# Contrasting roles of ground, trees, ponds and grazing in carbon dioxide, methane and nitrous oxide fluxes of an African semi-arid savanna

Aleksander Wieckowski, Patrik Vestin, Jonas Ardö, Olivier Roupsard, Ousmane Ndiaye, Seydina Ba, Claire Delon, Dominique Serça, Torbern Tagesson

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Aleksander Wieckowski, Patrik Vestin, Jonas Ardö, Olivier Roupsard, Ousmane Ndiaye, et al. Contrasting roles of ground, trees, ponds and grazing in carbon dioxide, methane and nitrous oxide fluxes of an African semi-arid savanna. Agriculture, Ecosystems & Environment, 2026, 399, pp.110199. 10.1016/j.agee.2025.110199. hal-05451268

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# Contrasting roles of ground, trees, ponds and grazing in carbon dioxide, methane and nitrous oxide fluxes of an African semi-arid savanna

Aleksander Wieckowski<sup>a,∗</sup> <sup>●</sup>, Patrik Vestin<sup>a</sup> <sup>●</sup>, Jonas Ardö<sup>a</sup> <sup>●</sup>, Olivier Roupsard<sup>c,d,f</sup>, Ousmane Ndiaye<sup>b</sup>, Seydina Ba<sup>e,f</sup> <sup>●</sup>, Claire Delon<sup>g</sup>, Dominique Serça<sup>g</sup> <sup>●</sup>, Torbern Tagesson<sup>a</sup>

## ARTICLE INFO

### Keywords:

- Greenhouse gas exchange
- Savanna ecosystems
- Dryland biogeochemistry
- Carbon-nitrogen cycling
- Methane emissions
- Nitrous oxide emissions
- Grazing
- African Sahel

## ABSTRACT

Understanding greenhouse gas fluxes in semi-arid ecosystems is critical for improving our understanding of biogeochemical cycles, particularly in underrepresented regions like the African Sahel. In these landscapes, greenhouse gas exchange arises from ground, trees, and water ponds, and is further shaped by environmental conditions and grazing. The carbon dioxide, methane, and nitrous oxide fluxes were quantified from these components in a Sahelian savanna in Senegal, while also assessing grazing impacts and environmental drivers (soil water content, temperature, vapor pressure deficit, photosynthetically active radiation). The ground was a net carbon dioxide sink during the rainy season but shifted toward neutrality or weak emission in the dry season, consistently acted as a methane sink, and was a year-round nitrous oxide source. Seasonal ponds were strong methane and nitrous oxide emission hotspots, with methane emissions being high enough to offset the sink of the overall savanna landscape. Trees contributed to carbon dioxide and methane uptake via branches, whereas stems were net methane and carbon dioxide emitters. Both stems and branches emitted nitrous oxide, and the presence of trees enhanced carbon dioxide, methane and nitrous oxide fluxes from soils beneath their canopies. Grazing enhanced ground gross primary production, reduced methane uptake, while no effect was seen on nitrous oxide fluxes. Temporal variability of carbon dioxide and nitrous oxide fluxes was strongly linked to soil water content and temperature, whereas methane fluxes showed no correlations with any of the measured drivers. These results demonstrate that tree- and pond-mediated fluxes, together with grazing, substantially alter the greenhouse gas fluxes of savanna ecosystems and incorporating these effects is essential for accurately representing semi-arid savannas in global greenhouse gas budgets.

## 1. Introduction

Human-induced climate change driven by the increase in atmospheric concentration of greenhouse gases is a major global challenge. Carbon dioxide, methane, and nitrous oxide account for ~ 90 % of the global warming (IPCC, 2022). Their atmospheric levels are strongly influenced by land-atmosphere exchanges, where terrestrial ecosystems act as both sources and sinks (Tian et al., 2016). The net flux represents the balance between emissions and uptake by soils, vegetation and other ecosystem components (Maier et al., 2022). While carbon dioxide fluxes

from terrestrial ecosystems are well studied (Baldocchi, 2020), methane and nitrous oxide remain poorly quantified, especially in Africa (Ernst et al., 2024).

Understanding greenhouse gas fluxes is essential for identifying regional sources and sinks, particularly in understudied regions like Africa (Ernst et al., 2024; Jiang et al., 2025; Saunois et al., 2024; Tian et al., 2024; Valentini et al., 2014). The African greenhouse gas budget is of interest because of Africa's large area (about 30 million km²), its rapid population increase and land use changes (Ernst et al., 2024). While Africa is a known carbon dioxide source (Ernst et al., 2024), major

<footnote><sup>a</sup> Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden</footnote>

<footnote><sup>b</sup> Institut Sénégalais de Recherches Agricoles, Dakar, Senegal</footnote>

<footnote><sup>c</sup> CIRAD, UMR Eco&Sols, Dakar, Senegal</footnote>

<footnote><sup>d</sup> Eco&Sols, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France</footnote>

<footnote><sup>e</sup> Université Cheikh Anta Diop, Faculté des Sciences et Techniques, Dakar, Senegal</footnote>

<footnote><sup>f</sup> LMI IESOL, Centre IRD-ISRA de Bel Air, Dakar, Senegal</footnote>

<footnote><sup>g</sup> Université de Toulouse, CNRS, IRD, LAERO, Toulouse, France</footnote>

<footnote>* Correspondence to: Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, SE-223 62, Lund, Sweden.
E-mail address: aleksander.wieckowski@nateko.lu.se (A. Wieckowski).</footnote>
knowledge gaps remain regarding fluxes of the other greenhouse gases and their drivers (Feng et al., 2020; Tian et al., 2020). Key drivers in semi-arid savannas of Africa include soil moisture, temperature and vapor pressure deficit, which regulate biological processes underlying gas exchange (Chen et al., 2024; Imer et al., 2013; Maier et al., 2022; Poblador et al., 2017). Yet, studies on these drivers for methane and nitrous oxide in African ecosystems are scarce, limiting understanding of their role in global budgets.

The Sahel is a key semi-arid savanna ecoregion located between the Sahara Desert and the humid Sudanian savanna. It is characterized by a dominant herbaceous understory, sparse tree and bush cover and ephemeral ponds, each playing a unique role in the greenhouse gas exchange (Agbohessou et al., 2023; Assouma et al., 2017; Gebremedhn et al., 2023; Verbruggen et al., 2021). Sahelian savannas are methane sinks (Song et al., 2024; Valentini et al., 2014), and act as both sources and sinks of nitrous oxide (Chapuis-Lardy et al., 2007; Savage et al., 2014), but the few existing estimates of flux magnitudes vary widely (Kim et al., 2016). Most studies focus on soils, and a comprehensive inventory across the landscape is lacking, leaving uncertainty about sources, sinks, drivers and management effects on the different ecosystem components (i.e. ground, trees, water bodies) (Grover et al., 2012; Machacova et al., 2021).

