Grassland state assessment is essential given their vital role in food security, carbon sequestration and other ecosystem services. Harvested aboveground biomass (HAB), aboveground net primary production (ANPP) and net primary production (NPP) are among the most important grassland state indicators. However, spatially explicit production estimates are largely lacking, and grassland area estimations also remain uncertain. This study addresses these gaps for drought-prone Central European grasslands over 2017-2024. We synthesized grassland extent data, collected extensive field measurements, and used remote sensing-based biophysical proxies to build an ensemble of eight linear models for spatial extrapolation at 10 m resolution. The proxies explained 11-41% of observed biomass (BM) variability. The ensemble mean ANPP was 325.7±56.6 gBM m2 year1 (median: 316 gBM m2 year1), with modest overall interannual variability. Upscaled country-wide ANPP averaged 35.1±9.2 Mt BM year-1 annually (range: 31.9-38.3; median: 35.9 Mt BM year-1). Uncertainty from grassland area estimation was roughly twice that from model choice. Using literature and local data, NPP was estimated at 421±110 gC m2 year-1 (median value), showing low interannual variability. Results highlight grassland area uncertainty as the dominant source of error in biomass estimation, rather than the remote sensing models themselves.

The two-source energy balance model pyTSEB-PT was used to model latent heat fluxes from sunflower and wheat crops before senescence, grown on the same field in consecutive years. Input maps for the pyTSEB model were prepared using UAV-acquired multispectral/thermal imagery and ground control canopy leaf angle distribution (χ) and leaf area index (LAI) estimations based on canopy light transmission measurements by linear ceptometers. The modelled sensible and latent heat fluxes (HpyTSEB, LEpyTSEB) were validated against eddy covariance-measured respective fluxes (Heddy, LEeddy). Actual χ (χa) was estimated from 2 h courses of canopy light transmission values and ranged between 0.5 and 1.2 for wheat and between 2.8 and 5.8 for sunflower crops, respectively, affecting canopy light extinction coefficients (k) and LAI in both crops compared to the case of the generally assumed spherical leaf angle distribution (χ = 1). Vegetation cover fraction (fc) was 3.4% smaller in wheat when using χa instead of χ1, but this led to only minor—though significant—changes in modelled Tcan, Tsoil and canopy and surface resistances. The effect of leaf angle distribution on the combined validation of sensible and latent heat flux data was shown primarily in sunflower due to the decrease in sensible heat flux error, while validation improvement was not detectable in the case of wheat. Using field-calibrated thermal images instead of uncalibrated ones strongly improved validation results (fit of modelled vs. measured sensible and latent heat fluxes), showing the necessity of field calibration of the thermal camera when the data are used for vegetation energy balance modelling.

As the major carbon sources of soil respiration (Rs) include the soil organic carbon content (SOC) and the belowground carbon allocation, we aimed to reveal their relative effects on actual CO2 efflux from soil. We measured soil respiration and additional variables in a dry grassland site in Hungary in the same spatial grid (78 points, 0.63 ha) during 23 campaigns over nine years. We used gross primary productivity (GPP) as a proxy for belowground carbon allocation, derived from eddy-covariance measurements and downscaled to the corresponding measuring positions. To visualize the multidimensional data, principal component analysis was performed. To describe the partial effects of the measured variables, general additive models (GAMs) were fitted. GPP was found to be the most important predictor variable in the middle of the vegetation period and during drought periods, while soil water content (SWC) proved to be most crucial factor in the first part of the vegetation period and soil temperature (Ts) dominated in the late season. The overall relative importance of Ts, SWC, GPP and SOC in GAMs were 36.0

