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UNCORRECTED PROOF
Soil Biology and Biochemistry xxx (xxxx) xxx-xxx
Contents lists available at ScienceDirect
Soil Biology and Biochemistry
journal homepage: www.elsevier.com
Rhizosphere size and shape: Temporal dynamics and spatial stationarity
Yakov Kuzyakov a, b, ∗, Bahar S. Razavi a, c
a-8):<5-6< 7. /:1+=4<=:- #714 #+1-6+- %61>-:;1<A 7. C<<16/-6 -:5)6A
b-8):<5-6< 7. #714 #+1-6+- 7. $-58-:)<- +7;A;<-5; %61>-:;1<A 7. C<<16/-6 -:5)6A
c-8):<5-6< 7. #714 )6, !4)6< 1+:7*175- 6;<1<=<- 7. !0A<78)<0747/A %61>-:;1<A 7. 1-4 -:5)6A
ARTICLE INFO
-A?7:,;
Rhizosphere processes
Biogeochemical gradients
Rhizodeposits
Microbial hotspots
Accumulation and depletion of nutrients
Enzyme distribution and localization
ABSTRACT
The soil volume affected by roots –the rhizosphere –is one of the most important microbial hotspots determin-
ing the processes, dynamics and cycling of carbon (C), nutrients and water in terrestrial ecosystems. Rhizosphere
visualization is necessary to understand, localize and quantify the ongoing processes and functions, but quanti-
tative conclusions are very uncertain because of: 1) the continuum of the parameters between the root surface
and root-free soil, i.e., there are no sharp borders, 2) differences in the distributions of various parameters (C,
nutrients, pH, enzyme and microbial activities, gases, water etc.) across and along roots, 3) temporal changes of
the parameters and processes with root growth as well as with water and C ^ows.
6 ;1<= techniques: planar optodes, zymography, sensitive gels, 14C and neutron imaging as well as destructive
approaches (thin layer slicing) have been used to analyze the rhizosphere extent and the gradients of various
physico-chemical and biological characteristics: pH, CO2, O2, redox potential, enzyme activities, content of wa-
ter, nutrients and excess elements, and organic compounds. A literature analysis allows the conclusion that: i) the
rhizosphere extent for most of the parameters assessed by non-destructive visualization techniques is 0.5–4 mm
but exceeds 4 mm for gases, nitrate, water and redox potential. ii) The rhizosphere extent of nutrients (N, P) is
decoupled from the extent of the corresponding enzyme activities. iii) The imbalance between element ^ows to
and uptake by roots may lead to accumulation of excess elements and formation of root carapaces (e.g. CaCO3
rhizoliths, Fe plaque) ranging up to a few cm. iv) All destructive approaches show a much (3–5 times) larger
rhizosphere extent compared to visualization techniques. These conclusions are crucial for a mechanistic under-
standing of rhizosphere properties and functioning, estimation of the nutrient stocks available to roots, and for
rhizosphere modelling considering root growth and architecture.
Overall, roots function as ecosystem engineers and build their environment, serving as the main factors shap-
ing rhizosphere extent. Sharp gradients are formed within a few days for nutrients and enzymes, but more time
is necessary for the establishment of speci]c microbial communities. Despite the very strong dynamics of most
parameters, their stationarity is reached within a few days because the release of C and enzymes or nutrient up-
take are very quickly compensated by utilization by surrounding microorganisms or/and sorption and diffusion
processes. We conclude that despite the dynamic nature of each property, the rhizosphere gradients, their extent
and shape are quasi-stationary because of the opposite directions of their formation processes.
1. Introduction
'0A :01B7;80-:-
The rhizosphere is the soil volume around the root that is strongly
affected by root functioning (Hiltner, 1904). This classical definition de-
scribes the rhizosphere as a four-dimensional (4D) object: 3D for vol
ume, and time for functioning. Do we need, and can we achieve, a 4D
picture for this object –the rhizosphere? We need an image, if only be-
cause humans obtain ∼90% of their information visually and any vi-
sualization simpli]es and accelerates the reception, preservation, local-
ization, understanding and exchange of information. This is especially
valid for the rhizosphere because (Kuzyakov and Razavi, 2016, 2017):
1) it is in the soil –hidden from view, 2) most sampling methods de-
stroy the rhizosphere –the spatial and functional connections between
∗Corresponding author. Department of Agriculture Soil Science, University of Göttingen, Germany.
5)14 ),,:-;;-; kuzyakov@gwdg.de (Y. Kuzyakov); brazavi@phytomed.uni-kiel.de (B.S. Razavi)
https://doi.org/10.1016/j.soilbio.2019.05.011
Received 31 December 2018; Received in revised form 10 May 2019; Accepted 14 May 2019
Available online xxx
0038-0717/ © 2019.
Review Paper
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
solid, liquid, gaseous and living matter are lost, 3) rhizosphere bound-
aries are not sharp –this makes their extent and shape very elusive, 4)
diverse soil parameters may change in varied and partly divergent ways,
and 5) the rhizosphere is very dynamic –the object changes over time
and it is dif]cult (but very intriguing) to imagine its “stable”, station-
ary state. We therefore have only a nebulous picture of what the rhizos-
phere looks like, and talking about “<0- :01B7;80-:-”at conferences and
in papers may conjure up different pictures for various colleagues, de-
pending on the speci]c parameters they study, plant and root features,
the equipment and methods used, and last but not least the imagination
of individual researchers.
The present overview was prompted not only by the hidden nature
of the rhizosphere, but also because it is the most important hotspot
in the soil (Kuzyakov and Blagodatskaya, 2015) and probably in terres-
trial ecosystems in general (Hinsinger et al., 2003). Consequently, most
processes measured along soil pro]les and at larger scales are actually
taking place in a very small soil volume –in hotspots –and will be sim-
ply ‘diluted’by the huge surrounding soil volume. This makes it even
more important to obtain an image of the dynamic locations at which
the processes are ongoing at much faster rates. Based on these premises,
this review presents a comprehensive attempt to visualize the extent and
shape of the rhizosphere. Thus, we take up the challenge of illustrating
a 4D object on 2D paper.
!:7+-;;-; )E-+<16/ ;=*;<)6+- D=@-; )6, /:),1-6<; 16 <0- :01B7;80-:-
The ]rst step is to de]ne the processes contributing to the extent,
shape and dynamics of a broad range of parameters in the rhizosphere.
Biotic and abiotic processes affect the concentration, movement and
thus the distribution of substances around the roots (Table S1). The
processes are bidirectional: from root to soil and from soil to the root,
and are connected with 1) uptake of water and nutrients by roots (in-
^ow); 2) active and passive release of various groups of rhizodeposits
(secretions, mucilage, exudates, sloughed-o` cells, enzymes; for defini-
tions and processes, see Nguyen, 2003) by roots (out^ow); 3) uptake of
these organics and nutrients by microorganisms; 4) uptake and release
of O2 and CO2 by both roots and microorganisms; and 5) physico-chem-
ical processes of sorption, desorption, precipitation and dissolution. The
rates of all these processes decrease with increasing distance from the
roots (or occur solely at the root surface, e.g. root exudation). Accord-
ingly, concentration gradients are established from the roots to the bulk
soil and reverse (Fig. S1). The importance of individual biotic and abi-
otic processes for establishing gradients differs for various substances.
This review therefore presents and evaluates the common gradients for
most substances and, based on these gradients, draws conclusions about
the extent of the rhizosphere, its temporal dynamics and spatial station-
arity, ultimately revealing rhizosphere shape.
Various models have simulated individual and interconnected
processes in the rhizosphere, including water uptake (Roose and
Schnepf, 2008; Carminati, 2012), nutrient uptake (Roose and Schnepf,
2008; Barber et al., 1963; Jungk and Claassen, 1997), and exudate re-
lease (Farrar and Jones, 2000), and have thus visualized the rhizosphere
(Jungk, 2001). For most simulated parameters, however, the modeling
results are dif]cult to validate experimentally because the spatial and
temporal resolution of experiments is considerably lower than that of
the models. This review therefore focuses solely on experimental results
that illuminate rhizosphere parameters related to functions.
2. Material and methods
!:16+184-; 7. ,)<) +744-+<176
To evaluate gradients in the rhizosphere, we collected literature
data based on destructive and non-destructive approaches (Kuzyakov
and Razavi, 2016, 2017). 1) The destructive approaches include: i)
growth of plants in pots with zonation by gauzes with small mesh size:
0.2–40 μm (Helal and Sauerbeck, 1981); ii) slicing of soil with increas-
ing distance to the root surface (Tarafdar and Jungk, 1987; Kuchenbuch
and Jungk, 1982; Begg et al., 1994; Zoysa et al., 1997; Kandeler et al.,
1999; Kandeler et al., 2002; Sauer et al., 2006; Hafner et al., 2014;
zu Schweinsberg-Mickan et al., 2010) and iii) compartment rhizoboxes
(Youssef and Chino, 1987, 1988, 1989).
2) The non-destructive approaches (reviewed by Oburger and
Schmidt, 2016) include: i) planar optodes for CO2, pH, O2 (Blossfeld et
al., 2011; Schreiber et al., 2012; Rudolph-Mohr et al., 2014; Larsen et
al., 2015; Koop-Jakobsen and Wenzhöfer, 2015); ii) gels sensitive for pH
(Römheld, 1986) of for the exudation of aluminum complexing ligands
or Fe(III) reducing agents (Engels et al., 2000; Neumann, 2007); iii)
zymography for enzyme activities (Spohn and Kuzyakov, 2013; Razavi
et al., 2016); iv) DGT (diffusive gradients in thin ]lms) gel for ele-
ments (Fresno et al., 2017); v) imaging of radioactive isotopes: 14C (Holz
et al., 2018a), 32P, 33P, 40Ca for nutrients; vi) neutron imaging and
X-ray synchrotron for water and rhizosphere porosity (Carminati, 2012;
Zarebanadkouki et al., 2013; Helliwell et al., 2017); vii) microelectrodes
for Eh (Fischer and Schaller, 1980) or pCO2 (Gollany et al., 1993). We
do not describe these approaches here and refer to the original papers
and reviews (Oburger and Schmidt, 2016) for further methodological
details. The full description of collected data and parameters, data stan-
dardization for assessing lateral gradients, and standardization of para-
meters along the roots are presented in detail in Supplementary Materi-
als: Methods.
