Two potential equilibrium states in long-term soil respiration activity of dry grasslands are maintained by local topographic features

Abstract

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 (R s), soil temperature (T s) 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 R s activity, as well as its temporal stability: average rankR s , the temporal average R s rank of a measuring position from the campaigns revealed the persistent spatial pattern of R s , while rangeR s , the range of ranks of the positions from the campaigns described the amplitude of the R s 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 R s activity: R s activity with smaller rangeR s , that is both the lower elevation positions with larger rankR s ("state I") and the higher elevation positions with smaller rankR s ("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 rangeR s for medium rankR s , suggesting resilience (not resistance) as a major strategy for this ecosystem. Grasslands exchange large quantities of greenhouse gases between the soil and the atmosphere. Uncertainties related to greenhouse gas flux estimates originate partly from the fact that these fluxes are spatio-temporally highly variable 1-5. Seasonal and diurnal fluctuations of these fluxes, e.g., soil respiration (R s) and its components are partly temperature (T s) driven 6 but temporal changes in soil moisture (SWC 7), plant biomass, photosynthetic performance 8 and litterfall also play a significant role in modifying the overall picture. Also, R s and its main abiotic drivers, T s and SWC, show substantial horizontal heterogeneity at different spatial scales 4,9-13 , which is made even more complex by the interaction of the explanatory variables (e.g., cooling effect of soil moisture 4,11,14). These point to the relevance of spatial studies with temporal replicates 14. Although the actual value and spatial distribution of the pattern-generating factors are responsible for the observed spatial pattern of R s , the functioning of ecosystems takes place through dynamically changing, forming and transforming spatial patterns 13,15-19 , which are worth further investigations. Furthermore, the stability of ecosystem functions and the existence of persistent patterns are of high significance as these patterns are sustained by long-term climatic, surface rel...

Co-varying effects of vegetation structure and terrain attributes are responsible for soil respiration spatial patterns in a sandy forest–steppe transition zone

“…The responses of R s to soil moisture and T s were investigated in several studies, which already reported that the correlation between R s and T s as well as SWC and T s differed in temporal and spatial studies (Allaire et al, 2012;Almagro et al, 2009;Fóti et al, 2020;Herbst et al, 2009;Lellei-Kovács et al, 2016;Moyes and Bowling, 2016;Shi et al, 2011;Tang et al, 2020). Our study is consistent with these findings, because R s showed positive correlation with SWC and LAI.…”

“…On the other hand, surface heterogeneity was lower under the grove due to the fact that the seeds of tree species in this habitat can only germinate in ideal depressions, where a sufficient amount of water can accumulate (Erdős et al, 2014). In the context of spatial heterogeneity, deeper positions contain more carbon due to accumulation, resulting in higher R s activity and SWC (Fóti et al, 2020).…”

“…Four terrain attributes were calculated for the best characterization of the surface with the least potential co-variance between the selected attributes and the ones which were found to be applicable for a range of terrain complexities. For a more detailed description of the calculations please refer to Fóti et al (2020). We used RSAGA (Brenning et al, 2018) and raster packages (Hijmans, 2018) for the terrain attribute analyses mentioned below.…”

“…Actually, the abiotic factors of the landscape/habitat related to terrain attributes (e.g., slope, altitudinal differences, aspect) and the subsequent distribution of plant species (Cuena-Lombraña et al, 2018;Hohnwald et al, 2020;Latif and Blackburn, 2010;Potter, 2014) mutually influence each other (Alexander et al, 2016). The slopes and altitudinal differences can be closely related to water accumulation and surface runoff, which were found to influence functional spatiotemporal patterns of the vegetation (Fóti et al, 2020;Lassueur et al, 2006). Slopes with different orientation are exposed to different physical effects (e.g., predominant wind direction and irradiation).…”

“…Slopes with different orientation are exposed to different physical effects (e.g., predominant wind direction and irradiation). The main difference between north-and south-facing slopes resides in their shade duration, due to the different amounts of incoming solar radiation (Alexander et al, 2016;Fóti et al, 2020), and the west side of a grove could be colder than the east side during a diurnal period (Süle et al, 2020). This variability in shading causes significant variation in plant composition (Erdős et al, 2014), with the subsequent differences in microclimate giving evidence of a mutual spatiotemporal effect.…”