# Biological inhibition of soil nitrification by forest tree species affects Nitrobacter populations

Amandine Laffite, Alessandro Florio, Kasaina Sitraka Andrianarisoa, Charline Creuzé Des Châtelliers, Brigitte Schloter-Hai, Sidy Ndaw, Charlotte Periot, Michael Schloter, Bernhard Zeller, Franck Poly, et al.

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## To cite this version:

Amandine Laffite, Alessandro Florio, Kasaina Sitraka Andrianarisoa, Charline Creuzé Des Châtelliers, Brigitte Schloter-Hai, et al. Biological inhibition of soil nitrification by forest tree species affects Nitrobacter populations. Environmental Microbiology, 2020, 22 (3), pp.1141-1153. 10.1111/1462-2920.14905. hal-02870271

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Biological inhibition of soil nitrification by forest tree species
affects *Nitrobacter* populations

Laffite A.¹, Florio A.¹, S. Andrianarisoa², C. Creuze des Chatelliers¹, B.

Schloter-Hai³, S.M. Ndaw¹, C. Periot¹, M. Schloter³, B. Zeller², F. Poly¹,& X.

Le Roux¹, #,*

¹ Laboratoire d'Ecologie Microbienne LEM, INRA UMR 1418, CNRS UMR 5557,
Université Lyon 1, Université de Lyon, F-69622 Villeurbanne Cedex, France

² Biogéochimie des Ecosystèmes Forestiers, INRA Grand-EST Nancy, UR 1138 Route d'Amance, 54280 CHAMPENOUX, France

³ Research Unit for Comparative Microbiome Analysis, Helmholtz Zentrum München,
Ingolstädter Landstraße 1, D-85764 Neuherberg

*Both authors co-lead the study

* Corresponding author: xavier.le-roux@univ-lyon1.fr

**Running title:** Biological inhibition of *Nitrobacter* by trees

**Submitted to** *Environmental Microbiology*

This article has been accepted for publication and undergone full peer review but has not
been through the copyediting, typesetting, pagination and proofreading process which
may lead to differences between this version and the Version of Record. Please cite this
article as doi: 10.1111/1462-2920.14905
Biological inhibition of soil nitrification by forest tree species
affects *Nitrobacter* populations

Laffite A.¹, Florio A.¹, S. Andrianarisoa², C. Creuze des Chatelliers¹, B.

Schloter-Hai³, S.M. Ndaw¹, C. Periot¹, M. Schloter³, B. Zeller², F. Poly¹,& X.

Le Roux¹, #,*

¹ Laboratoire d'Ecologie Microbienne LEM, INRA UMR 1418, CNRS UMR 5557,
Université Lyon 1, Université de Lyon, F-69622 Villeurbanne Cedex, France

² Biogéochimie des Ecosystèmes Forestiers, INRA Grand-EST Nancy, UR 1138 Route d'Amance, 54280 CHAMPENOUX, France

³ Research Unit for Comparative Microbiome Analysis, Helmholtz Zentrum München,
Ingolstädter Landstraße 1, D-85764 Neuherberg

*Both authors co-lead the study

* Corresponding author: xavier.le-roux@univ-lyon1.fr

**Running title:** Biological inhibition of *Nitrobacter* by trees

**Submitted to** *Environmental Microbiology*

This article has been accepted for publication and undergone full peer review but has not
been through the copyediting, typesetting, pagination and proofreading process which
may lead to differences between this version and the Version of Record. Please cite this
article as doi: 10.1111/1462-2920.14905
**Originality significance statement:** This is the first study demonstrating biological nitrification inhibition (BNI) by tree species which directly affects the abundance of soil *Nitrobacter*. Before this work, BNI was thought to mostly affect ammonia oxidizers. This is an important breakthrough for understanding plant-microorganisms interaction processes that underlie niche construction by plants growing in environments with low soil N availability.

**Summary**

Some temperate tree species are associated with very low soil nitrification rates, with important implications for forest N dynamics, presumably due to their potential for biological nitrification inhibition (BNI). However, evidence for BNI in forest ecosystems is scarce so far and the nitrifier groups controlled by BNI-tree species have not been identified. Here we evaluated how some tree species can control soil nitrification by providing direct evidence of BNI and identifying the nitrifier group(s) affected. First, by comparing 28 year-old monocultures of several tree species, we showed that nitrification rates correlated strongly with the abundance of nitrite oxidizers *Nitrobacter* (50- to 1000-fold changes between tree monocultures) and only weakly with the abundance of ammonia oxidizing archaea (AOA). Second, using reciprocal transplantation of soil cores between low and high nitrification stands, we demonstrated that nitrification changed 16 months after transplantation and was correlated to changes in the abundance of *Nitrobacter*, not AOA Third, extracts of litter or soil collected from the low nitrification stands of *Picea abies* and *Abies nordmanniana* inhibited the growth of *Nitrobacter hamburgensis* X14. Our results provide for the first time direct evidence of BNI by tree species directly affecting the abundance of *Nitrobacter*.

Accepted Article
**Originality significance statement:** This is the first study demonstrating biological nitrification inhibition (BNI) by tree species which directly affects the abundance of soil *Nitrobacter*. Before this work, BNI was thought to mostly affect ammonia oxidizers. This is an important breakthrough for understanding plant-microorganisms interaction processes that underlie niche construction by plants growing in environments with low soil N availability.

**Summary**

Some temperate tree species are associated with very low soil nitrification rates, with important implications for forest N dynamics, presumably due to their potential for biological nitrification inhibition (BNI). However, evidence for BNI in forest ecosystems is scarce so far and the nitrifier groups controlled by BNI-tree species have not been identified. Here we evaluated how some tree species can control soil nitrification by providing direct evidence of BNI and identifying the nitrifier group(s) affected. First, by comparing 28 year-old monocultures of several tree species, we showed that nitrification rates correlated strongly with the abundance of nitrite oxidizers *Nitrobacter* (50- to 1000-fold changes between tree monocultures) and only weakly with the abundance of ammonia oxidizing archaea (AOA). Second, using reciprocal transplantation of soil cores between low and high nitrification stands, we demonstrated that nitrification changed 16 months after transplantation and was correlated to changes in the abundance of *Nitrobacter*, not AOA Third, extracts of litter or soil collected from the low nitrification stands of *Picea abies* and *Abies nordmanniana* inhibited the growth of *Nitrobacter hamburgensis* X14. Our results provide for the first time direct evidence of BNI by tree species directly affecting the abundance of *Nitrobacter*.
**Keywords:** *Ammonia oxidizing archaea (AOA)*; *biological nitrification inhibition (BNI)*; *comammox*; *Nitrobacter*; *soil nitrogen cycling*
**Keywords:** *Ammonia oxidizing archaea (AOA)*; *biological nitrification inhibition (BNI)*; *comammox*; *Nitrobacter*; *soil nitrogen cycling*
Introduction

The oxidation of NH<sub>4</sub><sup>+</sup> to NO<sub>3</sub><sup>-</sup>, i.e. nitrification, is a key pathway of the nitrogen (N) cycle in many terrestrial ecosystems. Nitrification is of key importance for soil quality, as it largely regulates the levels and types of mineral N forms, i.e. NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup>, available for plant nutrition, leaching of NO<sub>3</sub><sup>-</sup>, and emission of the potent greenhouse gas N<sub>2</sub>O (Baggs, 2011). The classical concept is based on the close interplay of two different groups of microbes: ammonia-oxidizing bacteria (AOB) and archaea (AOA) which oxidize NH<sub>3</sub> to NO<sub>2</sub><sup>-</sup> (Kowalchuk and Stephen, 2001; Leininger et al., 2006); and nitrite-oxidizing bacteria (NOB), with two main genera present in soils performing the oxidation of NO<sub>2</sub><sup>-</sup> to NO<sub>3</sub><sup>-</sup> (*Nitrobacter* and *Nitrospira*: Freitag et al., 2005; Attard et al., 2010). Recently this view was completed as microorganisms were detected which are capable to perform the complete nitrification process (COMplete AMMonia OXidisers, comammox; Daims et al., 2015; Van Kessel et al., 2015).

Nitrogen availability in soil and the balance between NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup> are the main factors limiting plant growth in most terrestrial ecosystems (Vitousek and Howarth, 1991; Stuart Chapin III et al., 2011; Ma et al., 2019). Plants thus depend on the activity of nitrifiers and can strongly compete with them for NH<sub>4</sub><sup>+</sup> (Vitousek et al., 1982; Kuzyakov and Xu, 2013). However, it is increasingly recognized that plants can exert a major influence over soil N cycling rates (Chapman et al., 2006). Plant species indirectly control soil nitrification or denitrification by altering the main environmental variables affecting nitrifiers and denitrifiers, i.e. NH<sub>4</sub><sup>+</sup> (Bengtsson et al., 2003) and NO<sub>3</sub><sup>-</sup> availability (Britto and Kronzucker; Norton and Firestone, 1996; Stark

Accepted Article
Introduction

The oxidation of NH<sub>4</sub><sup>+</sup> to NO<sub>3</sub><sup>-</sup>, i.e. nitrification, is a key pathway of the nitrogen (N) cycle in many terrestrial ecosystems. Nitrification is of key importance for soil quality, as it largely regulates the levels and types of mineral N forms, i.e. NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup>, available for plant nutrition, leaching of NO<sub>3</sub><sup>-</sup>, and emission of the potent greenhouse gas N<sub>2</sub>O (Baggs, 2011). The classical concept is based on the close interplay of two different groups of microbes: ammonia-oxidizing bacteria (AOB) and archaea (AOA) which oxidize NH<sub>3</sub> to NO<sub>2</sub><sup>-</sup> (Kowalchuk and Stephen, 2001; Leininger et al., 2006); and nitrite-oxidizing bacteria (NOB), with two main genera present in soils performing the oxidation of NO<sub>2</sub><sup>-</sup> to NO<sub>3</sub><sup>-</sup> (*Nitrobacter* and *Nitrospira*: Freitag et al., 2005; Attard et al., 2010). Recently this view was completed as microorganisms were detected which are capable to perform the complete nitrification process (COMplete AMMonia OXidisers, comammox; Daims et al., 2015; Van Kessel et al., 2015).

Nitrogen availability in soil and the balance between NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup> are the main factors limiting plant growth in most terrestrial ecosystems (Vitousek and Howarth, 1991; Stuart Chapin III et al., 2011; Ma et al., 2019). Plants thus depend on the activity of nitrifiers and can strongly compete with them for NH<sub>4</sub><sup>+</sup> (Vitousek et al., 1982; Kuzyakov and Xu, 2013). However, it is increasingly recognized that plants can exert a major influence over soil N cycling rates (Chapman et al., 2006). Plant species indirectly control soil nitrification or denitrification by altering the main environmental variables affecting nitrifiers and denitrifiers, i.e. NH<sub>4</sub><sup>+</sup> (Bengtsson et al., 2003) and NO<sub>3</sub><sup>-</sup> availability (Britto and Kronzucker; Norton and Firestone, 1996; Stark

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and Hart, 1997; Ashton et al., 2010; Bardon et al., 2018), organic C availability (Berks et al., 1995), pH (Hobbie et al., 2007), soil moisture (Le Roux et al., 2013) and oxygen availability (Verstraete and Focht, 1977). In addition, some plant species directly inhibit nitrifiers (i.e. biological nitrification inhibition, BNI; Jordan et al., 1979; Paavolainen et al., 1998; Lata et al., 1999; Subbarao et al., 2006) or denitrifiers (i.e. biological denitrification inhibition, BDI; Bardon et al., 2014, 2018) through the release of specific compounds to the soil via plant litter or root exudation. For instance, Subbarao et al. (2012) identified sakuranetin and sorgoleone as compounds responsible for BNI in sorghum. These mechanisms are of high importance mainly in ecosystems with low soil N availability as they minimize N losses and allow plants to effectively utilize the scarce N resource (Vitousek and Sanford, 2003; Boudsocq et al., 2009).

