Imaging Rhizosphere CO 2 and O 2 Concentration to Localize Respiration Hotspots Linked to Root Type and Soil Moisture Dynamics

Purpose Rhizosphere respiration strongly affects CO 2 concentration within vegetated soils and resulting uxes to the atmosphere. Respiration in the rhizosphere exhibits high spatiotemporal variability that may be linked to root type, but also to small-scale variation of soil water content altering gas transport dynamics in the soil. We address spatiotemporal dynamics of CO 2 and O 2 concentration in the rhizosphere via non-invasive in-situ imaging. Methods Optodes sensitive to CO 2 and O 2 were applied to non-invasively measure in-situ rhizosphere CO 2 and O 2 concentration of white lupine (Lupinus albus) grown in slab-shaped glass rhizotrons. We monitored CO 2 concentration over the course of 16 days at constant water content and also performed a drying-rewetting experiment to explore sensitivity of CO 2 and O 2 concentration to soil moisture changes.


Introduction
Respiration by plant roots can seasonally account for the majority of soil CO 2 production (Hopkins et al. 2013; Hanson et al. 2000) and substantially impacts CO 2 concentration within and uxes from vegetated soils. The rhizosphere, de ned as the volume of soil in uenced by the activity of roots (Hinsinger et al. 2009), represents a hotspot of respiration: autotrophic respiration of living root tissue combined with the high abundance of microorganisms that decompose root exudates and other rhizosphere deposits leads to increased formation of CO 2 and consumption of O 2 within this region (Kuzyakov and Blagodatskaya, 2015). As both root and microbial respiration occur simultaneously and are di cult to separate, we refer to all respiration processes in the rhizosphere as "rhizosphere respiration" (as proposed by Kuzyakov, 2006). Similar to other physicochemical gradients and biological process rates in the rhizosphere, respiration and the resulting distribution of CO 2 and O 2 concentration exhibits high spatiotemporal heterogeneity (Kuzyakov and Razavi 2019). Within a plant individuals' root system, respiration rates can differ substantially along with photoassimilate allocation, growth rate or tissue N content (Lambers et al., 2002). Small-scale variation of soil properties, such as porosity and connectivity of the pore space, and particularly soil water content, affect soil aeration and gas transport dynamics, which control the amount of oxygen available for aerobic respiration and the local accumulation of CO 2 (Ben-Noah and Friedman 2018). In our study, we address the spatiotemporal dynamics of CO 2 and O 2 concentration in the rhizosphere of white lupine together with root system development and soil moisture changes via noninvasive imaging using planar optodes.
The application of planar optodes enables visualization and quanti cation of rhizosphere respiration with an emphasis on capturing spatial and temporal heterogeneity (Freschet et al. 2021). Planar optodes are uorescent sensor foils sensitive to e.g. pH, CO 2  However, a systematic investigation of both CO 2 and O 2 concentration in the rhizosphere of non-wetland plants in unsaturated soil in-situ over a longer time period (weeks) and under varying soil moisture conditions is not yet available.
Soil water content impacts rhizosphere respiration as it affects the availability of O 2 (Ben-Noah and Friedman 2018). Diffusive gas transport is decelerated considerably at high volumetric soil water content; this strongly restricts O 2 supply from the atmosphere into the soil and towards the plant roots while CO 2 produced by rhizosphere respiration accumulates in the soil. As a result, CO 2 uxes measured shortly after irrigation or rainfall can lead to a substantial underestimation of soil CO 2 concentration, particularly in ne-textured soils (Bouma and Bryla 2012). Several eld studies show that drying-rewetting cycles impact soil CO 2 ux and respiration rates (Morillas et al. 2017; Zhu and Cheng 2013; Min et al. 2020), and such short-term variations in soil moisture often occur under natural conditions. Studies addressing the dynamics of respiration at the rhizosphere scale as a function of soil moisture and its short-term uctuation are lacking because of methodological di culties of observing root-soil interaction in-situ.
We measured CO 2 and O 2 concentration in the rhizosphere of white lupines over the course of 19 days applying planar optodes and investigated the effect of variations of soil moisture. We chose white lupine (Lupinus albus) as it is a well-studied model plant with agricultural relevance (Neumann and Martinoia 2002). Lupinus albus features distinct physiological adaptation mechanisms under phosphorous (P) limited conditions. The plants invest a particularly large amount of carbon in the growth of cluster roots (Funayama-Noguchi et al., 2020) which release a high quantity of exudates such as citrate (Dinkelaker et al. 1989) and other organic acids (Watt and Evans 1999) to solubilize otherwise unavailable P resources. Experiments on hydroponically grown white lupines suggest that cluster roots can exhibit increased respiration rates and that root tissue nitrogen (N) content may positively correlate with respiratory activity (Langlade 2002; Funayama-Noguchi et al. 2020; Kania et al. 2003). We quanti ed effects of rhizosphere respiration of white lupines grown in soil via non-invasive mapping of pCO 2 and pO 2 and hypothesize that 1) rhizosphere respiration of Lupinus albus shows distinct spatiotemporal heterogeneity linked to root type, diurnal variation of plant activity and root tissue N content and that 2) the magnitude of measured CO 2 and O 2 concentration in the rhizosphere is highly sensitive to fast changes in water content.