Sylvopastoralism dominates the land use, with herbaceous biomass accumulating during the short rainy season sustaining livestock all year (Diatta et al., 2024). This reliance makes local livelihood vulnerable to overgrazing and rainfall (Gebremedhn et al., 2023; Verbruggen et al., 2021). Grazing also modifies soil nitrogen, plant biomass and species composition and soil organic carbon content and contributes to manure deposition and trampling, influencing greenhouse gas fluxes through multiple mechanisms (Assouma et al., 2019; Butterbach-Bahl et al., 2020; Gebremedhn et al., 2023; Gebremedhn et al., 2025; Tang et al., 2019; Wieckowski et al., 2024). Previous studies of greenhouse gas fluxes in Sahelian sylvopastoral systems have primarily focused on specific land-use practices, are short-term snapshots in time, or focus on particular greenhouse gasses (Agbohessou et al., 2024; Agbohessou et al., 2023; Assouma et al., 2019; Delon et al., 2017).

Water bodies are another critical yet understudied component (Borges et al., 2015; Borges et al., 2022). In Africa, greenhouse gas fluxes from small seasonal ponds remain largely unquantified, as most studies focus on large lakes, rivers, or wetlands (Borges et al., 2022; Ernst et al., 2024; Lauerwald et al., 2023). These ephemeral ponds can be hotspots for methane and nitrous oxide emissions due to anaerobic conditions and organic matter inputs from livestock (Assouma et al., 2017; Bernard et al., 2025). Despite their small area, their methane emissions may offset soil uptake, and even the carbon dioxide assimilated by trees (Assouma et al., 2019; Wang et al., 2005). Understanding their role is essential for improving regional and global greenhouse gas budgets.

Trees also play a crucial yet poorly understood role in greenhouse gas fluxes (Bréchet et al., 2021). Beyond carbon sequestration, they influence greenhouse gas exchange in complex ways (Bréchet et al., 2025). Stems can act as methane sinks (Gauci et al., 2024; Machacova et al., 2016), but also emit or absorb nitrous oxide (Machacova et al., 2021). It has also been found that leaves from tropical trees emit nitrous oxide, but both take up and emit methane (Karim et al., 2024), take up nitrous oxide in temperate ecosystems (Machacova et al., 2024) and emit methane in boreal ecosystem (Tenhovirta et al., 2024). Additionally, trees influence soil greenhouse gas fluxes with higher methane and nitrous oxide emissions observed near trunks (Butterbach-Bahl et al., 2002), partly because tree roots influence soil aeration, moisture distribution, and microbial activity, all of which are key factors in greenhouse gas production and consumption (Fender et al., 2013). No studies have examined fluxes of methane and nitrous oxide in African savannas, and their environmental drivers remain unclear (Bréchet et al., 2025; Karim et al., 2024).

The aim of this study is to quantify greenhouse gas fluxes covering the seasonal dynamics for the most important landscape components of

a semi-arid savanna ecosystem in the Sahel. The following research questions are to be responded to:

1) What are the magnitudes and seasonal variability of greenhouse gas exchange between the atmosphere and the ground surface, trees, and water ponds?

2) Which environmental variables (soil and air temperature, soil water content, photosynthetically active radiation, and vapor pressure deficit) drive temporal variability in greenhouse gas exchange across different landscape components?

3) How does grazing affect ground-level greenhouse gas exchange in this ecosystem?

# 2. Materials and methods

## 2.1. Site description

The study took place at the Dahra field site in the Sahelian zone of Senegal (15°24'10"N, 15°25'56"W, elevation 40 m) (Fig. 1). The area is a grazed semi-arid savanna with a short rainy season (July-mid October) and a ~9 month dry season (Tagesson et al., 2015). Tree cover is ~3 % (Rasmussen et al., 2011), dominated by *Balanites aegyptiaca*, *Vachellia tortilis* and *Senegalia Senegal*. Herbaceous vegetation consists mainly of annual C₄ grasses (e.g. *Cenchrus biflorus*, *Eragrostis tremula*, *Aristida adscensionis*) (Gebremedhn et al., 2023). The soil is sandy luvic arenosol with negligible amounts of organic material and low clay content (Clay = 0.4 %, silt = 4.6 %, and sand = 95.0 %) (Tagesson et al., 2015). The site is equipped with two towers: one with an eddy covariance system for carbon dioxide, water and energy flux measurement, and one for meteorological variables.

## 2.2. Flux measurements

### 2.2.1. Measurement system and instrumentation

The campaigns spanned 2023 and 2024, covering both rainy and dry seasons. The first campaign (June and September 2023), captured the onset, peak, and end of the rainy season, with ten measurement cycles per position. Dry season fluxes were measured in November and December 2023, and May and July 2024, adding four cycles.

Greenhouse gas concentrations were measured with laser-based analyzers using optical-feedback cavity-enhanced absorption spectroscopy (LI-7810 for carbon dioxide and methane; LI-7820 for nitrous oxide (LI-COR Biosciences, United States)), connected to chambers via ¼-inch black polyethylene tubing. Four different types of chambers were used (Figure S1). #1) A transparent acrylic chamber (Plastmästar'n, Sweden) with a wall thickness of 5 mm, a height of 400 mm, and an internal base diameter of 290 mm was used for the carbon dioxide and methane measurements (connected to the LI-7810), while #2) a similar non-transparent chamber was used connected with the LI-7820 for nitrous oxide flux measurements to minimize temperature effects. #3) For tree stem flux measurements, steel round duct saddles with air-tight lids were used. These were of varying base sizes (diameter range: 10–31 cm; volume range 400 and 1950 cm³), depending on the diameter of the stem, sealed using 19 mm thick glued Armaflex. Branch fluxes were measured using #4) a polypropylene chamber with 5 mm thickness, 254 mm height and 222 mm base diameter (Thermo Fisher Scientific, US). Fans ensured headspace air mixing in ground and branch chambers. Stem chambers lacked fans due to their small sizes.

### 2.2.2. Ground flux measurements

Each chamber measurement lasted three minutes, followed by at least one minute of ventilation to ensure ambient gas concentration before chamber re-deployment. Net carbon dioxide flux (F~CO2~) was measured using the transparent chamber (#1), then covered with a dark hood to measure respiration. Gross primary productivity (GPP) was calculated as the absolute difference between F~CO2~ and Respiration.
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Location of the study sites. Map on the right depicts location of the site within Senegal, Africa. Map on the left shows the location of the eddy covariance and meteorological towers and the chamber measurements sampling locations.</figcaption></figure>

Methane flux ($F_{CH4}$) measurements were taken during the dark phase to minimize the effect of chamber heating. The nitrous oxide fluxes ($F_{N2O}$) were then measured with the non-transparent chamber (#2).

Ground fluxes were measured at four different locations (Fig. 1): (1) 12 plots along a 1.1 km transect in the open savanna, (2) five plots randomly placed in a 200 m² fenced ungrazed area established in 2021 (a subscript ungrazed is hereinafter used for these fluxes), (3) at ~20 cm distance from the tree trunks (near), at the canopy edge (mid) and three meters outside of the canopy (far) of ten different trees (five *Vachelia tortillis* five *Balanites aegyptica*), and (4) at plots located with three meter intervals along 15-m long transects perpendicular and starting at the shallow water at the shore for two different ephemeral ponds. Soil volumetric water content (%Vol) and soil temperature (°C) at 0–5 cm depth were also measured using WET150 Multi-Parameter soil sensor (Delta-T Devices, United Kingdom).