Although BNI has been already observed in different ecosystems (Subbarao et al., 2006; Srikanthasamy et al., 2018), the underlying mechanisms have been identified only for a few perennial grass species, e.g. *Brachiaria* spp., *Andropogon* spp., and *Hyparrhenia diplandra* (Lata et al., 1999, 2004; Subbarao et al., 2009), as well as cultivated sorghum (Subbarao et al., 2012) and rice (Sun et al., 2016). In forest ecosystems, very low nitrification rates can occur in stands of particular tree species (Lodhi and Killingbeck, 1980; Degrange et al., 1998), presumably due to the production of species-specific secondary metabolites including phenolics, alkaloids and terpenoids (Northup et al., 1995; Erikson et al., 2000; Castaldi et al., 2008; Smolander et al., 2012). However, evidence for direct BNI in forest ecosystems is
and Hart, 1997; Ashton et al., 2010; Bardon et al., 2018), organic C availability (Berks et al., 1995), pH (Hobbie et al., 2007), soil moisture (Le Roux et al., 2013) and oxygen availability (Verstraete and Focht, 1977). In addition, some plant species directly inhibit nitrifiers (i.e. biological nitrification inhibition, BNI; Jordan et al., 1979; Paavolainen et al., 1998; Lata et al., 1999; Subbarao et al., 2006) or denitrifiers (i.e. biological denitrification inhibition, BDI; Bardon et al., 2014, 2018) through the release of specific compounds to the soil via plant litter or root exudation. For instance, Subbarao et al. (2012) identified sakuranetin and sorgoleone as compounds responsible for BNI in sorghum. These mechanisms are of high importance mainly in ecosystems with low soil N availability as they minimize N losses and allow plants to effectively utilize the scarce N resource (Vitousek and Sanford, 2003; Boudsocq et al., 2009).

Although BNI has been already observed in different ecosystems (Subbarao et al., 2006; Srikanthasamy et al., 2018), the underlying mechanisms have been identified only for a few perennial grass species, e.g. *Brachiaria* spp., *Andropogon* spp., and *Hyparrhenia diplandra* (Lata et al., 1999, 2004; Subbarao et al., 2009), as well as cultivated sorghum (Subbarao et al., 2012) and rice (Sun et al., 2016). In forest ecosystems, very low nitrification rates can occur in stands of particular tree species (Lodhi and Killingbeck, 1980; Degrange et al., 1998), presumably due to the production of species-specific secondary metabolites including phenolics, alkaloids and terpenoids (Northup et al., 1995; Erikson et al., 2000; Castaldi et al., 2008; Smolander et al., 2012). However, evidence for direct BNI in forest ecosystems is
scarce to date. Both litter and root exudates seem to be important sources of BNI compounds in forest soils (Castaldi *et al.*, 2008). BNI exerted by monoterpenes produced by roots was observed in soils under Norway spruce stands, although indirect nitrification inhibition through N immobilization could not be excluded (Paavolainen *et al.*, 1998). Caffeic acid, chlorogenic acid and ferulic acid from *Quercus* spp. and *Pinus* spp. soil suspensions strongly inhibited the growth of *Nitrosomonas* but only marginally *Nitrobacter* model strains (Lodhi and Killingbeck, 1980; Rice and Pancholy, 2006).

To date, most of BNI compounds (generally produced by grass species) are known to inhibit ammonia monooxygenases (AMO) which catalyses $NH_4^+$ oxidation to $NH_2OH$, and some of them can effectively block the hydroxylamino-oxidoreductases (HAO) which is responsible for the second step of ammonia oxidation, namely the oxidation of $NH_2OH$ to $NO_2^-$ (Coskun *et al.*, 2017). Since $NH_4^+$ oxidation is traditionally assumed as the limiting-step of nitrification (Stevenson and Schmidt, 1982), the majority of studies analysing the BNI effect were conducted on AOA and AOB and did not take into account possible effects on $NO_2^-$ oxidoreductase (NXR) and more generally on NOB (but see Lodhi and Ruess, 1988) as well as on the recently discovered comammox bacteria.

Here we evaluated how different temperate forest tree species can biologically control soil nitrifier activity by using a 3-step approach (Fig. 1). First, we compared the enzyme activities and abundances of nitrifiers (AOB, AOA, *Nitrospira*, *Nitrobacter* and Comammox from clades A and B), along with environmental
scarce to date. Both litter and root exudates seem to be important sources of BNI compounds in forest soils (Castaldi *et al.*, 2008). BNI exerted by monoterpenes produced by roots was observed in soils under Norway spruce stands, although indirect nitrification inhibition through N immobilization could not be excluded (Paavolainen *et al.*, 1998). Caffeic acid, chlorogenic acid and ferulic acid from *Quercus* spp. and *Pinus* spp. soil suspensions strongly inhibited the growth of *Nitrosomonas* but only marginally *Nitrobacter* model strains (Lodhi and Killingbeck, 1980; Rice and Pancholy, 2006).

To date, most of BNI compounds (generally produced by grass species) are known to inhibit ammonia monooxygenases (AMO) which catalyses $NH_4^+$ oxidation to $NH_2OH$, and some of them can effectively block the hydroxylamino-oxidoreductases (HAO) which is responsible for the second step of ammonia oxidation, namely the oxidation of $NH_2OH$ to $NO_2^-$ (Coskun *et al.*, 2017). Since $NH_4^+$ oxidation is traditionally assumed as the limiting-step of nitrification (Stevenson and Schmidt, 1982), the majority of studies analysing the BNI effect were conducted on AOA and AOB and did not take into account possible effects on $NO_2^-$ oxidoreductase (NXR) and more generally on NOB (but see Lodhi and Ruess, 1988) as well as on the recently discovered comammox bacteria.

Here we evaluated how different temperate forest tree species can biologically control soil nitrifier activity by using a 3-step approach (Fig. 1). First, we compared the enzyme activities and abundances of nitrifiers (AOB, AOA, *Nitrospira*, *Nitrobacter* and Comammox from clades A and B), along with environmental

<figure><img src="image_4.png" /></figure>
conditions (moisture, mineral N concentrations and pH) between soils from 28-year-
old monoculture stands (5 tree species) plus native forest. We assumed that AOA and
*Nitrospira* abundances would be correlated with nitrification rates in these soils, as
these groups are often reported to be better adapted than AOB and *Nitrobacter* to low
N substrate levels and low pH values in soil (Hatzenpichler, 2012; Le Roux et al.,
2016). We also assumed that commamox bacteria might have an important role in
nitrification, as their presence has been revealed in numerous environments (Daims et
al., 2015; Van Kessel et al., 2015), including forest soils (Pjevac et al., 2017). Second,
we used a reciprocal soil core transplantation approach between low- and high-
nitrification plots, i.e. putative BNI- and non BNI-tree species, respectively. The
objective was to analyse the kinetics of changes in nitrifier activity and abundance in
soils 16 and 28 months after transplantation. We assumed that soil cores transplanted
from putative BNI- to non BNI-species would experience a release from inhibition,
thus resulting in increased nitrifier abundance and activity. Conversely, we assumed
that soil cores transplanted from putative non-BNI- to BNI-species would face
inhibition, thus resulting in decreased nitrifier abundance and activity. More
particularly, we expected AOA abundance to respond rapidly to this second type of
transplantation assuming that BNI compounds would affect ammonia oxidizers rather
than nitrite oxidizers. We also assumed that *Nitrospira* abundance would follow
changes in AOA abundance as a result of changes in substrate availability. Third, to
test whether low nitrification rates were due to the production of specific plant
secondary metabolites, we incubated litter or soil extracts from BNI-tree species with a
conditions (moisture, mineral N concentrations and pH) between soils from 28-year-
old monoculture stands (5 tree species) plus native forest. We assumed that AOA and
*Nitrospira* abundances would be correlated with nitrification rates in these soils, as
these groups are often reported to be better adapted than AOB and *Nitrobacter* to low
N substrate levels and low pH values in soil (Hatzenpichler, 2012; Le Roux et al.,
2016). We also assumed that commamox bacteria might have an important role in
nitrification, as their presence has been revealed in numerous environments (Daims et
al., 2015; Van Kessel et al., 2015), including forest soils (Pjevac et al., 2017). Second,
we used a reciprocal soil core transplantation approach between low- and high-
nitrification plots, i.e. putative BNI- and non BNI-tree species, respectively. The
objective was to analyse the kinetics of changes in nitrifier activity and abundance in
soils 16 and 28 months after transplantation. We assumed that soil cores transplanted
from putative BNI- to non BNI-species would experience a release from inhibition,
thus resulting in increased nitrifier abundance and activity. Conversely, we assumed
that soil cores transplanted from putative non-BNI- to BNI-species would face
inhibition, thus resulting in decreased nitrifier abundance and activity. More
particularly, we expected AOA abundance to respond rapidly to this second type of
transplantation assuming that BNI compounds would affect ammonia oxidizers rather
than nitrite oxidizers. We also assumed that *Nitrospira* abundance would follow
changes in AOA abundance as a result of changes in substrate availability. Third, to
test whether low nitrification rates were due to the production of specific plant
secondary metabolites, we incubated litter or soil extracts from BNI-tree species with a
strain chosen from the nitrifier group found as the most sensitive to BNI, and we
measured its growth to more directly demonstrate the actual BNI capacity of the tree
species associated to low soil nitrification rates. Our results jeopardize the classical
belief that AOA would be the main nitrifiers targeted by BNI in these forest
ecosystems.

Results

Relationships between nitrification and nitrifier abundances among the 28 year-
old plots

In the 28 year-old plots, net nitrification and nitrifying enzyme activity (NEA, i.e. potential nitrification) were strongly and positively correlated (R²=0.90, p=0.039), with very similar values observed for both net and potential rates (Fig. S1). Soil nitrification strongly differed between tree species, with highest values around 0.05 µg-N h⁻¹ g⁻¹ soil observed for *P. nigra*, *P. menziesii* and *F. sylvatica*, and values lower than 0.01 µg-N h⁻¹ g⁻¹ soil observed for *P. abies*, *A. nordmanniana* and the native forest (Fig. 2 and S2). No relationship was observed between soil nitrification and soil pH (Fig. S3). For the 3 low nitrification plots (L), net mineralisation was much higher than net nitrification, i.e. nitrification was low despite the availability of NH₄⁺ (Fig. S2). For 2 of the 3 high nitrification plots (H), net nitrification was similar to net mineralisation, i.e. all the NH₄⁺ formed was converted into NO₃⁻ (Fig. S2).

Accepted Article
strain chosen from the nitrifier group found as the most sensitive to BNI, and we
measured its growth to more directly demonstrate the actual BNI capacity of the tree
species associated to low soil nitrification rates. Our results jeopardize the classical
belief that AOA would be the main nitrifiers targeted by BNI in these forest
ecosystems.

## Results

Relationships between nitrification and nitrifier abundances among the 28 year-
old plots

In the 28 year-old plots, net nitrification and nitrifying enzyme activity (NEA, i.e.
potential nitrification) were strongly and positively correlated (R²=0.90, p=0.039),
with very similar values observed for both net and potential rates (Fig. S1). Soil
nitrification strongly differed between tree species, with highest values around 0.05
µg-N h⁻¹ g⁻¹ soil observed for *P. nigra*, *P. menziesii* and *F. sylvatica*, and values lower
than 0.01 µg-N h⁻¹ g⁻¹ soil observed for *P. abies*, *A. nordmanniana* and the native
forest (Fig. 2 and S2). No relationship was observed between soil nitrification and soil
pH (Fig. S3). For the 3 low nitrification plots (L), net mineralisation was much higher
than net nitrification, i.e. nitrification was low despite the availability of NH₄⁺ (Fig.
S2). For 2 of the 3 high nitrification plots (H), net nitrification was similar to net
mineralisation, i.e. all the NH₄⁺ formed was converted into NO₃⁻ (Fig. S2).

Accepted Article
Differences in NEA across all stands were significantly and positively correlated to changes in the abundances of AOA and *Nitrobacter* (p=0.0113, R²=0.83 and p=0.0009, R²=0.95, respectively; Fig. 2, Top and middle left, respectively). However, differences in *Nitrobacter* abundance were particularly high (from 10³ *nxrA* copies g⁻¹ soil in the plot with the lowest NEA, up to 6 x 10⁵ *nxrA* copies g⁻¹ soil in the plot with the highest NEA) and the correlation between NEA and *Nitrobacter* abundance was particularly strong. In contrast, AOA abundance (from 6 x 10⁵ to 10⁶ *amoA* copies g⁻¹ soil) did not significantly change between plots. No significant relationship was observed between NEA and the abundances of AOB, *Nitrospira* or Comammox from clades A and B (Fig. 2). Because net nitrification and NEA values were similar (Fig. S1), the same (lack of) relationships hold when considering net nitrification (not shown).