Materials And Methods
To assess the spatiotemporal variability of respiration along with root system development of Lupinus albus and changes in soil water content, we conducted three experimental time series. First, we measured rhizosphere pCO 2 daily with soil water content kept constant and statistically located hotspots of respiration activity during 16 days. Second, we quanti ed the diurnal variation of respiratory activity by repeated measurements of pCO 2 during the photoperiod of selected days within this period. Finally, we conducted a 3-days drying-rewetting experiment to investigate the sensitivity of CO 2 and O 2 concentration to fast changes in soil water content. After these 19 days, we harvested and analyzed the roots from regions where pCO 2 strongly increased or pO 2 strongly decreased after rewetting to correlate root tissue N content and respiratory activity.

Rhizotron preparation and plant growth
We prepared ve glass rhizotrons (150 mm x 150 mm x 15 mm) with planar optodes sensitive to CO 2 and two of them additionally with O 2 -sensitive optodes. The CO 2 optodes (range: 1-25 % pCO 2 , size: 80 mm x 104 mm, product code: SF-CD1R, PreSens GmbH, Regensburg, Germany) were equilibrated in buffer solution (pH = 7.5) over night and then glued to the inner front windows (plants L1 -L5). The O 2 optodes (size: 130 mm x 105 mm, manufactured as described in Rudolph et al., 2012) were attached to the inner back sides of two of the ve rhizotrons (plants L4 and L5). Sandy soil (91 % sand, 8 % silt and 1 % clay, calcium acetate lactate (CAL) extractable P 8.6 mg kg -1 , total N 0.01 %, total C 0.13 %, and pH (CaCl2) 7.6) was sieved to < 2 mm and lled horizontally into the rhizotrons (mean bulk density: 1.45 g cm -3 ). Seeds of white lupine (Lupinus albus) were sterilized in 70 % ethanol and planted after germination. Each plant was initially watered with 85 ml of a nutrient solution (containing 7% N, 3% P 2 O 5 , 6% K 2 O and micronutrients, as described in Rudolph-Mohr et al., 2017). Water was added to obtain an initial volumetric water content of 0.30 cm³ cm -³, which is equivalent to 77 % of saturation water content. After plant emergence, a gravel layer of 10 mm was placed at the soil surface to minimize evaporation. The water content was re-adjusted every morning to 0.30 cm³ cm -³ by irrigating from the top; no further nutrients were supplied throughout this experiment to obtain P-de cient conditions and stimulate cluster root development. The lupines were grown under controlled conditions in a plant growth chamber (temperature day 24 °C, temperature night 19 °C, 14 hours photoperiod with a light intensity of 300 µmol m -2 s -1 , relative humidity 60 %). Light intensity was increased from 0 % to 100 % between 6 a.m. and 10 a.m. and ramped down again to 0 % between 4 p.m. and 8 p.m.; temperature was changed between 19 °C (night) and 24 °C (day) accordingly. All samples were kept in an upright position, so roots distributed in soil towards both sides of the rhizotrons. The rhizotrons were covered with aluminum foil to protect the optodes from photobleaching.
Imaging of CO 2 and O 2 concentration CO 2 concentration was monitored with VisiSensTD, a commercial 2D uorescence imaging and readout system (PreSens Precision Sensing GmbH, Regensburg, Germany). The CO 2 optodes contain two uorescent dyes (one sensitive to changes in pCO 2 , the other acting as a reference dye). A ring light source (built into the camera lens) and two external blue LEDs (wavelength 450 -550 nm) were used to excite the uorescent dyes. The uorescence intensity was captured with an RGB camera (1292 x 964 pixels) at an exposure time of 70 ms and the signal ratio of the red and green channel (red:green ratio) was stored pixelwise. To convert this information into CO 2 concentration (pCO 2 in %), a calibration curve was tted. For calibration, two pieces of CO 2 optode were equilibrated overnight in a buffer solution (pH = 7.5, ionic strength = 40mM) and then xed inside a small glass box lled with a similar buffer solution.
