Natural moisture limitation during summer drought can constitute a stress for microbial communities in soil. Given globally predicted increases in drought frequency, there is an urgent need for a ...greater understanding of the effects of drought events on soil microbial processes. Using a long-term field-scale drought manipulation experiment at Clocaenog, Wales, UK, we analysed fungal community dynamics, using internal transcribed spacer-denaturing gradient gel electrophoresis (DGGE), over a 1-year period in the 6th year of drought manipulation. Ambient seasonality was found to be the dominant factor driving variation in fungal community dynamics. The summer drought manipulation resulted in a significant decline in the abundance of dominant fungal species, both independently of, and in interaction with, this seasonal variation. Furthermore, soil moisture was significantly correlated with the changes in fungal diversity over the drought manipulation period. While the relationship between species diversity and functional diversity remains equivocal, phenol oxidase activity was decreased by the summer drought conditions and there was a significant correlation with the decline of DGGE band richness among the most dominant fungal species during the drought season. Climatically driven events such as droughts may have significant implications for fungal community diversity and therefore, have the potential to interfere with crucial ecosystem processes, such as organic matter decomposition.
The effects of 4 years of simulated nitrogen deposition, as nitrate (NO₃⁻) and ammonium (NH₄⁺), on microbial carbon turnover were studied in an ombrotrophic peatland. We investigated the ...mineralization of simple forms of carbon using MicroResptrade mark sign measurements (a multiple substrate induced respiration technique) and the activities of four soil enzymes involved in the decomposition of more complex forms of carbon or in nutrient acquisition: N-acetyl-glucosaminidase (NAG), cellobiohydrolase (CBH), acid phosphatase (AP), and phenol oxidase (PO). The potential mineralization of labile forms of carbon was significantly enhanced at the higher N additions, especially with NH₄⁺ amendments, while potential enzyme activities involved in breakdown of more complex forms of carbon or nutrient acquisition decreased slightly (NAG and CBH) or remained unchanged (AP and PO) with N amendments. This study also showed the importance of distinguishing between NO₃⁻ and NH₄⁺ amendments, as their impact often differed. It is possible that the limited response on potential extracellular enzyme activity is due to other factors, such as limited exposure to the added N in the deeper soil or continued suboptimal functioning of the enzymes due to the low pH, possibly via the inhibitory effect of low phenol oxidase activity.
Peatland restoration has become a common land-use management practice in recent years, with the water table depth (WTD) being one of the key monitoring elements, where it is used as a proxy for ...various ecosystem functions. Regular, uninterrupted, and spatially representative WTD data in situ can be difficult to collect, and therefore, remotely sensed data offer an attractive alternative for landscape-scale monitoring. In this study, we illustrate the application of Sentinel-1 SAR backscatter for water table depth monitoring in near-natural and restored blanket bogs in the Flow Country of northern Scotland. Among the study sites, the near-natural peatlands presented the smallest fluctuations in the WTD (with depths typically between 0 and 15 cm) and had the most stable radar signal throughout the year (~3 to 4 dB amplitude). Previously drained and afforested peatlands undergoing restoration management were found to have higher WTD fluctuations (depths up to 35 cm), which were also reflected in higher shifts in the radar backscatter (up to a ~6 dB difference within a year). Sites where more advanced restoration methods have been applied, however, were associated with shallower water table depths and smoother surfaces. Three models—simple linear regression, multiple linear regression, and the random forest model—were evaluated for their potential to predict water table dynamics in peatlands using Sentinel-1 SAR backscatter. The random forest model was found to be the most suited, with the highest correlation scores, lowest RMSE values, and overall good temporal fit (R2 = 0.66, RMSE = 2.1 cm), and multiple linear regression came in a close second (R2 = 0.59, RMSE = 4.5 cm). The impact of standing water, terrain ruggedness, and the ridge and furrow aspect on the model correlation scores was tested but found not to have a statistically significant influence. We propose that this approach, using Sentinel-1 and random forest models to predict the WTD, has strong potential and should be tested in a wider range of peatland sites.
