did not significantly change with the different gap
sizes if the last size value was removed from calculation. Xylem percentage area [
30
]
and cellulose:lignin ratio [
56
–
58
] increase with the secondary growth and, consequently,
increasing diameter. Conversely, RTD decreases with increasing root diameter [
59
,
60
] or
xylem percentage area [
30
], although other studies have provided inconsistent results on
these relationships [
61
]. Thus, the slight increase in the average diameter for the 1-2 mm
Forests 2021,12, 137 10 of 14
class with the increasing size of the gap (Figure S1) marginally correlated with the increas-
ing trend of the cellulose:lignin ratio. Readjustments in crown closure are well known
to increase the radial growth in stem and structural roots through the enhancement of
photosynthate production [
12
,
62
,
63
], and may have contributed to the moderate 1-2 mm
root class radial growth.
Forests 2021, 12, x FOR PEER REVIEW 11 of 15
Figure 4. Fine root chemical traits (rows) in relation to gap size, according to three diameter classes
(<0.5, 0.5–1, and 1–2 mm) (columns). Points represent one value per 9 gap sizes only (see Section
2.4); the uncut control, not included in the regression analysis, was conventionally assigned the gap
size value of 1 m2 and represents the mean of 9 replicates ± SE (see Section 2.5). If significant at p
<0.05, regression lines and the corresponding R2 were shown.
C (%)
50
48
46
44
42
40
P= 0.003
R
2
= 0.736 P= 0.005
R
2
= 0.703
N (%)
1.4
1.2
1.0
0.8
0.6
P= 0.015
R
2
= 0.595
P= 0.034
R
2
= 0.495
C:N ratio
70
60
50
40
30
P= 0.045
R
2
= 0.441
Cellulose (%)
90
88
86
84
82
80
P= 0.048
R
2
= 0.356
P= 0.047
R
2
= 0.393
Lignin(%)
100
90
80
70
60
50
40
4003002001000
Lignin:Nratio
120
80
40
Gap size (m
2
)
40030020010004003002001000
P= 0.031
R
2
= 0.508
P= 0.039
R
2
= 0.477
160
Cellulose:Ligninratio
1.8
1.6
1.4
1.2
1.0
0.8
P= 0.047
R
2
= 0.451
P= 0.026
R
2
= 0.532
Ø <0.5 0.5 <Ø <1.0 1.0 <Ø <2.0
Diameter class (mm)
Figure 4.
Fine root chemical traits (rows) in relation to gap size, according to three diameter classes
(<0.5, 0.5–1, and 1–2 mm) (columns). Points represent one value per 9 gap sizes only (see Section 2.4);
the uncut control, not included in the regression analysis, was conventionally assigned the gap size
value of 1 m
2
and represents the mean of 9 replicates
±
SE (see Section 2.5). If significant at p< 0.05,
regression lines and the corresponding R2were shown.
Forests 2021,12, 137 11 of 14
The cellulose:lignin and Lignin:N ratios, in particular, also belong to those chemical
traits of plant litter that have the highest impact on the decomposition rates. The lower
Lignin:N ratio with increasing gap size found in the present work could result in higher
decomposition rates [
64
–
66
]. However, simple extrapolation from the decomposability
of root litter to, for example, the long-term carbon sequestration in forest soils is not
possible, as additional factors such as the spatial inaccessibility of soil organic matter
and organo-mineral interactions cannot be ruled out (e.g., von Lutzow et al. [
67
]). Thus,
differently from the center of gaps, it may be assumed that stimulation of growth near the
edge trees was not as remarkable at the morphological level as at it was at the chemical level.
This apparent discrepancy between the morphological and chemical traits is explainable
in that most of the studies on the effects of gap size on tree fine root dynamics refer to
the short-term period, whereas in the present study, the medium term might have veiled
the morphological effects not as much as the nitrogen and lignin content in the larger
fraction. Morphological and chemical traits are frequently decoupled at the root system
level [
68
]. Indeed, phenotypic plasticity was found to be limited across soil conditions and
growing seasons for several temperate species [
16
,
69
,
70
]. Similarly, a correlation between
morphological traits such as SRL and N concentration was lacking for fine roots of many
softwood and hardwood North American species [68,71].
4. Conclusions
This work highlights that, in the medium term and within the adopted size range,
artificial gap opening derived from single-tree selection practice affected the chemistry
rather than the biomass and morphology of gap-facing fine roots in oriental beech edge
trees. These outcomes suggest that the below-ground carbon stock is not influenced
in the medium term by the forest gap openness following single-tree selection practice,
but readjustments in the crown closure of edge trees may contribute to a moderate radial
growth in the larger and woodier fine root fraction. Consequently, the derived increase in
C:N and decrease in Lignin:N ratios with increasing gap size may increase the fine root
decomposition, and subsequently the carbon input into the soil as medium-long-term
implication. A clear size threshold did not come out since the trends with increasing
gap size were either absent for the morphological or continuous for the chemical traits.
Nevertheless, for this latter, 300 m
2
may be considered a possible cut-off determining a
marked change in the responses of fine roots.
Supplementary Materials:
The following are available online at https://www.mdpi.com/1999-490
7/12/2/137/s1, Figure S1: Specific root length (SRL) and mean diameter (rows) in relation to gap
size of the 1–2 mm diameter fine root class, Table S1: Size of the 15 studied gaps and the related
tree-edge characteristics.
Author Contributions:
Conceptualization, K.A.V., A.A.K., M.F., and A.D.I.; methodology, K.A.V.,
A.A.K., M.F., A.M., A.D.I.; investigation, A.A.K., M.F., K.A.V.; software, A.D.I., A.A.K. and A.M.;
formal analysis, A.D.I., A.A.K. and A.M.; data curation, A.D.I., A.A.K.; writing—original draft prepa-
ration, A.A.K., K.A.V.; writing—review and editing, A.D.I., A.M.; visualization, A.D.I.; supervision,
K.A.V., A.D.I.; funding acquisition, K.A.V., A.D.I. All authors have read and agreed to the published
version of the manuscript.
Funding:
This study was supported by Lorestan University, Lorestan, Iran and the University of
Insubria (FAR no. 2019).
Data Availability Statement:
The datasets generated during the current study are available from the
corresponding author on reasonable request.
Acknowledgments:
The authors are grateful to Lorestan University, Lorestan, Iran, and the Univer-
sity of Insubria (University Research Funding—project FAR) to provide us with financial supports.
Special thanks to Enrico Caruso for his technical support with the Soxhlet system for cellulose
quantification, Delle Fratte Michele for assistance with the CHN analysis. The authors gratefully
acknowledge the two anonymous reviewers for their valuable comments.
Forests 2021,12, 137 12 of 14
Conflicts of Interest: The authors declare no conflict of interest.
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