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Livestock is both threatened by and contributing to climate change. The contribution of livestock to climate change and greenhouse gas (GHG) emission greatly vary under different management regimes. A number of mitigation options comprise livestock management, although there are a lot of uncertainties as to which management regime to use for a given pedoclimatic and farming system. Therefore, we 1) tested if an extensive cattle livestock farm is a net sink or a net source for GHG (carbon–dioxide, CO 2 ; methane, CH 4 ; nitrous oxide N 2 O) in Central–Eastern Europe, 2) compared the annual GHG balances between the grazed and mowed treatments of the farm 3) and investigated the role of climate variability in shaping these balances. Net ecosystem exchange of CO 2 ( NEE ) was measured with eddy covariance technique in both the grazed and mowed treatments. Estimations of lateral C fluxes were based on management data. Other GHG fluxes (CH 4 , N 2 O) were determined by chamber gas flux measurements technique (in case of soil) and IPCC guidelines (in case of manure decomposition and animal fermentation). Net greenhouse gas balance ( NGHG ) for the grazed treatment was 228 ± 283 g CO 2 equivalent m −2 year −1 (net sink) and −475 ± 144 g CO 2 equiv. m −2 year −1 (net source) for the mowed treatment. Net source activity at the mowed treatment was due to its higher herbage use intensity compared to the grazed treatment. At the farm scale the system was estimated to be a net sink for NGHG in a year with wet (135 g CO 2 equiv. m −2 year −1 ), while a net source in years with dry soil moisture conditions (−267 ± 214 g CO 2 equiv. m −2 year −1 ). We conclude that under a temperate continental climate extended extensive grazing could serve as a potential mitigation of GHG in contrast to mowing. Our study highlights the fact that livestock farming could create a net sink for GHG under proper management regimes. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) and net ecosystem exchange (NEE) of a semi-arid grassland (46.69˚N, 19.60˚ E near Bugacpuszta, Hungary) have been measured since 2002 by eddy covariance(EC) technique. The calculation of the turbulent fluxes from the raw (10 Hz) dataset was performed by theEddyPro® open source software. Gap-filling and flux partitioning was accomplished by theREddy ProcWeb online tool (Reichstein et al 2005). Based on the 14 years (2003-2017) long dataset the annual mean evapotranspiration at theBugac site is 488 mm (SD: 77 mm), while the mean annual precipitation for the same periodis 566 mm. The annual sum of ET was less than the annual sum of precipitation except fortwo years (2011, 2012) following a wet extreme year (2010) showing a significant memoryeffect. Mitigating effect of water storage was significant on shorter time scales as well, sinceprecipitation sums during the summer months were exceeded by those of ET indrought/heatwave years (2003, 2007, 2009, 2011, 2012). Strong coupling betweentranspiration and photosynthesis as shown by the strong correlation (R2=0.8618) between theannual sum of ET and GPP was due to high LAI (closed canopy) and more or less constantcover. EC based evapotranspiration data was compared to MODIS Evapotranspiration(MOD16). On annual basis MODIS ET is a close estimation of EC based ET, as the slope ofthe regression between the yearly sums (2003-2013) of MODIS based vs EC based ET is1.0168 (R2=0.6236, RMSE=43.03mm). However, when considering the main growingseason (1 May - 31 July) only, MODIS ET underestimated EC based ET by 10% (R2=0.77,RMSE=22.74), showing that there is a bias on seasonal basis in the MODIS data. Goodnessof fit for the regression of 8-days sums (temporal resolution of MODIS data) in the differentyears range between 0.6913 and 0.8879, while the slope ranges between 0.9271 and 1.2224. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 × 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. [ABSTRACT FROM AUTHOR]