Aims Soil respiration (R s ) is a complex process including a wide range of soil biota and pathways of carbon cycling, all being under the control of various drivers. The most important biotic driver is the photosynthetic activity of the vegetation providing supply mainly for the autotrophic component of R s : roots and their symbiotic partners. The objective of this study was to describe the time-lagged relationship between gross primary production (GPP) and the mycorrhizal R s component in order to determine the amount of carbon derived from GPP appearing as mycorrhizal respiration (R myc ). Methods Measurements of R s were conducted in three treatments - (i) undisturbed, root and arbuscular mycorrhizal fungi (AMF)-included (R s ), (ii) root-excluded (R het+myc ) and (iii) root- and AMF-excluded (R het ) plots - for three consecutive years in a Central-Hungarian dry sandy grassland. GPP data were derived from eddy-covariance measurements, while an automated system was used for continuous measurements of R s . We analysed the relationship between R myc and GPP by using cross-correlation and by fitting sine wave models on the diel datasets. Results GPP was found to be the main driver of R myc , responding with an average time lag of 18 h. The greatest lags were detected during periods characterized by minimal photosynthetic activity, while lags were the smallest during active periods. Conclusion Based on the seasonal changes in the delay, we concluded that GPP and soil temperature had simultaneous effects on the diel pattern of CO 2 emission of the different autotrophic components depending on the vegetation activity and environmental conditions.

The ability to access physiologically driven signals, such as surface temperature, photochemical reflectance index (PRI), and sun-induced chlorophyll fluorescence (SIF), through remote sensing (RS) are exciting developments for vegetation studies. Accessing this ecophysiological information requires considering processes operating at scales from the top-of-the-canopy to the photosystems, adding complexity compared to reflectance index-based approaches. To investigate the maturity and knowledge of the growing RS community in this area, COST Action CA17134 SENSECO organized a Spatial Scaling Challenge (SSC). Challenge participants were asked to retrieve four key ecophysiological variables for a field each of maize and wheat from a simulated field campaign: leaf area index (LAI), leaf chlorophyll content (Cab), maximum carboxylation rate (Vcmax,25), and non-photochemical quenching (NPQ). The simulated campaign data included hyperspectral optical, thermal and SIF imagery, together with ground sampling of the four variables. Non-parametric methods that combined multiple spectral domains and field measurements were used most often, thereby indirectly performing the top-of-the-canopy to photosystem scaling. LAI and Cab were reliably retrieved in most cases, whereas Vcmax,25 and NPQ were less accurately estimated and demanded information ancillary to RS imagery. The factors considered least by participants were the biophysical and physiological canopy vertical profiles, the spatial mismatch between RS sensors, the temporal mismatch between field sampling and RS acquisition, and measurement uncertainty. Furthermore, few participants developed NPQ maps into stress maps or provided a deeper analysis of their parameter retrievals. The SSC shows that, despite advances in statistical and physically based models, the vegetation RS community should improve how field and RS data are integrated and scaled in space and time. We expect this work will guide newcomers and support robust advances in this research field.

Eddy accumulation technique provides an opportunity to quantify the turbulent exchange processes of properties for which fast response measuring devices are not available. The signals of slow response instrument are separated based on the up- (c+) and down-flowing (c–) air concentration by using a long-term averaging process (20-30 minutes). The difference in the average concentration of the up- and down-flow, multiplied by the standard deviation of the vertical wind is proportional to the turbulent flux of the given property. Two applications are presented.i) The particle number concentration was measured by a condensation particle counter (CPC, type A30, Airmodus, Finland) at the ELTE BpART Lab (http://salma. elte.hu/BpART/) in summer 2023. The instrument uses butanol as a working fluid, and detects particles with a diameter >7 nm in single particle counting mode with coincidence correction up to 150 000 cm–3 with a time resolution of 1 s. Fast response (10 Hz) turbulence measurements were accomplished using an EC150 Open-Path CO2/H2O gas analyser combined with CSAT-3 sonic anemometer. The time lag between the two instruments due to air intake was considered. The autocovariance function of the vertical velocity and the particle number concentration were also calculated. The concentration within the 1-s averaging time was i) taken as constant, and ii) the tenth-second values were calculated by linear interpolation. A 10-Hz data series were generated, knowing that the covariance [cov(w,c)] is underestimated. In each case, 30-min averaging period was used. As a check of the method, the flux calculations based on relaxed eddy accumulation (REA) were compared with eddy covariance (EC) measurements for raw vertical fluxes of sonic temperature, moisture, and CO2. The fluxes calculated in these two ways were in good agreement (R2 > 0.83).ii) Another methodological development is a novel approach that involves combination of a photoacoustic ammonia sensor with a CSAT-3 sonic anemometer. The photoacoustic instrument, which is currently in the development phase, yields reliable concentration values with an averaging time of approximately 10 s. Similar to wind parameters, the output signals from the ammonia sensor were collected at a frequency of 10 Hz, acknowledging the presence of significant white noise. These measurements were started in a sunflower field even before sowing and fertilization during spring 2024. Our analysis encompassed: a) assessing the reliability of ammonia concentration measurements, b) studying the daily concentration patterns, c) investigating concentration differences detectable between upstream and downstream air flows. Initial findings from this new field campaign are summarised on the posters.