### 2.2.3. Tree flux measurements

Chambers were deployed on the ten trees for three minutes per measurement, with one-minute ventilation between cycles. For the stem flux measurements (stem), a steel round duct saddle (#3) was placed on each of the trees by strapping them to the stems at varying heights (between 30 and 190 cm). For the branch measurement (branch), branches (consisting of both foliage and woody stem) were put inside a transparent branch chamber (#4) which was sealed with a teflon foil to prevent gas leakage. Following transparent measurements, branch respiration was measured by covering the chambers with a dark cover. Branch GPP was calculated as the absolute difference between $F_{CO2-branch}$ and Respiration$_{branch}$.

Branch and leaf areas were estimated to convert concentrations to fluxes (Machacova et al., 2016). Branches placed on a referenced grid were photographed from above. The images were subsequently processed using OpenCV (Bradski, 2000), to segment and calculate projected area. Average branch diameter was derived from projected area and length using ImageJ (vers. 1.52a, National Institutes of Health, Bethesda Maryland, USA) (Machacova et al., 2024), assuming cylindrical shape (Gorgolewski et al., 2022). Leaves were segmented in OpenCV to calculate the leaf projected area. Leaves of *Balanites aegyptica* are amphistomatic, while leaves of *Vachelia tortillis* are hypostomatic (Mashile and Tshisikhawe, 2017), therefore a one-sided projected leaf

area of exchange for *Vachelia* and two-sided leaf area for *Balanites* was used. Total surface area was the sum of leaf and branch areas.

### 2.3. Flux calculations

Greenhouse gas fluxes were calculated using least-square linear fits of concentration time series. The first 15 s were discarded (Johannesson et al., 2024), and the optimal time series length to thereafter be included was found to be 30 s (Supplementary subsection S2). Slopes of the linear fits were converted to fluxes following Machacova et al. (2016). Minimum detectable thresholds were calculated per Christiansen et al. (2015); and no carbon dioxide fluxes, 4 % of the methane fluxes, and 0.3 % of the nitrous oxide fluxes were excluded due to being below the minimum detectable thresholds.

### 2.4. Statistical analyses

#### 2.4.1. Impact of grazing and tree proximity on greenhouse gas fluxes

All flux datasets were non-normal (Shapiro-Wilk test), thus linear mixed-effects models were applied (Lindstrom and Bates (1988), using statsmodels Python package v 0.14.1 (Seabold and Perktold, 2010). Specifically: 1) for evaluating the effect of grazing treatment (open grazed savanna vs. ungrazed), modelled fluxes were modelled as a function of treatment with measurement cycle included as a random effect. 2) For assessing the effect of tree proximity (near, mid, far) on the ground fluxes, linear mixed-effects models were used similarly, with tree proximity as a fixed effect and measurement cycle as a random effect. 3) For evaluating the effect of tree species (*Vachelia tortillis* vs *Balanites aegyptica*), fluxes were modelled as a function of tree species with measurement cycle as a random effect, for each position of the chamber (i.e. branches, stems and tree proximities). Pairwise comparisons were performed by rotating reference categories to extract sizes and p-values for specific differences while properly accounting for repeated measures. Significance was set at *p* < 0.05. Ground carbon dioxide fluxes were also compared with eddy covariance measurements to evaluate their consistency (Supplementary subsection S3).
### 2.4.2. Relationships between greenhouse gas fluxes and environmental variables

Environmental drivers of temporal variability in the greenhouse gas fluxes was analysed using soil water content and soil temperature measured simultaneously with the chamber measurements, and with data from the meteorological tower (Tagesson et al., 2015). From the meteorological tower, 15-minute averages of 2 m air temperature (°C), -0.10 m soil temperature (°C), -0.05 m soil water content (% Vol), incoming photosynthetically active radiation (µmol m⁻² s⁻¹), and 2 m vapor pressure deficit (hPa) were used. Moreover, the normalised difference vegetation index (NDVI) was calculated from Red and near-infrared reflectance measured at 10.5 m. Spearman correlations were computed between fluxes and these environmental drivers.

## 3. Results

### 3.1. Ground surface greenhouse gas fluxes

#### 3.1.1. Open grazed savanna

##### 3.1.1.1. Carbon dioxide.
Ground carbon dioxide fluxes showed a clear seasonal pattern with initial emission burst at the onset of the rainy season (Fig. 3), followed by increasing carbon dioxide uptake until a three week long dry spell marked by low NDVI, soil water content and no rainfall (Figs. 2–3). After subsequent short rainfalls, $F_{CO2}$, GPP and Respiration rose again before all fluxes declined during the dry season (Fig. 3). During the rainy season GPP (mean ± standard deviation: 1394.1 ± 1284.2 mg m⁻² h⁻¹) exceeded respiration (620.5 ± 446.5 mg m⁻² h⁻¹) resulting in a net $CO2$ uptake (-612.1 ± 1043.2 mg m⁻² h⁻¹) (Table S2). Respiration correlated positively with soil water content (r = 0.73) and negatively with soil temperature (r = -0.34), and GPP showed similar relationships (r = 0.41 and -0.21 respectively). In the dry season, $F_{CO2}$ was slightly positive (30.5 ± 12.1 mg m⁻² h⁻¹) (Table S2), and strongly negatively correlated with vapor pressure deficit and air temperature (Table 2).

##### 3.1.1.2. Methane.
The ground surface was a net methane sink (annual average: -2.9 ± 12.8 µg m⁻² h⁻¹) (Fig. 3, Table 3), but with some seasonal variability: it was near zero during the early rainy season and dry spell, followed by brief emission pulses and larger uptake at the rainy season peak. Average uptake was -5.1 ± 8.7 µg m⁻² h⁻¹ in the dry season and -1.8 ± 13.2 µg m⁻² h⁻¹ in the rainy season (Table S2). No significant correlations were found with environmental variables except a weak relationship with tower-measured soil temperature (Tables 1–2).

##### 3.1.1.3. Nitrous oxide.
The open grazed savanna was a nitrous oxide source (186.7 ± 168.7 µg m⁻² h⁻¹), and it showed a seasonal pattern, with low emissions during the dry season (92.1 ± 51.7 µg m⁻² h⁻¹) and increasing emissions following the first rainfall (Fig. 3). However, unlike the rapid pulse observed for carbon dioxide, the rise in nitrous oxide emissions was more gradual, continuing until the next rainfall event (Fig. 3). Nitrous oxide fluxes remained positive year-round, with higher emissions during the rainy season (202.7 ± 154.7 µg m⁻² h⁻¹) and peaks during the early August dry spell (275.0 ± 143.4 µg m⁻² h⁻¹) (Fig. 3). It correlated positively with soil temperature (r = 0.44) (Table 1), air temperature (r = 0.33), vapor pressure deficit (r = 0.38), and photosynthetically active radiation (r = 0.17), and negatively with soil water content (r = -0.31) (Table 2).

#### 3.1.2. Greenhouse gas fluxes of the pond transects

##### 3.1.2.1. Carbon dioxide.
Net exchange of carbon dioxide across the pond transects showed positive emissions during the rainy season from both pond surfaces and adjacent soils, with no clear pond distance

relationship (Fig. 4). In the dry season, fluxes decreased across all transect positions, and the dried-up ponds showed low carbon dioxide emissions, comparable to surrounding savanna soils (Figs. 3–4).