Aims: Our aim was to study the effect of potential biotic drivers, including evapotranspiration (ET) and gross primary production (GPP), on the soil CO production and efflux on the diel time scale. Methods: Eddy covariance, soil respiration and soil CO gradient systems were used to measure the CO and HO fluxes in a dry, sandy grassland in Hungary. The contribution of CO production from three soil layers to plot-scale soil respiration was quantified. CO production and efflux residuals after subtracting the effects of the main abiotic and biotic drivers were analysed. Results: Soil CO production showed a strong negative correlation with ET rates with a time lag of 0.5 h in the two upper layers, whereas less strong, but still significant time-lagged and positive correlations were found between GPP and soil CO production. Our results suggest a rapid negative response of soil CO production rates to transpiration changes, and a delayed positive response to GPP. Conclusions: We found evidence for a combined effect of soil temperature and transpiration that influenced the diel changes in soil CO production. A possible explanation for this pattern could be that a significant part of CO produced in the soil may be transported across soil layers via the xylem. [ABSTRACT FROM AUTHOR]

Aims: Soil respiration (Rs) 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 Rs: 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 Rs component in order to determine the amount of carbon derived from GPP appearing as mycorrhizal respiration (Rmyc).Measurements of Rs were conducted in three treatments - (i) undisturbed, root and arbuscular mycorrhizal fungi (AMF)-included (Rs), (ii) root-excluded (Rhet+myc) and (iii) root- and AMF-excluded (Rhet) 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 Rs. We analysed the relationship between Rmyc and GPP by using cross-correlation and by fitting sine wave models on the diel datasets.GPP was found to be the main driver of Rmyc, 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.Based on the seasonal changes in the delay, we concluded that GPP and soil temperature had simultaneous effects on the diel pattern of CO2 emission of the different autotrophic components depending on the vegetation activity and environmental conditions.Methods: Soil respiration (Rs) 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 Rs: 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 Rs component in order to determine the amount of carbon derived from GPP appearing as mycorrhizal respiration (Rmyc).Measurements of Rs were conducted in three treatments - (i) undisturbed, root and arbuscular mycorrhizal fungi (AMF)-included (Rs), (ii) root-excluded (Rhet+myc) and (iii) root- and AMF-excluded (Rhet) 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 Rs. We analysed the relationship between Rmyc and GPP by using cross-correlation and by fitting sine wave models on the diel datasets.GPP was found to be the main driver of Rmyc, 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.Based on the seasonal changes in the delay, we concluded that GPP and soil temperature had simultaneous effects on the diel pattern of CO2 emission of the different autotrophic components depending on the vegetation activity and environmental conditions.Results: Soil respiration (Rs) 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 Rs: 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 Rs component in order to determine the amount of carbon derived from GPP appearing as mycorrhizal respiration (Rmyc).Measurements of Rs were conducted in three treatments - (i) undisturbed, root and arbuscular mycorrhizal fungi (AMF)-included (Rs), (ii) root-excluded (Rhet+myc) and (iii) root- and AMF-excluded (Rhet) 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 Rs. We analysed the relationship between Rmyc and GPP by using cross-correlation and by fitting sine wave models on the diel datasets.GPP was found to be the main driver of Rmyc, 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.Based on the seasonal changes in the delay, we concluded that GPP and soil temperature had simultaneous effects on the diel pattern of CO2 emission of the different autotrophic components depending on the vegetation activity and environmental conditions.Conclusion: Soil respiration (Rs) 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 Rs: 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 Rs component in order to determine the amount of carbon derived from GPP appearing as mycorrhizal respiration (Rmyc).Measurements of Rs were conducted in three treatments - (i) undisturbed, root and arbuscular mycorrhizal fungi (AMF)-included (Rs), (ii) root-excluded (Rhet+myc) and (iii) root- and AMF-excluded (Rhet) 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 Rs. We analysed the relationship between Rmyc and GPP by using cross-correlation and by fitting sine wave models on the diel datasets.GPP was found to be the main driver of Rmyc, 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.Based on the seasonal changes in the delay, we concluded that GPP and soil temperature had simultaneous effects on the diel pattern of CO2 emission of the different autotrophic components depending on the vegetation activity and environmental conditions. [ABSTRACT FROM AUTHOR]