3. Rhizosphere shape and extent
To simplify the ]rst step of evaluating rhizosphere extent, we orga-
nized the results according to the processes mentioned in Table 1: Gra-
dients induced by *17<1+ (roots and microorganisms) and by )*17<1+ dri-
vers, and speci]ed them for: .:75 <0- :77<; and <7 <0- :77<;.
Table 1
Biotic and abiotic process groups directlya affecting the ^uxes of substances from and to
the roots and thus establishing the rhizosphere gradients.
Processesb From the root ╟→
To the root
╟←
To/from soil
matrix ↓↑
Biotic Root Release (active)
of: secretes,
mucilage,
enzymes, H+,
(OH−) etc.
Root CO2 release
Uptake of
nutrients
O2 uptake
Uptake of
organic and
inorganic
toxicants
Precipitation of
ballast elements
Oxidation: Fe2+
→Fe3+, Mn2+ →
Mn4+
CaCO3
precipitation
SiO2
precipitation
Microbes Uptake of
organics
Microbial CO2
release
Nutrient
transport by
mycorrhiza
Release of
enzymes
Uptake of
nutrients
Nutrient
mobilization
Depolymerization
of enzymes
Abioticc Release of
exudates (passive)
Ion di`usion
Water
uptake
Sorption,
Desorption
Precipitation,
Dissolution
Nutrient
exchange with
H+
Organics
decomposition by
exoenzymes
aVarious 16,1:-+< processes may a`ect the matter and energy ^uxes in the rhizosphere,
e.g. release of signaling molecules. 6,1:-+< processes are omitted in Table 1.
bCertain processes cannot be de]ned distinctly as biotic or abiotic (e.g. passive release
of root exudates, water uptake, etc.). Such processes may be abiotic by nature, but strongly
controlled by roots.
cDi`usion is not mentioned here as an abiotic process because it is driven by the
emerging gradients and proceeds in both directions: from and to the root, depending on
the gradient.
2
UNCORRECTED PROOF
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Fluxes from root to bulk soil.
"-4-);- 7. F )6, F−176;
The release of H+ by roots into slightly acidic, neutral and alka-
line soils (without N fertilization) is one of the dominant mechanisms of
plants to mobilize nutrients and maintain the electrochemical potential
on the root surface (Marschner, 2012). The common distance of root-in-
duced pH changes is about 2–3 mm (Fig. 1). The high bu`er capacity
of soil (CEC, aluminosilicate hydrolysis, Al3+ and Fe3+ release, CaCO3,
etc.) neutralizes the common difference of 0.5–1 pH units between root
surface and bulk soil (Begg et al., 1994; Hinsinger et al., 2009). Even the
largest reported changes of 2.5 pH units (Rao et al., 2002a,b) (350–400
fold difference in H+ concentration) are completely neutralized within
∼5 mm (Blossfeld et al., 2011). Depending on the neutralization agents
and the intensity of H+ release by roots, two changes are common with
increasing pH of the bulk soil: i) pH decrease at the root surface (com-
pare Fig. 1) and ii) decrease of the rhizosphere pH extent. Consequently,
the pH gradient between root surface and surrounding soil increases
with increasing soil pH.
Three key factors strongly affect the pH changes and gradients: i)
soil pH, ii) N fertilization and iii) plant species. The effect of the ini-
tial soil pH is much larger than that of N nutrition (Fig. 1), despite the
fact that N form (NH4+ or NO3−) is a major determinant of the overall
cation–anion balance for root uptake. Although most plant species acid-
ify the rhizosphere, some plants (e.g. most cereals) release OH−ions.
Plant species affect the rhizosphere pH depending on the initial soil pH
(Fig. 1). Specifically, the roots increase or decrease the rhizosphere pH
by H+ or OH−release and changing the equilibrium between cations
and anions at the root-soil interface (Youssef et al., 1989). The pH in-
creased by about 2 units for barley roots grown in clay loamy soil with
a bulk pH of 5, whereas rhizosphere pH was reduced by 1.5 units if the
initial bulk pH was 7 (Fig. 1). Consequently, roots compensate the ex-
treme (too low or too high) pH values of the soil and thereby alleviate
the associated constraints such as Al3+ or Fe3+ toxicity at acidic pH or
Fe or Mn de]ciency at alkaline pH.
Legumes strongly acidify the rhizosphere by two main mechanisms:
i) proton release following excess uptake of cations over anions dur-
ing N2 ]xation (Israel and Jackson, 1978; Haynes, 1983; Bolan et al.,
1991); ii) photosynthetic activity (light-induced acidi]cation) altering
the cation-anion uptake ratio (Rao et al., 2002a,b). NO3−fertilization
(especially in acidic soils) strongly contributes to OH−release (to main-
tain root cell electro-neutrality). The pH changes and gradients have a
very similar trend (Fig. 1) but in reverse directions (Heckman and E
Strick, 1996; Li et al., 2007; Zhou et al., 2009): the uptake of NH4+ pro-
motes H+ ef^ux and reduces the rhizosphere pH, whereas NO3−uptake
promotes OH−ef^ux and raises the rhizosphere pH (Marschner et al.,
1982). Exceptionally, legumes acidify their rhizosphere even when fed
with nitrate (Marschner and Römheld, 1983).
Root type and water content can alter rhizosphere pH. For instance,
pH as a function of radial distance from crown and lateral maize
roots under wet conditions (ϴ= 0.24 cm3 cm−3) showed no acidi]ca-
tion (Rudolph-Mohr et al., 2017). In contrast, under dry conditions
(ϴ= 0.12 cm3 cm−3) lateral roots acidi]ed their rhizosphere by 0.25 pH
units, and crown roots even acidi]ed their rhizosphere by up to 1.0 pH
unit compared to bulk soil (Rudolph-Mohr et al., 2017).
The pH bu`ering agents (CaCO3 for H+; organic acids for OH−) re-
duced the rhizosphere extent (Fig. 1, CaCO3 effect), which agrees with
the neutralization theory. The extension of root-mediated pH changes in
the rhizosphere of peanuts was larger (2.8 mm) in a poorly bu`ered soil
with an initial pH of 5.5 than in more bu`ered alkaline and acidic soils
(1.4 mm) (Schaller, 1987; Nye, 1981). Thus, the greater the pH bu`er-
ing capacity, the smaller the plant-induced pH changes (Schubert et al.,
1990; Hinsinger et al., 2009).
"-4-);- 7. 7:/)61+ ;=*;<)6+-;
The next group of rhizosphere parameters involves the release of
various organic substances by roots –the rhizodeposits.1 Rhizodeposits
include the continuously and passively released exudates, and the dy-
namically and actively released mucilage, secretions and enzymes from
various root zones (Jones et al., 2004, 2009; Nguyen, 2003). All these
substances have 1–3 orders of magnitude slower diffusion than H+. Two
main mechanisms decrease the concentration of organic compounds in
soil solution (Table 1): i) microbial uptake and utilization (Fischer et
al., 2010; Jones et al., 2005; Oburger et al., 2009), and ii) sorption on
surfaces of minerals or organic matter (Kalbitz et al., 2005; Kaiser and
Guggenberger, 2003). The diffusivity in soil depends strongly on the
water content, roughly as the square of the water content (Olesen et
al., 2000). With distance and time, the organic compounds are progres-
sively metabolized to CO2 or into recalcitrant C compounds (Hartmann
et al., 2009). For exudates (passively released soluble low molecular
weight organic compounds), microbial uptake is very fast –minutes
(Jones et al., 2005; Fischer et al., 2010; Dippold et al., 2014; Gunina
and Kuzyakov, 2015). This causes microbial uptake and mineralization
to dominate over sorption (Fischer et al., 2010; Oburger et al., 2009).
For secretions and mucilage, however, microbial uptake is much slower
because they are high molecular weight substances –mainly polysac-
charides –present in soil solution as gels (Carminati et al., 2017a;
Saez-Aguayo et al., 2017). This makes them less available for microor-
ganisms, requiring splitting by exoenzymes. Their gelled and sticky
properties promote attachment to the surface of soil minerals (Benard et
al., 2018) and additionally retard the decomposition.
Root development changes the zonation and composition of re-
leased exudates. Young root hairs and the cortical cells around emerg-
ing branches of legume roots release ^avonoids to trigger nodules in
only those speci]c regions (Mathesius et al., 2000). Sucrose is released
mostly from the apical region of the primary root, while ef^ux of the
amino acid tryptophan is associated with branch roots (Jaeger et al.,
1999).
The distribution of rhizodeposits is commonly measured by 14C and/
or 13C (and 15N) (rarely with 11CO2) labeling of plants and subsequent
tracing i) by autoradiography (for 14C, Fig. 2) (Holz et al., 2018a;
Rovira, 1973) (or with a positron emitting tracer imaging system PETIS,
for 11C; Fujikake et al., 2003; Suzuki et al., 2008; G. Bonito, personal
communication) as non-destructive approaches or ii) destructive slicing
of soil from the root surface and 14C or δ13C (or δ15N) analysis (Fig. 2).
