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# Nitrification, denitrification, and related functional genes under elevated CO2: A meta-analysis in terrestrial ecosystems

Robin Gineyts, Audrey Niboyet

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Robin Gineyts, Audrey Niboyet. Nitrification, denitrification, and related functional genes under elevated CO2: A meta-analysis in terrestrial ecosystems. Global Change Biology, 2023, 29 (7), pp.1839-1853. 10.1111/gcb.16568. hal-03989955

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RESEARCH ARTICLE

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Global Change Biology

WILEY

# Nitrification, denitrification, and related functional genes under elevated CO₂: A meta-analysis in terrestrial ecosystems

Robin Gineyts<fnref n="1" />,<fnref n="2" /> | Audrey Niboyet<fnref n="1" />,<fnref n="2" /> ID

Correspondence

Audrey Niboyet, AgroParisTech, 91120, Palaiseau, France.

Email: audrey.niboyet@agroparistech.fr

## Abstract

Global change may have profound effects on soil nitrogen (N) cycling that can induce positive feedback to climate change through increased nitrous oxide (N₂O) emissions mediated by nitrification and denitrification. We conducted a meta-analysis of the effects of elevated CO₂ on nitrification and denitrification based on 879 observations from 58 publications and 46 independent elevated CO₂ experiments in terrestrial ecosystems. We investigated the effects of elevated CO₂ alone or combined with elevated temperature, increased precipitation, drought, and N addition. We assessed the response to elevated CO₂ of gross and potential nitrification, potential denitrification, and abundances of related functional genes (archaeal *amoA*, bacterial *amoA*, *nirK*, *nirS*, and *nosZ*). Elevated CO₂ increased potential nitrification (+28%) and the abundance of bacterial *amoA* functional gene (+62%) in cropland ecosystems. Elevated CO₂ increased potential denitrification when combined with N addition and higher precipitation (+116%). Elevated CO₂ also increased the abundance of *nirK* (+25%) and *nirS* (+27%) functional genes in terrestrial ecosystems and of *nosZ* (+32%) functional gene in cropland ecosystems. The increase in the abundance of *nosZ* under elevated CO₂ was larger at elevated temperature and high N (+62%). Four out of 14 two-way interactions tested between elevated CO₂ and elevated temperature, elevated CO₂ and increased precipitation, and elevated CO₂ and N addition were marginally significant and mostly synergistic. The effects of elevated CO₂ on potential nitrification and abundances of bacterial *amoA* and *nirS* functional genes increased with mean annual temperature and mean annual precipitation. Our meta-analysis thus suggests that warming and increased precipitation in large areas of the world could reinforce positive responses of nitrification and denitrification to elevated CO₂ and urges the need for more investigations in the tropical zone and on interactive effects among multiple global change factors, as we may largely underestimate the effects of global change on soil N₂O emissions.

## KEYWORDS

climate change, drought, elevated CO₂, elevated temperature, increased precipitation, interactions, N₂O emissions, nitrogen addition, soil nitrogen cycling

This is an open access article under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2022 The Authors. *Global Change Biology* published by John Wiley & Sons Ltd.

<footnote n="1">¹Sorbonne Université, Université Paris Cité, UPEC, CNRS, INRAE, IRD, Institut d'Ecologie et des Sciences de l'Environnement de Paris, Paris, France</footnote>

<footnote n="2">²AgroParisTech, Palaiseau, France</footnote>
# 1 INTRODUCTION

Nitrogen (N) plays a pivotal role in terrestrial ecosystems, as N limits primary productivity in many terrestrial ecosystems and thus the terrestrial carbon (C) sink (LeBauer & Treseder, 2008; Vitousek & Howarth, 1991). Among the microbially-mediated N cycling processes, nitrification (the oxidation of ammonium (NH₄⁺) to nitrate (NO₃⁻)) and denitrification (the reduction of NO₃⁻ into N-containing gases) are critical to the functioning of terrestrial ecosystems. Indeed, both nitrification and denitrification regulate mineral N availability in soils and contribute to ecosystem N losses through the production of NO₃⁻ that is prone to leaching and of N-containing gases, including nitrous oxide (N₂O), a potent greenhouse gas (Bateman & Baggs, 2005; Maag & Vinther, 1996). Nitrification and denitrification are the most important sources of N₂O emissions in soils, with N₂O being produced as a by-product of the first step of nitrification and as an intermediate or end-product during nitrifier denitrification and denitrification (Wrage et al., 2001, 2004). Assessing and understanding the impacts of global change on nitrification and denitrification are thus important, as the effects of global change on these microbial processes could induce positive feedback on climate change (Tian et al., 2020).

Numerous global change experiments have been conducted on soil N cycling in terrestrial ecosystems and have reported significant changes in nitrification and denitrification rates in response to global change (Barnard et al., 2005). These effects were mostly attributed to changes in the soil parameters to which nitrifying and denitrifying microbial communities are sensitive, such as soil moisture, soil oxygen content, soil labile C content, and soil mineral N content (Prosser, 1990; Tiedje, 1988). In particular, rising atmospheric CO₂ can induce significant changes in nitrification and denitrification rates through three main mechanisms. First, elevated CO₂ has been shown to increase soil moisture through decreased plant evapotranspiration (Field et al., 1995) and consequently to decrease soil oxygen content with differential effects on nitrifying and denitrifying microbial communities that are respectively mostly aerobic and anaerobic. Second, elevated CO₂ has been found to increase soil labile C content through increased net primary productivity and rhizodeposition (Hungate, 1999) with expected positive effects on denitrifying microbial communities that are heterotrophic for C. Third, elevated CO₂ has been reported to alter soil mineral N availability through its effect on the balance of N mineralization and immobilization and on plant and microbial N uptake (de Graaff et al., 2006; Kuzyakov et al., 2019) with cascading effects on nitrification and denitrification microbial processes that rely on NH₄⁺ and NO₃⁻ availability.