Relationships between changes in nitrification and changes in AOA and
*Nitrobacter* abundances following soil core transplantation

Sixteen months after the soil core transplantation, net nitrification in the cores
originating from one of the high nitrification (H) plots and transplanted to one of the
low nitrification (L) plots, i.e. HL treatment, did not differ from nitrification in HH
cores (Fig. 3). In contrast, net nitrification in LH cores was significantly higher than in
LL cores (Fig. 3). However, nitrification for the LH treatment remained lower than for
the HH treatment. Twenty-eight months after the soil core transplantation, net
nitrification in the HL cores was significantly lower than in the HH cores, although it
Differences in NEA across all stands were significantly and positively correlated to changes in the abundances of AOA and *Nitrobacter* (p=0.0113, R²=0.83 and p=0.0009, R²=0.95, respectively; Fig. 2, Top and middle left, respectively). However, differences in *Nitrobacter* abundance were particularly high (from 10³ *nxrA* copies g⁻¹ soil in the plot with the lowest NEA, up to 6 x 10⁵ *nxrA* copies g⁻¹ soil in the plot with the highest NEA) and the correlation between NEA and *Nitrobacter* abundance was particularly strong. In contrast, AOA abundance (from 6 x 10⁵ to 10⁶ *amoA* copies g⁻¹ soil) did not significantly change between plots. No significant relationship was observed between NEA and the abundances of AOB, *Nitrospira* or Comammox from clades A and B (Fig. 2). Because net nitrification and NEA values were similar (Fig. S1), the same (lack of) relationships hold when considering net nitrification (not shown).

**Relationships between changes in nitrification and changes in AOA and Nitrobacter abundances following soil core transplantation**

Sixteen months after the soil core transplantation, net nitrification in the cores originating from one of the high nitrification (H) plots and transplanted to one of the low nitrification (L) plots, i.e. HL treatment, did not differ from nitrification in HH cores (Fig. 3). In contrast, net nitrification in LH cores was significantly higher than in LL cores (Fig. 3). However, nitrification for the LH treatment remained lower than for the HH treatment. Twenty-eight months after the soil core transplantation, net nitrification in the HL cores was significantly lower than in the HH cores, although it

Accepted Article
remained higher than nitrification in the LL cores (Fig. 3). Net nitrification was much higher in the LH than in LL cores and not significantly different from nitrification in the HH cores (Fig. S4).

Sixteen months after the soil core transplantation, nitrification was strongly correlated to the abundance of *Nitrobacter* but only weakly correlated to the abundance of AOA (p<0.0001, R²=0.80 and p=0.046, R²=0.34, respectively; Fig. 4, top). In particular, the increase in nitrification observed for LH treatment was strongly linked to an increase in the abundance of *Nitrobacter*, whereas AOA abundance did not increase (Fig. 4). After 28 months, nitrification was well correlated to the abundances of AOA and *Nitrobacter* (p=0.0006, R²=0.71 and p=0.0002, R²=0.78, respectively; Fig. 4, bottom).

## Effects of soil and litter extracts from low nitrification stands on the growth of a model *Nitrobacter* strain

All the extracts of soil and litter from the low nitrification *P. abies* and *A. nordmanniana* plots decreased the growth of the nitrite-oxidizing strain *Nitrobacter hamburgensis* X14 (Fig. 5). The growth inhibition was strongly linked to the extract type, i.e. litter or root exudates (p<0.001), with a low effect of the extract concentration (p=0.032). The extracts from the litter derived from *A. nordmanniana* plots induced a decrease in *N. hamburgensis* growth of around -12% without any effect of extract concentration (Fig. 5, right). The extracts derived from the soil of plots grown with *A. nordmanniana* induced a decrease in *N. hamburgensis* growth of
remained higher than nitrification in the LL cores (Fig. 3). Net nitrification was much higher in the LH than in LL cores and not significantly different from nitrification in the HH cores (Fig. S4).

Sixteen months after the soil core transplantation, nitrification was strongly correlated to the abundance of *Nitrobacter* but only weakly correlated to the abundance of AOA (p<0.0001, R²=0.80 and p=0.046, R²=0.34, respectively; Fig. 4, top). In particular, the increase in nitrification observed for LH treatment was strongly linked to an increase in the abundance of *Nitrobacter*, whereas AOA abundance did not increase (Fig. 4). After 28 months, nitrification was well correlated to the abundances of AOA and *Nitrobacter* (p=0.0006, R²=0.71 and p=0.0002, R²=0.78, respectively; Fig. 4, bottom).

## Effects of soil and litter extracts from low nitrification stands on the growth of a model *Nitrobacter* strain

All the extracts of soil and litter from the low nitrification *P. abies* and *A. nordmanniana* plots decreased the growth of the nitrite-oxidizing strain *Nitrobacter hamburgensis* X14 (Fig. 5). The growth inhibition was strongly linked to the extract type, i.e. litter or root exudates (p<0.001), with a low effect of the extract concentration (p=0.032). The extracts from the litter derived from *A. nordmanniana* plots induced a decrease in *N. hamburgensis* growth of around -12% without any effect of extract concentration (Fig. 5, right). The extracts derived from the soil of plots grown with *A. nordmanniana* induced a decrease in *N. hamburgensis* growth of

Accepted Article
around -16% and -26% for the lowest and highest extract concentration, respectively (Fig. 5, right). The extracts from both the litter and soil derived from *P. abies* plots induced a decrease in *N. hamburgensis* growth of -25 to -31%, respectively, without any significant effect of extract concentration (Fig. 5, left).

Discussion

Tree species effects on soil nitrification in old stands are mostly correlated to
changes in *Nitrobacter* abundance

As previously reported (Moukoumi *et al.*, 2006; Zeller *et al.*, 2007; Andrianarisoa *et al.*, 2010), forest tree species strongly influenced soil nitrification. In the long term, here after 28 years, *P. abies*, *A. nordmanniana* and the native forest were associated with potential and net nitrification rates 10- to 1000-fold lower than the rates associated to *P. nigra*, *P. menziesii* and *F. sylvatica*. The differences between high and low nitrification stands were higher than within stand variations in nitrifier activity and abundances, and sampling a few soil cores per stand was adequate to capture within stand variability. This is likely due to the fact that in forest ecosystems one soil core includes roots from several tree individuals in relation to large horizontal root extension (e.g. Meinen *et al.*, 2009). Here, we demonstrated that these contrasted nitrification rates were correlated to the size of particular ammonia- and nitrite-oxidizing groups. Nitrification rates were not correlated to the abundances of AOB. In contrast, nitrification rates in the forest soils studied were significantly correlated to

<figure><img src="image_1.png" /></figure>
around -16% and -26% for the lowest and highest extract concentration, respectively (Fig. 5, right). The extracts from both the litter and soil derived from *P. abies* plots induced a decrease in *N. hamburgensis* growth of -25 to -31%, respectively, without any significant effect of extract concentration (Fig. 5, left).

Discussion

Tree species effects on soil nitrification in old stands are mostly correlated to
changes in *Nitrobacter* abundance

As previously reported (Moukoumi *et al.*, 2006; Zeller *et al.*, 2007; Andrianarisoa *et al.*, 2010), forest tree species strongly influenced soil nitrification. In the long term, here after 28 years, *P. abies*, *A. nordmanniana* and the native forest were associated with potential and net nitrification rates 10- to 1000-fold lower than the rates associated to *P. nigra*, *P. menziesii* and *F. sylvatica*. The differences between high and low nitrification stands were higher than within stand variations in nitrifier activity and abundances, and sampling a few soil cores per stand was adequate to capture within stand variability. This is likely due to the fact that in forest ecosystems one soil core includes roots from several tree individuals in relation to large horizontal root extension (e.g. Meinen *et al.*, 2009). Here, we demonstrated that these contrasted nitrification rates were correlated to the size of particular ammonia- and nitrite-oxidizing groups. Nitrification rates were not correlated to the abundances of AOB. In contrast, nitrification rates in the forest soils studied were significantly correlated to

Accepted Article
AOA abundances. This appears to be consistent with a large body of literature suggesting that AOA would be the main players of nitrification in forest soils (Stopnišek et al., 2010; Zhang et al., 2012). This would be due to better adaptation of AOA than AOB to low N-substrate availability and low pH, which are common conditions for forest soils (Verhamme et al., 2011; He et al., 2012; Hu et al., 2015). However, our results indicated that the abundances of AOA and AOB were similar in the studied soils, i.e. $5.77 \times 10^5$ and $5.58 \times 10^5$ copies g$^{-1}$ dry soil on average, respectively. This finding is in contrast with several studies reporting higher abundances of AOA than AOB in forest soils (Szukics et al., 2010; Yao et al., 2011; Stempfhuber et al., 2017; but see Wertz et al., 2012; Zhang et al., 2012). In addition, AOA abundances varied only by 8-fold while nitrification rates showed 100- to 1000-fold changes. Further, the low nitrification rates were observed despite high abundances of both AOA and AOB and rather high ammonification rates similar to those observed in high nitrification plots (Fig. S2), and were not explained by soil pH values (Fig. S3). All these results are thus not consistent with a tree species effect on nitrification mostly mediated by an effect on ammonia oxidizers, pH and/or N availability.

Concurrently, nitrification rates in soils of the 28-year-old stands were strongly correlated to the abundance of *Nitrobacter*, but not *Nitrospira*, although higher abundances were found for *Nitrospira* compared to *Nitrobacter*. Similarly, it has been shown that despite higher *Nitrospira* abundances, nitrification rates were mostly related to *Nitrobacter* abundances in agricultural (Attard et al., 2010) and grassland

<figure><img src="image_2.png" /></figure>
AOA abundances. This appears to be consistent with a large body of literature suggesting that AOA would be the main players of nitrification in forest soils (Stopnišek et al., 2010; Zhang et al., 2012). This would be due to better adaptation of AOA than AOB to low N-substrate availability and low pH, which are common conditions for forest soils (Verhamme et al., 2011; He et al., 2012; Hu et al., 2015). However, our results indicated that the abundances of AOA and AOB were similar in the studied soils, i.e. $5.77 \times 10^5$ and $5.58 \times 10^5$ copies g$^{-1}$ dry soil on average, respectively. This finding is in contrast with several studies reporting higher abundances of AOA than AOB in forest soils (Szukics et al., 2010; Yao et al., 2011; Stempfhuber et al., 2017; but see Wertz et al., 2012; Zhang et al., 2012). In addition, AOA abundances varied only by 8-fold while nitrification rates showed 100- to 1000-fold changes. Further, the low nitrification rates were observed despite high abundances of both AOA and AOB and rather high ammonification rates similar to those observed in high nitrification plots (Fig. S2), and were not explained by soil pH values (Fig. S3). All these results are thus not consistent with a tree species effect on nitrification mostly mediated by an effect on ammonia oxidizers, pH and/or N availability.

Concurrently, nitrification rates in soils of the 28-year-old stands were strongly correlated to the abundance of *Nitrobacter*, but not *Nitrospira*, although higher abundances were found for *Nitrospira* compared to *Nitrobacter*. Similarly, it has been shown that despite higher *Nitrospira* abundances, nitrification rates were mostly related to *Nitrobacter* abundances in agricultural (Attard et al., 2010) and grassland

<figure><img src="image_5.png" /></figure>
soils (Le Roux et al., 2016). Thus, although the abundances of *Nitrospira* are often higher than *Nitrobacter* in forest soils, as observed here and as reported for soils under beech, spruce and pine (Wertz et al., 2012; Stempfhuber et al., 2017), our results suggest that *Nitrobacter* may have a more prominent role in nitrification. More specifically, *Nitrobacter* abundances showed 100- to 1000-fold changes (from 4.12 x 10² to 3.62 x 10⁶ copies g⁻¹ dry soil, respectively) in parallel to the 100- to 1000-fold changes in nitrification rates. This means that in plots with no nitrification, high abundances of AOA, AOB and *Nitrospira*—along with high mineralization rates—were still observed, whereas only *Nitrobacter* abundances were strongly reduced. Furthermore, nitrification rates were not correlated to the abundances of neither Comammox clade A nor Comammox clade B. It has been suggested that comammox organisms may outcompete other nitrifier groups in acidic (Shi et al., 2018) and substrate-limited environments (Kits et al., 2017). However, little is known on the actual role of comammox on nitrification in forest ecosystems (but see Wang et al., 2019).