The solution was ushed with gas mixtures of stepwise increasing CO 2 concentration between 0 % and 25 % pCO 2 and images were captured every 60 seconds at each calibration point until the signal was stable (taking between 15 and 20 minutes per concentration step). The calibration curve was tted using the software VisiSens AnalytiCal (PreSens Precision Sensing GmbH). Fluorescence images (pixelsize 213 µm) were captured and directly converted to pCO 2 maps in the software VisiSens AnalytiCal via the calibration curve.
The optodes were calibrated in water with O 2 -concentration between 0 mg L -1 and 10 mg L -1 and a calibration curve was tted based on the measured uorescence intensities (as described in Rudolph et al., 2012). Fluorescence signals after excitation with UV light (type 215 L, Peqlab, Erlangen, Germany) were captured with a camera (Kappa DX 4C-285 FW) with a 500 nm long-pass lter and a cooled CCD sensor (1392 x 1040 pixels). The gray-value images (pixel size: 219 µm) were converted to O 2concentration maps based on the tted calibration curve in MATLAB R2020(a) (The MathWorks).
Time series of rhizosphere pCO 2 at constant water content and diurnal variation of rhizosphere pCO 2 (experiment 1 & 2) Experiment 1.We monitored pCO 2 in the soil every day until day 16 after planting (DAP 16) to be able to identify hotspots of respiration amongst the growing root systems and the rhizosphere. As the only study to date applying CO 2 optodes in unsaturated soil (Holz et al. 2020) suggests that measured magnitude of rhizosphere CO 2 concentration is strongly in uenced by soil moisture, we kept the volumetric soil water content constant at 0.30 cm³ cm -³ by irrigation every morning at 8:30 a.m. and always conducted the measurements 30 minutes after adjusting the water content to enable comparisons across plant individuals and root replicates. To limit stress during our experiments, plants were only brie y taken out of the plant growth chamber to a darkroom for imaging and returned directly afterwards. In the darkroom the rhizotrons were placed in a sample holder mounted on a table to ensure that they were always aligned in the same position relative to the camera.

Measurement of root position and cluster root development
Since the CO 2 optodes include an optical isolation layer, it was not possible to capture optical images of the precise location of roots systematically without removing the optode. To avoid disturbing gas transport dynamics in the soil, we did not open the rhizotrons or remove the optodes until the end of all experiments. However, several cluster and lateral roots or root segments were visible through the optode and we could trace their position with a pen on the glass window. These regions were later used for quantitative analysis of root zone pCO 2 in experiment 1 and 2. After the drying-rewetting experiment on DAP 19, we opened the rhizotrons, removed the CO 2 optodes and captured images of the exposed root systems (plant age: 21 days) to locate the position of all roots growing along the optodes. Plants L1, L2, L3 and L5 had developed several cluster roots close to the CO 2 optode. Just plant L4 grew only lateral roots without clusters close to the CO 2 optode (Fig. S1). The O 2 optodes are semi-transparent and therefore we could trace roots directly from images taken at ambient light conditions. Both L4 and L5 grew cluster roots close to the oxygen optode. After imaging the opened rhizotrons, we washed the root systems carefully to remove soil particles and captured images to determine the extent of cluster root development amongst the entire root system.