Among the elevated CO₂ experiments conducted to date, divergent responses of nitrification and denitrification rates have been reported, with either negative, positive or neutral effects of elevated CO₂ on nitrification and denitrification rates (on nitrification, see Barnard et al., 2006 for decreases, Shen et al., 2021 or Waqas et al., 2021 for increases and Barnard et al., 2004 or Niboyet, Le Roux, et al., 2011 for no changes; on denitrification, see Barnard

et al., 2004 for decreases, Baggs et al., 2003 or Carnol et al., 2002 for increases and Niboyet et al., 2010 or Niboyet, Le Roux, et al., 2011 for no changes). The responses to elevated CO₂ of the abundances of nitrifying and denitrifying functional genes, used as markers for the abundances of the nitrifying and denitrifying microbial communities in soils, have also been investigated: archaeal *amoA* gene for ammonia-oxidizing archaea (AOA), bacterial *amoA* gene for ammonia-oxidizing bacteria (AOB) (Leininger et al., 2006), *nirK* and *nirS* genes for denitrifying microbial communities that reduce nitrite (NO₂⁻) to nitric oxide (NO), and *nosZ* gene for denitrifying microbial communities that reduce N₂O to N₂ (Kuypers et al., 2018; Levy-Booth et al., 2014). Similarly, discrepancies have been reported in the responses to elevated CO₂ of the abundances of nitrifying and denitrifying functional genes, with either decreases, increases or no significant changes in the abundances of archaeal *amoA*, bacterial *amoA*, *nirK*, *nirS* and *nosZ* functional genes in response to elevated CO₂ (on nitrifying functional genes, see Yang et al., 2019 for decreases, Shen et al., 2021 for increases and Nelson et al., 2010 or Simonin et al., 2015 for no changes; on denitrifying functional genes, see Kelly et al., 2013 for increases and Brenzinger et al., 2017 or Yang et al., 2019 for no changes).

This great inter-study variability of responses of nitrification and denitrification rates and abundances of related functional genes to elevated CO₂ clearly stresses the need to conduct a meta-analysis to assess the response of nitrification and denitrification to elevated CO₂. Divergent responses to elevated CO₂ among studies might notably be due to differences in ecosystem type, climate and soil characteristics, or magnitude and duration of the elevated CO₂ treatment-potential explanatory factors that a meta-analysis could uncover. Previous reviews and meta-analyses have been conducted to assess the effects of elevated CO₂ on nitrification and denitrification rates (Barnard et al., 2005; Liang et al., 2016) and abundances of nitrifying and denitrifying functional genes (Du et al., 2022; Li, Ma, et al., 2022), however, none of them have simultaneously analyzed the effects of elevated CO₂ on both rates and genes. Besides, global change is multifactorial, and these meta-analyses have not statistically assessed the effects of elevated CO₂ in combination with multiple other global change factors, including warming, increased precipitation, drought, and N addition. All these global change factors can also alter the soil conditions to which nitrifying and denitrifying microbial communities are sensitive and have been reported to elicit significant changes in nitrification and denitrification (Bai et al., 2013; Dai et al., 2020; Deng et al., 2021; Li, Zheng, et al., 2020; Lu et al., 2011). They could interact with elevated CO₂ and modify the response of nitrification and denitrification to elevated CO₂ as suggested by the few individual studies that have investigated interactive effects among CO₂ and other global change factors and have reported significant interactions on nitrification and denitrification (Larsen et al., 2011; Zhang et al., 2017).

Here, we seek to understand the collective response of nitrification and denitrification rates and related functional genes to elevated CO₂ alone or combined with other global change factors. We conducted a meta-analysis based on 879 observations from
58 publications and 46 independent elevated CO₂ experiments in terrestrial ecosystems, including cropland, grassland and forest ecosystems. Our objectives were to (i) assess the responses of nitrification and denitrification rates and related functional genes to elevated CO₂ alone or combined with warming, increased precipitation, drought, and N addition, (ii) investigate the interactive effects of elevated CO₂ and warming, elevated CO₂ and increased precipitation or drought, and elevated CO₂ and N addition, (iii) analyze to what extent responses of nitrification and denitrification rates and related functional genes to elevated CO₂ are linked, and (iv) examine whether these responses to elevated CO₂ differ among ecosystem types and climate and soil characteristics.

# 2 | MATERIALS AND METHODS

## 2.1 | Data collection

We searched journal articles using the Web of Science Core Collection database and the search equation ((elevat* OR rising OR enrich*) NEAR/2 (CO2 OR "carbon dioxide")) AND (*nitrif* OR amoA OR AOA OR AOB OR nirK OR nirS OR nosZ* OR "functional genes") in the title, abstract and keywords (349 results on July 18, 2022). Then, papers meeting the following criteria were selected: (i) research papers (not a review or a book chapter), (ii) including both control and CO₂ enrichment treatments with uninterrupted CO₂ application across the duration of the experiment, (iii) elevated CO₂ experiment conducted in a terrestrial ecosystem on a plant-soil system, (iv) at least one of the following variables was measured: gross or potential nitrification or denitrification rates, abundances of nitrifying and denitrifying functional genes (amoA-AOA, amoA-AOB, nirK, nirS, or nosZ), and (v) means, standard deviations or standard errors or confidence intervals, and sample sizes are available or extractable, either from tables, figures or the dataset when provided by the authors.

In each paper, we collected the following information: elevated CO₂ experiment location (GPS coordinates, or, if not reported, we estimated them using gps-coordinates.net; when different locations or when soils from different locations were studied in the same paper, they were considered as independent experiments), ecosystem type (cropland, grassland or forest), mean annual temperature and mean annual precipitation (if not reported, we estimated them using climate-data.org for experiments conducted in the field and with no irrigation), soil pH, magnitude of the CO₂ treatment, duration of the CO₂ treatment, other global change factors manipulated and crossed with the CO₂ treatment among elevated temperature, increased precipitation, drought, and N addition, magnitude of N addition in the elevated CO₂ experiment.