As ammonia oxidation is often assumed to be the rate-limiting step of nitrification, the majority of the studies published in the last decades have focused on ammonia oxidizers to better understand changes in nitrification rates, overlooking the possible importance of nitrite oxidizers. Hence, little information is available on the importance of NOB for determining nitrification rates in forest ecosystems. In addition, co-occurrences (relationships between abundances) of AOA and *Nitrospira* on the one hand, and of AOB and *Nitrobacter* on the other hand, have been previously

Accepted Article
soils (Le Roux et al., 2016). Thus, although the abundances of *Nitrospira* are often higher than *Nitrobacter* in forest soils, as observed here and as reported for soils under beech, spruce and pine (Wertz et al., 2012; Stempfhuber et al., 2017), our results suggest that *Nitrobacter* may have a more prominent role in nitrification. More specifically, *Nitrobacter* abundances showed 100- to 1000-fold changes (from 4.12 x 10² to 3.62 x 10⁶ copies g⁻¹ dry soil, respectively) in parallel to the 100- to 1000-fold changes in nitrification rates. This means that in plots with no nitrification, high abundances of AOA, AOB and *Nitrospira*—along with high mineralization rates—were still observed, whereas only *Nitrobacter* abundances were strongly reduced. Furthermore, nitrification rates were not correlated to the abundances of neither Comammox clade A nor Comammox clade B. It has been suggested that comammox organisms may outcompete other nitrifier groups in acidic (Shi et al., 2018) and substrate-limited environments (Kits et al., 2017). However, little is known on the actual role of comammox on nitrification in forest ecosystems (but see Wang et al., 2019).

As ammonia oxidation is often assumed to be the rate-limiting step of nitrification, the majority of the studies published in the last decades have focused on ammonia oxidizers to better understand changes in nitrification rates, overlooking the possible importance of nitrite oxidizers. Hence, little information is available on the importance of NOB for determining nitrification rates in forest ecosystems. In addition, co-occurrences (relationships between abundances) of AOA and *Nitrospira* on the one hand, and of AOB and *Nitrobacter* on the other hand, have been previously

Accepted Article
reported for forest (Stempfhuber *et al.*, 2017), grassland (Ma *et al.*, 2016) and
agricultural soils (Assémien *et al.*, 2017). This is traditionally explained by the fact
that NO₂⁻ availability would be the main driver of niche partitioning between these
groups, AOB and *Nitrobacter* being favoured under high N availability (Attard *et al.*,
2010). Here we did neither observe a strong correlation between the abundances of
*Nitrobacter* and AOB or AOA, nor a relationship between *Nitrobacter* abundances and
mineralization rates. These results strongly suggest that (i) *Nitrobacter* was the main
nitrifier group restricting nitrification rates in low nitrification plots, and (ii) soil N
availability and pH were not the main drivers of *Nitrobacter* abundances and
consequently of nitrification.

Dynamics of nitrifier activity and abundances following soil core transplantation further suggests tree control of nitrification through *Nitrobacter* rather than AOA

Reciprocal transplantation of soil cores has already been used to investigate the effects
of abiotic and biotic drivers on nitrifiers in situ (Bottomley et al., 2004; Reed and
Martiny, 2007; Kageyama et al., 2013), and it has been shown that nitrifiers have the
capacity to respond to changes in soil environmental conditions over a few weeks or
months (Le Roux et al., 2008). For instance, complete resilience of AOB abundance
has been observed 2 years after a soil core transplantation experiment (Bottomley et
al., 2004). Here, the transplantation of soil cores amongst stands of different forest tree
species allowed a better identification of the nitrifier group(s) mostly sensitive to tree
species influence and determining nitrification rates. Assuming that the first step of
reported for forest (Stempfhuber et al., 2017), grassland (Ma et al., 2016) and
agricultural soils (Assémien et al., 2017). This is traditionally explained by the fact
that NO₂⁻ availability would be the main driver of niche partitioning between these
groups, AOB and *Nitrobacter* being favoured under high N availability (Attard et al.,
2010). Here we did neither observe a strong correlation between the abundances of
*Nitrobacter* and AOB or AOA, nor a relationship between *Nitrobacter* abundances and
mineralization rates. These results strongly suggest that (i) *Nitrobacter* was the main
nitrifier group restricting nitrification rates in low nitrification plots, and (ii) soil N
availability and pH were not the main drivers of *Nitrobacter* abundances and
consequently of nitrification.

Dynamics of nitrifier activity and abundances following soil core transplantation
further suggests tree control of nitrification through *Nitrobacter* rather than AOA

Reciprocal transplantation of soil cores has already been used to investigate the effects of abiotic and biotic drivers on nitrifiers in situ (Bottomley et al., 2004; Reed and Martiny, 2007; Kageyama et al., 2013), and it has been shown that nitrifiers have the capacity to respond to changes in soil environmental conditions over a few weeks or months (Le Roux et al., 2008). For instance, complete resilience of AOB abundance has been observed 2 years after a soil core transplantation experiment (Bottomley et al., 2004). Here, the transplantation of soil cores amongst stands of different forest tree species allowed a better identification of the nitrifier group(s) mostly sensitive to tree species influence and determining nitrification rates. Assuming that the first step of
nitrification would be the limiting one as commonly accepted, and that AOA would be
the main functional players for nitrification in these forest soils as previously
suggested (Stempfhuber et al., 2017), we expected that soil core transplantation from
low (L) to high (H) nitrification plots, i.e. LH treatment, would first result in increased
AOA abundance, and then in subsequent increased NOB abundance due to an increase
in their substrate availability (De Boer, et al., 1991). Unexpectedly, our results showed
that the LH treatment first led to an increase in *Nitrobacter* abundance in parallel to
the observed increase in nitrification after 16 months, whereas no change in AOA
abundance was observed. Only 28 months after the LH transplantation, an increase
was also observed for AOA abundance. Overall, after 16 months, nitrification rates
were strongly correlated to *Nitrobacter* abundances but only weakly to AOA
abundances. This strongly suggests that *Nitrobacter* rather than AOA were the main
nitrifier group restricting nitrification in low nitrification (L) plots, and that the driver
of low *Nitrobacter* abundances in L plots was quickly released in H plots.

Interestingly, the responses of nitrification activity and both *Nitrobacter* and AOA abundances were slower for transplantation of soil cores from H to L plots than for the reverse LH treatment, a decrease in potential nitrification being observed only 28 months after HL transplantation. Similar asymmetric changes in nitrification rates and ammonia oxidizer abundances have been observed for grassland soils exposed to reversion of management (Le Roux *et al.*, 2008). Given that tree roots were cut when establishing the core transplantation experiment, one possibility is that the results of the soil core transplantation experiment would be due to a strong biological control of
nitrification would be the limiting one as commonly accepted, and that AOA would be
the main functional players for nitrification in these forest soils as previously
suggested (Stempfhuber et al., 2017), we expected that soil core transplantation from
low (L) to high (H) nitrification plots, i.e. LH treatment, would first result in increased
AOA abundance, and then in subsequent increased NOB abundance due to an increase
in their substrate availability (De Boer, et al., 1991). Unexpectedly, our results showed
that the LH treatment first led to an increase in *Nitrobacter* abundance in parallel to
the observed increase in nitrification after 16 months, whereas no change in AOA
abundance was observed. Only 28 months after the LH transplantation, an increase
was also observed for AOA abundance. Overall, after 16 months, nitrification rates
were strongly correlated to *Nitrobacter* abundances but only weakly to AOA
abundances. This strongly suggests that *Nitrobacter* rather than AOA were the main
nitrifier group restricting nitrification in low nitrification (L) plots, and that the driver
of low *Nitrobacter* abundances in L plots was quickly released in H plots.

Interestingly, the responses of nitrification activity and both *Nitrobacter* and
AOA abundances were slower for transplantation of soil cores from H to L plots than
for the reverse LH treatment, a decrease in potential nitrification being observed only
28 months after HL transplantation. Similar asymmetric changes in nitrification rates
and ammonia oxidizer abundances have been observed for grassland soils exposed to
reversion of management (Le Roux *et al.*, 2008). Given that tree roots were cut when
establishing the core transplantation experiment, one possibility is that the results of
the soil core transplantation experiment would be due to a strong biological control of

<figure><img src="image_6.png" /></figure>
*Nitrobacter* by roots. For LH treatments, cutting roots of trees that initially prescribed low nitrification rates, possibly through specific compounds, may have quickly relapsed this control depending, e.g. on the stability of the specific compounds involved. This could explain why a rather fast increase in *Nitrobacter* abundances was observed for LH treatments. In contrast, after establishment of HL cores, time would be needed for a sufficient colonization of soil cores by roots of the tree species able to inhibit *Nitrobacter*. However, this possible biological inhibition of *Nitrobacter* by specific compounds associated to some tree species required to be evaluated, which we tested through the laboratory experiment (without identifying any specific compounds).

**Evidence that some tree species can inhibit *Nitrobacter***

Low pH and low N availability, typical for most forest (He *et al.*, 2012; Hu *et al.*, 2015), heathland (Bardon *et al.*, 2018) and humid savanna ecosystems (Le Roux *et al.*, 1995), harbor selected plants with diverse mechanisms for improving soil N availability (Chapman *et al.*, 2006). In particular, it has been shown that some plant species in these ecosystems can inhibit nitrifiers (Lata *et al.*, 2004; Subbarao *et al.*, 2009; Srikanthasamy *et al.*, 2018) and that this inhibition is due to the production of specific compounds, often by roots (Subbarao *et al.*, 2006, 2015; Coskun *et al.*, 2017). However, most plants previously identified as having a biological nitrification inhibition (BNI) capacity were grass species. Further, previous studies have reported that these species inhibited ammonia oxidizers, generally AOB (Subbarao *et al.*,
*Nitrobacter* by roots. For LH treatments, cutting roots of trees that initially prescribed low nitrification rates, possibly through specific compounds, may have quickly relapsed this control depending, e.g. on the stability of the specific compounds involved. This could explain why a rather fast increase in *Nitrobacter* abundances was observed for LH treatments. In contrast, after establishment of HL cores, time would be needed for a sufficient colonization of soil cores by roots of the tree species able to inhibit *Nitrobacter*. However, this possible biological inhibition of *Nitrobacter* by specific compounds associated to some tree species required to be evaluated, which we tested through the laboratory experiment (without identifying any specific compounds).