Root sampling for nitrogen (N) content analysis
Based on the uorescence image time series captured during the drying-rewetting experiment (DAP 19), we selected regions of considerably higher and lower respiratory activity (considering both CO 2 and O 2 concentration) and took root samples there. We did not distinguish between cluster and lateral roots during sampling, but only selected roots growing close to the optodes. The sampled roots and root segments were dried at 60 °C for at least 48 h and then ground for analysis. Root carbon (C) and nitrogen (N) contents as well as the C:N ratio were determined in two replicates per region by elemental analysis (Euro EA 3000 Elemental Analyser, HEKAtech GmbH, Wegberg, Germany).

Image analysis
All images were registered with the Plugin "Stackreg" in ImageJ prior to further analysis. CO 2 concentration (in % pCO 2 ) was directly calculated from the uorescence images in the VisiSens AnalytiCal software and saved as TIFF images. O 2 concentration was calculated in MATLAB R2020a as described in Rudolph-Mohr et al. (2017) and converted to % pO 2 .
We statistically located hotspots of CO 2 concentration in the rhizosphere following the approach suggested by Bilyera et al. (2020). First, we converted the CO 2 image time series of each plant to 8-bit gray value maps of pCO 2 and saved the histogram of gray values of each image (MATLAB R2020a). The gray value distribution was then statistically split into two distributions (package "mixtools" in RStudio, Bengalia et al., 2009) to separate hotspots from background. Pixels were classi ed as hotspots when the gray value was higher than the mean + 3SD (three times the standard deviation) of the background pixel values (Bilyera et al. 2020). The hotspot area (in mm²) was calculated by multiplying the number of hotspot pixels by the pixel size and was compared to the total area covered by the optode.
Diurnal variation of pCO 2 was compared in selected regions of interest (10 x 10 pixel, approx. 4 mm²) close to roots that were visible through the optode (cluster roots: n = 7, lateral roots: n = 18 on DAP 14) and within the bulk soil (n = 25). To compare rhizosphere respiration during the drying-rewetting experiment on DAP 19, we rst segmented roots growing close to the optodes from the images of the exposed root systems captured after opening the rhizotrons ("SmartRoot" Plugin in ImageJ, Lobet et al., 2011). We then interactively selected a total of 47 non-overlapping roots or root segments from the binary images obtained from segmentation ("drawpolygon" and "poly2mask" function, Image Processing Toolbox, MATLAB R2020a). CO 2 and O 2 concentration as a function of distance to the root surface was calculated using the Euclidean distance transform (via "bwdist" function in Matlab). We graphically estimated the extent of CO 2 accumulation resp. O 2 depletion zones at different volumetric soil water contents by tting local regression curves (function "loess" in RStudio) to the mean CO 2 resp. O 2 concentration with increasing distance from the roots.

Statistics
Measured CO 2 and O 2 concentration in the root zone and the bulk soil were analyzed for normality and homogeneity of variances applying Shapiro Wilk's test and Levene's test, respectively. Differences between cluster and lateral roots as well as the effect of soil water content were tested for statistical signi cance using Kruskal-Wallis test followed by a Wilcoxon test. C and N content and C:N ratio of roots from regions of high vs. low respiration was compared pairwise also applying a Wilcoxon test. All statistical tests were computed at a signi cance level of α < 0.05 in RStudio (R Core Team, 2020).