Drought stress occurrence and recovery from drought can be detected using a single spatial set of simultaneous observations of SIF and canopy temperature records. Temporal and spatial responses to drought and heat stresses by plant stands of a drought-adapted diverse grassland ecosystem were studied using sun induced fluorescence (SIF,O2A and O2B bands) and further ecophysiological (canopy temperature (Tsurf), spatially modeled evapotranspiration, vegetation reflectance spectra) variables collected along spatial sampling grids while also utilizing eddy covariance measured carbon dioxide (net ecosystem exchange: NEE, gross primary production: GPP) and water flux (evapotranspiration: ET) data. The grids were of 0.5 and 5 ha spatial extents and contained 78 sampling points. Data were collected in four spatial sampling campaigns, two under drought (early summer) and another two during and after recovery (midsummer) at both spatial resolutions.Small values of spatial SIF_A averages (around 0.5 mW m 2 nm 1 sr-1) under strong early summer drought increased (to around 2 mW m 2 nm 1 sr 1) due recovery upon rain arrivals, showing high (R2: 0.8-0.88) positive temporal correlations to eddy covariance measured carbon (GPP, NEE) and water (ET) fluxes. Spatial averages of LAI, vegetation indices (NDVI, NIRv) and modeled ET followed similar temporal patterns.While SIF was depressed by drought, it showed higher values in high canopy temperature vegetation patches than in vegetation patches with lower Tsurf. The spatial pattern of higher SIF in higher Tsurf patches was

A számos kutatás és módszertani fejlesztés ellenére az evapotranspiráció az egyik legnehezebben becsülhető komponense a vízmérlegnek. Az egyik közvetlen módszer, amivel az evapotranspirációt becsülni tudjuk, az ún. eddy-kovariancia mérés, amelyet a sok befolyásoló tényező és alapfelvetés miatt számottevő bizonytalanság terhel. Kutatásunk célja az evapotranspiráció mértékének és korlátainak meghatározása és becslése gyepes és szántóföldi területek felett a Magyarországon rendelkezésre álló hosszú idejű eddy-kovariancia mérések alapján.

<p>Soil respiration is a highly complex process including a wide range of soil biota (autotrophic and heterotrophic functioning) and different pathways of carbon cycling (decomposition, arbon allocation), all being under the control of environmental and biotic drivers. The most important biotic driver is the photosynthetic activity of the vegetation providing supply mainly for the autotrophic component of soil respiration: plant roots and their symbiotic partners - such as arbuscular mycorrhizal fungi (AMF). By acting as a source of CO<sub>2</sub> and a pathway of carbon to the SOM, the role of AMF in carbon balance is unquestionable, not to mention that mycorrhizal C allocation could determine the long-term C storage potential of an ecosystem.</p> <p>The objective of this study was to describe the time-lagged relationship between gross primary production (GPP) and the mycorrhizal soil respiration component, so to determine the amount of carbon derived from GPP appearing as mycorrhizal mycelial respiration. Measurements of CO<sub>2</sub> efflux were conducted in three different treatments – i) undisturbed, root and AMF-included (R<sub>s</sub>), ii) root-excluded (R<sub>basal + myc</sub>) and iii) root- and AMF-excluded (R<sub>basal</sub>) plots – for three consecutive years in a Central-Hungarian dry sandy grassland between July 2011 and May 2014. GPP data were derived from eddy-covariance (EC) measurements, while an automated soil respiration system (SRS) consisting of ten chambers was used for continuous and long-term measurement of soil CO<sub>2</sub> efflux. We analysed the relationship between mycorrhizal mycelial respiration and GPP by using cross-correlation and GAMs (generalized additive models). Besides, we used sine wave models to describe the diel pattern of basal and mycorrhizal fungi respiration in the soil together with the diel patterns of soil temperature and GPP.</p> <p>Considering the whole dataset correlation between GPP and mycorrhizal fungi respiration was highest at 13.5 hours time lag, while the average difference between peak timing of mycorrhizal fungi respiration and peak timing of GPP was 15 hours. However, the time lag and the peak timing difference varied from 10-24 hours. According to the results, carbon allocation to mycorrhizal fungi is a fast process in dry grasslands and the main driver of this respiration component is the GPP.</p>