##### 3.1.2.2. Methane.
The ephemeral ponds were consistently strong sources of methane, with high emissions during the rainy season (191 ± 247 mg m⁻² h⁻¹) (Fig. 4, Supplementary Figure S4). However, emissions showed a clear spatial gradient, rapidly declining and turning into an uptake within a few meters from the edge of the pond (Fig. 4). Seasonal changes were evident not only in the magnitude of methane emissions but also in this gradient (Supplementary Figure S5). During the rainy season, the source-sink transition was sharp, with fluxes dropping by over two orders of magnitude within 4–6 m from the pond shore. During the dry season, the now dried up pond bottom showed small but positive emissions, while the surrounding soil showed a weak uptake (Fig. 4).

##### 3.1.2.3. Nitrous oxide.
Nitrous oxide emissions showed clear spatial and seasonal variation (Fig. 4). Emissions from the pond water averaged 133.1 ± 106.3 µg m⁻² h⁻¹, whereas the highest fluxes (430.6 ± 566 µg m⁻² h⁻¹) occurred 2–4 m from the shore during the rainy season (Fig. 4, Supplementary figure S4). Beyond ~6 m, emissions declined to levels similar to grazed savanna soils (Figs. 3, 4). In the dry season, emissions from ponds and shore zones dropped markedly, and the pattern with highest fluxes at the ponds observed in the rainy season disappeared (Fig. 4).

#### 3.1.3. Impact of grazing on the greenhouse gas fluxes

##### 3.1.3.1. Carbon dioxide.
Gross primary productivity was significantly higher in the open grazed savanna (1394 ± 1290 mg m⁻² h⁻¹) than in the ungrazed area (821 ± 900 mg m⁻² h⁻¹) (Fig. 5, Table 3), while Respiration showed no significant difference (Fig. 5, Table 3). Consequently, the grazed savanna was a net carbon dioxide sink (-538 ± 1003 mg m⁻² h⁻¹), whereas the ungrazed area was a net source (89.9 ± 889 mg m⁻² h⁻¹) (Fig. 5, Table 3). The ungrazed area had slightly cooler (34.1 ± 4.2°C vs 35.6 ± 3.4°C) and drier (6.2 ± 3.4 % vs 7.3 ± 4.1 %) soils (Fig. 5). Both areas showed strong carbon dioxide uptake during the rainy season, but GPP was consistently higher in the grazed area (Fig. 3, Supplementary figure S5). During the rainy season dry spell, and shortly afterwards, the ungrazed area changed from a net carbon dioxide sink to a source, unlike the open grazed savanna (Supplementary Figure S5). In the dry season, GPP approached zero in both areas, and the net carbon dioxide exchange fluxes were dominated by Respiration (Figure 3, S5). Environmental drivers of Respiration were similar between the two areas (Tables 1, 2). For GPP, it was positively correlated with soil temperature in the ungrazed area, while it was negatively correlated with soil temperature, vapor pressure deficit, and air temperature in the open grazed savanna (Tables 1–2).

##### 3.1.3.2. Methane.
Methane uptake was significantly larger in the ungrazed area (-8.1 ± 10.2 µg m⁻² h⁻¹) than in the open grazed savanna (-2.9 ± 12.8 µg m⁻² h⁻¹), especially during the dry season (Fig. 5, Table 3; Table S2). However, no clear seasonal patterns were seen in the ungrazed area (Supplementary Figure S5). Weak correlations were seen between methane flux and soil temperature in the open grazed savanna, and with photosynthetically active radiation and vapor pressure deficit in the ungrazed area (Tables 1, 2).

##### 3.1.3.3. Nitrous oxide.
Fluxes of nitrous oxide did not differ significantly between the open grazed savanna and the ungrazed area (Fig. 5, Table 3). They remained positive year-round in both areas, with higher values during the rainy season (Figure 3 and S5). In the ungrazed area, nitrous oxide fluxes correlated negatively with soil water content (r = -0.45) and positively with soil temperature (r = 0.62), but these
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Time series of the carbon dioxide (CO₂) exchange fluxes (FₐCO₂) and the environmental variables at the Dahra field site; (a) daily means (± standard deviation) of FₐCO₂ measured by chamber (blue) and eddy covariance (red) methods, (b) daily sum of rainfall (mm), (c) 15-minute average of soil water content (SWC) at 5 cm depth, (d) daily mean of soil temperature at 10 cm depth (Tₐsoil), (e) daily mean of air temperature (Tₐair), (f) daily mean vapor pressure deficit (VPD), (g) daily mean incoming photosynthetically active radiation (PAR), (h) daily mean normalized difference vegetation index (NDVI).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 3. Time series of the greenhouse gas fluxes at the open grazed savanna. Daily means (± one standard deviation) of: a) net carbon dioxide flux (FCO2) (blue), gross primary production (GPP) (pink), Respiration (orange), (b) methane fluxes (FCH4), and (c) nitrous oxide fluxes (FN2O).</figcaption></figure>

correlations were not significant in the open grazed savanna (Table 2).

### 3.1.4. Effect of tree proximity on ground-level greenhouse gas fluxes

Tree proximity influenced net exchange of carbon dioxide, with

emissions near the tree stems (near: 112.7 ± 984.3 mg m⁻² h⁻¹) and uptake at the edge of canopy (mid: -101.6 ± 1001.9 mg m⁻² h⁻¹) and in the open savanna (far: -64.8 ± 1014.4 mg m⁻² h⁻¹) (Fig. 6). GPP was similar across positions, while Respiration was higher under
<caption>**Table 1**</caption>

Spearman correlation coefficients between spatiotemporal variability in greenhouse gas fluxes and locally measured soil temperature ($T_{soil}$) and soil water content (SWC) at 0–5 cm depth. For correlation with stem and branch fluxes, SWC and $T_{soil}$ measurements were done underneath the trees. $F_{CO2}$ is a net carbon dioxide exchange, GPP is gross primary productivity.

<table><thead><tr><th rowspan="2">Flux</th><th colspan="2">Ground fluxes at the grazed site (n = 488)</th><th colspan="2">Ground fluxes at the ungrazed site (n = 55)</th><th colspan="2">Stem fluxes (n = 107)</th><th colspan="2">Branch fluxes (n = 109)</th></tr><tr><th>SWC</th><th>$T_{soil}$</th><th>SWC</th><th>$T_{soil}$</th><th>SWC</th><th>$T_{soil}$</th><th>SWC</th><th>$T_{soil}$</th></tr></thead><tbody><tr><td>$F_{CO2}$</td><td>-0.09</td><td>-0.03</td><td>0.76<sup>***</sup></td><td>-0.7<sup>***</sup></td><td>NA</td><td>NA</td><td>0.25<sup>**</sup></td><td>-0.25<sup>**</sup></td></tr><tr><td>GPP</td><td>0.41<sup>***</sup></td><td>-0.21<sup>*</sup></td><td>-0.08</td><td>0.38<sup>*</sup></td><td>NA</td><td>NA</td><td>0.29<sup>**</sup></td><td>-0.26<sup>**</sup></td></tr><tr><td>Respiration</td><td>0.73<sup>***</sup></td><td>-0.34<sup>***</sup></td><td>0.6<sup>**</sup></td><td>-0.47<sup>***</sup></td><td>0.13</td><td>-0.33<sup>**</sup></td><td>0.24<sup>**</sup></td><td>-0.17<sup>*</sup></td></tr><tr><td>$F_{CH4}$</td><td>0.05</td><td>0.020</td><td>-0.22</td><td>0.15</td><td>0.29<sup>**</sup></td><td>-0.20</td><td>-0.03</td><td>-0.02</td></tr><tr><td>$F_{N2O}$</td><td>0.03</td><td>0.44<sup>***</sup></td><td>-0.45<sup>***</sup></td><td>0.62<sup>***</sup></td><td>0.07</td><td>-0.14</td><td>0.01</td><td>-0.02</td></tr></tbody></table>