Results
Experiment 1: time series of rhizosphere pCO 2 at constant water content During the rst 16 day after planting (until DAP 16), pCO 2 was measured every morning at 9:00 a.m. at constant water content (0.30 cm³ cm -³). Initially, the tip of the taproot and young parts of the growing lateral roots released most CO 2 (Fig. 1a). Between DAP 10 to 13, all plants with the exception of L4 developed cluster roots close to the CO 2 optode where large, overlapping hotspot areas formed and local CO 2 concentration increased to a maximum of 22.8 % pCO 2 (DAP 16, Fig. 1a). At that stage the CO 2 hotspots (pCO 2 ≥ mean background concentration + 3SD) covered 27 % of the optode area (Fig. 1c).
Plant L4 grew no cluster roots in direct vicinity to the CO 2 optode (Fig. S1). We measured lower overall CO 2 concentration (Fig. 1b) with a maximum of 8.6 % pCO 2 at the root surface (DAP 16) and smaller hotspot areas (max. 0.7 % of the area covered by the optode, Fig. 1d) in the rhizosphere of this plant. Despite plant L4 formed multiple cluster roots elsewhere in its root system (images of washed root systems of L3 and L4 in Fig. S1), their effect on CO 2 concentration was not measurable because they grew at some distance to the optode. In general, hotspot area increased over time as more roots developed and CO 2 from rhizosphere respiration accumulated in the soil as the high water content decelerated gas exchange with the ambient air. Experiment 2: Diurnal variation of pCO 2 in the lupine rhizosphere Rhizosphere CO 2 concentration increased between morning and noon (9 a.m. to 1 p.m., Fig. 2, center panels). In certain regions, pCO 2 continued to rise until the afternoon (5 p.m.), but already decreased in other parts of the root system (Fig. 2, right panels).
Comparing different individual root regions across all plant individuals (Fig. 3a) shows that pCO 2 around some root segments peaked at noon or increased throughout the afternoon, but other roots did not exhibit a clear diurnal variation in respiration and pCO 2 remained close to constant. Close to several cluster roots near the CO 2 optode, CO 2 concentration strongly increased, but pCO 2 around some lateral roots was within the same order of magnitude (Fig. 3a). The smallest diurnal variation of pCO 2 was measured for plant L4 (no cluster roots close to the CO 2 optode). Average root zone CO 2 concentration (mean ± SD) was 8.7 ± 3.9 % pCO 2 and 5.3 ± 3.3 % for cluster and lateral roots, respectively, in the morning and 11.7 ± 4.5 % pCO 2 vs. 7.1 ± 4.3 % in the afternoon. However, due to the pronounced heterogeneity between the selected root segments and the resulting scatter of the morning and afternoon values it could not be shown with statistical signi cance that the mean CO 2 concentration was higher in the afternoon than in the morning (Fig. 3b). Nevertheless, CO 2 concentration in the selected root regions individually increased signi cantly (p<1.7*10 -7 ) from morning to afternoon, with an average rate of 0.27 % pCO 2 h -1 . Thus, we can conclude that pCO 2 in the rhizosphere of the selected root segments increased statistically signi cantly from morning to afternoon and that the individual afternoon value in a root segment is signi cantly larger than its morning value.
Mean bulk soil CO 2 concentration increased signi cantly (p=0.0098) from 1.82 ± 0.75 % pCO 2 in the morning to 2.34 ± 0.84 % pCO 2 in the afternoon (mean ± SD, n= 25, Fig. 3b). This was likely caused by the diffusive spread of CO 2 also released from rhizosphere respiration in parts of the root system located at greater distance to the optode. Experiment 3: Sensitivity of rhizosphere pCO 2 and pO 2 to changes in soil water content Hotspots of respiration form after rewetting from dry conditions After three days without irrigation (DAP 16 to 19), the rhizotrons were rewetted from 0.10 cm³ cm -³ to 0.30 cm³ cm -³ and pCO 2 and pO 2 were measured hourly. In general, CO 2 concentration increased around the roots after rewetting and continued to rise over the course of ve hours. Fig. 4a shows the evolution of pCO 2 of plant L2, where the increase of CO 2 around cluster roots after rewetting was most pronounced (images of other plants in Fig. S2). Similar increase and hotspot formation after rewetting was observed for the other plants except plant L4, where no cluster roots grew close to the CO 2 optode. Three hours after rewetting, CO 2 concentration at the surface of cluster roots growing close to the optodes was signi cantly higher than at the lateral root surface (Fig. 5a, p<0.05). Statistically de ned hotspot area of the plants with cluster root abundance near the CO 2 optode increased (Fig. S3). However, for plant L3 hotspot area remained < 3 % after rewetting (Fig. S3) despite pronounced cluster root abundance close to the CO 2 optode and high rhizosphere CO 2 concentration observed until DAP 16 (see Fig. 1). This could be due to cluster root maturation and associated decrease of respiration activity, but we could not track the exact age of the root segments in this experiment.
For plants L4 and L5, O 2 concentration was measured by an optode attached to the back side of the rhizotron. Immediately after rewetting, regions of high oxygen consumption formed, and after only one hour, pO 2 measured at the surface of cluster roots was signi cantly lower than concentrations at the surface of lateral roots (Fig. 5b). Five hours after rewetting, most of the available oxygen in the rhizosphere was consumed and the depletion zones of different roots overlapped in large parts (plant L5 :   Fig. 4b, center and last panel; this was similar for plant L4 (not shown)). Oxygen consumption around cluster roots was faster and more pronounced compared to lateral roots (Fig. 5b).