Data were extracted manually from tables or graphically from figures using WebPlotDigitizer 4.5 (Rohatgi, 2021), or were computed based on the dataset when provided by the authors for gross or potential nitrification or denitrification rates, abundances of nitrifying and denitrifying functional genes (amoA-AOA, amoA-AOB, nirK, nirS, or nosZ), N₂O emission rates and putative drivers of nitrifying and

denitrifying microbial activities, including soil water content (gravimetric or volumetric soil water content or water-filled pore space), soil dissolved organic carbon (DOC) content, soil NH₄⁺ and NO₃⁻ contents, gross N mineralization rates and gross N immobilization rates, soil pH, and plant biomass (aboveground, belowground, or total plant biomass). When several sampling dates were available in a single study, we extracted all data on nitrification and denitrification rates and related functional genes, and we extracted data on N₂O emission rates and putative drivers of nitrifying and denitrifying microbial activities for the measurement dates that were the closest to the dates of measurements of nitrification and denitrification rates and related functional genes. Negative values of N₂O emission rates and gross N transformation rates were excluded, as they do not enable to compute an effect size based on the natural log of the response ratio. When several sampling dates, sampling depths, or sampling modalities (e.g., rhizosphere versus bulk soil) were available in a single study, we extracted all data and considered them as multiple outcomes from the same elevated CO₂ experiment. Similarly, when several plant species or plant community composition, or different species management were manipulated in a single study, we considered them as multiple outcomes from the same elevated CO₂ experiment. When pollutants were manipulated in addition to the CO₂ treatment, we extracted the data from the treatment with no pollutant (e.g., cadmium (Jia et al., 2021), chlorpyrifos (Kollah et al., 2019) or tropospheric ozone (Kanerva et al., 2006)). Data were extracted for the control and the elevated CO₂ treatments (when several elevated levels of CO₂ were manipulated, data were extracted for each high CO₂ treatment, see Maxwell et al., 2022). If other global change factors than elevated CO₂ were manipulated among elevated temperature, increased precipitation, drought, and N addition, data for the control and the elevated CO₂ treatments were extracted for each level of the other manipulated global change factor.

Overall, a total of 879 observations (including 456 observations of nitrification and denitrification rates and abundances of nitrifying and denitrifying functional genes) taken from 58 papers (Table S1) and 46 independent elevated CO₂ experiments were reported. The global distribution of the elevated CO₂ experiments included in the meta-analysis is shown in Figure 1 (along with the data that were reported in each location) and Figure S1 (along with the ecosystem type studied at each location), and the distribution of mean annual temperature and mean annual precipitation of the experimental sites is shown in Figure S2.

## 2.2 | Data analysis

The natural log of the response ratio, defined as the effect size, was used to assess the responses of the variables studied to elevated CO₂ (Hedges et al., 1999).

The natural log of the response ratio (ln R) and its associated variance (v) were calculated as:

$$ \ln R = \ln \frac{\bar{X}_t}{\bar{X}_c} \qquad (1) $$
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<figure><img src="image_5.png" /><figcaption>FIGURE 1 Global distribution of the elevated CO₂ experiments included in the meta-analysis. The shape shows if elevated CO₂ was manipulated alone (circle) or if it was combined with other global change factors among elevated temperature, increased precipitation, drought, and N addition (triangle). The color indicates the data that were reported in each location, either nitrification and/or denitrification rates and related functional genes (in red), nitrification and/or denitrification rates (in green), or nitrifying and/or denitrifying functional genes (in blue).</figcaption></figure>

$$v = \frac{s_t^2}{n_t X_t^2} + \frac{s_c^2}{n_c X_c^2} \qquad (2)$$

where $\overline{X}_c$ and $\overline{X}_t$ are the means of the control and elevated CO₂ treatments, $s_c$ and $s_t$ are the standard deviations of the control and elevated CO₂ treatments, and $n_c$ and $n_t$ are the number of replicates of the control and elevated CO₂ treatments.

Because we anticipate between-study heterogeneity in the effect sizes, we used a random-effects model to determine the total effect size with the restricted maximum likelihood (REML) estimator to compute the variance of the distribution of true effect sizes $\tau^2$ (Viechtbauer, 2005). We further used Knapp-Hartung adjustments to calculate the confidence interval of the total effect size (Knapp & Hartung, 2003). For each study, the weighting factor ($W_i$) was calculated as the inverse of the sum of the pooled variance and heterogeneity for each treatment. When multiple observations were used from the same elevated CO₂ experiment, we adjusted the weights by the total number of observations per experiment ($n_i$) to get the final weights ($W'_i$) (Bai et al., 2013):

$$W_i = \frac{1}{v_i + \tau^2} \qquad (3)$$

$$W'_{i} = \frac{W_{i}}{n_{i}} \qquad (4)$$

The total effect size ($\overline{\ln R}$) was estimated as the weighted average of all effect sizes:

$$\overline{\ln R} = \frac{\sum_{i} W'_{i} \ln R_{i}}{\sum_{i} W'_{i}} \qquad (5)$$

where $\overline{\ln R_i}$ is the ith individual effect size.

To facilitate the description of the results, the total effect size was then transformed back to the percentage change induced by the elevated CO₂ treatment as follows:

$$CO_2 \text{ effect (\%) } = (e^{\overline{\ln R}} - 1) \times 100\% \qquad (6)$$

To further explore the two-way interactive effects of elevated CO₂ and other global change factors, among elevated temperature, increased precipitation, drought, and N addition, we used Hedge's d, an estimate based on standardized mean difference that was adapted for the assessment of interaction (Gurevitch et al., 2000). Hedge's d was computed for each two-way interaction and for each variable among nitrification and denitrification rates and abundances of related functional genes for which sufficient studies were available.

The main effects of the global change factors A and B ($d_A$ and $d_B$) and their interaction ($d_{A \times B}$) were calculated as:

$$d_A = \frac{(\overline{X_A} + \overline{X_{A \times B}}) - (\overline{X_B} + \overline{X_C})}{2s} J(m) \qquad (7)$$

$$d_B = \frac{(\overline{X_B} + \overline{X_{A \times B}}) - (\overline{X_A} + \overline{X_C})}{2s} J(m) \qquad (8)$$

$$d_{A \times B} = \frac{(\overline{X_{A \times B}} - \overline{X_A}) - (\overline{X_B} - \overline{X_C})}{2s} J(m) \qquad (9)$$
where $\overline{X_A}, \overline{X_B}, \overline{X_{A \times B}},$ and $\overline{X_C}$ are the means in the groups A, B, and their combination A x B, and in the control group; s is the pooled standard deviation and $J(m)$ is the correction term for small sample bias (Hedges & Olkin, 1985). s and $J(m)$ were calculated as:

$$s = \sqrt{\frac{(n_C - 1)\sigma_C^2 + (n_A - 1)\sigma_A^2 + (n_B - 1)\sigma_B^2 + (n_{A \times B} - 1)\sigma_{A \times B}^2}{n_C + n_A + n_B + n_{A \times B} - 4}} \quad (10)$$

$$J(m) = 1 - \frac{3}{4(n_C + n_A + n_B + n_{A \times B} - 4) - 1} \quad (11)$$

where $n_C, n_A, n_B$, and $n_{A \times B}$ are the sample sizes in the control group, groups A and B, and their combination A x B, and $\sigma_C, \sigma_A, \sigma_B$, and $\sigma_{A \times B}$ are the standard deviations in the control group, groups A and B, and their combination A x B. The variance ($v_d$) of Hedge's d for a given treatment i (A, B or A x B) was calculated as:

$$v_d = \frac{\frac{1}{n_C} + \frac{1}{n_A} + \frac{1}{n_B} + \frac{1}{n_{A \times B}} + \frac{d_i^2}{2(n_C + n_A + n_B + n_{A \times B})}}{4} \quad (12)$$