<caption>**Table 2**</caption>

Spearman correlation coefficients between spatiotemporal variability in greenhouse gas fluxes and environmental variables (Soil temperature [$T_{soil}$], Soil water content [SWC], Air temperature [$T_{air}$], photosynthetically active radiation [PAR]) measured by the sensors mounted on the meteorological tower. $F_{CO2}$ is a net carbon dioxide exchange, GPP is gross primary productivity, $F_{CH4}$ and $F_{N2O}$ are methane and nitrous oxide fluxes respectively. Footnotes by fluxes indicate the location, i.e. inside the ungrazed area (ungrazed), on the tree branches (branch) and tree stems (stem).

<table><thead><tr><th></th><th>Flux</th><th>$T_{soil}$</th><th>SWC</th><th>$T_{air}$</th><th>VPD</th><th>PAR</th></tr></thead><tbody><tr><td rowspan="5">Ground at the open grazed savanna</td><td>$F_{CO2}$</td><td>-0.16<sup>*</sup></td><td>-0.15<sup>*</sup></td><td>-0.14<sup>*</sup></td><td>-0.18<sup>**</sup></td><td>0.42<sup>***</sup></td></tr><tr><td>GPP</td><td>-0.28<sup>***</sup></td><td>0.28<sup>***</sup></td><td>-0.28<sup>***</sup></td><td>-0.43<sup>***</sup></td><td>0.29<sup>***</sup></td></tr><tr><td>Respiration</td><td>-0.31<sup>***</sup></td><td>0.68<sup>***</sup></td><td>-0.38<sup>***</sup></td><td>-0.6<sup>***</sup></td><td>0.02</td></tr><tr><td>$F_{CH4}$</td><td>-0.14<sup>*</sup></td><td>0.12</td><td>-0.06</td><td>-0.05</td><td>0.09</td></tr><tr><td>$F_{N2O}$</td><td>0.34<sup>***</sup></td><td>-0.31<sup>**</sup></td><td>0.33<sup>***</sup></td><td>0.38<sup>***</sup></td><td>0.17<sup>*</sup></td></tr><tr><td rowspan="5">Ground at the ungrazed plot</td><td>$F_{CO2\_ungrazed}$</td><td>-0.05</td><td>0.64<sup>***</sup></td><td>0.08</td><td>-0.29<sup>*</sup></td><td>0.85<sup>***</sup></td></tr><tr><td>GPP<sub>ungrazed</sub></td><td>-0.31<sup>*</sup></td><td>0.16</td><td>0.26</td><td>-0.18</td><td>0.47<sup>**</sup></td></tr><tr><td>Respiration<sub>ungrazed</sub></td><td>-0.23</td><td>0.73<sup>***</sup></td><td>-0.15</td><td>-0.46<sup>***</sup></td><td>-0.63<sup>***</sup></td></tr><tr><td>$F_{CH4\_ungrazed}$</td><td>0.15</td><td>-0.25</td><td>0.10</td><td>0.28<sup>*</sup></td><td>0.30<sup>*</sup></td></tr><tr><td>$F_{N2O\_ungrazed}$</td><td>0.12</td><td>-0.39<sup>*</sup></td><td>0.28<sup>*</sup></td><td>0.47<sup>***</sup></td><td>0.74<sup>***</sup></td></tr><tr><td rowspan="5">Branches</td><td>$F_{CO2\_branch}$</td><td>0.22</td><td>0.15</td><td>-0.27<sup>**</sup></td><td>-0.32<sup>***</sup></td><td>0.3<sup>***</sup></td></tr><tr><td>GPP<sub>branch</sub></td><td>-0.17</td><td>0.2</td><td>-0.27<sup>**</sup></td><td>-0.3<sup>**</sup></td><td>0.16</td></tr><tr><td>Respiration<sub>branch</sub></td><td>-0.03</td><td>0.09</td><td>-0.18</td><td>-0.2<sup>*</sup></td><td>-0.19</td></tr><tr><td>$F_{CH4\_branch}$</td><td>0.07</td><td>0.14</td><td>0.1</td><td>0.03</td><td>-0.01</td></tr><tr><td>$F_{N2O\_branch}$</td><td>0.05</td><td>0.1</td><td>-0.01</td><td>-0.07</td><td>0.01</td></tr><tr><td rowspan="3">Stems</td><td>Respiration<sub>stem</sub></td><td>0.04</td><td>0.13</td><td>0.02</td><td>0.01</td><td>0.12</td></tr><tr><td>$F_{CH4\_stem}$</td><td>0.02</td><td>0.10</td><td>0.03</td><td>0.01</td><td>0.05</td></tr><tr><td>$F_{N2O\_stem}$</td><td>-0.22</td><td>0.10</td><td>-0.09</td><td>-0.17</td><td>-0.11</td></tr></tbody></table>

canopies (near: 802.4 ± 736 mg m⁻² h⁻¹) than open savanna (far: 578.0 ± 581 mg m⁻² h⁻¹, respectively) (Fig. 6). Methane was generally emitted directly near the trees (near: 15.9 ± 29 µg m⁻² h⁻¹) and taken up in the open savanna (far: -4.92 ± 7.9 µg m⁻² h⁻¹) (Fig. 6). Nitrous oxide emissions were also higher close to the trees (near: 230.0 ± 196.3 µg m⁻² h⁻¹) than further away (mid: 191.5 ± 176.2 µg m⁻² h⁻¹, far: 187 ± 168.2 µg m⁻² h⁻¹) (Fig. 6). Soil water content was higher near trees (near: 8.6 ± 6.2 %) than in the open savanna (far: 7.5 ± 4.8 %) (Fig. 6). Tree species had no significant effect between any of the measured positions between the *Vachellia tortillis* and the *Balanites aegyptica* according to the linear mixed-effects models.

## 3.2. Greenhouse gas fluxes of tree stems and branches

### 3.2.1. Carbon dioxide

Tree stems had an average stem respiration rate of 288.8 ± 296.3 mg m⁻² h⁻¹ (Table 3), peaking in the early dry season (Fig. 7; Table S2). It correlated negatively with soil temperature (r = -0.33), but showed no other significant relationships. It was also significantly higher for the *Vachellia tortillis* than the *Balanites aegyptica* (346.1 ± 340.7 vs 202.6 ± 149.8 mg m⁻² h⁻¹) (Supplementary Figure S6).

Branch carbon dioxide fluxes followed a similar seasonal pattern as the fluxes of the ground (Figs. 8, 3) They were high during the rainy season (GPP: 712.0 ± 626.2 mg m⁻² h⁻¹; Respiration: 189

± 245.3 mg m⁻² h⁻¹) (Table S2), with the highest during the growing season peak (corresponding to peak NDVI; Figs. 2, 5). During the dry season, both GPP and Respiration declined (GPP: 152.6 ± 203.1 mg m⁻² h⁻¹; Respiration: 116.3 ± 297.4 mg m⁻² h⁻¹) (Table S2). Both GPP and Respiration of branches correlated positively with soil water content and negatively with soil temperature and vapor pressure deficit (Tables 1–2).