Extent of CO 2 accumulation and O 2 depletion zones depend on soil water content and root type
The spatial extent of the CO 2 accumulation zone around roots varied with changes in soil water content and differed between root types (Fig. 6, Tab. S1). In wet soil (daily irrigation to 0.30 cm³ cm -3 , measured on DAP 16), the region of increased CO 2 concentration extended approx. 8 mm from the cluster root surface, but only ≤ 0.3 mm in dry soil (0.10 cm³ cm -3 , three days after irrigation was stopped, DAP 19, Fig. 6). After rewetting the soil to 0.30 cm³ cm -3 , the CO 2 accumulation zone expanded rapidly up to 9.5 mm. At the cluster root surface, CO 2 concentration was signi cantly higher (p <0.001) in wet and rewetted soil than in dry soil (Tab. S1). Around lateral roots, gradients of pCO 2 extended ~ 1 mm from the root surface in dry soil. Despite similar water content (0.30 cm³ cm -3 ), the pCO 2 gradients from the surface of the lateral roots extended twice as far from into the rewetted (4-5 mm) than into the wet soil (~ 2 mm). And though soil water content in wet and rewetted soil was similar, lateral root surface and bulk soil CO 2 concentration 5 h after rewetting exceeded values measured in wet soil (p<0.05, Tab. S1).
After rewetting, the O 2 depletion zone extended > 10 mm from the cluster root surface, but only ~ 5 mm from the lateral root surface (Fig. S4). One hour after rewetting, pO 2 at the cluster and lateral root surface was lower than in wet soil prior to drying (p<0.05, Tab. S1).

Respiration hotspots and root tissue N content
Roots from the regions with the highest as well as the lowest change in CO 2 or O 2 concentration during the drying-rewetting experiment were sampled and root tissue N and C content was measured. The roots from regions with high rhizosphere respiration contained signi cantly less N and C (Tab. 1).

Discussion
Spatiotemporal variability of rhizosphere respiration is linked to root type Our experimental results con rm the hypothesis that rhizosphere respiration varies between root types among Differences of rhizosphere pCO 2 and pO 2 between root types were most pronounced after rewetting the soil from dry conditions: around cluster roots, oxygen consumption was signi cantly faster and CO 2 release signi cantly higher compared to lateral root segments without clusters. In contrast to the mentioned studies where (autotrophic) root respiration rates were quanti ed for soil-free roots, we refer to rhizosphere respiration only as the sum of CO 2 released respectively O 2 consumed by roots themselves and by rhizomicrobial respiration. Microbial respiration can constitute more than 50 % of rhizosphere respiration (Kuzyakov and Larionova 2005) and is strongly enhanced when high amounts of organic compounds are available, e.g. via rhizodeposition and root exudation. Yin et al. (2020) showed via noninvasive imaging of white lupine root systems grown in soil that root allocated C was released in hotspots where cluster roots were present. Also, cluster roots release higher amounts of citrate into the rhizosphere than non-cluster roots (Dessureault-Rompré et al. 2007). This could lead to increased microbial respiration activity speci cally in the areas directly surrounding these root structures and explain the strong increase of pCO 2 we observed around cluster roots.
Magnitude and extent of CO 2 accumulation and O 2 depletion zones are highly sensitive to soil water content Soil water content strongly altered pCO 2 and pO 2 at the root surface as well as the extent of CO 2 and O 2 gradients around the roots. Around cluster roots, CO 2 and O 2 gradients extended up to 9.5 mm and more than 10 mm, respectively, in moist soil (0.30 cm³ cm -³ volumetric soil water content), but decreased to 0. In summary, the actual soil water content, as well as its variations prior and during respiration measurements, needs to be reported along with CO 2 and O 2 concentration in order to enable informed comparisons of absolute values and respiration activity.