14C (and 11C) imaging over a very short period (few hours) after label-
ing mainly re^ects the distribution of root exudates because the high
molecular weight compounds (secretions, mucilage) are released later
(Oburger et al., 2018). The rhizosphere extent measured by 14C imag-
ing of exudates is usually only 2–3 mm (Fig. 2) (Holz et al., 2018a). De-
structive slicing, however, reveals much larger extents: up to 10–12 mm
(Sauer et al., 2006; Kuzyakov et al., 2003; Helal and Sauerbeck, 1981;
zu Schweinsberg-Mickan et al., 2010). Increasing the time after label-
ing re^ects the distribution of more high molecular weight organics –
secretions, mucilage, and sloughed-o` cells (Dennis et al., 2010; Holz
et al., 2018a). The secretions and mucilage have never been visualized
in soil. Their physico-chemical parameters (charge, molecular weight,
functional groups; Saez-Aguayo et al., 2017) allow the assumption that
their gradients in the rhizosphere will be similar to those of enzymes
(Holz et al., 2018b).
1Rhizodeposits also include the sloughed-o` root cells, broken root hairs etc. We do not
describe these groups because they do not move in soil. We are aware, however, that even
insoluble organic root debris may strongly a`ect enzyme activities and a`ect the content,
composition and activity of microorganisms in the rhizosphere.
3
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
Fig. 1. pH gradients in the rhizosphere depending on N sources (top left and middle): NH4+ and NO3−, and soil bu`ering capacity (top right). NH4+ and NO3−were added combined with
nitri]cation inhibitor under ryegrass (modi]ed, Heckman and E Strick, 1996). The generalized pH changes (ΔpH) from root surface to the bulk soil are presented depending on the initial
soil pH (bottom left): barley roots increased the initial bulk pH of 4.8 (red line) to 7.1 and reduced pH of 7.1 to 5.5 (blue line) in the clay loam soil. Vertical arrows show maximum ΔpH.
Effect of soil bu`ering capacity (bottom right) is presented based on the example of CaCO3 content in soil (1.5% and 6% of soil d.w.) under chickpea (1+-: ):1-<16=5 L.). The extension
of root-induced rhizosphere acidi]cation strongly increases with the decrease of the bu`ering capacity: color bars at the bottom of the left ]gure show the rhizosphere extents. Data for
NH4+ and NO3−fertilization are extracted from Rudolph et al. (2013); Youssef et al., 1989 and for CaCO3 bu`ering from Römheld (1986); Luster et al., 2009, modi]ed. Color gradients at
the bottom of the graphs show the rhizosphere extents. (For interpretation of the references to color in this ]gure legend, the reader is referred to the Web version of this article.)
6BA5- /:),1-6<;
Although enzymes belong to the organic substances released by roots
into the rhizosphere and could have been described in the previous sec-
tion, we devote a separate section to them because: 1) Enzyme gradi-
ents are characterized by activity and not by concentration. 2) The mol-
ecular weight of enzymes (∼12–500 kD) is generally much higher than
that of other organic substances released by roots. As diffusion strongly
decreases with molecular weight, the gradients may differ from other
organics with lower molecular weight. 3) Enzymes have various func-
tions and re^ect processes, not pools. 4) Various enzymes directly and
strongly affect the gradients of other soil properties: nutrient (N, P, S)
contents, available C, microbial biomass and activity, etc. 5) Enzymes
are released not only by roots but also by microorganisms, whose activ-
ities directly depend on root functions, mainly organic C release. 6) A
broad range of visualization studies is available on the spatial distribu-
tion of enzymes, allowing conclusions about the rhizosphere extent for
individual enzyme groups.
Enzyme activities in the rhizosphere are commonly much higher
than in bulk soil (Fig. 3). The distribution of enzyme activity can be vi-
sualized by soil zymography (Spohn et al., 2013; Razavi et al., 2016;
Liu et al., 2017) or by measurements involving destructive approaches
(Tarafdar and Jungk, 1987; Kandeler et al., 1999; Marschner et al.,
2012). The rhizosphere extent for most enzymes is 1–3 mm (Fig. 3) and
activity decreases with distance from the root surface. Enzyme activity
in the rhizosphere is 1.3–2 times higher than in the bulk soil (Fig. 3) and
typically demonstrates a sigmoidal curve.
Nutrient de]ciency widens the rhizosphere. For instance, P starva-
tion of roots due to infection by nematodes (-471,7/A6- 16+7/61<)) en
larged the rhizosphere 1 mm more than in uninfected plants (Razavi et
al., 2017). Similarly, cellulose addition enlarges the rhizosphere with re-
gard to acid and alkaline phosphatases (Wei et al., 2019b), which ac-
tively compensates for the increased C/P stoichiometric ratio by P min-
eralization from SOM. Correspondingly, P fertilization decreases the rhi-
zosphere extent.
Generally, independent of soil nutrient content, the maximal rhizos-
phere extent is shown by the enzymes of the P cycle (up to 5 mm), fol-
lowed by those of N and C cycles (Ge et al., 2017; Ma et al., 2018) (Fig.
3). This re^ects the intensity of limita tion for plants (P > N > C) and
the lesser P mobility in soils and solution compared to N. Plants must
therefore acquire the most strongly limiting nutrient (P > N) that can
be enzymatically mobilized from soil organic matter, plant residues and
microbial necromass.
The duration of root occupation of a soil volume affects the max-
imal activity: with time, enzyme activities at the root surface can in-
crease by 10–30% (Fig. 3), but the rhizosphere extent remains stable
(Ge et al., 2017). The rhizosphere boundaries for chitinase and phos-
phatase remained constant in response to temperature (Ge et al., 2017)
or heavy metal pollution (Duan et al., 2018). The spatial stability of the
rhizosphere extent re^ects the equilibrium between the input –release
from roots and diffusion –and the output –microbial decomposition
and other enzyme inactivation (Schimel et al., 2017). This stable pat-
tern is an excellent strategy for plants to ef]ciently acquire nutrients in
a narrow root zone independent of root age (Ge et al., 2017; Vetterlein
and Doussan, 2016). Root hairs can expand the rhizosphere extent by
about 2–7 times, whereas the root radius merely increases enzyme ac-
tivity per root area (Ma et al., 2018). The high exudate release in the
presence of root hairs (Fig. 2) (Holz et al., 2018c) stimulates microbial
activity (Pausch et al., 2016) and thus enzyme production by microor-
ganisms (Ma et al., 2018).
4
UNCORRECTED PROOF
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Fig. 2. Gradients of root exudates. Top left: 14C pro]les re^ecting the exudate release by barley roots: Wild type with root hairs (blue dashed line) vs. hairless mutant (red dash-dotted
line). Shading demonstrates ± SE between replicates (data from Holz et al., 2018с, mod i]ed). Bottom left: 14C image of lupine roots re^ecting photoassimilate allocation (after 14CO2
labeling). The arrows show the high intensity of the light color corresponding to high 14C activity (high C allocation) in nodules (from Razavi unpublished). Top right: Incorporation of 13C-
and 15N-labeled rhizodeposits into microbial biomass in the rhizosphere depending on increasing distance to the root surface of 741=5 8-:-66- (after 14CO2 labeling and 15N leaf labeling).
Bottom right: Distribution of adenine and hexose as a function of distance along the root (data extracted from Vetterlein and Doussan, 2016). The Y axis re^ects the relative concentration
measured as the mass-to-charge (m/z) ratio measured on GC-MS. The X axis is presented in pixels because no scale was provided in the original paper. According to our rough estimation,
100 pixels correspond to 1 mm. (For interpretation of the references to color in this ]gure legend, the reader is referred to the Web version of this article.)
Although the diffusivity of high molecular weight enzymes is much
slower (actually negligible, Siddiqui and Cavicchioli, 2006) than that of
the low molecular weight compounds forming root exudates (see pre-
vious section and Kuzyakov et al., 2003; Zhang et al., 2019), the rhi-
zosphere range is similar: 1–3 mm (compare Figs. 2 and 3). We explain
this phenomenon by two mechanisms: 1) enzymes are released not only
by roots, but also by microorganisms. As microbial activity strongly in-
creases in the presence of root exudates, more enzymes will be micro-
bially produced compared to the bulk soil; and 2) much longer stabil-
ity of enzymes in soil (weeks, Schimel et al., 2017) compared to low
molecular weight organic compounds (minutes to hours Jones et al.,
2005). Enzyme stability re^ects their rapid sorption to the soil (within
10 min), and protection from microbial consumption and/or thermal de-
naturation (George et al., 2005). Consequently, the longer half-lives of
enzymes may contribute to their wider dissemination from roots. Com-
paring these two process groups, we conclude that only the enzyme ac-
tivities on the rhizoplane (root surface) or associated with root hairs
originate directly from roots. Because the diffusion of enzymes is very
limited (Guber et al., 2018), the direct enzyme release by roots is rele-
vant only for the rhizoplane, and most of the rhizosphere enzymes are
produced by microorganisms (which are stimulated by root exudates).
This conclusion calls for simultaneously analyzing the spatial distribu-
tion of root exudates (e.g. by 14C imaging), enzyme activities (Spohn
and Kuzyakov, 2013; Bilyera et al., 2019) and omics analysis to identify
enzyme origins in the rhizosphere.
:),1-6<; 7. F )6, F +76+-6<:)<176; )6, 7. <0- :-,7@ 87<-6<1)4
Roots and root endophytes utilize photoassimilates, consume O2
and release CO2 into the soil. The CO2 production rates by roots vary
from around 20 mg C g−1root d−1(for maintenance) up to 600 mg C
g−1root d−1(for young, growing roots) (Eissenstat and Yanai, 1997;
Eissenstat et al., 2000). Because CO2 is distributed mainly in the gaseous
phase, its rhizosphere extent is much larger compared to the substances
dissolved in water. The rhizosphere range for CO2 is extremely dif]cult
to assess because the very high temporal and spatial variation of the CO2
concentration in bulk soil hinders calculating a distinct SD (see Fig. 4).