To investigate the temporal dynamics of CO2 efflux from the soil surface in a temperate cropland and to quantify the effects of soil temperature, soil water content, N fertilization and plant growth on soil carbon dioxide efflux (Rs) field and lab experiments were performed. The field experiment was conducted in a cropland site with a conventional farming system in Central Hungary. The temporal changes of Rs were estimated using a closed chamber IRGA system about bi-weekly/monthly between November 2017–November 2019 in 10 positions. The measured average soil CO2 efflux values ranged from 0.06 ± 0.007 to 7.04 ± 0.44 µmol CO2 m–2 s–1 Soil respiration model including soil temperature (Ts), soil water content (SWC) and the incorporation of VIgreen (plant growth and functioning) gave a higher goodness-of-fit value (r2 = 0.54) than the simple temperature response. According to our field results, different variables including Ts, SWC and VIgreen play a principal role in the carbon cycle of the investigated cropland. We further investigated the effects of the main drivers in a laboratory experiment with the same soil. Closed chamber technique was used for measuring the emission of carbon dioxide by a Picarro G1101-i gas analyzer. We also introduced a fertilization experiment: three different N treatments were applied (N0, N75 and N150) with different levels of soil water content on the soil planted with maize and bare soil. According to our laboratory results, the cumulative CO2 efflux from soil was found to have a positive correlation with plant growth and with N fertilizer rate: as higher plant biomass and more N added, more CO2 was emitted, whereas, the cumulative emissions values from planted soil were around two times higher than in bare soil in all treatments. Significant positive correlations were found between CO2 efflux and SWC indicating that the soil water content was the main factor limiting the rate of the CO2 emission from soil in both planted and bare soil, in which the cumulative CO2 efflux was increased with the increase in soil water content, and it was almost three times higher in planted soils at higher soil moisture level than in the bare soil. We can conclude that the effects of plant presence and soil moisture on soil respiration had similar magnitude; however, the effect of N addition was small. [ABSTRACT FROM AUTHOR]

Diel variability of soil respiration is influenced by several factors including temperature and carbon allocation as the most significant ones, co-varying on multiple time scales. In an attempt to disentangle their effects we analyzed the dynamics of soil respiration components using data from a three-year soil respiration study. We measured CO2 efflux in intact, root-excluded and root- and mycorrhizal fungi excluded plots and analyzed the diel variability in different phenological stages. We used sine wave models to describe the diel pattern of soil respiration and to disentangle the effects of temperature from belowground carbon allocation based on the differences between component dynamics inferred from the fitted models. Rhizospheric respiration peaked 8–12 hours after GPP peak, while mycorrhizal fungi respiration had a longer time lag of 13–20 hours. Results of δ13CO2 isotopic signals from the respiration components showed similar patterns. It was found that drought affected the component respiration rates differently. Also, the speed and the amount of carbon allocation to the roots as well as to the mycorrhizal fungi was reduced under drought. We conclude that the diel variability of soil respiration is the result of the integrated patterns of temperature- and carbon allocation-driven components in dry grasslands and their share depends on their phenological stages and stress state. [ABSTRACT FROM AUTHOR]

The main objective of the present study was to determine the contributions of autotrophic and heterotrophic components to the total soil CO 2 efflux over three years with high-frequency data acquisition by means of automated measurements. Soil CO 2 efflux was measured continuously by using an automated open system of 10 soil respiration chambers in a sandy grassland in Hungary. Mesh-collar technique was applied to separate the components of the total respiration. Data were collected (1) in root-exclusion (Exr), (2) in root- and mycorrhiza exclusion (Exrm) and (3) in control plots (Exc, roots and mycorrhiza included). We fitted three different models to describe the dependence of total soil CO 2 efflux measured on the Exc (Rs), CO 2 efflux measured on Exr (R TR ) and CO 2 efflux measured on Exrm (R TRM ) on abiotic and biotic drivers. The best fitted model (based on AIC) was later on used in a simulation process. The contribution by rhizospheric respiration (simulated, R rhizo* ) was 36 ± 21%, the contribution by mycorrhizal respiration (simulated, R myc* ) to the total soil respiration was 9 ± 9% while the contribution by heterotrophic respiration (simulated, R het* ) was 55 ± 21% on average. Measured mycorrhizal respiration (R M ) responded to GPP with a time lag of 0–2 days in active period. Drought affected the autotrophic component of soil respiration the most intensively: raise of soil water content resulted in increase of R S by 175% while R TR and R TRM increased by 127% and 93%, respectively. The results highlight the fact that it would be useful to establish and apply separate models for each component. [ABSTRACT FROM AUTHOR]