### 3.2.2. Methane

Stems were on average emitting methane with (1.4 ± 3.2 µg m⁻² h⁻¹) (Table 3; Fig. 7), but with no clear seasonal pattern. A weak positive correlation was found with soil water content (r = 0.29), but none with the other environmental variables (Tables 1–2). Stem methane fluxes were unrelated to measurement height (Fig. S7). Branches, in contrast, had a methane uptake (-5.2 ± 16.3 µg m⁻² h⁻¹; Fig. 8, Table 3), but also without seasonal patterns. No significant correlations were seen with any of the environmental drivers (Tables 1–2).

### 3.2.3. Nitrous oxide

Tree stems were emitting nitrous oxide, with an average flux of 4.1 ± 9.0 µg m⁻² h⁻¹ (Table 3; Fig. 7). Emissions peaked at the beginning of the rainy season (Fig. 7), but showed no significant correlations with environmental variables (Tables 1–2). No effect of height on the stem were seen on the emissions (Figure S7). Branches were also emitting

<footnote>* significant at p < 0.050</footnote>

<footnote>** significant at p < 0.01</footnote>

<footnote>*** significant at p < 0.001</footnote>

<footnote>* significant at p < 0.05</footnote>

<footnote>** significant at p < 0.01</footnote>

<footnote>*** significant at p < 0.001</footnote>
<caption>**Table 3**</caption>

Summary of the measured greenhouse gas fluxes across the different landscape components. The values are the mean ± one standard deviation taken of the full time series. F<sub>CO2</sub> is net exchange of carbon dioxide, GPP is gross primary production averaged from rainy season, and F<sub>CH4</sub> and F<sub>N2O</sub> are the methane and nitrous oxide fluxes. Fluxes are reported in mg m<sup>-2</sup> h<sup>-1</sup> for F<sub>CO2</sub> and µg m<sup>-2</sup> h<sup>-1</sup> for F<sub>CH4</sub> and F<sub>N2O</sub>. “X” denotes no measurements conducted on photosynthesizing components. Near, mid, and far denote relative distance from the tree stem (i.e. next to the tree stem, at the edge of the canopy, outside of the canopy respectively).

<table><thead><tr><th>Component</th><th>F<sub>CO2</sub></th><th>GPP</th><th>Respiration</th><th>F<sub>CH4</sub></th><th>F<sub>N2O</sub></th></tr></thead><tbody><tr><td>Open grazed savanna ground</td><td>-538 ± 1003</td><td>1394 ± 1290</td><td>567 ± 459</td><td>-2.9 ± 12.8</td><td>186.7 ± 168.7</td></tr><tr><td>Ungrazed ground</td><td>89.9 ± 889</td><td>821 ± 900</td><td>601 ± 492</td><td>-8.1 ± 10.2</td><td>193.2 ± 210.7</td></tr><tr><td>Water ponds</td><td>X</td><td>X</td><td>395.5 ± 311.8</td><td>191206 ± 246872</td><td>149.7 ± 113.1</td></tr><tr><td>Tree stems</td><td>X</td><td>X</td><td>288.8 ± 296.3</td><td>1.4 ± 3.2</td><td>4.1 ± 9.0</td></tr><tr><td>Tree branches</td><td>-426.7 ± 532</td><td>629.6 ± 616.3</td><td>178 ± 255.2</td><td>-5.2 ± 16.3</td><td>10.5 ± 52.9</td></tr><tr><td>Ground near tree</td><td>112.7 ± 984</td><td>689.8 ± 1158</td><td>802.4 ± 736</td><td>15.9 ± 29</td><td>230 ± 196.3</td></tr><tr><td>Ground at mid-distance tree</td><td>-101.6 ± 1001</td><td>822.9 ± 1399</td><td>721.3 ± 714</td><td>2.1 ± 17.4</td><td>191.5 ± 176.2</td></tr><tr><td>Ground at far distance tree</td><td>-64.8 ± 1014</td><td>642.8 ± 1175</td><td>578 ± 581</td><td>-4.9 ± 7.9</td><td>187 ± 168.2</td></tr></tbody></table>

nitrous oxide, with an average flux of 10.5 ± 52.9 µg m<sup>-2</sup> h<sup>-1</sup> (Fig. 8, Table 3), but again without clear seasonal patterns (Fig. 8) or significant relationships with environmental drivers (Tables 1–2).

# 4. Discussion

## 4.1. Greenhouse gas fluxes of the open grazed savanna and their drivers

Seasonal dynamics in ground GPP and Respiration, and their correlation with soil water content, vapor pressure deficit, and temperature, were expected and is consistent with previous findings for semi-arid savannas (Brümmer et al., 2008; Flores-Rentería et al., 2023; Owusu-Prempeh et al., 2024; Tarin et al., 2020; Wachiye et al., 2020; Zhang et al., 2020). Methane uptake also followed the typical pattern of oxic, unsaturated soils acting as sinks via methanotrophy (Dutaur and Verchot, 2007), but showed no correlation with environmental drivers. This may reflect high spatial variability even from this seemingly homogeneous landscapes (McDaniel et al., 2017), or deeper processes at the rhizosphere-groundwater interface, rather than by variations in surface-level methanotrophy. Also, a major limitation with this study was the employment of manual chamber measurements for just one single year. Manual chamber measurements cannot fully capture the large spatial and temporal variability of the greenhouse gas exchange of these ecosystems; they mainly take snapshots in both space and time, due to their small footprint sizes and short term deployment time (Pavelka et al., 2018). They thereby miss to capture important spatiotemporal dynamics. Future studies, employing long-term automatic chamber measurements at these different landscape components, would help capturing their full temporal variability; including diurnal, seasonal, and interannual dynamics. Also, combining microbial and isotopic analyses of subsurface soil layers and root zones would be valuable to clarify mechanisms responsible for the greenhouse gas exchange fluxes of these ecosystems.

Nitrous oxide emissions were dominated by nitrification, as soil moisture never reached levels favouring denitrification (Agbohessou et al., 2023; Zhang et al., 2023). Emissions rose gradually after the first rainfall, likely due to substrate accumulation during the dry season

(Delon et al., 2017), and, surprisingly, continued to rise during the dry spell of the rainy season despite decreasing soil water content levels. This suggests drought-adapted nitrifiers and possibly enhanced nitrification under rising soil temperatures (Heinzle et al., 2023; Hu et al., 2016; Zhang et al., 2023; Zhang et al., 2019). Emissions dropped during the prolonged dry season, indicating suppression of microbial activity and substrate depletion (Barrat et al., 2021). These patterns underscore the need to capture intra-seasonal variability, as short-term pulses and unexpected patterns during dry-spell may otherwise be missed.