Only a small amount of the light absorbed by the photosynthetic pigments including chlorophylls and carotenoids is de-excited via emission as heat or red and far-red chlorophyll fluorescence under normal physiological conditions. Most of the energy is utilized for photosynthetic quantum conversion. In contrast, photosynthetic performance decreases under numerous stress effects, which is accompanied by a rise in the steady-state levels of chlorophyll fluorescence. Field crops in Hungary are increasingly exposed to extreme weather conditions. Therefore, the main objective of our field study in wheat and sunflower crops was to investigate the effects of heat and drought stress and heterogeneous nutrient availability on the vegetation by quantifying the spatial and temporal variability of photosynthetic efficiency and fluorescence. In a parallel laboratory experiment we attempted to create a pool of plants developing under controlled environment, to meet similar appearance as under field conditions. We found that simultaneous observation of multiple spectral domains and an approach based on field and laboratory measurements were adequate to assess stress and its severity for individual plants and for vegetation canopy. Vegetation indices were good tools to separate the healthy state from the stressed state, and, further combined with fluorescence parameters, we could even draw some conclusion about stress severity. Indices linked to anthocyanin and carotenoid were found to be higher in the already damaged plants, while steady-state fluorescence was higher for leaves with still functioning tissues. Above all, individual species differences were much larger than expected.

In parameterization of the bi-directional ammonia exchange models over vegetated surfaces there are three most crucial parameters: (1) the stomatal (χs) and (2) the soil (χg) compensation point concentrations as the function of Γ=[NH4+]/[H+] in the apoplast and soil, as well as (3) the cuticular resistance Rw. These factors determine the direction and magnitude of the ammonia flux. Moreover, in the sophisticated models the soil (Fg) and litter (Fl) fluxes must be distinguished as well. Furthermore, the recapture of ammonia volatilized from the ground in the lower layer of the canopy should also be considered. For partitioning the measured ammonia flux into stomatal, cuticular and ground parts two-layer, bi-directional exchange models are generally used. However, the parameterization mostly based on empirical relationships involves uncertainties, resulting in disagreements among the applied models in the estimation of the stomatal/soil flux ratio. The main reasons of the deviations may be the following: a) Overestimation of the soil compensation-point (χg).The Γg calculated from the ammonium content of the soil and the pH of the soil solution is overestimated, because part of the ammonium content in the soil is bound in the solid phase hence Henry's law for the liquid phase cannot be applied for this fraction. b) Neglecting of the part of soil derived ammonia recaptured by leaves. For this reason, soil emissions may be underestimated. c) Uncertainty or lack of bioassay measurement for Γs and difficulties with the Γs determined by indirect way. Instead of complicated bioassay measurements, the models generally use empirical approximations to calculate the stomatal compensation point concentration or infer it from the bulk ammonium content of the leaf tissue. Both methods can be a source of error. d) Inaccurate or rough estimate of cuticular resistance. Beside the temperature and humidity, the ratio of acidic air components and ammonia determines the Rw. Models often consider a constant site-specific average for this parameter, even though the ratio of acidic substances to ammonia varies from day to day. Due to these uncertainties, the estimation of the share of fluxes controlled by soil and vegetation is often uncertain. Furthermore, the uncertainty of the parameterization limits the applicability of the model and reduces its robustness. As a conception, we are aiming the use of the following measurement and parameterisation protocol:a) Measurement of the flux above bare soil and above the litter covered soil separately, by soil chambers using the PICARRO-G2103 NH3 Hence, the Fg and Fl and the ratio of compensation point concentrations (χg/χl) can be estimated separately. Comparison of the χg calculated from soil NH4+ and pH with the measured values. b) Calculation of the recaptured ammonia by the model as the residual term among soil-cuticular-stomatal exchange. c) Performing bioassay measurements. d) Use of daily acid/base gas ratio from the nearby regional background air pollution station. Model conception based on previously developed models. Bulk fluxes above the canopy will be measured by the relaxed eddy accumulation technique (REA) with a newly designed photoacoustic system using a QCL as light source.