The total effect size of each global change factor A and B and their interaction A x B were assessed using a random-effects model as described above with a REML estimator and Knapp-Hartung adjustments. We classified the interaction between A and B into additive (if 95% confidence interval overlapped zero), synergistic and antagonistic interactions. When the individual effect sizes of global change factors A and B were positive, an effect size of the interaction greater than zero was classified as synergistic and an effect size of the interaction lower than zero as antagonistic. When the individual effect sizes were negative, an effect size of the interaction greater than zero was classified as antagonistic and an effect size of the interaction lower than zero as synergistic. When the individual effect sizes were in opposite directions, the interaction was classified as synergistic when it had the same sign as the expected combined effect under an additive regime, and as antagonistic when the sign of the interaction was opposite to the expected combined effect under an additive regime (Crain et al., 2008; Li, Ma, et al., 2022; Wang et al., 2021).

Relationships between effect sizes of elevated CO₂ on the variables studied were investigated using correlations and linear regressions with adjusted R-squared. Meta-regressions were conducted with either a categorical variable (ecosystem type) or continuous variables (mean annual temperature, mean annual precipitation, soil pH, duration of the CO₂ treatment, magnitude of the CO₂ treatment, or magnitude of N addition in the elevated CO₂ experiment) used as moderators for the random-effects model (mixed-effects meta-regression model). For each categorical or continuous variable, statistical results were reported as between-group heterogeneity of effect sizes (QM), residual error (QE), and p-value from mixed-effects meta-regression model.

All statistical analyses were conducted using R 4.0.3 software (R Core Team, 2022) and the meta (Balduzzi et al., 2019) and metafor (Viechtbauer, 2010) packages.

# 3 | RESULTS

## 3.1 | Effects of elevated CO₂ across all terrestrial ecosystems and as a function of ecosystem type

Overall, elevated CO₂ significantly increased the abundances of denitrifying functional genes nirK (+25%, $p = .008$) and nirS (+27%, $p < .001$) and induced a marginally significant increase in the abundances of bacterial amoA functional gene (+16%, $p = .08$) and of denitrifying functional gene nosZ (+16%, $p = .07$) (Figure 2a). Increases in the abundances of bacterial amoA functional gene and denitrifying functional genes nirK, nirS, and nosZ in response to elevated CO₂ were more pronounced and all significant in cropland ecosystems (amoA-AOB: +62%, $p = .003$; nirK: +36%, $p = .006$; nirS: +30%, $p = .002$ and nosZ: +32%, $p = .006$) (Figure 2b), while abundances of bacterial amoA functional gene and denitrifying functional genes nirK, nirS, and nosZ were not significantly altered by elevated CO₂ in grassland and forest ecosystems (Figure 2b). In contrast to other functional genes, the abundance of archaeal amoA functional gene was unresponsive to elevated CO₂ (Figure 2a,b). In addition to the increases in the abundances of bacterial amoA, nirK, nirS, and nosZ functional genes, elevated CO₂ also significantly increased potential nitrification in cropland ecosystems (+28%, $p = .03$) and induced a marginally significant increase in gross nitrification in forest ecosystems (+23%, $p = .07$) (Figure 2b). Elevated CO₂ had no significant effect on potential denitrification rates across all terrestrial ecosystems (Figure 2a,b).

In the studies selected in the present meta-analysis, elevated CO₂ induced a marginally significant increase in soil N₂O emissions (+26%, $p = .06$; Figure 3). In addition, elevated CO₂ significantly increased plant biomass (+23%, $p = .008$) and soil moisture (+5%, $p = .03$) and significantly decreased soil NO₃⁻ content (-18%, $p = .005$) (Figure 3), while it had no significant overall effect on soil DOC content, gross N mineralization and N immobilization rates, soil NH₄⁺ content, and soil pH (Figure 3).

## 3.2 | Effects of elevated CO₂ under elevated levels of other global change factors

Looking at the effects of elevated CO₂ under all possible combinations of elevated levels of other global change factors among elevated temperature, increased precipitation, drought, and N addition revealed that elevated CO₂ induced significant responses in potential denitrification rates under certain global change combinations: elevated CO₂ increased potential denitrification under N addition and higher precipitation (+116%, $p = .04$) and tended to decrease potential denitrification under elevated temperature (-15%, $p = .09$) (Figure 4a). Responses of gross nitrification rates, potential nitrification rates and abundances of nitrifying and denitrifying functional genes to elevated CO₂ were overall similar under all possible combinations of elevated levels of other global change factors (Figure 4a-c), except for the abundance of nosZ that exhibited a significant and
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

FIGURE 2 Effects of elevated CO₂ on nitrification and denitrification rates and nitrifying and denitrifying functional genes across all terrestrial ecosystems (a) and as a function of ecosystem type (cropland, grassland or forest) (b). Mean effect sizes were expressed as percentage changes resulting from elevated CO₂. Error bars indicate 95% confidence intervals. The blue slash with dots indicates a confidence interval going outside of the box. The dashed line was drawn at the mean effect equal to zero. Effects were considered significant if the 95% confidence interval did not overlap zero. Significant effects (*p* < .05) are indicated in red, marginally significant effects (*p* < .1) in orange, and non-significant effects (*p* > .1) in blue. The number of observations for each variable is shown next to the point, and the number of independent experiments is indicated in parentheses.

larger increase in response to elevated CO₂ when associated with N addition and elevated temperature (CO₂+N+T: +62%, *p* = .03; Figure 4c).