**Evidence that some tree species can inhibit *Nitrobacter***

Low pH and low N availability, typical for most forest (He *et al.*, 2012; Hu *et al.*, 2015), heathland (Bardon *et al.*, 2018) and humid savanna ecosystems (Le Roux *et al.*, 1995), harbor selected plants with diverse mechanisms for improving soil N availability (Chapman *et al.*, 2006). In particular, it has been shown that some plant species in these ecosystems can inhibit nitrifiers (Lata *et al.*, 2004; Subbarao *et al.*, 2009; Srikanthasamy *et al.*, 2018) and that this inhibition is due to the production of specific compounds, often by roots (Subbarao *et al.*, 2006, 2015; Coskun *et al.*, 2017). However, most plants previously identified as having a biological nitrification inhibition (BNI) capacity were grass species. Further, previous studies have reported that these species inhibited ammonia oxidizers, generally AOB (Subbarao *et al.*,
2012). Here, we cannot exclude that ammonia oxidizer populations were affected by BNI, as most of the nitrification inhibitors are bacteriostatic and not bactericidal (Amberger, 1989; Rodgers and Ashworth, 2011). This could be further explored in future research by determining to what extent AOB and AOA populations are functional using RNA-based approaches. However, the present study demonstrates for the first time a BNI capacity for tree species inducing inhibition of *Nitrobacter*. Indeed, our results clearly show that soil and litter extracts from spruce and Nordmann fir effectively inhibited the growth of the NOB strain *N. hamburgensis*. We have used *N. hamburgensis* as it is one of the few species of *Nitrobacter* isolated from soil for which the level of knowledge regarding its ecophysiology and ecology is very good, but further studies will be needed to detail BNI effects on a higher number of strains and species. The higher inhibition observed after incubation with soil rather than litter extracts from Nordmann fir suggests that this tree species might control *Nitrobacter* abundance and nitrification rates mainly through root exudation. In contrast, both soil and litter extracts from spruce were sources of BNI compounds. These findings thus demonstrate that the tree species associated to the lowest nitrification rates in situ can inhibit *Nitrobacter*, which explains the results obtained in the soil core transplantation experiment. Accordingly, NO₂⁻ accumulation in soil could be expected in soils under BNI tree species, but NO₂⁻ concentration was below detection limit during the nitrification assays, except for a very few soil samples (not shown). As NO₂⁻ accumulation might lead to plant, animal and microbial toxicity (Van Cleemput and Samater, 1996), alternative metabolic pathways, i.e. nitrifier-denitrification (Wrage *et*
2012). Here, we cannot exclude that ammonia oxidizer populations were affected by BNI, as most of the nitrification inhibitors are bacteriostatic and not bactericidal (Amberger, 1989; Rodgers and Ashworth, 2011). This could be further explored in future research by determining to what extent AOB and AOA populations are functional using RNA-based approaches. However, the present study demonstrates for the first time a BNI capacity for tree species inducing inhibition of *Nitrobacter*. Indeed, our results clearly show that soil and litter extracts from spruce and Nordmann fir effectively inhibited the growth of the NOB strain *N. hamburgensis*. We have used *N. hamburgensis* as it is one of the few species of *Nitrobacter* isolated from soil for which the level of knowledge regarding its ecophysiology and ecology is very good, but further studies will be needed to detail BNI effects on a higher number of strains and species. The higher inhibition observed after incubation with soil rather than litter extracts from Nordmann fir suggests that this tree species might control *Nitrobacter* abundance and nitrification rates mainly through root exudation. In contrast, both soil and litter extracts from spruce were sources of BNI compounds. These findings thus demonstrate that the tree species associated to the lowest nitrification rates in situ can inhibit *Nitrobacter*, which explains the results obtained in the soil core transplantation experiment. Accordingly, NO₂⁻ accumulation in soil could be expected in soils under BNI tree species, but NO₂⁻ concentration was below detection limit during the nitrification assays, except for a very few soil samples (not shown). As NO₂⁻ accumulation might lead to plant, animal and microbial toxicity (Van Cleemput and Samater, 1996), alternative metabolic pathways, i.e. nitrifier-denitrification (Wrage *et*

Accepted Article
al., 2001), archaeal aerobic nirK-denitrification (Treusch et al., 2005), production of nitrous acid through $NO_2^-$ conversion (Su et al., 2011), and $NO_2^-$ incorporation into soil organic matter (Fitzhugh et al., 2003) might take place and explain lack of $NO_2^-$ accumulation.

The fast increase in *Nitrobacter* abundance 16 months after the LH transplantation suggests that the compounds responsible for BNI might be labile and might have been quickly degraded when roots of tree species with BNI capacity were cut and soil cores exposed to a new environment without BNI compound production. Consistently, some BNI molecules has been proved to lose their effectiveness after 100 days in soil (Subbarao *et al*., 2008). In contrast, following HL transplantation, the slower response of *Nitrobacter* abundance might be due to the progressive colonization of the soil cores by BNI tree species roots. BNI molecules released at low concentrations during the early stages of root colonization might not be sufficient to exert a strong inhibiting effect. Overall, our findings demonstrate that the tree species associated with low nitrification rates in *situ* had the capacity to inhibit *Nitrobacter*. Yet, identification of the compounds responsible for BNI was beyond the scope of this study and remains to be investigated. Further, we worked on composite from 3 samples for each plot and each soil layer. This is sufficient to demonstrate the existence of inhibitors and for a first characterization of their action on *Nitrobacter*, but a more extensive sampling would be needed to characterize the possible spatial and temporal variation in BNI in forest stands.

<figure><img src="image_3.png" /></figure>
al., 2001), archaeal aerobic nirK-denitrification (Treusch et al., 2005), production of nitrous acid through $NO_2^-$ conversion (Su et al., 2011), and $NO_2^-$ incorporation into soil organic matter (Fitzhugh et al., 2003) might take place and explain lack of $NO_2^-$ accumulation.

The fast increase in *Nitrobacter* abundance 16 months after the LH transplantation suggests that the compounds responsible for BNI might be labile and might have been quickly degraded when roots of tree species with BNI capacity were cut and soil cores exposed to a new environment without BNI compound production. Consistently, some BNI molecules has been proved to lose their effectiveness after 100 days in soil (Subbarao *et al.*, 2008). In contrast, following HL transplantation, the slower response of *Nitrobacter* abundance might be due to the progressive colonization of the soil cores by BNI tree species roots. BNI molecules released at low concentrations during the early stages of root colonization might not be sufficient to exert a strong inhibiting effect. Overall, our findings demonstrate that the tree species associated with low nitrification rates *in situ* had the capacity to inhibit *Nitrobacter*. Yet, identification of the compounds responsible for BNI was beyond the scope of this study and remains to be investigated. Further, we worked on composite from 3 samples for each plot and each soil layer. This is sufficient to demonstrate the existence of inhibitors and for a first characterization of their action on *Nitrobacter*, but a more extensive sampling would be needed to characterize the possible spatial and temporal variation in BNI in forest stands.
## Conclusion

It is increasingly recognised that many components of a plant's environment are determined by the plant itself, each plant individual shaping to some extent its own environment which ultimately influences its fitness (Schweitzer et al., 2004). This ecological-evolutionary feedback loop is called 'niche construction' (Lewontin and Lewontin, 2000; Odling-Smee et al., 2003). Plant niche construction abilities often concern plant-soil feedback loops (Schweitzer et al., 2013). In particular, it was known that some grass species adapted to low soil N availability were able to inhibit nitrification via the exudation of specific compounds inhibiting ammonia oxidizers, mostly AOB (Subbarao et al., 2009). Recently, Bardon et al. (2014, 2018) demonstrated that some forb and shrub species are able to inhibit denitrification, through the exudation of phenolic compounds by roots. Our results demonstrate for the first time that some tree species can also inhibit nitrification through knock out of the nitrite oxidizers *Nitrobacter*. This is an important breakthrough for understanding the range of plant-microorganisms interaction processes that underlie niche construction by plants growing in environments with low soil N availability.

## Material and methods

### Study site and soil sampling in 28 year-old plots

The study site is a long-term experimental site managed by INRA, located in the Breuil-Chenue forest ('SOERE F-OreT' site, Nièvre Morvan, France; 47°18'N and

Accepted Article
## Conclusion

It is increasingly recognised that many components of a plant's environment are determined by the plant itself, each plant individual shaping to some extent its own environment which ultimately influences its fitness (Schweitzer et al., 2004). This ecological-evolutionary feedback loop is called 'niche construction' (Lewontin and Lewontin, 2000; Odling-Smee et al., 2003). Plant niche construction abilities often concern plant-soil feedback loops (Schweitzer et al., 2013). In particular, it was known that some grass species adapted to low soil N availability were able to inhibit nitrification via the exudation of specific compounds inhibiting ammonia oxidizers, mostly AOB (Subbarao et al., 2009). Recently, Bardon et al. (2014, 2018) demonstrated that some forb and shrub species are able to inhibit denitrification, through the exudation of phenolic compounds by roots. Our results demonstrate for the first time that some tree species can also inhibit nitrification through knock out of the nitrite oxidizers *Nitrobacter*. This is an important breakthrough for understanding the range of plant-microorganisms interaction processes that underlie niche construction by plants growing in environments with low soil N availability.

## Material and methods

### Study site and soil sampling in 28 year-old plots

The study site is a long-term experimental site managed by INRA, located in the Breuil-Chenue forest ('SOERE F-OreT' site, Nièvre Morvan, France; 47°18'N and

Accepted Article
4°44'E; elevation of 650 m). Mean annual temperature and precipitation are 9°C and 1280 mm, respectively. The native forest is a 150-year-old coppice dominated by beech (Fagus sylvatica L.) with Quercus sessiliflora Smith, Betula verruosa Ehrh, and Corylus avenala L. In the end of the 1970s, a 10-ha flat area was clear-cut, and bole wood and large branches were harvested. The area was planted in rows with tree monocultures of beech (Fagus sylvatica), Corsican pine (Pinus nigra Arn. Spp laricio Poiret var corsicana), Douglas fir (Pseudotsuga menziesii Franco), Nordmann fir (Abies nordmanniana Spach.) and spruce (Picea abies Karst) (1000 m² for each species) (Andrianarisoa et al., 2010). A reference plot of native forest was also studied. The humus in the native forest is a dysmoder and the soil developed from granite is classified as a Typic Dystrochrept (USDA 1999). The texture of the soil is sandy-loam (60% sand and <20% clay) and the soil is acidic (pH around 4).

Soil was sampled at 6 locations randomly chosen within each of the 6 plots with a corer (0-10 cm depth; 8 cm diameter). The 36 soil samples were sieved (4 mm) and visible roots were removed. Soil sub samples were stored during 4 days at 4°C before assays for pH and potential and net nitrification rates. Other sub samples were stored at -20°C for molecular analysis.

## Soil core transplantation experiment and core sampling

Twenty eight years after plantation, 300 intact soil cores including the forest floor layer were collected with an auger (diameter 8 cm; depth 15 cm) along two parallel lines located 0.5 m away from a tree row (Fig S4), i.e. 60 cores for each pure stand

Accepted Article
4°44'E; elevation of 650 m). Mean annual temperature and precipitation are 9°C and 1280 mm, respectively. The native forest is a 150-year-old coppice dominated by beech (Fagus sylvatica L.) with Quercus sessiliflora Smith, Betula verruosa Ehrh, and Corylus avenala L. In the end of the 1970s, a 10-ha flat area was clear-cut, and bole wood and large branches were harvested. The area was planted in rows with tree monocultures of beech (Fagus sylvatica), Corsican pine (Pinus nigra Arn. Spp laricio Poiret var corsicana), Douglas fir (Pseudotsuga menziesii Franco), Nordmann fir (Abies nordmanniana Spach.) and spruce (Picea abies Karst) (1000 m² for each species) (Andrianarisoa et al., 2010). A reference plot of native forest was also studied. The humus in the native forest is a dysmoder and the soil developed from granite is classified as a Typic Dystrochrept (USDA 1999). The texture of the soil is sandy-loam (60% sand and <20% clay) and the soil is acidic (pH around 4).

Soil was sampled at 6 locations randomly chosen within each of the 6 plots with a corer (0-10 cm depth; 8 cm diameter). The 36 soil samples were sieved (4 mm) and visible roots were removed. Soil sub samples were stored during 4 days at 4°C before assays for pH and potential and net nitrification rates. Other sub samples were stored at -20°C for molecular analysis.

## Soil core transplantation experiment and core sampling

Twenty eight years after plantation, 300 intact soil cores including the forest floor layer were collected with an auger (diameter 8 cm; depth 15 cm) along two parallel lines located 0.5 m away from a tree row (Fig S4), i.e. 60 cores for each pure stand

Accepted Article
plot. In the native forest, each of the 60 cores was located at 0.5 m from a beech
dominant tree. Soil cores were wrapped in mesh bags (2 mm mesh size). Ten cores
were placed back into their original location (i.e., 10 beech soil cores placed back in
the beech plot, etc.) and 50 cores were placed into the empty holes in the five other
plots (i.e. 10 beech soil cores translocated to the spruce plot, etc.). In each plot, half of
the soil cores (i.e. 6 treatments x 5 replicates = 30) were collected 16 months after
transplantation, and the other half after 28 months.

At each sampling date, the residual forest floor material from the original stand
and the newly fallen litter from the host stand were collected before removing soil
cores. For each core, soil was sieved (4 mm) and visible roots were removed. Soil sub
samples were stored at 4°C for the nitrification assays, and frozen at -20°C for
molecular analysis.