Furthermore, the CO2 concentration strongly increases with depth: from
<1000 ppm in the upper 3–5cm to >20,000 ppm in subsoil (Gaudinski
et al., 2000; Pausch and Kuzyakov, 2012). This re^ects the longer dif-
fusion path from the production site to the soil surface and atmosphere
(not higher speci]c respiratory activity of roots or microorganisms in
deep soil).
The increase in root and microbial respiration with temperature re-
duces the O2 concentration (Blossfeld, 2008). O2 limitation may be by-
passed by O2 supply from the rhizosphere of other nearby plant species.
Thus, even if the O2 supply of one species is comparatively sensitive to
temperature increase, other plant species can sustain the rhizospheric
O2 concentration within the dense inter-speci]c root network (Blossfeld,
2008).
CO2-sensitive sensors help overcome some of the measurement dif-
]culties and reveal a CO2 rhizosphere range of 1.5–1.8 mm (Fig. 4)
(Blossfeld, 2013; Uteau et al., 2015). Optodes showed an O2 deple-
tion range of a few millimeters (Koop-Jakobsen and Wenzhöfer, 2015;
Larsen et al., 2015), which is very similar but reverse to that of CO2
(Fig. 4). The O2 and CO2 ranges decrease very strongly with soil mois-
ture (Moldrup at al., 2000). In lowland conditions, the concentration
and gradients of CO2 and O2 decrease over time around the root, but
the rhizosphere extent increases (Larsen et al., 2015). Conversely, in
5
UNCORRECTED PROOF
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Fig. 3. Enzyme gradients. Top left: Activity gradients of 4 enzymes )+:7;; roots in the maize rhizosphere. Bottom left: Effects of root occupation period (14 and 30 days) of soil on the
chitinase activity gradients in rice rhizosphere. Each line represents one root (data from Razavi et al., 2016 and Ge et al., 2017). Right: β-glucosidase activity )476/ the maize root. Each
dotted line represents one root (example of a zymogram is presented in the inset). The continuous black line re^ects the average. Although maximal activity at the root tip is 2–4-fold
larger than 6–8 cm from it, the enzyme activity along the whole root is 2–3-fold larger than in the root-free soil (data from Razavi et al., 2016).
Fig. 4. Concentration gradients of gases and redox potential around the roots. Top left: CO2 gradients around the roots of & 2=6+-) (extracted from Blossfeld, 2013); Top right: O2 gradients
around the roots of maize (extracted from Rudolph-Mohr et al., 2015) and rice (extracted from Uteau et al., 2015). Bottom: Redox potential around rice root (extracted from Schmidt et
al., 2011; Atulba et al., 2015) and the respective distribution of oxidized areas in rice rhizosphere (red, true color) (Courtesy of Xiaomeng Wie). The color gradient bars at the bottom show
the rhizosphere extents. Note the opposite O2 gradients to and from the roots by maize and rice. Eh values were measured by redox electrodes and recalculated by digital image analysis.
(For interpretation of the references to color in this ]gure legend, the reader is referred to the Web version of this article.)
6
UNCORRECTED PROOF
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upland plants (e.g. maize) both the O2 gradient and range decrease over
time (Rudolph-Mohr et al., 2017).
Closely associated with O2 concentration, the redox potential may
have sharp gradients around the roots, especially under water-saturated
conditions (Fig. 4, rice roots photo). According to the Nernst equation,
pH decreases lead to Eh increases. Thus, any Eh changes are affected by
H+ release by roots (Fischer et al., 1989). Redox potential variations in
the rhizosphere are caused by several processes: 1) Oxygen consump-
tion combined with CO2 release by living roots. 2) Growing roots re-
lease exudates containing phenolic compounds, which reduce Fe3+ and
Mn4+ oxides (Brown and Ambler, 1973; Marschner et al., 1982). The
respective electron transfer reactions are rapid and are active mainly
on the root tip. Thus, these Eh effects are restricted to a short period
and restricted rhizosphere volume. 3) Even if root exudates themselves
have no reducing properties, the redox potential is lowered by micro-
bial utilization of exudates and consumption of O2 or other electron ac-
ceptors. Except for the second group (release of phenolic compounds),
these processes in^uence a relatively large soil volume because O2 (de-
termining Eh) has a high diffusion rate in soils compared to that of
root exudates. The rhizosphere-oxidized area is not controlled by plant
growth stage, cultivars or yield parameters directly. Among the para-
meters, only root biomass strongly correlated with the rhizosphere-oxi-
dized area (Atulba et al., 2015).
Fluxes from bulk soil to the root.
=<:1-6< /:),1-6<;
The most important gradients formed by the ^uxes from the bulk soil
to the roots involve nutrients. The nutrient rhizosphere volume is cru-
cial for plant nutrition because it de]nes the total amount of each nu-
trient potentially available to the plant. The nutrient gradients are well
known, especially for P and for both mineral N forms: NH4+ and NO3−.
Nutrients move towards the root by diffusion and mass ^ow (the move-
ment of nutrients with water) (Barber et al., 1963). The effective diffu-
sion rate of a nutrient depends on the concentration gradient, the charge
between particle surfaces and the nutrient, and saturation with water
and other nutrient concentrations. The nutrient diffusion that depends
strongly on soil particles is limited, and the depletion zones will be nar-
row (few mm). Very strong depletion zones (e.g. 1–2 cm) are created
when the uptake of a nutrient exceeds mass ^ow to the root (Barber et
al., 1963). According to solubility and a_nity, the shortest gradients are
common for phosphate (2–3 mm), then for NH4+ and K+ (3–5 mm) and
longer for NO3−(5–20 mm) (Fig. 5) (Bray, 1954; Barber et al., 1963).
Note however, that these large rhizosphere extents for P, N and K were
obtained by destructive approaches and may be not supported by the
visualization techniques. Within this range, depletion can be so strong
that the concentration of the soluble nutrients falls close to 0 at the root
surface (Fig. 5) (Gahoonia and Nielsen, 1991). The gradients have a dif-
fusion shape similar to that of pH and 14C labeled exudates (Figs. 2 and
5).
Such nutrient gradients become established within a few days –
faster for low-mobility nutrients such as P and K (Jungk and Claassen,
1997). The gradient within the root hair cylinder is established within
just one day, and the concentration gradient to the bulk soil evolves
within 3–4 days (Jungk, 2001). Generally, the gradients are steeper for
nutrients with low diffusivity and higher a_nity to clays, sesquioxides,
carbonates and organic matter (Barber et al., 1963) (Fig. 5). If, how-
ever, the uptake of chemicals moving to the root surface does not ex-
ceed the supply from mass ^ow, then those chemicals increase in con-
centration surrounding the root and create accumulation zones (Barber
and Ozanne, 1970; York et al., 2016). For instance, because the Ca and
Mg contents in many soils of arid and semiarid climates are in huge ex-
cess compared to plant demand, these elements take on a role both as
nutrients and as excess or ballast elements.
@+-;; -4-5-6<;
Various excess elements (present in soil as ions: Na+, H2SiO42−,
HCO3−, Al3+) and those nutrients that are present in the soil in excess
(in arid and semiarid environments: Ca2+, Mg2+, Cl−, SO42−; or under
anoxic conditions: Fe2+ and Mn2+) are moved with water to the roots
and precipitate in the rhizosphere. Because their uptake is lower than
the mass ^ow, they accumulate at the root surface and build up gra-
dients opposite to those of nutrient depletion (Fig. 5). Accordingly, the
composition and concentration of excess ions is typically much higher
in the rhizosphere than the bulk soil (Hinsinger et al., 2003).
Extremely high accumulations of excess elements in the rhizosphere
may lead to speci]c phenomena such as calci]ed roots –rhizoliths (Fig.
5) –common in semiarid climates (Zamanian et al., 2016) or Fe3+ pre-
cipitation and formation of plaque around the roots in reduced environ-
ments or under changing redox conditions (Melton et al., 2014; Khan et
al., 2016; Kölbl et al., 2017). Both the rhizoliths and the Fe3+ plaques
can grow up to a few cm in diameter, leading to the formation of new
pedogenic features (Fig. 5) that remain in the soil as relict rhizospheres
over centuries and millennia (Zamanian et al., 2015).
1,1:-+<176)4 ?)<-: /:),1-6<;
One of the most important functions of roots is water uptake from
soil. If soil is wet and the water pressure de]cit in the air is high, then
water continuously ^ows to the root, creating gradients of water pres-
sure and sometimes of water content (Carminati, 2012; Zarebanadkouki
et al., 2012, 2013; 2014): In wet soil, the rhizosphere is drier than the
surrounding soil (Fig. 6). In contrast, the rhizosphere in dry soil is wet-
ter. This is especially pronounced during changes of water content (by
drying or rewetting) and is related to the hydrophobic and hydrophilic
properties of mucilage (Carminati, 2012; Zarebanadkouki et al., 2018;
Ahmed et al., 2017; Young, 1995; Carminati et al., 2010; Moradi et al.,
2011). Decreased porosity (Fig. S2) (and increased soil density, see be-
low) at the root surface (rhizoplane) also increases the water content
near the root surface at negative water potentials (Aravena et al., 2014).
In contrast, the presence of surfactants in the mucilage can decrease the
water content in the rhizosphere relative to the bulk soil (Read et al.,
2003; Dunbabin et al., 2006).
The water content in the rhizosphere increases during soil drying
toward the roots within 0.5–2 mm. The reverse process –rewetting –
however, produces stronger gradients with a similar extent. This indi-
rectly re^ects the zone penetrated by mucilage –mainly polysaccharides
(∼95%) and proteins (∼5%) (Bacic et al., 1986; Read et al., 2003) –re-
leased by roots into the soil to lubricate root growth and maintain the
water content in the rhizosphere. Therefore, although the rhizosphere
extent varies from 0.5 to 2 mm, it may increase during periods of soil
moisture changes (Carminati, 2012; Carminati et al., 2010; Moradi et
al., 2011; Ahmed et al., 2017; Benard et al., 2018).