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented).Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance. [ABSTRACT FROM AUTHOR]

Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types. [ABSTRACT FROM AUTHOR]

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil moisture related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multi-layer soil module). Case studies on a managed forest, cropland and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance. [ABSTRACT FROM AUTHOR]

Abstract: High variability of soil respiration measured at fine spatial scale increases the uncertainty when trying to determine the representative average soil respiration (Rs) flux. A possible way to decrease the uncertainty, while also optimising measurement effort, could be the calculation of required number of Rs measurements (Nopt) together with the optimisation of their spatial arrangement. The goals of this study were to find explanatory variables of the structural parameters of fine-scale Rs spatial pattern and of Nopt for sampling optimisation. We conducted field Rs, soil temperature (Ts) and soil water content (SWC) measurements in a Hungarian sandy pasture over several years along circular transects of 75 evenly spaced (20cm distance) sampling positions. Structural parameters of patterns of Rs and the covariates were determined from variograms. Ranges of spatial autocorrelation varied between 0 and 3.6m for Rs, 0 and 3m for SWC and 0 and 2.9m for Ts. Patch size of Rs depended negatively on transect average SWC. To understand and quantify the spatial dependence of variables, cross-variograms were calculated. Rs proved to be positively spatially correlated to SWC at low water supply, while Ts-Rs and SWC-Ts spatial correlations were mostly negative, both due the direct effect of evaporative cooling on Ts. We found that spatial patchiness became less robust and the correlations generally decreased as soil moisture content was high. We found that explanatory variable of Nopt was also SWC, with negative correlation between them. We conclude that sampling could be optimized on the basis of the easily measurable actual SWC, which determines both the optimal number of Rs measurements and the minimum distances between individual samples in semi-arid ecosystems. [Copyright &y& Elsevier]

• Vegetation composition and diversity did not change for six years after the conversion from grazing to mowing. • Even the detailed fine-scale analyses could not reveal differences. • Carbon uptake differed between grazed vs. mowed sites due to biomass removal intensity. • Returning from mowing to grazing would probably restore C uptake because the vegetation composition remained stable. Grasslands could play an important role in supporting livestock, in carbon sequestration and in biodiversity conservation. Different grassland managements may change the vegetation composition of grasslands, which could alter these ecosystem services. We studied the effects of grazing vs. mowing on the vegetation composition (2012–2016) and on the carbon uptake (2011–2013) of sandy grasslands in Hungary to study if the vegetation composition differs and if it does, whether it affects carbon uptake. To observe differences in vegetation composition between the two types of management regimes we performed fine-scale vegetation survey in adjacent grazed and mowed sites. We compared species compositions and vegetation diversity indices between the management regimes based on permutational ANOVA, mixed effect model and information theory models. We used fine-scale vegetation survey because it has the potential to indicate vegetation changes within six years as changes in species richness and diversity are usually detected after 10–20 years. Carbon uptake was measured in parallel with eddy covariance technique at both sites. In spite of the contrasting management regimes the vegetation composition was stable (no differences observed in the diversity indices), while carbon uptake was significantly greater in the grazed (sink: +1 ± 0.7 t C ha−1 year−1) compared to the mowed site (source: -0.3 ± 0.6 t C ha−1 year−1). The vegetation was heterogeneous (patchy) and had a high species richness at both sites (grazed: 91 species ha−1, mowed: 90 species ha−1) which might have contributed to the stability of the vegetation composition. We concluded that differences in carbon uptake existed between the grazed vs. mowed sites due to biomass removal intensity with no differences in the vegetation composition. [ABSTRACT FROM AUTHOR]