Measurements of soil environmental variables and nitrification activities

Gravimetric soil moisture and soil pH (using 1/1 vol/vol soil/water slurry) were
measured for each of the 36 soil samples taken from the 28 year-old plots. On each
sample, nitrifying enzyme activity (NEA) was measured using short-term laboratory
incubations under non-limiting conditions according to (Dassonville *et al.*, 2011). Sub-
samples of fresh soil (3 g equivalent dry soil) were incubated at 28°C with 6 ml of a
solution of (NH₄)₂SO₄ (50 µg N-NH₄⁺ g⁻¹ dry soil), and distilled water was added in
each sample to reach 24 ml of total liquid volume in flasks. Soil NO₃⁻ content was
measured after 5, 24, 48 and 72 hours during an aerobic incubation under constant

Accepted Article
plot. In the native forest, each of the 60 cores was located at 0.5 m from a beech
dominant tree. Soil cores were wrapped in mesh bags (2 mm mesh size). Ten cores
were placed back into their original location (i.e., 10 beech soil cores placed back in
the beech plot, etc.) and 50 cores were placed into the empty holes in the five other
plots (i.e. 10 beech soil cores translocated to the spruce plot, etc.). In each plot, half of
the soil cores (i.e. 6 treatments x 5 replicates = 30) were collected 16 months after
transplantation, and the other half after 28 months.

At each sampling date, the residual forest floor material from the original stand
and the newly fallen litter from the host stand were collected before removing soil
cores. For each core, soil was sieved (4 mm) and visible roots were removed. Soil sub
samples were stored at 4°C for the nitrification assays, and frozen at -20°C for
molecular analysis.

Measurements of soil environmental variables and nitrification activities

Gravimetric soil moisture and soil pH (using 1/1 vol/vol soil/water slurry) were
measured for each of the 36 soil samples taken from the 28 year-old plots. On each
sample, nitrifying enzyme activity (NEA) was measured using short-term laboratory
incubations under non-limiting conditions according to (Dassonville *et al.*, 2011). Sub-
samples of fresh soil (3 g equivalent dry soil) were incubated at 28°C with 6 ml of a
solution of (NH4)2SO4 (50 µg N-NH4+ g-1 dry soil), and distilled water was added in
each sample to reach 24 ml of total liquid volume in flasks. Soil NO3- content was
measured after 5, 24, 48 and 72 hours during an aerobic incubation under constant

Accepted Article
agitation (180 rpm) by ion chromatography (DX120, Dionex, Salt Lake City, USA). NEA was computed as the linear rate of nitrate production over 72h (no nitrite accumulation was observed, except on a very few soils). Net nitrification and net mineralization rates were also measured for each of the 36 samples according to Andrianarisoa *et al.* (2010). Sub-samples of 200 g fresh soil were placed into jars with airtight lids and incubated at 20°C in the dark for 42 days. The jars were opened for a few minutes twice a week. $NH_4^+$ and $NO_3^-$ were extracted at the beginning and at the end of the incubation using 20 g of soil shaken in 1 M KCl for 1 h and then filtered. The $NH_4^+$ and $NO_3^-$ concentrations of extracts were measured with a continuous-flow colorimeter (TRAACS, Bran and Luebbe). Net mineralization and nitrification rates were computed as the amount of total inorganic N and of nitrate, respectively, accumulated during the incubation. All concentrations and rates are presented on a dry soil mass basis.

For the soil core transplantation experiment, gravimetric soil moisture and net nitrification rate were measured as described above for each of the 360 fresh soil samples.

## DNA extraction and quantification of nitrifier abundances

DNA was extracted from 0.5 g of soil for all soil samples using a PowerSoil DNA Isolation Kit (MO BIO laboratories, Inc, USA) according to the manufacturer's protocol. Extracted DNA was stored at -20°C until use. The abundances of AOB and AOA, *Nitrobacter*, *Nitrospira*, and *Nitrospira comammox* clades A and B were

Accepted Article
agitation (180 rpm) by ion chromatography (DX120, Dionex, Salt Lake City, USA). NEA was computed as the linear rate of nitrate production over 72h (no nitrite accumulation was observed, except on a very few soils). Net nitrification and net mineralization rates were also measured for each of the 36 samples according to Andrianarisoa et al. (2010). Sub-samples of 200 g fresh soil were placed into jars with airtight lids and incubated at 20°C in the dark for 42 days. The jars were opened for a few minutes twice a week. $NH_4^+$ and $NO_3^-$ were extracted at the beginning and at the end of the incubation using 20 g of soil shaken in 1 M KCl for 1 h and then filtered. The $NH_4^+$ and $NO_3^-$ concentrations of extracts were measured with a continuous-flow colorimeter (TRAACS, Bran and Luebbe). Net mineralization and nitrification rates were computed as the amount of total inorganic N and of nitrate, respectively, accumulated during the incubation. All concentrations and rates are presented on a dry soil mass basis.

For the soil core transplantation experiment, gravimetric soil moisture and net nitrification rate were measured as described above for each of the 360 fresh soil samples.

## DNA extraction and quantification of nitrifier abundances

DNA was extracted from 0.5 g of soil for all soil samples using a PowerSoil DNA Isolation Kit (MO BIO laboratories, Inc, USA) according to the manufacturer's protocol. Extracted DNA was stored at -20°C until use. The abundances of AOB and AOA, *Nitrobacter*, *Nitrospira*, and *Nitrospira comammox* clades A and B were

Accepted Article
quantified by real-time PCR targeting sequences of the bacterial and archaeal *amoA*
(coding for the ammonia monooxygenase), the *nxrA* gene of *Nitrobacter* (coding for
the nitrite oxidoreductase), the *16S rRNA* gene for *Nitrospira*, and the specific *amoA*
genes for comammox clades A and B, respectively. All these 6 nitrifier groups were
quantified for the 36 soil samples retrieved from the 28 year-old plots. Given the
results obtained on old plots, only AOA and *Nitrobacter* were targeted for the 360 soil
samples retrieved part of the core transplantation experiment. All samples were run in
duplicate on a Lightcycler 480 (Roche Diagnostics, Meylan, France). Dilution series
of the extracted DNA were performed to control for possible PCR inhibition by co-
extracted compounds, and no inhibition was observed (data not shown).

For AOA and AOB, amplification was performed using the primer sets
CrenamoA23f and CrenamoA616r (Tourna et al., 2011) and amoA_1F and amoA_2R
(Roththauwe and Witzel, 1997), respectively. Linearized plasmids containing cloned
archaeal (54d9 fosmide fragment) and bacterial (Nitrosomonas europaea, GenBank
accession number L08050) amoA genes served as standards. For Nitrobacter, the
amplification was performed according to Attard et al. (2010) using the gene primers
F1norA and R2norA (Wertz et al., 2012). A linearized plasmid containing a cloned
fragment of the nxrA gene of Nitrobacter hamburgensis X14 (DSMZ 10229) was used
as standard. For Nitrospira, the amplification was performed according to Attard et al.
(2010) using the gene primers Ns675f and Ns746r. Copies of a fragment of the
Nitrospira 16S rRNA gene (GenBank accession number FJ529918) served as standard
for quantification. For Nitrospira comammox clades A and B, the amplification was

<figure><img src="image_4.png" /></figure>
quantified by real-time PCR targeting sequences of the bacterial and archaeal *amoA*
(coding for the ammonia monooxygenase), the *nxrA* gene of *Nitrobacter* (coding for
the nitrite oxidoreductase), the *16S rRNA* gene for *Nitrospira*, and the specific *amoA*
genes for comammox clades A and B, respectively. All these 6 nitrifier groups were
quantified for the 36 soil samples retrieved from the 28 year-old plots. Given the
results obtained on old plots, only AOA and *Nitrobacter* were targeted for the 360 soil
samples retrieved part of the core transplantation experiment. All samples were run in
duplicate on a Lightcycler 480 (Roche Diagnostics, Meylan, France). Dilution series
of the extracted DNA were performed to control for possible PCR inhibition by co-
extracted compounds, and no inhibition was observed (data not shown).

For AOA and AOB, amplification was performed using the primer sets
CrenamoA23f and CrenamoA616r (Tourna et al., 2011) and amoA_1F and amoA_2R
(Rotthauwe and Witzel, 1997), respectively. Linearized plasmids containing cloned
archaeal (54d9 fosmide fragment) and bacterial (Nitrosomonas europaea, GenBank
accession number L08050) amoA genes served as standards. For Nitrobacter, the
amplification was performed according to Attard et al. (2010) using the gene primers
F1norA and R2norA (Wertz et al., 2012). A linearized plasmid containing a cloned
fragment of the nxrA gene of Nitrobacter hamburgensis X14 (DSMZ 10229) was used
as standard. For Nitrospira, the amplification was performed according to Attard et al.
(2010) using the gene primers Ns675f and Ns746r. Copies of a fragment of the
Nitrospira 16S rRNA gene (GenBank accession number FJ529918) served as standard
for quantification. For Nitrospira comammox clades A and B, the amplification was

<figure><img src="image_7.png" /></figure>
performed according to Pjevac *et al.* (2017) using the gene primers comaA-244F/comaA-659R and comaB-244F/comaB-659R. A linearized plasmid containing cloned sequences from comammox clade A (DQ008369.1) and clade B (GenBank accession number AJ564438.1) *amoA* genes served as standard. Efficiency of qPCR assays was between 85 % and 100 %.

**Quantification of the effect of soil and litter extracts on N. hamburgensis**

In January 2014, three soil cores (10 cm depth) were randomly sampled from each plot for two low nitrifying stands (i.e. Spruce and Nordmann pine). For each of the six cores, the soil horizon O (organic layer made up mostly of leaf litter and humus) and the A horizon (topsoil of horizon A) were separated, and a composite sample was obtained for each layer per plot. Litter and mineral soils layers were subjected to sequential extraction with acetone, 70% methanol and water (3 times each, extracts pooled together for each sample). Supernatants were evaporated and re-suspended in 50% methanol/water at 50 mg ml⁻¹. The samples also contained roots just cut and the extracts could contain root compounds and exudates ; but retrieving root exudates from living tree roots is highly challenging and was beyond the scope of our study.

The *in vitro* activity of litter and soil extracts for BNI was tested using *Nitrobacter hamburgensis* X14 as a model by performing continuous absorbance measurements taken with a Bioscreen C system (Labsystems, Helsinki, Finland). Bacterial suspensions were prepared from cultures grown in DSMZ 756a media for 5 days at 28°C. Suspensions were adjusted to a final OD₆₀₀nm of 0.2. Honeycomb 100-well
performed according to Pjevac *et al.* (2017) using the gene primers comaA-244F/comaA-659R and comaB-244F/comaB-659R. A linearized plasmid containing cloned sequences from comammox clade A (DQ008369.1) and clade B (GenBank accession number AJ564438.1) *amoA* genes served as standard. Efficiency of qPCR assays was between 85 % and 100 %.

Quantification of the effect of soil and litter extracts on N. *hamburgensis*

In January 2014, three soil cores (10 cm depth) were randomly sampled from each plot for two low nitrifying stands (i.e. Spruce and Nordmann pine). For each of the six cores, the soil horizon O (organic layer made up mostly of leaf litter and humus) and the A horizon (topsoil of horizon A) were separated, and a composite sample was obtained for each layer per plot. Litter and mineral soils layers were subjected to sequential extraction with acetone, 70% methanol and water (3 times each, extracts pooled together for each sample). Supernatants were evaporated and re-suspended in 50% methanol/water at 50 mg ml⁻¹. The samples also contained roots just cut and the extracts could contain root compounds and exudates ; but retrieving root exudates from living tree roots is highly challenging and was beyond the scope of our study.

The *in vitro* activity of litter and soil extracts for BNI was tested using *Nitrobacter hamburgensis* X14 as a model by performing continuous absorbance measurements taken with a Bioscreen C system (Labsystems, Helsinki, Finland). Bacterial suspensions were prepared from cultures grown in DSMZ 756a media for 5 days at 28°C. Suspensions were adjusted to a final OD₆₀₀nm of 0.2. Honeycomb 100-well

Accepted Article
microplates were filled with 888.9 µl of bacterial suspension and 111.1 µl of extract reaching the concentration of 0.25, 0.5 and 1 mg ml⁻¹. The plates were incubated in the Bioscreen C system at 28°C for 5 days and optical density was measured every 20 min with 5 s of prior shaking. The maximal growth µmax was determined in day⁻¹. All growth curves were done in quadruples.