<p>Soil respiration of grasslands is highly variable both in time and space reflecting the topographic characteristics, the changing environmental constrains and biological activity of the vegetation. The aim of this study was to describe the effect of gross primary productivity (GPP) and soil organic carbon content (SOC) on soil respiration under varying environmental conditions in a dry grassland site in Hungary. We made spatially explicit measurements of variables including soil respiration, aboveground biomass, green vegetation index, soil water content, and soil temperature during an 8-year study in the vegetation periods. Sampling was conducted 23 times in 80 x 60 m grids of 10 m resolution with 78 sampling points. Altitude, slope, and soil organic carbon were used as background factors at each sampling position. Site-level GPP data were derived from eddy-covariance measurements and used for the estimation of GPP at every sampling position as a weighted metric on the basis of the biomass and green vegetation index of the positions. Data were analyzed using generalized additive models (GAM). Spatially, soil respiration had negative correlation with soil temperature, altitude and slope, while it was positively correlated with soil water content, aboveground biomass, green vegetation index and SOC. Soil respiration was significantly different between SOC groups (low-medium-high carbon content), mean soil respiration increased with soil carbon content. According to the GAM analysis, the shape of the GPP response was almost linear in each SOC groups and GPP had a strong influence on soil respiration in all of the groups besides temperature and soil water content. The results suggest that GPP and the resulting belowground carbon allocation<strong> </strong>affecting mainly the autotrophic components of soil respiration have similar influence on soil respiration as the main environmental variables.</p>

In parameterization of the bidirectional ammonia exchange models over vegetated surfaces there are some crucial parameters: the stomatal, the soil, and the cuticular compensation point concentrations as the function of [NH4+]/[H+] ratio in the apoplast, soil, and droplets on leaves, as well as the cuticular resistance. These factors determine the direction and the magnitude of the ammonia flux. Two-layer bidirectional exchange models are generally used to partition the measured flux into different parts. However, the parameterizations are mostly based on empirical relationships involving uncertainties and resulting in disagreements among the applied models in the estimation of the stomatal/soil/cuticular flux ratio. The main reasons for the deviations may be the following: i) Overestimation of the soil compensation-point when calculated from the bulk ammonium content of the soil because a part of ammonium content in the soil is bound in the solid phase. Hence Henry's law for the liquid phase cannot be applied to this fraction. ii) Neglecting the part of soil-derived ammonia recaptured by leaves. For this reason, soil emissions may be underestimated. iii) Lack of bioassay measurement. The models generally use empirical approximations to calculate the stomatal compensation point concentration e.g., by deriving it from the bulk ammonium content of the leaf tissue, which can be a source of bias. iv) Inaccurate or rough estimate of cuticular resistance, which is determined by the ratio of acidic air components and ammonia, besides the temperature and humidity. Models often consider a constant site-specific average for this parameter, even though the ratio of acidic substances to ammonia gas has diurnal and annual variations. Due to these uncertainties, the estimation of the share of fluxes controlled by soil and vegetation is often uncertain. Furthermore, the uncertainty of the parameterization limits the model's applicability and reduces its robustness. As a conception, we aim to simultaneously measure the ammonia flux above the canopy and on the soil. Hence, as the difference between the two fluxes we can determine the amount of ammonia recaptured by the canopy. By means of the soil flux measurement, we can also estimate the bias of empirical soil flux parameterization from soil bulk ammonium content. We also plan performing bioassay measurements to exclude the potential error derived from empirical estimation. Also, we intend calculate the acid/base gas ratio using daily mean concentrations, considering the diurnal variations of humidity-dependent nitric acid/ammonia/ammonium nitrate equilibrium. We will use different conceptional models separately, based on previously developed simulation for all variations of day/night, wet/dry bare soil/vegetation cases in flux estimation at a fertilized crop, making it possible to partition the ratio of ammonia emitted by soil and recaptured either by stomata (built up in plant tissue) or by wet cuticula (net loss).