## 3.3 | Relationships between responses to elevated CO₂ of nitrification and denitrification rates and related functional genes

The effect size of elevated CO₂ on potential nitrification was significantly and positively correlated with the effect sizes of elevated CO₂ on the abundance of archaeal *amoA* functional gene (*p* = .02, R² = .15) and of bacterial *amoA* functional gene (*p* = .02, R² = .13) (Figure S3; Table S2), although with low R-squared of the corresponding linear regressions. The responses of most nitrifying and denitrifying functional genes to elevated CO₂ were significantly and positively correlated. In particular, the effect size of elevated CO₂ on bacterial *amoA* functional gene significantly increased with the effect size of elevated CO₂ on *nirK* (*p* = .01, R² = .24), *nirS* (*p* = .02, R² = .23) and *nosZ* (*p* < .001, R² = .54) functional genes (Figure S3; Table S2); the effect size of elevated CO₂

on *nirK* significantly increased with the effect size of elevated CO₂ on *nirS* (*p* < .001, R² = .48) and *nosZ* (*p* < .001, R² = .55) (Figure S3; Table S2) and the effect size of elevated CO₂ on *nirS* also significantly increased with the effect size of elevated CO₂ on *nosZ* (*p* = .01, R² = .23) (Figure S3; Table S2). In contrast, the relationships between effect sizes of elevated CO₂ on nitrification and denitrification rates and related functional genes and effect sizes of elevated CO₂ on putative drivers of nitrifying and denitrifying microbial activities were mostly not significant (Tables S3 and S4).

## 3.4 | Interactive effects of elevated CO₂ with other global change factors

Overall, there were few available studies on the combined effects of elevated CO₂ and other global change factors among elevated temperature, increased precipitation, drought, and N addition to investigate interactive effects on nitrification and denitrification and related functional genes (Figure 5; Figure S4). Among the 14 interactions tested between elevated CO₂ and elevated temperature, elevated CO₂ and increased precipitation,
<figure><img src="image_8.png" /></figure>

FIGURE 3 Effects of elevated CO₂ on soil N₂O emissions and putative drivers of nitrifying and denitrifying microbial activities. Mean effect sizes were expressed as percentage changes resulting from elevated CO₂. Error bars indicate 95% confidence intervals. The dashed line was drawn at the mean effect equal to zero. Effects were considered significant if the 95% confidence interval did not overlap zero. Significant effects (*p* < .05) are indicated in red, marginally significant effects (*p* < .1) in orange, and non-significant effects (*p* > .1) in blue. The number of observations for each variable is shown next to the point, and the number of independent experiments is indicated in parentheses.

and elevated CO₂ and N addition, four interactions were mar-
ginally significant: an antagonistic interaction between el-
evated CO₂ and elevated temperature on potential nitrification
(Hedge's *d* = -.23, *p* = .07; Figure 5a), a synergistic interaction
between elevated CO₂ and increased precipitation on potential
denitrification (Hedge's *d* = .47, *p* = .052; Figure 5b), a syner-
gistic interaction between elevated CO₂ and N addition on the
abundance of archaeal *amoA* functional gene (Hedge's *d* = -.12,
*p* = .052; Figure 5c), and a synergistic interaction between el-
evated CO₂ and elevated temperature on the abundance of
*nosZ* functional gene (Hedge's *d* = .23, *p* = .08; Figure 5d).
Additive effects of elevated CO₂ and elevated temperature,
elevated CO₂ and increased precipitation, and elevated CO₂
and N addition were found for 10 out of 14 interactions tested
(i.e., the effect size of the interaction was not significantly
different from zero for 10 out of 14 interactions tested;
Figure S4).

**3.5 | Relationships between responses to elevated CO<sub>2</sub> of nitrification and denitrification rates and related functional genes and main characteristics of ecosystems and CO<sub>2</sub> experiments**

Mean annual temperature and mean annual precipitation had sig-
nificant and positive effects on the effect size of elevated CO₂ on

potential nitrification (p = .009 and p < .001; Figure 6a,b; Table S5), on the abundance of bacterial *amoA* functional gene (p = .01 and p < .001; Figure 6d,e; Table S6) and on the abundance of *nirS* functional gene (p = .004 and p < .001; Figure 6g,h; Table S6). Soil pH had also a significant and positive effect on the effect size of elevated CO₂ on potential nitrification (p = .002; Figure 6c; Table S5) and on the abundance of bacterial *amoA* functional gene (p = .02; Figure 6f; Table S6). The effect size of elevated CO₂ on the abundance of bacterial *amoA* functional gene further significantly increased with the magnitude of N addition in the elevated CO₂ experiments (p = .002; Figure 6i; Table S6).

**3.6 | Effects of elevated CO₂ as a function of climate and soil characteristics**

In the elevated CO₂ experiments where the mean annual tempera-
ture was lower than 10°C (the mid-range of mean annual tempera-
ture in the temperate zone, Woodward et al., 2004), elevated CO₂
had no significant effect on nitrification and denitrification rates and
related functional genes, while in the study sites where the mean an-
nual temperature was higher than 10°C, elevated CO₂ significantly
increased the abundances of bacterial *amoA* (+39%, *p* = .004), *nirK*
(+43%, *p* = .02) and *nirS* (+48%, *p* = .001) functional genes (Figure S5)
and induced a marginally significant increase in potential denitrifi-
cation (+19%, *p* = .08; Figure S5). In the elevated CO₂ experiments
where the mean annual precipitation was lower than 800 mm (the av-
erage mean annual precipitation in the temperate zone, Woodward
et al., 2004), elevated CO₂ had no significant effect on nitrification
and denitrification rates and related functional genes, while in the
study sites where the mean annual precipitation was higher than
800 mm, elevated CO₂ significantly increased the abundances of
bacterial *amoA* (+55%, *p* = .0004) and *nirS* (+39%, *p* = .002) func-
tional genes (Figure S6) and induced a marginally significant increase
in potential nitrification (+20%, *p* = .06; Figure S6).

The effect of elevated CO₂ on potential nitrification and abundances of some nitrifying and denitrifying functional genes varied across soil pH (Figure S7): elevated CO₂ significantly increased potential nitrification in alkaline soils (+31%, *p* = .008), while it had no significant effect in neutral soils and induced a marginally significant decrease in potential nitrification in acidic soils (–15%, *p* = .09) (Figure S7); elevated CO₂ significantly increased the abundance of bacterial *amoA* functional gene in neutral (+41%, *p* = .0009) and alkaline soils (+42%, *p* = .02), while it had no significant effect on bacterial *amoA* in acidic soils (Figure S7); elevated CO₂ significantly increased the abundance of *nosZ* functional gene in neutral soils (+33%, *p* = .01), while it had no significant effect on *nosZ* in acidic soils (Figure S7).