The water gradients in the rhizosphere are very dynamic (Carminati,
2012). Therefore, the timing of changed conditions is crucial for best es-
timating the rhizosphere extent for water (Fig. 6), whether this be dry-
ing or rewetting or day/night cycles. For instance, root water uptake de-
creases in the evening to avoid excessive dehydration of the rhizosphere
(Caldeira et al., 2014). Also, the root morphology (e.g. root hairs) or
root type (e.g. seminal, crown and lateral roots) extend the water deple-
tion zone (Segal et al., 2008; Carminati et al., 2017b; Holz et al., 2018;
Ahmadi et al., 2018).
1.- /:),1-6<; 51+:7*1)4 ,1;<:1*=<176 16 <0- :01B7;80-:-
The distribution of life in the rhizosphere is a very interesting and
intriguing aspect, but the respective data are nearly absent. The pre-
vious sections and ]gures clearly show that microhabitat properties
change across and along the roots (Schmidt et al., 2018). Accordingly,
7
UNCORRECTED PROOF
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Fig. 5. Gradients of nutrients and excess elements in the rhizosphere. Top left: Generalized gradients and extents of nutrients (below the X axis, blue lines) with rapid (3–5 mm) and slow
diffusion (0.5–2 mm) and of excess elements (above the X axis, red lines) from soil to root. The depletion and accumulation are presented relative to the concentration of nutrients or
excess elements in the bulk soil. The periods of nutrient depletion within the root hair cylinder and in the rhizosphere correspond to ∼1 and 3–4 days, respectively. The duration of excess
element accumulation at the root surface strongly depends on their concentration in solution and cannot be generalized. Top right: Depletion of the isotopically exchangeable phosphate
in the rhizosphere of maize and rape grown in a sandy soil. The data were obtained from scanning autoradiographs of 5-day-old root segments with a micro-densitometer (modi]ed
from Hendriks et al., 1981).Bottom left: Nitrate depletion in the rhizosphere of ryegrass grown in a sandy soil. The soil was separated from roots by a ]ne-meshed screen to provide for
a planar soil-root interface. Only soil solution and root hairs could penetrate the screen, but not the root cylinders. After ten days, the soil was frozen, divided into thin layers parallel
to the screen, and the layers separately analyzed for nitrate (modi]ed, from Claassen and Steingrobe, 1999). The 20% of concentration di`erence (ΔC) are presented as an example for
signi]cant di`erence to the initial NO3−concentration in root una`ected soil to show the rhizosphere size.Bottom right: Gradients of excess elements: Al, Fe and Mn in the rhizosphere
of metal-accumulating willow and rice (data extracted from Hoefer et al., 2017; Williams et al., 2014). Although Fe and Mn are plant nutrients, their mass ^ow (as Fe2+ or Mn2+) with
water is frequently much higher than the root uptake. Consequently, they accumulate in excess in the rhizosphere compared to the bulk soil and form gradients. The extremely high
accumulation of excess elements on the root surface (because their mass ^ow with water is much larger than the root uptake) is presented in the inset below. Inset left: Thin-section
photography of Fe2O3 plaque accumulation by mass ^ow of Fe2+ with water and oxidation to Fe3+ and precipitation at the root surface (courtesy Dr. Otto Ehrmann, Bildarchiv Boden –
Landwirtschaft –Umwelt: http://www.bildarchiv-boden.de); Inset right: Photo of rhizolith –CaCO3 accumulation around the root and its calci]cation (courtesy of Dr. Kazem Zamanian,
see also Zamanian et al., 2015). . (For interpretation of the references to color in this ]gure legend, the reader is referred to the Web version of this article.)
these microhabitats are occupied by microorganisms specialized for var-
ious niches, de]ned mainly by pH (Fig. 1), amounts and composition
of organics (Fig. 2), as well as direct mutualistic interactions with the
roots. The time for the development of microbial communities speci]c
for individual root zones is decisive (Watt et al., 2006; Dupuy and Silk,
2015). This combination of properties and time leads to gradients of mi-
crobial groups from the root endodermis to the bulk soil (Figs. 7 and
8): endophytes/nodules –arbuscular mycorrhiza –ectomycorrhiza/rhi-
zoplane bacteria –rhizosphere bacteria –mycorrhizal hyphae –bulk soil
bacteria/fungi (Watt et al., 2006).
This life distribution (Fig. 7) is typically visualized statically –it
does not re^ect the niche development and occupation over time. The
niches are associated with various microbial communities common for
root zones because they re^ect various substrate inputs and develop
ment periods. To evaluate such niche formation and their occupation,
microbial growth rates must be seen in light of the root growth rates
(Dupuy and Silk, 2015). The main dif]culty here is that root growth
(∼20 mm day−1corresponding to ∼1 mm h−1Watt et al., 2006) is linear,
but microbial growth (averaging 0.01–0.1 h−1, van Bodegom, 2007) re-
^ects the local biomass increase. Accordingly, to establish the biogeo-
chemical niches in the rhizosphere, the longitudinal root growth must
correspond to the local increase of microbial biomass in the soil volume.
Bacteria may adhere to roots, and certain populations may therefore be
very temporary at a given position on a root and may wash easily from
that location (Silk et al., 1989; Huang et al., 1994; Watt et al., 2006).
The root development stage affects rhizosphere life as well: young
root regions covered by epidermal cells have more abundant
8
UNCORRECTED PROOF
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Fig. 6. Gradients of water content in soil and rhizosphere: Water content around lupine roots when soil is dry, but rhizosphere is still wet (color left) –shortly before irrigation; and
shortly after irrigation when the soil is wet, but the rhizosphere still has low water content (right). The color scale re^ects the volumetric water content (cm3 cm−3) (from Carminati,
2012). Note the clear hotspots of high water content (white patches) around some roots in the left color sub]gure and the same hotspots with low water content in the right sub]gure.The
sub]gures on the left represent the water gradients from the roots calculated from the left and right color ]gures under dry and wet conditions, respectively. The water gradients under
drought increase to the root, 2) under wet conditions –decrease to the root (from Carminati, 2012 and Rudolph-Mohr et al., 2017). The rhizosphere extent after drying is ∼10 mm, but
after rewetting ∼0.3 mm. Note that the scales at the top sub]gure are in mm and at the bottom in cm. . (For interpretation of the references to color in this ]gure legend, the reader is
referred to the Web version of this article.)
Fig. 7. Gradients of life in the rhizosphere: Top: Microbial biomass content (MBC, from
Chen et al., 2002). Gradient of total PLFA in rhizosphere of 741=5 8-:-66- L. (from He
et al., 2009, modi]ed). Bottom: Abundances of Proteobacteria in the rhizosphere, rhizo-
plane, and endosphere fractions (Chen et al., 2016, modi]ed).
!;-=,7576); and A<780)/), whereas the older regions with abscised
sheaths and cortices have much more abundant actinomyces. Root de-
velopment, however, does not always change bacterial populations, and
e.g. 741/7<:7801+ and +7817<:7801+ bacteria frequently coexist in various
root branches (Semenov et al., 1999). The gradients in the diversity and
abundance of microbiomes have opposite trends (Fig. 8): while abun-
dance and activity decrease from roots to the bulk soil, the diversity
from roots to the bulk soil increases (Figs. 7 and 8) (Chen et al., 2016;
Poole, 2017; Semenov et al., 2019). In both wheat and rice, for exam-
ple, alpha diversity of the bacterial community was lowest in the root
compartment (Wang et al., 2018).
Mobility of “life”in the rhizosphere is crucial for gradient formation.
Some bacteria swim quickly in aqueous media. !;-=,7576); D=7:-;+-6+-
swims at between 1.7 and 6.0 m d−1in water (Arora and Gupta, 1993),
two orders of magnitude faster than the root growth, and three orders
of magnitude faster than hyphal extension (1.5–4 mm d−1). Certain bac-
teria therefore move rapidly through water-]lled spaces in the rhizos-
phere. Nonetheless, the motility and the true expansion rates of bacteria
in the soil environment (liquid-solid interfaces) remain unknown.
The evaluation of rhizosphere size and shape are more complicated
for signaling compounds, secondary metabolites and other chemo-at-
tractants because most of them are volatile and not strongly absorbed
by soil minerals. Consequently, the travel distances and concentration
gradients of signaling compounds and secondary metabolites are very
dynamic and depend on soil properties (e.g. organic matter content)
and moisture, root release (pathogen infections) and root development
(reviewed in Bowen and Rovira, 1999). Accordingly, the distance from
which microorganisms are stimulated and grow or move towards a root
indicates the solutes' and exudates’diffusion ranges (Huisman, 1982).
These distances are determined by the densities of a fungal inoculum
in the soil and on infection densities on the root. The response dis-
tances for most microorganisms are within 1 mm from the root, but
"01B7+<761) ;74)61 can respond at 5 mm, )-5)6675A+-; /:)55161; at
12 mm, and VAM up to 16 mm away from the root (Huisman, 1982).