A significant part of the nitrogen content of fertilizers applied in crops is released into the atmosphere as a loss and pollution sources. Emission occurs partly from the soil and partly through the stomata, but if the compensation point concentration of the apoplast is lower than the air concentration, stomatal absorption takes place. In addition, the processes of cuticular deposition and bidirectional exchange of droplets on the foliage (rain, dew, guttation) also contribute to the exchange processes. In this work, we outline a concept based on modelling and measurements, describing a method for determining ammonia loss from fertilized fields and the amount of it recaptured by the canopy. Furthermore, the method is suitable for partitioning the ammonia flux of the soil-plant system into direct soil emission and stomatal flux (uptake or emission). The rate of exchange processes between the dry or wet cuticle and air can also be estimated, considering the day/night, the diurnal, and the annual variations of ammonium nitrate dissociation and acid/base ratio of gases.Stomatal uptake or emission, cuticular adsorption, as well as bidirectional flux of droplets on the wet leaf, can be separated with models. Since the exchange processes are different depending on the conditions (wet or dry leaves, open or closed stomata) different model conceptions can be used.The article provides a review of sampling and measurement techniques, as well as different model concepts and the parameterization of different model inputs. Among the different concepts and parameterizations, the most suitable one will be selected using the best-fit method, by comparing the measured and modelled fluxes.

This study used the ECOSSE model (v. 5.0.1) to simulate soil respiration (Rs) fluxes estimated from ecosystem respiration (Reco) for eight European permanent grassland (PG) sites with varying grass species, soils, and management. The main aim was to evaluate the strengths and weaknesses of the model in estimating Rs from grasslands, and to gain a better understanding of the terrestrial carbon cycle and how Rs is affected by natural and anthropogenic drivers. Results revealed that the current version of the ECOSSE model might not be reliable for estimating daily Rs fluxes, particularly in dry sites. The daily estimated and simulated Rs ranged from 0.95 to 3.1 g CO2-C m−2, and from 0.72 to 1.58 g CO2-C m−2, respectively. However, ECOSSE could still be a valuable tool for predicting cumulative Rs from PG. The overall annual relative deviation (RD) value between the cumulative estimated and simulated annual Rs was 11.9%. Additionally, the model demonstrated accurate simulation of Rs in response to grass cutting and slurry application practices. The sensitivity analyses and attribution tests revealed that increased soil organic carbon (SOC), soil pH, temperature, reduced precipitation, and lower water table (WT) depth could lead to increased Rs from soils. The variability of Rs fluxes across sites and years was attributed to climate, weather, soil properties, and management practices. The study suggests the need for additional development and application of the ECOSSE model, specifically in dry and low input sites, to evaluate the impacts of various land management interventions on carbon sequestration and emissions in PG.