**4 | DISCUSSION**

Overall, and as summarized in Figure 7, our meta-analysis shows that elevated CO₂ induced increases in both nitrification and denitrification rates and abundances of most nitrifying and denitrifying functional genes and
<figure><img src="image_9.png" /><figcaption>FIGURE 4 Effects of elevated CO₂ alone or under elevated levels of other global change factors among N addition (+N), elevated temperature (+T), increased precipitation (+W), or drought (+D) on nitrification and denitrification rates (a), nitrifying functional genes (b), and denitrifying functional genes (c). The treatments are indicated as defined by the authors of the individual studies, except for N addition, where all studies with N addition greater than 30 kg N ha⁻¹ year⁻¹ were included. Mean effect sizes were expressed as percentage changes resulting from elevated CO₂. Error bars indicate 95% confidence intervals. The blue slash with dots indicates a confidence interval going outside of the box. The dashed line was drawn at the mean effect equal to zero. Effects were considered significant if the 95% confidence interval did not overlap zero. Significant effects (*p* < .05) are indicated in red, marginally significant effects (*p* < .1) in orange, and non-significant effects (*p* > .1) in blue. The number of observations for each variable is shown next to the point, and the number of independent experiments is indicated in parentheses.</figcaption></figure>

that some of these positive responses to elevated CO₂ were more pro-
nounced or occurred only in cropland ecosystems, or under particular
global change scenarios, or particular climate and soil characteristics.

4.1 | Effects of elevated CO₂ on nitrification rates and nitrifying functional genes

Elevated CO₂ induced significant increases in potential nitrifica-
tion rates and in the abundance of bacterial *amoA* functional gene
in cropland ecosystems (the effect was marginally significant across

all terrestrial ecosystems), while the abundance of archaeal *amoA*
functional gene was unresponsive to elevated CO₂. Previous meta-
analyses had reported no response or decreases in nitrification rates
under elevated CO₂ (Barnard et al., 2005; Liang et al., 2016), in particu-
lar in long-term CO₂ experiments and in ecosystems where no N was
added (Liang et al., 2016), and negative responses of nitrification have
been attributed to decreased NH₄⁺ availability for nitrifiers under el-
evated CO₂. The increase in the abundance of bacterial *amoA* func-
tional gene in cropland ecosystems occurred along with no significant
change in the abundance of archaeal *amoA* functional gene, which is
in agreement with a previous meta-analysis assessing the effects of
<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>FIGURE 5 Individual effects and interactive effects of elevated CO₂ and other global change factors among N addition (N), elevated temperature (T), and increased precipitation (W) on potential nitrification (a), potential denitrification (b), archaeal *amoA* functional gene (c) and *nosZ* functional gene (d). Values are Hedge's *d* of elevated CO₂, N addition, elevated temperature, increased precipitation and their combinations (CO₂×N, CO₂×T, CO₂×W). Error bars indicate 95% confidence intervals. The dashed line was drawn at Hedge's *d* equal to zero. Interactive effects were considered significant if the 95% confidence interval did not overlap zero. Significant interactive effects (*p* < .05) are indicated in red, marginally significant interactive effects (*p* < .1) in orange, and non-significant interactive effects (*p* > .1) in blue. The number of observations is specified in each panel, and the number of independent experiments assessing the investigated two-way interaction is indicated in parentheses.</figcaption></figure>

elevated CO₂ on nitrifying functional genes in agricultural soils (Du et al., 2022) and supports the idea of a niche differentiation between AOA and AOB microbial communities in soils (Prosser & Nicol, 2012). A possible explanation for increases in potential nitrification rates and the abundance of bacterial *amoA* functional gene in response to elevated CO₂ in cropland ecosystems and for the marginally significant increase in gross nitrification rates in forest ecosystems may be related to increases in soil moisture resulting from decreased stomatal conductance at high CO₂, an effect that has been widely documented (van Groenigen et al., 2011) and is observed in our meta-analysis (Figure 7). Indeed, a relatively moderate elevation of soil moisture can increase nitrification rates and abundance of the nitrifying microbial communities by reducing water stress (Horz et al., 2004).

## 4.2 | Effects of elevated CO₂ on denitrification rates and denitrifying functional genes

Elevated CO₂ induced significant or marginally significant changes in potential denitrification rates but only under certain global change scenarios: elevated CO₂ significantly increased potential

denitrification when combined with N addition and higher precipitation and tended to decrease potential denitrification when combined with elevated temperature. In addition, elevated CO₂ significantly increased the abundances of *nirK* and *nirS* (increases were more pronounced in cropland ecosystems). Elevated CO₂ also significantly increased the abundance of *nosZ* in cropland ecosystems (the effect was marginally significant across all terrestrial ecosystems), and the increase in the abundance of *nosZ* in response to elevated CO₂ was remarkably larger when elevated CO₂ was combined with N addition and elevated temperature. Previous meta-analyses assessing the effects of elevated CO₂ on denitrification rates have reported both decreases in denitrification rates, although with a large variability among studies (Barnard et al., 2005), and increases in denitrification rates under elevated CO₂ in ecosystems where N was added (Liang et al., 2016). Increases in the abundances of *nirK* and *nirS* functional genes were previously observed in meta-analyses assessing the effects of elevated CO₂ on denitrifying functional genes in agricultural soils (Du et al., 2022) and across all terrestrial ecosystems for the abundance of *nirK* (Li, Ma, et al., 2022). In contrast, increases in the abundance of *nosZ* in response to elevated CO₂ in cropland ecosystems, or when elevated
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /><figcaption>FIGURE 6 Relationships between the effect sizes of elevated CO₂ on potential nitrification rate or abundances of bacterial *amoA* and *nirS* functional genes and mean annual temperature MAT (a, d, g), mean annual precipitation MAP (b, e, h), soil pH (c, f), and magnitude of N addition (i) at the experimental site. In each panel, the blue line shows the regression line given by the mixed-effects meta-regression model, and the dotted lines represent the 95% confidence interval. The bubble size is proportional to the weight of the studies in the analysis (with larger points for studies with more weight). The *p*-value from the mixed-effects meta-regression model is indicated with stars encoding significance levels (***p < .001; **p < .01; *p* < .05, see Tables S5 and S6), and the number of effect sizes included in the meta-regression is specified.</figcaption></figure>