!;-=,7576); 8=<1,) cells in tomato rhizosphere have a maximum com-
munication distance of ∼80 μm that is de]ned by the concentration of
9
UNCORRECTED PROOF
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Fig. 8. Distribution of life in the rhizosphere. The abundance of various microbial groups across (X axis at the bottom, in mm from the root surface) and along (Y axis at the right, in cm,
not proportional) the young root is presented by continuous color curves. Microbial groups include: Arbuscular mycorrhiza (violet) and Ectomycorrhiza (blue); Endophytic, Rhizoplane and
Rhizosphere bacteria (green). The gradients of microbial density, activity and diversity, as well as the dominance of r and K strategists are presented at the top right.The loupes magnify
various processes and microbial distribution: A: higher density of plant growth promoting rhizobacteria (PGPR) compared to pathogens in 2) the rhizosphere and 3) reverse in bulk soil;
B: abundance of various microbial groups 1) on rhizoplane, 2) in the rhizosphere, 3) in bulk soil; C: infection of root hairs by rhizobia and formation of nodules; D: release of signaling
compounds and attraction of rhizobia and other PGPR. The numbers in the loupes re^ect: 1) rhizoplane, 2) the rhizosphere, 3) bulk soil.The schematic presentation of the abundance of
individual microbial groups to the left or right of the root is made solely to avoid much overlapping of the curves. The overall life density is presented with orange shading on the right.
Note that the size of (micro)organisms is not proportional to their real size. . (For interpretation of the references to color in this ]gure legend, the reader is referred to the Web version of
this article.)
N-acyl homoserine lactone as chemoattractant (Gantner et al., 2006).
Despite the crucial importance of signaling compounds for understand-
ing root-microbial interactions in the rhizosphere, only very few stud-
ies have investigated these topics experimentally, with most of them fo-
cused on i) bacterial cell-to-cell communication and ii) root-pathogen
interactions.
Similarly, only few studies have attempted to connect root zones or
the distance from the root surface (i.e. the 3D picture) with microbial
community structures (Silk et al., 1989; Huang et al., 1994; He et al.,
2007, 2009; Chen et al., 2016; Wang et al., 2018). We found no studies
on the stationarity of microbial communities in the root zones (except
one in which OTU richness remained stable in the rice rhizosphere dur-
ing 1.5 months of ^ooding, Wei et al., 2019). The data on gradients of
microfauna (protozoans, nematodes), microarthropods (mites, collem-
bolans), and macroarthropods in the rhizosphere are much rarer than
those on microorganisms.
)+<7:; )E-+<16/ :01B7;80-:- -@<-6< )6, ;0)8-
The distributions of the parameters described above are not ]xed,
and various plant, root, soil, environmental and management factors
affect the rhizosphere extent, the gradients and the time necessary to
reach the quasi-stationary state. Although this review is not aimed at
an exhaustive analysis of these factors, they need to be mentioned
(Table 2). The following conclusions on the key factors are warranted:
1) Time: The duration of root occupation of a soil volume makes all
gradients steeper –from and to the root (Fig. 3). Importantly, these
steeper gradients pertain to mainly the maximum or minimum values
at the root surface, but the rhizosphere extent remains nearly constant
(Fig. 3). 2) Root morphology: All root morphological properties –root
hairs (Fig. 2), ]ne roots, mycorrhiza, etc. –leading to a higher release
of exudates also increase the rhizosphere extent for organics, enzymes
and consequently for other microbial parameters. The root hairs en-
large the rhizosphere extent (Ma et al., 2018) and, together with ]ne
10
UNCORRECTED PROOF
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Table 2
Effects of soil, plant and environmental factors (columns) on rhizosphere extent for main parameters (rows)a.
Factorb/Parameterc pH Exudates Secretes CO2/O2 NO3−NH4+, K+ P Ca2+, Mg2+ Life Enzymes Mechanismsd
Soil
- Moisture ↑ ↑ ↑ ↓↓ ↑↑ ↑ ↑ ↑↑ ↑ ↑ Di`usion ↑
- Fe3+, Al3+ ↓ ↑↑ ↓ ↓↓↓ ↓ ↓ Sorption ↑
- SOM ↓ ↑ ↑ ↓ ↑ ↑ ↓ ↓ ↑ ↑ Sorption ↑, Di`usion ↓
- Clay ↓ ↓ ↓ ↓ ↓ ↓↓↓ ↓↓ ↓↓ ↓ Di`usion ↓, Sorption ↑
- pH ↓ ↑ ↑ ↓ ↓ ↑ ↑ ↑↑ ↓ ↓ Neutralization
- Salinity ↓ ↑ ↑ ↓↓ ↓ ↓ ↓↓↓ ↓ ↓↓ ↓↓ Ion competition ↑, Osmosis ↑
- Density/Compaction ↓ ↓ ↓ ↓↓ ↓ ↓ ↓ ↓ ↓↓ ↓↓ Ion competition ↑, Osmosis ↑
Plant/Root
- Root age ↓↓ ↓ ↓ ↑ ↑ ↑ ↑ ↑↑↑ ↑↑ Process duration
- Proteolytic Roots ↓↓↓ ↓↓↓ ↓↓ ↑↑↑ ↑↑ ↑↑ ↑↑↑ ↑ ↑↑ ↑↑ Process intensity
- Mycorrhiza ↓ ↑ ↑ ↑ ↑↑ ↑↑ ↑↑↑ ↑↑↑ ↑↑
Environmente
- WPD ↑ ↑ Uptake ↑
- Light ↑↑ ↑↑ ↑ ↑↑ ↑↑ ↑↑ ↑ ↑ ↑↑ ↑↑ Rhizodeposition ↑
-4->)<-, ↑ ↑↑ ↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑ ↑↑ Rhizodeposition ↑
-$-58-:)<=:- ↓ ↑ ↓ ↓ ↓↓ ↑ ↑ Rhizodeposition ↓
-,-87;1<176 ↑↑↑ ↓ ↓ ↓ ↓ ↑ ↑↑ ↑ ↑↑ Rhizodeposition ↓
The environmental factors a`ecting the gradients of all parameters in the rhizosphere in the same direction: decreasing (soil porosity, etc.) or increasing (clay content) are not mentioned
in the Table.
aNote that the Table presents the changes of the rhizosphere extents from or to the root, not the changes of processes.
bTo correctly read the Table: Factors always increase, and the extents may ↑increase, ↓decrease, or ≈remain nearly unchanged.
cNote that the arrows show extents changes.
dOnly the main mechanisms are mentioned here.
eThe factors mentioned in 1<)41+ in Environment corresponds to the global change components.
roots, increase the maximum of each property close to the root (Fig. 2).
Mycorrhiza also increase the rhizosphere extent. The speci]c root zones
crucially in^uence rhizosphere size and shape. Most visualization ap-
proaches clearly show that certain processes are especially intensive at
the root tip (e.g. exudation: Fig. 2, enzyme activities: Fig. 3), whereas
others dominate in the elongation and root hair zones (e.g. pH: Fig. 1,
redox: Fig. 4, water uptake: Fig. 6). 3) Soil factors increasing sorption
(contents of Fe3+, Al3+, SOM, clays, biochar) or uptake (microbial bio-
mass) of organics decrease the rhizosphere extent, causing steeper gradi-
ents. 4) Soil moisture: Increasing soil moisture increases the rhizosphere
extent of all parameters (except gases), mainly because of faster diffu-
sion from/to the root surface. 5) Environmental parameters: All environ-
mental parameters (light, elevated CO2, temperature, etc.) that intensify
rhizodeposition and especially exudation increase the rhizosphere ex-
tent for organics, enzymes and nutrients. Light promotes photosynthesis
and may affect pH changes of more than 2.5 units even during a single
day, leading to a diurnal acidity pattern (Rao et al., 2002a). 6) Tem-
perature stimulates microbial activity and membrane permeability of
root cells, accelerating exudation and enlarging the rhizosphere for CO2
and enzyme activities (Razavi et al., 2019). Despite the effects of root/
plants, soil and environmental factors on various processes, we conclude
that most of them make the gradients steeper, but the rhizosphere ex-
tent remains nearly constant. Beyond the abiotic factors affecting such
gradients (see above) (Whalley et al., 2005; Daly et al., 2015; Naveed et
al., 2018), the roots themselves structure the environment. Plants mod-
ify the local soil environment in the rhizosphere very early during root
growth (Helliwell et al., 2019) and in^uence the pore structure at the
root–soil interface by root hairs (Koebernick et al., 2014, 2019). Thus,
roots structure not only the entire range of biotic and chemical para-
meters, but also the physical environment. This is clearly demonstrated
by the increased soil porosity around roots (Fig. S2). Decreased porosity
(Fig. S2) and increased soil density (see below) directly at the root sur-
face (rhizoplane) also increase the water content near the root surface at
negative water potentials (Aravena et al., 2014). Growing roots increase
the soil density in the rhizoplane to improve water uptake and decrease
porosity in the rhizosphere for better water ^ow. Soils with contrasting
textures are variously deformed by roots, depending on the initial bulk
density and plant species. X-ray microtomography of loam sandy and
clay loamy soils showed an increase in porosity adjacent to the roots of
pea, tomato and wheat, but this increase was independent of root di
ameter (Helliwell et al., 2019). A porosity increase by 5–15% of the soil
volume leads to a much faster diffusion of gases as well as of water with
dissolved nutrients and exudates. This broadens the rhizosphere extent.
4. Synthesis
758):1;76 7. ,-;<:=+<1>- )6, 676,-;<:=+<1>- )88:7)+0-;
The rhizosphere extent depends not only on the speci]c parame-
ters, but also on the resolution of the methods. This calls for comparing
the two major groups of approaches: i) destructive approaches –mainly
soil slicing, and ii) non-destructive approaches –mainly 16 ;1<= visual-
ization. Destructive methods (Helal and Sauerbeck, 1981; Tarafdar and
Jungk, 1987; Youssef and Chino, 1987, 1988, 1989; Sauer et al., 2006;
Marschner et al., 2012; Kuzyakov et al., 2003; zu Schweinsberg-Mickan
et al., 2010) showed a (much) larger rhizosphere extent for all para-
meters compared to 16 ;1<= visualizations (Römheld, 1986; Gahoonia
and Nielsen, 1991; Fidzer and Sc]aller, 1980; Blossfeld et al., 2011;
Carminati, 2012; Zarebanadkouki et al., 2012; Schreiber et al., 2012;
Rudolph et al., 2013; Razavi et al., 2016, 2017; Fresno et al., 2017). This
was opposite to our own expectation that 16 ;1<= methods would show at
least similar and probably larger rhizosphere extents. We have only one
straightforward explanation for this phenomenon: the experimental pots
used for most destructive approaches produce a large root mat (Sauer
et al., 2006; Hafner et al., 2014). Consequently, ^uxes from and to the
root mat are ongoing in parallel and are actually one-dimensional. In
contrast, the ^uxes from individual roots (common for all 16 ;1<= visu-
alization approaches) are radial, i.e., two-dimensional. This means that
the ^ux from (or to) an individual root will be diluted according to the
distance to the power of two (or power of three at the root tip) by sur-
rounding soil, making it negligible already after a few mm. This con-
]rms that 16 ;1<= visualization approaches re^ect the real rhizosphere
state and processes more correctly than the destructive approaches.