Soil respiration of grasslands is spatio-temporally variable reflecting the changing biological activities of the soil. In our study we analysed how the long-term soil respiration activities of dry grasslands would perform in terms of resistance and resilience. We also investigated how terrain features are responsible for response stability. We conducted a 7-year-long spatial study in a Hungarian dry grassland, measuring soil respiration (Rs), soil temperature (Ts) and soil water content (SWC) along 15 measuring campaigns in 80 × 60 m grids and soil organic carbon content in 6 of the occasions. Two proxy variables were introduced to grasp the overall Rs activity, as well as its temporal stability: average rankRs, the temporal average Rs rank of a measuring position from the campaigns revealed the persistent spatial pattern of Rs, while rangeRs, the range of ranks of the positions from the campaigns described the amplitude of the Rs response in time, referring to the response stability in terms of resistance or resilience. We formulated a hypothetic concept of a two-state equilibrium to describe the performance of the long-term Rs activity: Rs activity with smaller rangeRs, that is both the lower elevation positions with larger rankRs ("state I") and the higher elevation positions with smaller rankRs ("state II") correspond to an equilibrium state with several terrain attributes being responsible for the equilibrium responses. Majority of the measuring positions was belonging to none of these equilibrium states. These positions showed higher rangeRs for medium rankRs, suggesting resilience (not resistance) as a major strategy for this ecosystem. [ABSTRACT FROM AUTHOR]

Grasslands, such as other managed fields, release large quantities of greenhouse gases (GHG). Fluxes of GHG are highly variable spatio-temporally, which hampers the quantification of the yearly sum. Although actual spatial patterns of ecosystem functions (EF) are determined by the actual spatial distribution and intensity of background or driving variables, a potential "optimal" or persistent state can also be detected on the basis of long-term climatic, surface relief and soil conditions. Changing climate could alter these instant and long-term patterns through the modification of the drivers. Field studies and spatial analysis can help to reveal such temporal dynamics of spatial patterns and to understand the shifts in EF.We used two ways of spatial analysis to study grassland EF. One way was the geostatistical analysis of low-resolution field-scale manual measurements on 10 × 10 m grids. Geostatistical data processing revealed that topographic differences, however small they might be, had primary importance in the generation of spatial patterns of both the soil nutrients and the microclimate due to the variability of the available soil moisture and fine shading effects of crests and depressions, both the patterns of the above-ground biomass, soil respiration, and nitrous oxide flux. We found that spatial patterns and spatial correlations between variable pairs were dynamically changing characteristics. A further controlling factor was the management of the grasslands, creating different levels of homogeneity/heterogeneity.The other way in spatial analysis can be the use of a high-resolution data. We used a 0.2 × 0.2 m resolution digital elevation model (DEM) in the geostatistical analysis for external drift kriging. In many cases kriging with DEM gave us better result than ordinary kriging with the variable itself. However, a more important use of DEM could be the calculation of different topographic attributes (e.g., slope, aspect, topographic position index, surface rugosity), because these data can reveal more about the neighboring effects within a landscape. We hypothesized that not just DEM, but the calculation of different indices along a spatial series can help to have a more detailed insight into the effects of topography on the spatial patterns of e.g. erosion, soil nutrient horizontal heterogeneity, and also on the EF. [ABSTRACT FROM AUTHOR]

Diel variability of soil respiration could be driven by several factors, but temperature and carbon allocation have the most significant effect on that. However, these two factors covariate on multiple time scales, therefore it is not easy to disentangle their effect.We measured CO2 efflux in undisturbed, root-excluded and root- and mycorrhizal fungi excluded plots and analyzed the diel variability and the responses to GPP in different phenological stages. We used sine wave models to describe the characteristics of diel variability and to estimate the temperature and GPP driven part of total soil respiration.Rhizospheric respiration peaked 8-12 hours after GPP peak, while mycorrhizal fungi respiration had a longer time lag of 13-20 hours. Results of isotopic measurements also showed similar pattern. Drought affected respiration rates as well as carbon allocation pattern; both the amount and the speed of carbon allocated to mycorrhizal fungi were reduced under drought.Based on these results we assume that the commonly used Q10 values does not always reflect the temperature response of soil CO2 efflux, but the propagated effect of the temperature and belowground carbon allocation and those share in soil respiration vary with phenological stages. [ABSTRACT FROM AUTHOR]