CO₂ was combined with N addition and elevated temperature, were not previously reported. A possible explanation for increases in potential denitrification rates with elevated CO₂, N addition and increased precipitation is related to the relaxation of multiple limiting factors of denitrifying microbial communities under the combined effects of these global change factors. First, increased soil moisture (Figure 7) and associated decreased soil oxygen content under elevated CO₂ should favor anaerobic denitrifying microbial

communities, an effect that was likely more pronounced when elevated CO₂ was associated with increased precipitation (Brown et al., 2012). Second, increased plant biomass in response to elevated CO₂, a response that is widely documented (Ainsworth & Long, 2005) and observed in our meta-analysis (Figure 7), should result in higher soil labile C availability through increased inputs of root exudates and litter to soils and favor heterotrophic denitrifying microbial communities (Baggs et al., 2003). Third, N addition
<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /><figcaption>FIGURE 7 Diagram illustrating how elevated CO₂ altered nitrification and denitrification rates and abundances of related functional genes across terrestrial ecosystems. Responses to elevated CO₂ of putative drivers of nitrifying and denitrifying microbial activities investigated in the meta-analysis are also shown. Percentage changes resulting from elevated CO₂ are indicated. The arrows next to the variables indicate significant (in red) or marginally significant (in orange) effects of elevated CO₂ on the corresponding variables, ns indicates a non-significant effect. Effects occurring only in croplands or under certain global change scenarios are indicated (high N+W: N addition and increased precipitation; high N+T: N addition and elevated temperature).</figcaption></figure>

should increase mineral N availability and relax N limitation of denitrification (Niboyet et al., 2010; Niboyet, Le Roux, et al., 2011). Similar mechanisms (increased soil moisture, decreased soil oxygen content, and increased soil labile C content) are also likely to be responsible for the observed increases in the abundances of *nirK*, *nirS* and *nosZ* denitrifying functional genes in response to elevated CO₂, especially in cropland ecosystems (Attard et al., 2011).

## 4.3 | Relationships between responses of nitrification and denitrification rates and related functional genes to elevated CO₂

Overall, the responses of bacterial *amoA*, *nirK*, *nirS*, and *nosZ* functional genes were well related as indicated by concurrent increases in the abundances of these functional genes with CO₂ enrichment and as confirmed by the significant and positive relationships between the effect sizes of elevated CO₂ on these different functional genes, which suggests that CO₂ enrichment induced positive effects on total soil bacteria, including the nitrifying and denitrifying microbial communities. Increases in the abundances of the nitrifying and denitrifying functional genes under elevated CO₂ mostly translated into increases in potential nitrification (in cropland ecosystems) and in potential denitrification (when CO₂ was combined with N addition and increased precipitation) and are consistent with the observed increase in soil N₂O emissions in our meta-analysis (+26%, Figure 7) as observed in previous meta-analyses on the effects of elevated CO₂ on soil N₂O emissions (Du et al., 2022; Liang et al., 2016; van Groenigen et al., 2011; Wang et al., 2021).

The response of potential nitrification to elevated CO₂ was consistent with the response of bacterial *amoA* functional gene, and we found significant and positive relationships between the effect size of elevated CO₂ on potential nitrification and on the abundances of bacterial and archaeal *amoA* functional genes, although the effect size of elevated CO₂ on the abundances of *amoA* functional genes only explained 13%-15% of the variance of the effect size of elevated CO₂ on potential nitrification. Such positive relationships between nitrification rates and abundances of nitrifying genes were not previously reported in the only meta-analysis on the impact of global change on soil N cycling that also assessed the responses of both nitrification and denitrification rates and abundances of related functional genes (Dai et al., 2020) and suggest that abundances of nitrifying functional genes may well reflect abundances of functionally active nitrifying enzymes in the soils under elevated CO₂. In contrast, the response of potential denitrification to elevated CO₂ shows some discrepancies with those of denitrifying functional genes, and we found no significant relationships between the effect sizes of elevated CO₂ on potential denitrification and on the abundances of *nirK*, *nirS* and *nosZ* functional genes, an apparent paradox that could be due to no expression of these functional genes. Under elevated CO₂, soil environmental conditions were likely favorable for denitrifying microbial communities, but the amount of functionally active denitrifying enzymes may have been hindered by low substrate availability, decreasing functional genes expression and thus potential denitrification. Consistent with this, soil NO₃⁻ content significantly decreased in response to elevated CO₂ (Figure 7), an effect that could be due to increased plant and microbial N demand associated with increased
plant and microbial biomass under elevated CO₂ and/or with in-
creased leaching of NO₃⁻ resulting from increased soil moisture
under CO₂ enrichment (Barnard et al., 2005).

4.4 | Interactive effects of elevated CO₂ and other global change factors on nitrification and denitrification rates and related functional genes

We investigated all possible two-way interactions between elevated CO₂ and other global change factors among elevated temperature, increased precipitation, drought, and N addition. To date, the limiting number of available studies of interactive effects constrained our capacity of detecting significant interactions between elevated CO₂ and other global change factors on nitrification and denitrification rates and related functional genes (Niboyet, Brown, et al., 2011; Niboyet, Le Roux, et al., 2011). However, we found four marginally significant interactive effects among elevated CO₂ and other global change factors (CO₂×T on potential nitrification, CO₂×W on potential denitrification, CO₂×N on archaeal *amoA*, and CO₂×T on *nosZ*). Among those, synergistic interactions were dominant, such as the interaction between elevated CO₂ and increased precipitation on potential denitrification, with a positive combined effect of elevated CO₂ and increased precipitation on potential denitrification that was larger than expected based on an additive assumption. A likely explanation is that elevated CO₂ and increased precipitation, by increasing soil moisture and soil labile C, induced optimal conditions for denitrification, resulting in amplifying effects of these global change factors when they were combined. To our knowledge, only two meta-analyses have statistically investigated interactive effects among global change factors on soil N cycling: Wang et al., 2021 assessed the interactive effect of elevated CO₂ and elevated temperature on soil N₂O emissions and reported a synergistic interaction, while Li, Ma, et al. (2022) assessed the interactive effects of warming and N addition, warming and increased precipitation, and warming and decreased precipitation on abundances of N cycling functional genes and reported a synergistic interaction of warming and N addition. Synergistic interactions on soil N cycling were thus dominant in our meta-analysis and in the literature, which clearly highlights the need for further investigations on interactive effects, as we could underestimate the effects of multiple global change factors on nitrification and denitrification and associated soil N₂O emissions.