Diurnal variation of rhizosphere respiration
We observed that CO 2 concentration in the rhizosphere locally increased from morning to afternoon along with the diurnal course of illumination and temperature. Allocation of assimilates from photosynthesis to

Hotspots of respiration and root tissue N content
We observed the formation of distinct hotspots of increased respiration after rewetting the soil from 0.10 cm³ cm -3 to 0.30 cm³ cm -3 on DAP 19 and compared C and N content as well as C:N ratio from roots sampled in hotspots to regions of low respiratory activity. The N content of roots attributed to respiration hotspots was signi cantly lower than that of roots sampled from regions of lower respiration activity after rewetting (26 mg N g -1 dry weight vs. 37 mg N g -1 dry weight). This is contrary to the ndings of Funayama-Noguchi et al. (2020) who reported a positive correlation of root respiration rate and tissue N content of white lupine roots. Several studies investigating ne roots of trees also found that root respiration rates increase with root N content (Hishi 2007;Jia et al. 2013;Pregitzer et al. 1998). In contrast to these studies, we did not determine speci c root respiration rates based on root weight, but measured changes of CO 2 and O 2 concentration induced by root and rhizomicrobial respiration. As we observed strong variations and heterogeneity of respiration not only after rewetting, but also throughout the previous growing period, it is likely that the regions we classi ed as "low" vs. "high" respiratory activity where roots were sampled for C/N analysis were representative of the time of sampling rather than the conditions over the duration of the experiment. For example, we observed that one cluster root formed a CO 2 hotspot on DAP 16 but showed lower respiration activity after rewetting compared to other regions that previously had not been classi ed as hotspots. Furthermore, we did not differentiate between younger and older root tissue or cluster vs. non-cluster roots for sampling. However, Funayama-Noguchi et al. (2020) did not nd signi cant differences of cluster root tissue C and N content compared to non-cluster roots of white lupine under P-de ciency. Thus, it is not fully clear if our sampling concept was not able to represent the general behavior or if exudation with the inherent transfer of C into the rhizosphere induces a higher respiration activity outside roots leading to an overall higher respiration activity.

Methodological considerations
We have demonstrated that non-invasive imaging with planar optodes is suitable for the quanti cation of rhizosphere respiration at the root system scale over several weeks and that this imaging technique can be applied to measure pCO 2 and pO 2 at soil moisture levels between 0. 10    Changes of pCO 2 from morning to afternoon on day 14 after planting for plant L2 (a) and L3 (b). The plants were irrigated to 0.30 cm³ cm -³ at 8:30 a.m., and if water content changed by more than 0.02 cm³ cm -³, soil moisture was re-adjusted at noon and in the afternoon. Left panels: pCO 2 measured 30 minutes after watering at 9 a.m.; center panels: difference (Δ pCO 2 ) between 1 p.m. and 9 a.m.; right panels: difference (Δ pCO 2 ) between 5 p.m. and 1 p.m. Regions for quantitative analysis of root zone pCO 2 (see  to capture the diurnal variation in rhizosphere respiration. Water content was adjusted to 0.30 cm³ cm -³ in the morning and, if water content changed by more than 0.02 cm³ cm -³, again at noon and / or in the afternoon. Plant L4 did not grow cluster roots close to the CO 2 optode. b) Diurnal variation of pCO 2 in selected 4 mm² regions in bulk soil (n = 25), around cluster roots (n = 7) and lateral roots (n = 18) on day 14 after planting. Signi cant differences following Wilcoxon test (α < 0.05) are highlighted with * (p≤ 0.05).   shaded area indicate the local regression curve ("loess" function in RStudio, package: "stats") with 95% con dence interval.