## 4.2. Greenhouse gas fluxes of the ephemeral pond transects

Carbon dioxide fluxes along pond transects indicate that ponds have little effect on the overall savanna carbon dioxide balance, consistent with Assouma et al. (2017). In contrast, methane emissions from ephemeral ponds were very high (191 ± 247 mg m<sup>-2</sup> h<sup>-1</sup>), far exceeding typical freshwater (~10 mg m<sup>-2</sup> h<sup>-1</sup>) (Bastviken et al., 2011; Deemer et al., 2016) and wetland emissions (up to ~35 mg m<sup>-2</sup> h<sup>-1</sup>) (Xiao et al., 2024), and although lower than manure lagoons (1–2 g m<sup>-2</sup> h<sup>-1</sup>) (Hamilton et al., 2006; Todd et al., 2011) they stand out as exceptionally large for any natural water body. Ephemeral ponds cover only ~0.06 % of the area of the Ferlo region, where Dahra is located (Mishra et al., 2020), and upscaling using this area fraction, yields an annual budget of ~2.5 kg CH<sub>4</sub> ha<sup>-1</sup> y<sup>-1</sup>. This is approximately 10 times higher than the mean sink of the soil measured at Dahra site (-254 g CH<sub>4</sub> ha<sup>-1</sup> y<sup>-1</sup>), and higher than the assumed dryland methane sink of ~2 kg CH<sub>4</sub> ha<sup>-1</sup> y<sup>-1</sup> (Castaldi et al., 2006; Song et al., 2024). This suggests that these ephemeral ponds, despite taking up such a small area, can substantially influence the methane budget of semi-arid savannas of the Sahel. However, only two ponds were included in this study and they may not represent the full variability of ephemeral water bodies across the region. Future studies should ensure to measure several ponds across the Sahel with different environmental conditions (in a rainfall gradient; different grazing intensity; and various pond sizes) to confirm high emissions.

Nitrous oxide emissions showed non-uniform patterns along transects, likely due to shifting anoxic-oxic conditions (Chen et al., 2022; Mengis et al., 1997). Fluctuating moisture promotes both nitrification and denitrification (Bateman and Baggs, 2005; Pinto et al., 2021), making riparian zones important nitrous oxide hotspots, even in arid landscapes.

## 4.3. Impact of grazing on the greenhouse gas exchange

Grazing affected greenhouse gas fluxes differently for each gas, reflecting complex interactions among vegetation cover, soil properties, and microclimate (Mgalula et al., 2021; Tang et al., 2019). Lower soil temperature in the ungrazed area suggests insulation by standing dead litter (Fekete et al., 2016; Qi et al., 2024), whereas the lower soil water content may be caused by rainfall interception by standing dead litter (Acharya et al., 2017; Xie et al., 2022). These conditions, along with shading, possibly contributed to lower GPP compared to grazed plots, where compensatory growth enhances productivity (McNaughton, 1985; Tagesson et al., 2016). Despite microclimatic contrasts, respiration was similar, making the grazed savanna a stronger net carbon dioxide sink (Marston et al., 2017; Stevens et al., 2017).

Higher methane uptake in the ungrazed area likely reflects more favourable conditions for methanotrophy despite slightly lower soil moisture and temperature (Dijkstra et al., 2011; Hou et al., 2012; Wen et al., 2024; Yue et al., 2022). These effects may have been offset by trampling in the open grazed savanna, that reduced soil porosity and limited gas diffusion (Chen et al., 2011). Previously, it has been found that grazing may increase nitrous oxide emissions due to manure inputs (Assouma et al., 2017) and soil compaction (Bessou et al., 2010), or decrease them due to lower root biomass (Song et al., 2019), soil degradation and nutrient depletion (Assouma et al., 2017; Tang et al.,
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Heatmaps of carbon dioxide (F<sub>CO2</sub>), methane (F<sub>CH4</sub>) and nitrous oxide (F<sub>N2O</sub>) exchange with distance from the seasonal water ponds. The F<sub>CH4</sub> and F<sub>N2O</sub> fluxes are depicted in symmetrical logarithmic scale (i.e. showing both positive and negative values). White color indicates occasions with a missed measurement due to technical issues. Dry season measurements are from day of year 125 and 181, whereas remaining are from the rainy season.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Effect of grazing on greenhouse gas fluxes, soil water content (SWC) and soil temperature (T<sub>soil</sub>). The “Grazed” and the “Ungrazed” indicates fluxes from chamber measurements in the open grazed savanna and in the ungrazed area, respectively. All fluxes are expressed as medians (solid lines) of the measurements. Box boundaries represent 25th and 75th percentiles and whiskers 10th and 90th percentiles. Red diamonds indicate mean values. Different letters above the boxes indicate statistically significant differences between groups.</figcaption></figure>

2019; Yin et al., 2023).

4.4. Tree contribution to greenhouse gas fluxes

Stem respiration, which is assumed to be highest during the rainy
season (Levy and Jarvis, 1998) unexpectedly peaked at the start of the
dry season. This may reflect increased root activity as soils dry and roots
seek for remaining water (Simon, 2007), though further research is

needed to confirm this pattern. In addition, soils beneath trees acted as
carbon dioxide “hotspots”, likely due to the “fertile island” effect, i.e.
high carbon and nutrient concentrations under the tree due to tree litter
and animal excreta enhancing microbial activity (Eldridge et al., 2024;
Fall et al., 2012). Nevertheless, ecosystem-scale carbon dioxide uptake
during the dry season (Wieckowski et al., 2024) indicates that foliar
assimilation compensates for stem and soil emissions.

Tree stems were a consistent source of methane across seasons and
<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Effect of tree proximity on greenhouse gas fluxes, soil water content (SWC) and soil temperature (T<sub>soil</sub>). The position “near” indicates chamber placement next to the tree stem, “mid” is the edge of the canopy, while “far” is outside of the canopy. All fluxes are expressed as medians (solid lines) of the measurements. Box boundaries represent 25th and 75th percentiles and whiskers 10th and 90th percentiles. Red diamonds indicate mean values. Different letters above the boxes indicate statistically significant differences between groups.</figcaption></figure>

chamber heights, contrasting with global findings that trees often act as methane sinks (Gauci et al., 2024). It should be however noted that in this study, a single chamber was mounted per tree and height relationships with fluxes could differ along the stem profile within the single tree. Additionally, measurements were taken for two species and there are obviously more species in the Sahel, that may have a different effect on the fluxes. Nevertheless, according to authors’ knowledge, this is the

first evidence of stem methane emissions in semi-arid ecosystems, with the only comparable study reporting stem emissions being from an upland tropical forest (Welch et al., 2019). The tree density in Dahra is 27.2 trees ha<sup>-1</sup> (Buschinelli Carreño, 2024), which is representative for the Sahel (30.1 trees ha<sup>-1</sup>; Brandt et al., 2020). Following the methodology of Machacova et al. (2016), the estimate of mean stem area of trees in Dahra is 10.8 m<sup>2</sup> per tree. Thus, despite stem emission being 1.4
<figure><img src="image_9.png" /><figcaption>Fig. 7. Time series of stem greenhouse gas fluxes. Daily means (± one standard deviation) of stem a) respiration, (b) methane fluxes (FCH4), and (c) nitrous oxide fluxes (FN2O).</figcaption></figure>

± 3.2 µg m⁻² h⁻¹ and soil uptake being -2.9 ± 12.8 µg m⁻² h⁻¹, the small contribution of the tree stem area per ground area (294 m² vs 10 000 m²) leads to that these emissions have a minor contribution to the overall methane exchange of the savanna landscape.