4.5 | Effects of elevated CO₂ vary across ecosystem types and climate and soil characteristics

Increases in potential nitrification and the abundances of bacte-
rial *amoA*, *nirK*, *nirS* and *nosZ* functional genes in response to el-
evated CO₂ occurred in cropland ecosystems and not in grassland
and forest ecosystems, where no significant changes in nitrifica-
tion and denitrification rates and abundances of related functional

genes were found (except a marginally significant increase in gross
nitrification in forest ecosystems). Agricultural soils often receive
substantial amounts of N fertilizer (up to 265 kg N ha⁻¹ year⁻¹ in our
study), so that nitrifying and denitrifying microbial communities
were likely not, or at least less, constrained by mineral N availability
in these soils compared with grassland and forest soils, and could
thus benefit from the relaxation of other limiting factors of nitrifi-
cation and denitrification induced by elevated CO₂ (e.g., increased
soil moisture and soil labile C content). In agreement with this and
with the preference of AOB for soils with high N content (Prosser
& Nicol, 2012), increases in the abundance of bacterial *amoA* func-
tional gene with elevated CO₂ increased with the amount of added
N in the elevated CO₂ experiments.

The effect of elevated CO₂ on nitrification varied across soil pH. Increases in potential nitrification occurred in alkaline soils, and increases in the abundance of bacterial *amoA* functional gene occurred in neutral and alkaline soils. Furthermore, the magnitude of increases in potential nitrification and the abundance of bacterial *amoA* functional gene in response to elevated CO₂ significantly increased with soil pH. At a global scale, soil nitrification rate has been shown to increase with soil pH, with higher nitrification rates in alkaline soils, as lower soil pH may dampen the soil microbial activity of nitrification, reduce richness and diversity of ammonia-oxidizers, and provide less substrate for soil nitrification (Li, Zeng, et al., 2020). Alkaline soils are known to be common in arid climates (Slessarev et al., 2016), which may thus be particularly sensitive to rising atmospheric CO₂ for the nitrification microbial process.

The effect of elevated CO₂ on nitrification and denitrification and related functional genes also varied across climate characteristics. Increases in the abundances of nitrifying and denitrifying functional genes in response to elevated CO₂ occurred in ecosystems with a mean annual temperature higher than 10°C (for bacterial *amoA*, *nirK* and *nirS*, along with a marginally significant increase in potential denitrification) and in ecosystems with a mean annual precipitation higher than 800mm (for bacterial *amoA* and *nirS*, along with a marginally significant increase in potential nitrification), while nitrification and denitrification rates and abundances of related functional genes remained unaffected by elevated CO₂ in ecosystems with a mean annual temperature lower than 10°C or a mean annual precipitation lower than 800mm. Furthermore, the magnitude of increases in potential nitrification and in the abundances of bacterial *amoA* and *nirS* functional genes in response to elevated CO₂ significantly increased with mean annual temperature and mean annual precipitation. Global syntheses on the controlling factors of soil nitrification and denitrification have shown that soil nitrification rate increased with mean annual temperature (Li, Zeng, et al., 2020) and that soil denitrification rate increased with mean annual temperature and mean annual precipitation (Li, Tang, et al., 2022). Taken together, these results suggest that the highest nitrification and denitrification rates occur in ecosystems with the highest mean annual temperature and mean annual precipitation, which are also ecosystems where the largest increases in nitrification and denitrification rates and abundances of related functional genes in response to elevated CO₂ are expected. The global distribution of
<figure><img src="image_16.png" /></figure>

elevated CO₂ experiments is clearly biased, with experiments mostly concentrated on the temperate zone (Figure 1, Figure S1), with a particular range of mean annual temperature and mean annual precipitation (Figure S2). Our meta-analysis clearly highlights the need for more global change experiments in biomes with higher mean annual temperature and mean annual precipitation, where elevated CO₂ might elicit the largest increases in nitrification and denitrification rates and associated N₂O emissions (e.g., in tropical rainforest, Woodward et al., 2004).

## 5 | CONCLUSIONS

Our meta-analysis shows that elevated CO₂ can cause increases in nitrification and denitrification rates and abundances of bacterial *amoA*, *nirK*, *nirS* and *nosZ* functional genes, resulting in increased soil N₂O emissions. We found that positive responses to elevated CO₂ were clearly most pronounced in cropland ecosystems and that responses to elevated CO₂ vary across soil pH and climate characteristics. Furthermore, some positive effects of elevated CO₂ occurred under certain global change scenarios (e.g., when CO₂ was combined with N addition and higher precipitation for potential denitrification), and our meta-analysis suggests potential interactions among CO₂ and other global change factors on nitrification and denitrification, resulting in effects that could be greater than those predicted based on single-factors experiments (i.e., synergistic interactions), which underlines the importance of assessing interactive effects among global change factors if we wish to be able to accurately predict the response of soil N cycling to global change. Our meta-analysis further shows that the magnitude of increases in potential nitrification and abundances of bacterial *amoA* and *nirS* functional genes under elevated CO₂ increased with mean annual temperature and mean annual precipitation and stresses the need for studies in biomes outside the temperate zone, in particular in the tropical zone, where the highest increases in nitrification and denitrification in response to elevated CO₂ might occur. Also, as the mean annual temperature is expected to increase globally and as the mean annual precipitation is expected to increase in large regions of the world (IPCC, 2021), the positive effects of elevated CO₂ on nitrification, denitrification, and associated N₂O emissions could be reinforced with ongoing climate change, thereby accelerating positive feedback on climate change.

## ACKNOWLEDGMENTS

This study was supported by Sorbonne Université, AgroParisTech and the Ecole Normale Supérieure of Lyon.

## CONFLICT OF INTEREST

The authors declare no conflict of interest.

## DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in Zenodo at https://zenodo.org/record/7457227#.Y6BEjHbMJPY.

## ORCID

Audrey Niboyet https://orcid.org/0000-0003-3355-706X

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## SUPPORTING INFORMATION

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**How to cite this article:** Gineyts, R., & Niboyet, A. (2023). Nitrification, denitrification, and related functional genes under elevated CO₂: A meta-analysis in terrestrial ecosystems. *Global Change Biology*, 29, 1839-1853. https://doi.org/10.1111/gcb.16568