In contrast to the rhizosphere extent, the relative increase of max-
ima measured by destructive approaches is less than that by 16 ;1<= vi-
sualization. This is because the latter re^ects the ongoing processes,
whereas the former stops most processes that maintain the gradients.
Accordingly, the subsequent analyses measure gradients that are al
11
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
ready partly dampened by ongoing diffusion, microbial C utilization,
H+ neutralization, etc.
The difference between destructive and non-destructive approaches
increases as the maximal rhizosphere extent is reduced. This means that
differences between the approaches are greatest for the parameters with
the narrowest rhizosphere. Consequently, 16 ;1<= visualization methods
are especially important for revealing the localized soil parameters very
close to the root surface. Based on these methodological differences, we
recommend estimating rhizosphere extent and shape by non-destructive
visualization approaches where possible.
:7=816/ 7. 8):)5-<-:; *);-, 76 <0-1: :01B7;80-:- -@<-6< )6, ;0)8-
All the gradients, rhizosphere extents and shapes of the parameters
described above can be summarized into a few groups according to: 1)
direction of the ^ow: to or from the root (Table 1), 2) increase or de-
crease toward the root, corresponding to the accumulation or depletion
in the rhizosphere, respectively, and 3) the shape of the curve: diffusion
(D) curve or sigmoidal (S) curve. Figs. 9 and 10 summarize these prop-
erties for most of the main parameters and macronutrients (Fig. 9, left),
and separately for micronutrients and toxic elements (Fig. 9, top right),
and enzymes (Fig. 9, bottom right).
Even though the reviewed studies applied a broad range of ap-
proaches (only the results of non-destructive approaches were consid-
ered here) and involved various soils and plants, all parameters can be
subdivided into three groups according to the rhizosphere extent (Fig.
10): 1) The minimal extents are common for micronutrients and heavy
metals, i.e., typically 0.5 mm and not exceeding 1.0 mm (Fig. 9 top
right). The ^uxes are directed to the root and lead to depletion of the
element concentration according D or S curves. 2) Most of the parame-
ters exhibit a rhizosphere extent between 2 and 4mm (Fig. 9). Most en-
zymes also belong to this group despite negligible diffusion (Fig. 9). 3)
Only very few parameters have rhizosphere extents >4 mm. This group
encompasses: gases (Figs. 9 and 10), electrical conductivity, Eh (Fig. 9),
water content (Fig. 9), and the gradients of microorganisms (Fig. 9).
Importantly, the rhizosphere extent of microorganisms exceeds the dis-
tance of root exudates by nearly two times. Thus, the rhizosphere effect
on microorganisms is larger than the measured distance of exudate con-
centration, enabling some organic compounds to reach up to 4–5 mm
before they are trapped by microbial cells.
#<)<176):1<A 7. <0- :01B7;80-:-
In comparing the data from many studies focused on the same pa-
rameters, we were surprised about the agreement in the rhizosphere
ranges (Fig. 10) and in the shape of the gradient curves, which were
nearly independent of plant species or soil conditions. This allows an
important conclusion: Despite the very high dynamics of root growth, of
water ^uxes with nutrients and exudates, of microbial growth etc., <0-
;0)8- 7. 16,1>1,=)4 8):)5-<-:; 16 <0- :01B7;80-:- 1; ;<)*4- –1< 1; 9=);1;<)
<176):A. Despite a broad number of factors affecting the gradients (Table
2), most of them affect the concentration maximum or mini
Fig. 9. Summary of rhizosphere extents and gradients for the most frequently investigated parameters. Left: Main parameters: Gases (O2, CO2), Ions and Nutrients (H+, NH4+, NO3−,
PO43−, K+, Ca2+, Mg2+), Root exudates (sugars, amino acids, carboxylic acids and enzymes), and other parameters (Eh, Electrical conductivity, H2O content, Microbial life, Soil porosity).
Top right: Micronutrients, excess elements (Fe3+, Mn4+, Al3+) and heavy metals. Bottom right: Activities of enzymes responsible for C, N, P and S cycles.Circles and whiskers re^ect the
mean ±SE; Vertical dashes indicate the median. The closer the median is to the mean, the higher the probability that the distribution is normal. All parameters were calculated based
on at least 3 measurements. The points, whiskers and dashes for an individual group of parameters were calculated based on all values of all parameters belonging to that group. Arrows
on right of each Figure re^ect the direction of ^ux: ↗: ^ux from the root with increasing concentration (or activity), ↘: from the root decreasing concentration, ↖: ^ux to the root with
increasing concentration, ↙: to the root with decreasing concentration. Dor Sre^ects the shape of the gradient curve: Diffusion curve or Sigmoidal curve, respectively. Note that the
presented summary does not re^ect the whole complex of processes leading to gradient establishment. Only the results of non-destructive approaches were considered.
12
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
Fig. 10. Generalization of rhizosphere extents and gradient types for the most investi-
gated parameters: Gases, Root exudates, Nutrients and Excess elements, pH and Eh, En-
zyme activities and microorganisms (Life). Three groups of rhizosphere extents were typ-
ical: 0.5–2 mm (right), 2–4 mm (left bottom), and >4 mm (left top). The shapes of the
curves re^ect the “diffusion”(D) or “sigmoidal”(S) gradients (compare Fig. 9). Despite the
dynamic nature of each parameter, these gradients are quasi-stationary because of oppo-
site directions of their formation processes. HM: heavy metals (Zn, Cu, Ni, Co, Pb, Cd, As).
mum at the root surface, but not the rhizosphere extent and not its
shape. This re^ects the outcome of competitive processes: release by
roots, diffusion, root uptake, microbial uptake, sorption/desorption,
precipitation (Table 3). The dominance of these processes can be easily
recognized based on the nature of each property and the diffusion or
sigmoidal curve. We conclude that, despite the dynamic nature of each
parameter, these gradients are quasi-stationary because of opposing for-
mation processes. In most cases, only 2 main processes determine the
rhizosphere extent and the shape for individual parameters.
More precisely estimating the process parameters for speci]c soil
conditions and root characteristics will be a research topic in the future
and is expected to provide important inputs for modeling. Should this
quasi-stationary state be con]rmed in further –more detailed –stud-
ies, the rhizosphere extent can be clearly de]ned for various parameters
and can be used in further applications, e.g. extrapolations considering
root architecture (Downie et al., 2015), modeling, assessment of the soil
volume occupied by roots, stocks of nutrients potentially available for
plants, etc.
=<=:- :-;-):+0 ,1:-+<176;
The future experimental research directions are multi-facetted, and
include developing new and optimizing existing methods, analyzing
new rhizosphere properties, coupling various parameters, site-speci]c
sampling, effects of various new factors crucial for root development
and rhizosphere properties, and ]nally assessing the ecological rele-
vance. Despite the broad range of available 16 ;1<= visualization ap-
proaches (Oburger and Schmidt, 2016), many of them have significant
limitations in sensitivity, spatial and temporal resolution, and applica-
bility. Importantly, nearly all visualization approaches started to be de-
veloped just a few years ago (except imaging of radioisotopes –autora-
diography, which has already been applied for > 40 years for rhizos-
phere research, Claassen et al., 1981). A key prerequisite for the future
development of all visualization approaches is that their spatial resolu-
tion should be at least 3–5 times (preferably one order of magnitude)
smaller that the gradients to be investigated. Assuming a rhizosphere
extent of 2 mm (Figs. 8 and 9), visualization methods having a resolu-
tion of <0.2 mm across a total image size of at least a few cm (the size
Table 3
Main mechanisms responsible for the distribution and gradients of various parameters in the rhizosphere.
Property Ra release R uptake Di`usion Mass ^ow Micr uptake Sorption Desorption Precipitation Other
Gases
- O2 +++ +++ +++
- CO2 +++ +++
pH (H+) +++ + +++ Neutralization
Redox + + + e–acceptors
EC/ions ++ ++ +++
H2O +++ + +++
Exudates +++ + +++ ++ +++ + + + Mineralization
Enzymes +++ + ++ ++ Mineralization
Nutrients +++ ++ ++ ++
- NO3−+++ + +++ ++
- NH4+ +++ ++ + ++ ++
- PO43–+++ +++ + + +++ + +++
- K+ ++ ++ + ++
- Ca2+ + + ++ + +++
- Mg2+ ++ ++ ++ + +
- SO42–++ ++ + + +
MicroNutr. +++ +++ + ++
Ballast elements + + +++
- Ca2+ + +++ +++
- Fe2+/3+ +++ ++ ++ Oxidation
- Si + + ++ ++
- Al3+ + +
- Mn2+/4+ + Oxidation
Microorganisms + Growth, (motility)
The number of + corresponds to the relative importance of individual processes for speci]c properties.
aR means root.
13
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
of small roots) are desirable. Most of the methodologies presented in
this review do not have this resolution (>100:1).