## Statistical analyses

All statistical analyses were conducted using R software v3.4.2. Data were log-transformed for normality when needed (i.e. for abundance data). To test the effects of treatments on the microbial activities and abundances or *Nitrobacter* growth, one-way analysis of variance (ANOVA) was performed. This was followed by Turkey's honestly significant difference (HSD) at a p=0.05 level. Correlations between enzyme activity and abundance data were tested using the Pearson's product-moment correlation at a p=0.05 level.

## Acknowledgments

This study was funded by the French Institute for agronomic Research, INRA (EFPA Department) and CNRS (INEE Department). We thank Vincent Gaillard and Gwenaelle Berrocal (Centre d'Etude des Substances Naturelles, CESN, LEM, Villeurbanne) for help during HPLC assays, and Claire Commeaux (LEM UMR INRA 1418) for help during qPCR assays.

Accepted Article
microplates were filled with 888.9 µl of bacterial suspension and 111.1 µl of extract reaching the concentration of 0.25, 0.5 and 1 mg ml⁻¹. The plates were incubated in the Bioscreen C system at 28°C for 5 days and optical density was measured every 20 min with 5 s of prior shaking. The maximal growth µmax was determined in day⁻¹. All growth curves were done in quadruples.

## Statistical analyses

All statistical analyses were conducted using R software v3.4.2. Data were log-transformed for normality when needed (i.e. for abundance data). To test the effects of treatments on the microbial activities and abundances or *Nitrobacter* growth, one-way analysis of variance (ANOVA) was performed. This was followed by Turkey's honestly significant difference (HSD) at a p=0.05 level. Correlations between enzyme activity and abundance data were tested using the Pearson's product-moment correlation at a p=0.05 level.

## Acknowledgments

This study was funded by the French Institute for agronomic Research, INRA (EFPA Department) and CNRS (INEE Department). We thank Vincent Gaillard and Gwenaelle Berrocal (Centre d'Etude des Substances Naturelles, CESN, LEM, Villeurbanne) for help during HPLC assays, and Claire Commeaux (LEM UMR INRA 1418) for help during qPCR assays.

Accepted Article
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Accepted Article
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Accepted Article
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Ma, W., Jiang, S., Eline Assemien, F., Qin, M., Ma, B., Xie, Z., et al. (2016) Response

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Le Roux, X., Bouskill, N.J., Niboyet, A., Barthes, L., Dijkstra, P., Field, C.B., et al. (2016) Predicting the responses of soil nitrite-oxidizers to multi-factorial global change: A trait-based approach. *Front Microbiol* 7: 628.

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Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G.W., et al. (2006) Archaea predominate among ammonia-oxidizing prokaryotes in soils. *Nature* 442: 806–809.

Lewontin, R.C. and Lewontin, R.C. (2000) The triple helix: gene, organism, and environment, Harvard University Press.

Lodhi, M.A.K. and Killingbeck, K.T. (1980) Allelopathic inhibition of nitrification and nitrifying bacteria in a Ponderosa Pine (*Pinus Ponderosa* Dougl.) community. *Am J Bot* 67: 1423–1429.

Lodhi, M.A.K. and Ruess, R.W. (1988) Variation in soil nitrifiers and leaf nitrate reductase activity of selected tree species in a forest community. *Soil Biol Biochem* 20: 939-943.

Ma, W., Jiang, S., Eline Assemien, F., Qin, M., Ma, B., Xie, Z., et al. (2016) Response

<figure><img src="image_10.png" /></figure>
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Ma, B., Zhou, X., Xie, Z., Ma, W., Liu, Y., Feng, H., et al. (2019) How do soil microorganisms and plants concurrently respond to N, P and NP additions? *Application of the ecological framework of (co-)limitation by multiple resources at community and taxa levels.* *J Ecol* **107**: 2329–2345.

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<figure><img src="image_7.png" /></figure>
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Ma, B., Zhou, X., Xie, Z., Ma, W., Liu, Y., Feng, H., et al. (2019) How do soil microorganisms and plants concurrently respond to N, P and NP additions? *Application of the ecological framework of (co-)limitation by multiple resources at community and taxa levels.* *J Ecol* **107**: 2329–2345.

Meinen, C., Leuschner, C., Ryan, N.T. and Hertel, D. (2009) No evidence of spatial root system segregation and elevated fine root biomass in multi-species temperate broad-leaved forests. *Trees* **23**: 941-950.

Moukoumi, J., Munier-Lamy, C., Berthelin, J., and Ranger, J. (2006) Effect of tree species substitution on organic matter biodegradability and mineral nutrient availability in a temperate topsoil. *Ann For Sci* **63**: 763–771.

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Odling-Smee, F.J., Laland, K.N., and Feldman, M.W. (2003) Niche construction : the neglected process in evolution, Princeton University Press.

Paavolainen, L., Kitunen, V., and Smolander, A. (1998) Inhibition of nitrification in forest soil by monoterpenes. *Plant Soil* **205**: 147–154.

Pjevac, P., Schaubberger, C., Poghosyan, L., Herbold, C.W., van Kessel, M.A.H.J., Daebeler, A., et al. (2017) *AmoA*-targeted polymerase chain reaction primers for

Accepted Article
the specific detection and quantification of Comammox *Nitrospira* in the
environment. *Front Microbiol* **8**: 1508.

Reed, H.E. and Martiny, J.B.H. (2007) Testing the functional significance of microbial
composition in natural communities. *FEMS Microbiol Ecol* **62**: 161–170.

Rice, E.L. and Pancholy, S.K. (2006) Inhibition of nitrification by climax ecosystems.
III. Inhibitors Other than Tannins. *Am J Bot* **61**: 1095.

Rodgers, G.A. & Ashworth, J. (2011) Bacteriostatic action of nitrification inhibitors.
*Can J Microbiol* **28**:1093-1100.

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Schweitzer, J.A., Juric, I., Van De Voorde, T.F.J., Clay, K., Van Der Putten, W.H., and Bailey, J.K. (2013) Are there evolutionary consequences of plant-soil feedbacks along soil gradients? *Funct Ecol* **28**: 55–64.

Shi, X., Hu, H.-W., Wang, J., He, J.-Z., Zheng, C., Wan, X., and Huang, Z. (2018)
Niche separation of comammox *Nitrospira* and canonical ammonia oxidizers in
an acidic subtropical forest soil under long-term nitrogen deposition. *Soil Biol
Biochem* **126**: 114–122.

Smolander, A., Kanerva, S., Adamczyk, B., and Kitunen, V. (2012) Nitrogen

<figure><img src="image_8.png" /></figure>
the specific detection and quantification of Comammox *Nitrospira* in the
environment. *Front Microbiol* **8**: 1508.

Reed, H.E. and Martiny, J.B.H. (2007) Testing the functional significance of microbial
composition in natural communities. *FEMS Microbiol Ecol* **62**: 161–170.

Rice, E.L. and Pancholy, S.K. (2006) Inhibition of nitrification by climax ecosystems.
III. Inhibitors Other than Tannins. *Am J Bot* **61**: 1095.

Rodgers, G.A. & Ashworth, J. (2011) Bacteriostatic action of nitrification inhibitors.
*Can J Microbiol* **28**:1093-1100.

Rotthauwe, J. and Witzel, K. (1997) The ammonia monooxygenase structural gene *amoA* as a functional marker : Molecular fine-scale analysis of natural ammonia-oxidizing populations. *Appl Environ Microbiol* **63**: 4704–4712.

Schweitzer, J.A., Bailey, J.K., Rehill, B.J., Martinsen, G.D., Hart, S.C., Lindroth, R.L., et al. (2004) Genetically based trait in a dominant tree affects ecosystem processes. *Ecol Lett* **7**: 127–134.

Schweitzer, J.A., Juric, I., Van De Voorde, T.F.J., Clay, K., Van Der Putten, W.H., and Bailey, J.K. (2013) Are there evolutionary consequences of plant-soil feedbacks along soil gradients? *Funct Ecol* **28**: 55–64.

Shi, X., Hu, H.-W., Wang, J., He, J.-Z., Zheng, C., Wan, X., and Huang, Z. (2018)
Niche separation of comammox *Nitrospira* and canonical ammonia oxidizers in
an acidic subtropical forest soil under long-term nitrogen deposition. *Soil Biol
Biochem* **126**: 114–122.

Smolander, A., Kanerva, S., Adamczyk, B., and Kitunen, V. (2012) Nitrogen
transformations in boreal forest soils—does composition of plant secondary
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Srikanthasamy, T., Leloup, J., Brigitte N'dri, A., Barot, S., Gervaix, J., Koné, A.W., et al. (2018) Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna. *Soil Biol Biochem* **117**: 153–163.

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Stempfhuber, B., Richter-Heitmann, T., Bienek, L., Schöning, I., Schrumpf, M., Friedrich, M., et al. (2017) Soil pH and plant diversity drive co-occurrence patterns of ammonia and nitrite oxidizer in soils from forest ecosystems. *Biol Fertil Soils* **53**: 691–700.

Stevenson, F.J. and Schmidt, E.L. (1982) Nitrification in soil. In: *Nitrogen in agricultural soils*. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, pp. 253–288.

Stopnišek, N., Gubry-Rangin, C., Pela Höfferle, S., Nicol, G.W., Mandič-Mulec, I., and Prosser, J.I. (2010) Thaumarchaeal ammonia oxidation in an acidic forest peat soil is not influenced by ammonium amendment. *Appl Environ Microbiol* **76**: 7626–7634.

Stuart Chapin III, F., Matson, P.A., and Mooney, H.A. (2011) Principles of terrestrial ecosystem ecology, Springer.

Su, H., Cheng, Y., Behrendt, T., and Trebs, I. (2011) Soil nitrite as a source of atmospheric HONO and OH radicals. *Science* **333**: 1616–1618.

Accepted Article
transformations in boreal forest soils—does composition of plant secondary
compounds give any explanations? *Plant Soil* **350**: 1–26.

Srikanthasamy, T., Leloup, J., Brigitte N'dri, A., Barot, S., Gervaix, J., Koné, A.W., et al. (2018) Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna. *Soil Biol Biochem* **117**: 153–163.

Stark, J.M. and Hart, S.C. (1997) High rates of nitrification and nitrate turnover in undisturbed coniferous forests. *Nature* **385**: 61–64.

Stempfhuber, B., Richter-Heitmann, T., Bienek, L., Schöning, I., Schrumpf, M., Friedrich, M., et al. (2017) Soil pH and plant diversity drive co-occurrence patterns of ammonia and nitrite oxidizer in soils from forest ecosystems. *Biol Fertil Soils* **53**: 691–700.

Stevenson, F.J. and Schmidt, E.L. (1982) Nitrification in soil. In: *Nitrogen in agricultural soils*. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, pp. 253–288.

Stopnišek, N., Gubry-Rangin, C., Pela Höfferle, S., Nicol, G.W., Mandič-Mulec, I., and Prosser, J.I. (2010) Thaumarchaeal ammonia oxidation in an acidic forest peat soil is not influenced by ammonium amendment. *Appl Environ Microbiol* **76**: 7626–7634.

Stuart Chapin III, F., Matson, P.A., and Mooney, H.A. (2011) Principles of terrestrial ecosystem ecology, Springer.

Su, H., Cheng, Y., Behrendt, T., and Trebs, I. (2011) Soil nitrite as a source of atmospheric HONO and OH radicals. *Science* **333**: 1616–1618.

<figure><img src="image_11.png" /></figure>
Subbarao, G.V., Nakahara, K., Hurtado, M.P., Ono, H., Moreta, D.E., Salcedo, A.F., et al. (2009) Evidence for biological nitrification inhibition in *Brachiaria* pastures. *Proc Natl Acad Sci 106*: 17302-17307.

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Subbarao, G.V., Rondon, A.M., Ito, A.O., Ishikawa, A.T., Rao, A.I.M., Nakahara, A.K., et al. (2006) Biological nitrification inhibition (BNI)—is it a widespread phenomenon? *Plant Soil* **294**: 5-18.

Subbarao, G.V., Sahrawat, K.L., Nakahara, K., Ishikawa, T., Kishii, M., Rao, I.M., et al. (2012) Biological nitrification inhibition: a novel strategy to regulate nitrification in agricultural systems. *Adv Agron* **114**: 249-302.