<p>Quantifying greenhouse gas emissions has been a priority for climate scientists for decades. As a result, the spatial and temporal dynamics of emissions have been widely studied, but to date, we still do not fully understand the main drivers of the variation in patterns. The aim of our research is to quantify the spatio-temporal variability of these greenhouse gases under various nutrient supply conditions and different tillage practices (plow or cultivator) on sandy-clay and loam soils.</p> <p>Our measurements took place near Kartal on loam soil and near Gödöllő on sandy-clay soil, in Central Hungary, in 2022 on winter wheat. CO<sub>2</sub> and N<sub>2</sub>O fluxes are analyzed with Li-cor gas analyzers (LI-870 CO<sub>2</sub>/H<sub>2</sub>O Analyzer and LI-7820 N<sub>2</sub>O/H<sub>2</sub>O Trace Gas Analyzer) connected to the 8200-01S Smart Chamber. We can track both modest changes brought on by natural factors (precipitation, temperature variations) and the impact of more significant artificial factors (fertilization, type of tillage) on the N<sub>2</sub>O and CO<sub>2</sub> flux using these rather sensitive devices. In Kartal, 24, and in Gödöllő 40 KG-PVC rings with a diameter of 20 cm were placed in the study areas and measured on a weekly basis. In Kartal half of the collars received fertilizer, and the other half was covered during the application. In Gödöllő, 8 different treatments can be distinguished, resulting from a combination of 3 different fertilizer doses (0kg/ha, 75kg/ha, and 150kg/ha), 2 tillage methods (plow and cultivator), and soil conditioners. The collars protrude 4 cm from the soil and the inner soil surface has been cleared of vegetation. The gas exchange between soil and air is measured for 3 minutes on each collar, while simultaneously measuring soil moisture, temperature, and vegetation cover (LAI) near the collars. Soil samples were taken monthly to a depth of 15 cm, and 50 cm from the collars.</p> <p>Based on our observation, in the case of N<sub>2</sub>O emission, there are significant differences between the two study areas. On average N<sub>2</sub>O emissions in Gödöllő were higher than in Kartal. Cumulative N<sub>2</sub>O emissions were significantly higher in areas receiving higher doses of fertilizer. For 150kg/ha, the highest value was 42 g N m<sup>2</sup>, while for 0kg/ha and 75kg/ha, lower values of around 16-20 g N m<sup>2</sup> were observed. With average emissions of 420–500 g C m<sup>2</sup>, there are no discernible variations in cumulative CO<sub>2</sub> emission across treatments. However, the temporal variation of both GHG emissions shows differences due to the persistent drought in summer. During the rainy season, spring and autumn, a more intense N<sub>2</sub>O and CO<sub>2</sub> flux were observed due to soil respiration.</p>

Aims The relative importance of species within an ecosystem shows spatio-temporal variability related to both the terrain features and numerous rapidly changing factors. Accordingly, functional and species patterns may show some level of persistence, or, due to various disturbances, fluctuations. Communities with high species richness were found to maintain a higher degree of stability than species-poor or perturbed vegetations; however, diversity and its stability may be spatio-temporally variable. Based on these considerations, our aim was to assess the responses of a sandy pasture, both species-wise and at the community level, to the relatively invariant habitat, and to the more rapidly changing environmental conditions.Location Hungary.Methods We surveyed the vegetation in an area of about 1 ha by means of high-resolution spatio-temporal sampling: we recorded the surface aerial cover (%) of the plant species during 15 campaigns covering spring, summer and autumn aspects for seven years (2013-2019) in 80 x 60 m grids. The biological activity of the ecosystem (above-ground biomass, soil respiration) was also followed up together with the environmental limiting factors.Results During the study period, which was characterized by significant warming, the grassland showed a balanced physiological performance with year-to-year variability. Fluctuating differentiation of the plant species with different environmental optima along with the terrain attributes was assumed to be responsible for this balanced physiological performance. Although community-level diversity remained stable, some species favoring cooler, wetter positions disappeared.Conclusions Terrain features of the study area within 1.5 m or less elevation differences created considerably heterogeneous conditions for a high number (114) of plant species with different ecological needs to co-occur. The stability of the diversity was found to show terrain relatedness, that is spatial as well as temporal patterns compared to the null model of spatio-temporal independence, and the ecosystem functions followed these patterns.