The development of visualization methods that are especially fo-
cused on rhizodeposition components is very desirable. Despite sig-
nificant progress in the analysis of exudates, secretions, mucilage,
sloughed-o` cells, etc., no suitable approaches allow them to be visual-
ized at the rhizosphere level. Even 14C imaging, well suited to localizing
organic substances, enables only hypothetical separation based on the
very weak assumption that individual groups of rhizosphere compounds
will be subsequently released with increasing time after 14C allocation
into the roots (Oburger et al., 2018). The major future challenge is to
adapt and optimize the methods for the broad range of soil conditions,
especially for their physical structures. This challenge includes improv-
ing the resolution of all methods to accommodate the roughness of the
soil surface on rhizotron windows and the contact between the sensor
and the soil (Bais et al., 2006).
Another direction of future studies should focus on combining vari-
ous properties characterizing the same roots. This will be a crucial step
in understanding rhizosphere processes and determining how the mi-
cro-cycles of nutrients are coupled with C, water ^uxes with nutrients,
microbial community structure with rhizodeposition and enzyme activ-
ities, as well as rhizodeposition release with its decomposition (O2 con-
sumption and CO2 production).
The switch from pure 2D mapping to 3D visualization and localiza-
tion, and even tracing the dynamics (4D) of properties (Downie et al.,
2015) will become a crucial and fascinating step in understanding of
rhizosphere processes, their sequence and interactions (Baveye et al.,
2018). Methods need to be developed to produce 3D maps of soil prop-
erties based on spatial sequences of 2D maps, e.g. based on the regres-
sion trees and ordinary kriging (Hapca et al., 2015) or other spatial cor-
relation approaches (Kravchenko et al., 2019).
The most limiting (nearly absent) data are the life gradients: micro-
bial community structure and functions across and along the roots. Most
studies sampling the rhizosphere and root-free (bulk) soil do not cap-
ture microbial successions during root growth or community composi-
tion and functions at the level of microhabitats common in the rhizos-
phere. As the rhizosphere forms gradients of microbial communities to
the root-free soil, we can expect that microbial predators and other ene-
mies (e.g. viruses) follow these gradients. The above-mentioned site-spe-
ci]c sampling would shed ]rst light on this aspect of life in the rhizos-
phere.
Process visualization in the rhizosphere goes beyond providing satis-
fying images, to achieve a better understanding of ongoing interactions.
It should also be used in site-speci]c micro-sampling to enable much
more detailed analyses with destructive methods. This would allow the
application of physico-chemical and molecular biology approaches to
identify the properties, functions and interactions in hotspots.
This review focused solely on the rhizosphere. Roots, however, also
grow to or in other hotspots, e.g. into the detritusphere (due to the
abundant nutrients released by litter decomposition) or biopores (be-
cause of the much lower impedance and fast transfer of available water
and nutrients from the subsoil, Athmann et al., 2017). The mechanisms
and consequences of such hotspot interactions are completely unknown
and their effects on gradients need to be investigated.
Currently, the effects of factors affecting the rhizosphere extent
(Table 2) are qualitative and mainly based on educated guesses. Future
studies should specify and quantify these effects and identify which of
these effects are more important in developing rhizosphere management
strategies.
Among the important applied questions that can be addressed based
on rhizosphere size and shape is the amount of available nutrients. An-
other key aspect is assessing when and how the rhizospheres of two
(or more) roots start to overlap (Jungk, 2001). Despite the many stud-
ies on root architecture and nutrient gradients, these two issues have
been very seldom linked to predict the resource (nutrients, water) stocks
available for roots (Ahmed et al., 2015). For instance, recent develop
ment of root growth visualization by using Synchrotron Radiation X-ray
Tomographic Microscopy (SRXTM) uncovered the three-dimensional in-
teractions of root hairs (Keyes et al., 2013). Methods for imaging nutri-
ent uptake by root hairs growing in real soils are absent (Keyes et al.,
2013). Linking root architecture and rhizosphere gradients would be a
step forward in helping plant breeders to develop varieties exhibiting
expanded rhizospheres with a branched architecture.
5. Conclusions and relevance
Based on a critical evaluation of studies analyzing the effects of
growing roots on the characteristics and functions in the surrounding
soil, we calculated the extent of the rhizosphere and presented the shape
and gradients of the key parameters: gases, water, macro- and micro-nu-
trients, organic substances, enzymes, redox potential, and microbial life
(Figs. 9 and 10). All gradients were formed by two (seldom more) main
oppositely directed processes (Tables 1 and 3): release or uptake by
roots, and utilization by microorganisms or precipitation and sorption
on clay minerals and sesquioxides (Bray, 1954; Barber et al., 1963). All
curve shapes are either diffusion (D) or sigmoid (S) types, but more than
one process is always responsible for the gradients of all parameters in
the rhizosphere (Table 3).
Generalizing, the spatial stationarity of each property gradient is
reached at least after a few days and sometimes within hours –despite
the high temporal dynamics of the parameters in the rhizosphere re-
lated to root growth and aging, and despite the interactions of various
processes (Hinsinger et al., 2003; Watt et al., 2006; York et al., 2016).
This means that, after occupying a new soil volume, roots immediately
structure the local microenvironment, which then remains stable (9=);1
;<-),A ;<)<-). Roots can therefore be interpreted as ecosystem engineers
that optimize their habitat for better growth under speci]c soil condi-
tions.
The stability of the gradients in the rhizosphere is fundamentally rel-
evant.
1) Roots structure the environment to optimize their functioning (water
and nutrient uptake), to establish habitats for microorganisms and
their activities, e.g. for nutrient mobilization, to attract and stimulate
root-growth-promoting bacteria and mycorrhiza, to protect against
pathogens, and probably to mediate kin recognition and coopera-
tion with neighboring roots and plants to reduce wasteful competi-
tion (Semchenko et al., 2014). For instance, exudates transport in-
formation about plant identity (kinship, species and community ori-
gin) and trigger behavior changes such as increased cooperation with
relatives and competition with non-relatives. Such cooperation can
be identi]ed by roots showing less competitive traits like reduced
branching or speci]c root length (Semchenko et al., 2014). 2) The
rhizosphere size enables calculating the maximal root density in a
soil layer at which the competition between individual roots is ab-
sent or minimal (Jungk, 2001). This helps optimize plant density, ir-
rigation and fertilization by considering the belowground competi-
tion between individual roots and rhizosphere size.
3) Knowledge about the extent and shape of the rhizosphere simpli]es
calculating the soil volume of potentially available nutrients (and
other parameters). Multiplying the root length by the integrated gra-
dient of each nutrient (assuming the same gradient in all radial di-
rections in soil) will yield the total amount of nutrients available for
crops. This approach works well for nutrients with slow diffusion
(P, K) (Fusseder and Kraus, 1986) and can be used when fertilizing
with macro-nutrients to optimize the N, P, K, S, Ca, Mg stoichiome-
try of crops. Importantly, this effort will be based not on the nutrient
amounts available in the total soil but those present in the rhizos-
phere.
4) Assuming similar (not identical) nutrient gradients of various plants
(Jungk, 2001), the selection of crops with better nutrient uptake
and acquisition should focus mainly on improving root architecture
and the characteristics enlarging the rhizosphere: more roots, espe
14
UNCORRECTED PROOF
(=BA)37>#")B)>1 #7141747/A)6,17+0-51;<:A @@@ @@@@ @@@@@@
cially ]ne roots or roots with long hairs (Silk et al., 1989; Huang et
al., 1994; Watt et al., 2003). Consequently, the ef]ciency of inter-
cropping can be optimized if the rhizosphere extents do not overlap
between two or more species and if maximal niche differentiation is
attained.
5) Analysis of physical and chemical properties should be combined
with simultaneous measurements of biological properties and func-
tions, along with their dynamics. This will allow, for the ]rst time,
linking rhizosphere habitats with their occupation by microbial com-
munities and their speci]c functioning as related to the recycling of
C and nutrients between plants and microorganisms.
6) Determining the correspondence of the rhizosphere extent and shape
for various parameters can help to understand their interactions. For
example, the correspondence of the rhizosphere shape for enzymes
with that of microorganisms re^ects the proportion of enzymes pro-
duced microbially versus released by roots. Furthermore, the corre-
spondence of rhizosphere shape for nutrients with that of the speci]c
enzymes can re^ect what portion of the nutrients will be mobilized
from organic matter. Similarly, the overlapping of nutrients with pH
re^ects the area of nutrient acquisition from mineral forms.
7) The density gradients of life (e.g. bacteria, fungi) and of soil bio-
chemical properties will help identify safe zones protecting from
pathogen invasion. Microbial abundance on the rhizoplane and in
the rhizosphere in^uence nutrient availability either i) through di-
rect competition for nutrients between microorganisms and the root,
or ii) via the microbial decomposition of nutrient-mobilizing exu-
dates and enzymes.
These insights yield the ]rst generally valid conclusions about the
extent and shape of the most important hotspot in the soil –the rhizos-
phere.
Acknowledgements
We would like to acknowledge the work carried out by the re-
searchers whose published data were included in this study. YK is very
thankful for the long-term support by Deutsche Forschungsgemeinschaft
within various rhizosphere projects investigating belowground C alloca-
tion by plants, root–microbial interactions, rhizodeposition and micro-
bial transformation of rhizodeposits. BR is thankful to her spiritual sup-
porter: Ali Feizi and gratefully acknowledge the DFG for supporting the
project: RA3062/3-1 within priority program 2089 and highlighted im-
portance of imaging approach to overcome current knowledge gap be-
tween soil, microbiome and plant scientists. We thank two anonymous
reviewers for their critical but very constructive comments, Dr. Søren O.
Petersen for the ]nal suggestions and improvements, and Dr. Kyle Ma-
son-Jones for the improvement of language and writing style.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.soilbio.2019.05.011.
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