Subbarao, G.V., Yoshihashi, T., Worthington, M., Nakahara, K., Ando, Y., Sahrawat, K.L., et al. (2015) Suppression of soil nitrification by plants. *Plant Sci* **233**: 155-164.

Sun, L., Lu, Y., Yu, F., Kronzucker, H.J., and Shi, W. (2016) Biological nitrification inhibition by rice root exudates and its relationship with nitrogen-use efficiency. *New Phytol* **212**: 646-656.

Szukics, U., Abell, G.C.J., Hödl, V., Mitter, B., Sessitsch, A., Hackl, E., and Zechmeister-Boltenstern, S. (2010) Nitrifiers and denitrifiers respond rapidly to changed moisture and increasing temperature in a pristine forest soil. *FEMS Microbiol Ecol* **72**: 395-406.
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Subbarao, G.V., Nakahara, K., Ishikawa, T., Yoshihashi, T., Ito, O., Ono, H., et al. (2008) Free fatty acids from the pasture grass *Brachiaria humidicola* and one of their methyl esters as inhibitors of nitrification. *Plant Soil* **313**: 89-99.

Subbarao, G.V., Rondon, A.M., Ito, A.O., Ishikawa, A.T., Rao, A.I.M., Nakahara, A.K., et al. (2006) Biological nitrification inhibition (BNI)—is it a widespread phenomenon? *Plant Soil* **294**: 5-18.

Subbarao, G.V., Sahrawat, K.L., Nakahara, K., Ishikawa, T., Kishii, M., Rao, I.M., et al. (2012) Biological nitrification inhibition: a novel strategy to regulate nitrification in agricultural systems. *Adv Agron* **114**: 249-302.

Subbarao, G.V., Yoshihashi, T., Worthington, M., Nakahara, K., Ando, Y., Sahrawat, K.L., et al. (2015) Suppression of soil nitrification by plants. *Plant Sci* **233**: 155-164.

Sun, L., Lu, Y., Yu, F., Kronzucker, H.J., and Shi, W. (2016) Biological nitrification inhibition by rice root exudates and its relationship with nitrogen-use efficiency. *New Phytol* **212**: 646-656.

Szukics, U., Abell, G.C.J., Hödl, V., Mitter, B., Sessitsch, A., Hackl, E., and Zechmeister-Boltenstern, S. (2010) Nitrifiers and denitrifiers respond rapidly to changed moisture and increasing temperature in a pristine forest soil. *FEMS Microbiol Ecol* **72**: 395-406.

<figure><img src="image_12.png" /></figure>
Tourna, M., Stieglmeier, M., Spang, A., Könneke, M., Schintlmeister, A., Urich, T., et al. (2011) *Nitrososphaera viennensis*, an ammonia oxidizing archaeon from soil. *Proc Natl Acad Sci 108*: 8420–8425.

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Verhamme, D.T., Prosser, J.I., and Nicol, G.W. (2011) Ammonia concentration determines differential growth of ammonia-oxidising archaea and bacteria in soil microcosms. *ISME J* 5: 1067–1071.

Verstraete, W. and Focht, D.D. (1977) Biochemical ecology of nitrification and denitrification. Springer, Boston, MA, pp. 135–214.

Vitousek, P.M., Gosz, J.R., Grier, C.C., Melillo, J.M., and Reiners, W.A. (1982) A Comparative analysis of potential nitrification and nitrate mobility in forest ecosystems. *Ecol Monogr* 52: 155–177.

Vitousek, P.M. and Howarth, R.W. (1991) Nitrogen limitation on land and in the sea: How can it occur? *Biogeochemistry* 13: 87–115.

Vitousek, P.M. and Sanford, R.L. (2003) Nutrient cycling in moist tropical forest. *Annu Rev Ecol Syst* 17: 137–167.

Wang Z., Cao Y., Zhu-Barker X., Nicol G.W., Wright A.L., Jia Z. & Jiang X. (2019) *Comammox Nitrospira* clade B contributes to nitrification in soil. *Soil Biol Biochem* 135: 392–395.
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Treusch, A.H., Leininger, S., Kietzin, A., Schuster, S.C., Klenk, H.P., and Schleper, C. (2005) Novel genes for nitrite reductase and *Amo*-related proteins indicate a role of uncultivated mesophilic crenarchaeota in nitrogen cycling. *Environ Microbiol* 7: 1985–1995.

Verhamme, D.T., Prosser, J.I., and Nicol, G.W. (2011) Ammonia concentration determines differential growth of ammonia-oxidising archaea and bacteria in soil microcosms. *ISME J* 5: 1067–1071.

Verstraete, W. and Focht, D.D. (1977) Biochemical ecology of nitrification and denitrification. Springer, Boston, MA, pp. 135–214.

Vitousek, P.M., Gosz, J.R., Grier, C.C., Melillo, J.M., and Reiners, W.A. (1982) A Comparative analysis of potential nitrification and nitrate mobility in forest ecosystems. *Ecol Monogr* 52: 155–177.

Vitousek, P.M. and Howarth, R.W. (1991) Nitrogen limitation on land and in the sea: How can it occur? *Biogeochemistry* 13: 87–115.

Vitousek, P.M. and Sanford, R.L. (2003) Nutrient cycling in moist tropical forest. *Annu Rev Ecol Syst* 17: 137–167.

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<figure><img src="image_9.png" /></figure>
Wertz, S., Leigh, A.K.K., and Grayston, S.J. (2012) Effects of long-term fertilization of forest soils on potential nitrification and on the abundance and community structure of ammonia oxidizers and nitrite oxidizers. *FEMS Microbiol Ecol* **79**: 142–154.

Wrage, N., Velthof, G.L., Van Beusichem, M.L., and Oenema, O. (2001) Role of nitrifier denitrification in the production of nitrous oxide. *Soil Biol Biochem* **33**: 1723–1732.

Yao, H., Gao, Y., Nicol, G.W., Campbell, C.D., Prosser, J.I., Zhang, L., et al. (2011) Links between ammonia oxidizer community structure, abundance, and nitrification potential in acidic soils. *Appl Environ Microbiol* **77**: 4618–4625.

Zeller, B., Recous, S., Kunze, M., Moukoumi, J., Colin-Belgrand, M., Bienaimé, S., et al. (2007) Influence of tree species on gross and net N transformations in forest soils. *Ann For Sci* **64**: 151–158.

Zhang, L.M., Hu, H.W., Shen, J.P., and He, J.Z. (2012) Ammonia-oxidizing archaea have more important role than ammonia-oxidizing bacteria in ammonia oxidation of strongly acidic soils. *ISME J* **6**: 1032–1045.

<figure><img src="image_13.png" /></figure>
## Figure captions

**Fig. 1:** Schematic representation of the three steps used in this work to analyse how tree species control soil nitrifier activity and abundance.

**Fig. 2:** Relationships between net nitrification and the abundances of (Top-Left) ammonia oxidizing archaea, AOA, (Top-Right) ammonia oxidizing bacteria, AOB, (Middle-Left) *Nitrobacter*, (Middle-Right) *Nitrospira*, (Bottom-Left) comammox clade A and (Bottom-Right) comammox clade B for 28 year-old plots. Each point corresponds to the mean value for a given tree species and bars are standard errors (n=6). NS: no significant relationship. Note that a common scale was used for all X axes. In the *Nitrobacter* panel, tree species are indicated: A n: *Abies nordmanniana*; F s: *Fagus sylvatica*; N f: Native forest; P a: *Picea abies*; P n: *Pinus nigra*; P m: *Pseudotsuga menziesii*.

**Fig. 3:** Comparison of soil net nitrification (Top) 16 months and (Bottom) 28 months after the soil core transplantation. Cores were transplanted from high to high nitrification plots (HH1, HH2 and HH3), from high to low nitrification plots (HL1, HL2 and HL3), from low to high nitrification plots (LH1, LH2 and LH3), and from low to low nitrification plots (LL1, LL2 and LL3). See Table S1 indicating which label corresponds to which treatments; for instance, LL1 includes the 3 treatments ‘Native forest to native forest’, ‘Native forest to *Picea abies*’ and ‘Native forest to

Accepted Article
## Figure captions

**Fig. 1:** Schematic representation of the three steps used in this work to analyse how tree species control soil nitrifier activity and abundance.

**Fig. 2:** Relationships between net nitrification and the abundances of (Top-Left) ammonia oxidizing archaea, AOA, (Top-Right) ammonia oxidizing bacteria, AOB, (Middle-Left) *Nitrobacter*, (Middle-Right) *Nitrospira*, (Bottom-Left) comammox clade A and (Bottom-Right) comammox clade B for 28 year-old plots. Each point corresponds to the mean value for a given tree species and bars are standard errors (n=6). NS: no significant relationship. Note that a common scale was used for all X axes. In the *Nitrobacter* panel, tree species are indicated: A n: *Abies nordmanniana*; F s: *Fagus sylvatica*; N f: Native forest; P a: *Picea abies*; P n: *Pinus nigra*; P m: *Pseudotsuga menziesii*.

**Fig. 3:** Comparison of soil net nitrification (Top) 16 months and (Bottom) 28 months after the soil core transplantation. Cores were transplanted from high to high nitrification plots (HH1, HH2 and HH3), from high to low nitrification plots (HL1, HL2 and HL3), from low to high nitrification plots (LH1, LH2 and LH3), and from low to low nitrification plots (LL1, LL2 and LL3). See Table S1 indicating which label corresponds to which treatments; for instance, LL1 includes the 3 treatments ‘Native forest to native forest’, ‘Native forest to *Picea abies*’ and ‘Native forest to

Accepted Article
*Abies nordmanniana*'. Mean values are presented with standard errors (n=15). For each date, different letters indicate significant differences between treatments.

**Fig. 4:** Relationships between net nitrification and the abundance of (Left) *Nitrobacter* and (Right), ammonia oxidizing archaea, AOA, (Top) 16 months and (Bottom) 28 months after the soil core transplantation. Main treatment acronyms are as in figure 3. Mean values are presented with standard errors (n=15). Core transplantation treatments: HH, from high to high nitrification plots ; HL, from high to low nitrification plots ; LH, from low to high nitrification plots ; and LL, from low to low nitrification plots.

**Fig. 5:** Level of the decrease in *Nitrobacter hamburgensis* maximum growth rate, µmax, induced by the extracts of litter and soil from the –low nitrification– *Picea abies* and *Abies Nordmanniana* plots, as compared to the control without any extract. For each tree species and type of extract, 3 concentrations were tested. Mean values are presented with standard errors (n=4). Different letters indicate significant differences between treatments.

<figure><img src="image_10.png" /></figure>
*Abies nordmanniana*'. Mean values are presented with standard errors (n=15). For each date, different letters indicate significant differences between treatments.

**Fig. 4:** Relationships between net nitrification and the abundance of (Left) *Nitrobacter* and (Right), ammonia oxidizing archaea, AOA, (Top) 16 months and (Bottom) 28 months after the soil core transplantation. Main treatment acronyms are as in figure 3. Mean values are presented with standard errors (n=15). Core transplantation treatments: HH, from high to high nitrification plots ; HL, from high to low nitrification plots ; LH, from low to high nitrification plots ; and LL, from low to low nitrification plots.

**Fig. 5:** Level of the decrease in *Nitrobacter hamburgensis* maximum growth rate, µmax, induced by the extracts of litter and soil from the –low nitrification– *Picea abies* and *Abies Nordmanniana* plots, as compared to the control without any extract. For each tree species and type of extract, 3 concentrations were tested. Mean values are presented with standard errors (n=4). Different letters indicate significant differences between treatments.

<figure><img src="image_14.png" /></figure>
<figure><img src="image_11.png" /><figcaption>Fig. 1</figcaption></figure>
<figure><img src="image_15.png" /><figcaption>Fig. 1</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>Fig. 2</figcaption></figure>
<figure><img src="image_16.png" /><figcaption>Fig. 2</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Fig. 3</figcaption></figure>
<figure><img src="image_17.png" /><figcaption>Fig. 3</figcaption></figure>
<figure><img src="image_14.png" /><figcaption>Fig. 4</figcaption></figure>
<figure><img src="image_18.png" /><figcaption>Fig. 4</figcaption></figure>
<figure><img src="image_15.png" /><figcaption>Fig. 5</figcaption></figure>
<figure><img src="image_19.png" /><figcaption>Fig. 5</figcaption></figure>