Branches, in contrast, acted as methane sinks, likely via foliar methanotrophy (Gorgolewski et al., 2023; Putkinen et al., 2021; Sundqvist et al., 2012). Assuming a stable mean tree leaf area index of 0.4 (Do et al., 2008; Kahiu and Hanan, 2018), a 3 % canopy cover
<figure><img src="image_10.png" /><figcaption>Fig. 8. Time series of branch greenhouse gas fluxes. Daily means (± standard deviation) of branch: (a) net carbon dioxide (CO₂) flux (FₐCO₂) (blue), gross primary production (GPP) (pink), respiration (Respiration) (orange), (b) methane fluxes (FₐCH₄), and (c) nitrous oxide fluxes (FₐN₂O).</figcaption></figure>

(Tagesson, Fensholt, Guiro, et al., 2015), the landscape branch uptake of
would be ~624 µg ha⁻¹ h⁻¹, which offsets the stem emissions
(~412 µg ha⁻¹ h⁻¹), resulting in a near-neutral methane balance of the
trees. Thus, while the overall contribution of an average tree to the

landscape methane exchange budget is minor, trees can influence local
spatial variability of methane flux depending on factors such as tree size,
canopy cover, and leaf area index.

Methane was also emitted from soils adjacent to trees despite the
uptake in the open savanna. Given that the groundwater depth is lower than 25 m (Kane et al., 2013), methane may originate from anaerobic locations at these depths, and then be transported upwards, bypassing oxidizing soil layers via roots (Gauci et al., 2022), Alternatively, methane may be produced in the rhizosphere with the root exudates being the main carbon source (Bomberg et al., 2011; Girkin et al., 2018; Kimura et al., 1991). Given the low tree coverage (3 %) at the Dahra field site, these emissions also have a relatively small role in the overall savanna methane exchange budget (~13 % of the total ground methane sink (-21.3 mg ha⁻¹ h⁻¹ uptake in the open savanna vs 2.7 mg ha⁻¹ h⁻¹ emissions underneath the tree). However, in savanna ecosystems with a higher tree coverage this contribution could have a major impact, and our estimated methane tree mediated emissions may therefore be underestimated for the other parts of the Sahel.

Reported stem nitrous oxide emissions vary widely (between -0.25 and 138, µg m⁻² h⁻¹ (Welch et al., 2019; Daniel et al., 2023; Machacova et al., 2024), and observations in Dahra (4.1 ± 59 µg m⁻² h⁻¹) falls well within this range. Higher nitrous oxide fluxes beneath trees likely reflect increased nitrogen availability from root exudates, litter, and larger amounts of animal excreta (Fall et al., 2012; Sanon et al., 2007). Remarkably, branch emissions (10.5 ± 52.9 µg m⁻² h⁻¹) are the highest reported worldwide (-4.54–5.54 µg m⁻² h⁻¹) (Karim et al., 2024; Machacova et al., 2016; Machacova et al., 2021; Machacova et al., 2024; Timilsina et al., 2022). This could be due to the transport of nitrous oxide from the soil (Qin et al., 2024) as higher soil nitrous oxide fluxes were observed at the Dahra site than in these other studies (Karim et al., 2024; Machacova et al., 2016; Timilsina et al., 2022). Considering the importance of nitrous oxide emissions from foliage globally (Qin et al., 2024), current estimates might be too low if these large nitrous oxide emissions are representative also for other semi-arid regions.

## 5. Conclusions

This study provides the first integrated assessment of greenhouse gas fluxes from ground, trees and ephemeral ponds of a Sahelian savanna, including the influence of grazing. By capturing spatial and seasonal variability across these components, it offers a comprehensive overview of ecosystem greenhouse gas dynamics over a full annual cycle, which has not been yet applied in a semi-arid region. The findings highlight several overlooked processes that are critical for improving global greenhouse gas budgets, especially for semi-arid ecosystems which remain underrepresented or oversimplified in global assessments (IPCC, 2021; Saunois et al., 2024; Tian et al., 2020). The findings point to several overlooked factors. First, large methane emissions from ephemeral ponds, which may cause freshwater methane sources in drylands to be underestimated. Second, even though small in this ecosystem, tree-mediated methane and nitrous oxide fluxes and elevated soil emissions near trees indicate that trees may play a greater role in savanna greenhouse gas cycling than currently recognized. Third, grazing modifies carbon dioxide and methane exchange, underscoring the effect of management on greenhouse gas cycling. Finally, pronounced spatial and temporal variability across microhabitats and seasonal phases shows that simple biome-level parametrizations cannot capture real-world flux patterns. While this study provides detailed intra-seasonal dynamics, a major limitation is its single-year scope, daytime-only measurements and sampling of few numbers of ponds and trees. Future research should focus on long-term continuous monitoring of these different landscape components at an increased number of locations across the Sahel, to assure an improved understanding of the processes governing the greenhouse gas exchange of this important key semi-arid savanna ecoregion.

### CRediT authorship contribution statement

**Jonas Ardö:** Writing – review & editing, Supervision, Methodology, Investigation, Conceptualization.
**Patrik Vestin:** Writing – review &

editing, Supervision, Methodology, Investigation, Conceptualization.
**Więckowski Aleksander:** Writing – review & editing, Writing – original draft, Visualization, Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Olivier Roupsard:** Writing – review & editing.
**Seydina Ba:** Writing – review & editing.
**Ousmane Ndiaye:** Writing – review & editing.
**Torbern Tagesson:** Writing – review & editing, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization.
**Dominique Serça:** Writing – review & editing.
**Claire Delon:** Writing – review & editing.

## Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Aleksander Wieckowski reports financial support was provided by FORMAS. Torbern Tagesson reports financial support was provided by Carl Trygger Foundation for Scientific Research. Torbern Tagesson reports financial support was provided by Development Smart Innovation through Research in Agriculture. Torbern Tagesson reports financial support was provided by Swedish National Space Agency. Torbern Tagesson reports financial support Fysiografiska Sällskapet. Olivier Roupsard reports financial support was provided by EU-Horizon Europe GALILEO. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

This project was funded by FORMAS (Dnr 2021–00644), Carl Trygers Stiftelse, Kungliga Fysiografiska Sällskapet, and the Carbon Sequestration and Green-house Gas Emissions in (Agro) Sylvopastoral Ecosystems in the Sahelian CILSS States (CaSSECS) project, supported by the European Union under the Development Smart Innovation through Research in Agriculture (DeSIRA) Initiative (OOD/2019/410–169). Torbern Tagesson also acknowledges funding from the Swedish National Space Agency (SNSA Dnr 2021–00144; 2021–00111), FORMAS (Dnr 2023–02436). Roupsard acknowledges funding from EU-Horizon Europe GALILEO (Grant no. 101181623) and ANR-PEPR FairCarbonN/PC3-RIFT. The research presented in this paper is a contribution to the Strategic Research Area “Biodiversity and Ecosystem Services in a Changing Climate,” BECC, funded by the Swedish Government. We are very grateful to the Institut Sénégalais de Recherche Agricole for all logistic, administrative, and technical support. Thanks also to our guards who provided night and day surveillance of the study site.

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.agee.2025.110199.

### Data availability

Data will be made available on request.

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