The net impact of greenhouse gas emissions from degraded peatland environments on national Inventories and subsequent mitigation of such emissions has only been seriously considered within the last ...decade. Data on greenhouse gas emissions from special cases of peatland degradation, such as eroding peatlands, are particularly scarce. Here, we report the first eddy covariance-based monitoring of carbon dioxide (CO
2
) emissions from an eroding Atlantic blanket bog. The CO
2
budget across the period July 2018–November 2019 was 147 (± 9) g C m
−2
. For an annual budget that contained proportionally more of the extreme 2018 drought and heat wave, cumulative CO
2
emissions were nearly double (191 g C m
−2
) of that of an annual period without drought (106 g C m
−2
), suggesting that direct CO
2
emissions from eroded peatlands are at risk of increasing with projected changes in temperatures and precipitation due to global climate change. The results of this study are consistent with chamber-based and modelling studies that suggest degraded blanket bogs to be a net source of CO
2
to the atmosphere, and provide baseline data against which to assess future peatland restoration efforts in this region.
Peatlands provide important ecosystem services including carbon storage and biodiversity conservation. Remote sensing shows potential for monitoring peatlands, but most off-the-shelf data products ...are developed for unsaturated environments and it is unclear how well they can perform in peatland ecosystems. Sphagnum moss is an important peatland genus with specific characteristics which can affect spectral reflectance, and we hypothesized that the prevalence of Sphagnum in a peatland could affect the spectral signature of the area. This article combines results from both laboratory and field experiments to assess the relationship between spectral indices and the moisture content and gross primary productivity (GPP) of peatland (blanket bog) vegetation species. The aim was to consider how well the selected indices perform under a range of conditions, and whether Sphagnum has a significant impact on the relationships tested. We found that both water indices tested normalized difference water index (NDWI) and floating water band index (fWBI) were sensitive to the water content changes in Sphagnum moss in the laboratory, and there was little difference between them. Most of the vegetation indices tested the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), structure insensitive pigment index (SIPI), and chlorophyll index (CIm) were found to have a strong relationship with GPP both in the laboratory and in the field. The NDVI and EVI are useful for large-scale estimation of GPP, but are sensitive to the proportion of Sphagnum present. The CIm is less affected by different species proportions and might therefore be the best to use in areas where vegetation species cover is unknown. The photochemical reflectance index (PRI) is shown to be best suited to small-scale studies of single species.
Peatland is a globally important store of carbon. Peatland restoration efforts are being increasingly undertaken yet effective monitoring of landscape-scale restoration projects has been limited. A ...particular gap in our understanding is the length of time required before a site reaches the target state. To address this, a classification model based on remote sensing data was developed for a peatland restoration area on blanket bog in northern Scotland, UK, to evaluate whether post-restoration trajectories followed predictable trends over time. The model was trained against a chronosequence of sites within a 20 × 10 km study area that are being restored following drainage and intensive non-native afforestation. Two versions of the model were created to compare the accuracy obtainable from the suite of Sentinel-2 satellite data versus sub-metre resolution aerial imagery from GetMapping (RGB and IR). The Sentinel-2 based model greatly outperformed the aerial imagery-based model. Adding surface slope to the classification did not significantly improve the accuracy of prediction. Prediction of starting and target land covers was very robust, and both the most recent and oldest restoration sites were well predicted spatially. The main uncertainties in the model were within sites of intermediate restoration age, and sites which underwent additional treatments after the initial restoration. Using standard vegetation and wetness indices as indicators, it was possible to track the progression of areas that had been felled and rewetted towards the spectral signal of the control blanket bog locations. A further study examined the use of multiple years of satellite data (2015-2021) and including Sentinel-1 SAR imagery, and confirmed the findings obtained with only a single climatically average year, and furthermore examined the efficacy of different restoration methods. We observed consistent trends of restoration sites beginning to resemble the target hydrologically and ecologically functional blanket bog state after 10-20 years post intervention.
Vegetational changes during the restoration of cutover peatlands leave a legacy in terms of the organic matter quality of the newly formed peat. Current efforts to restore peatlands at a large scale ...therefore require low cost and high throughput techniques to monitor the evolution of organic matter. In this study, we assessed the merits of using Fourier transform infrared (FTIR) spectra to predict the organic matter composition in peat samples at various stages of peatland regeneration from five European countries. Using predictive partial least squares (PLS) analyses, we were able to reconstruct peat C:N ratio and carbohydrate signatures with reasonable accuracy, but not the micromorphological composition of vegetation remains. Despite utilising different size fractions, both carbohydrate (<200
μm fraction) and FTIR (bulk soil) analyses report on the composition of plant cell wall constituents in the peat and therefore essentially reveal the composition of the parent vegetational material. The accuracy of the FTIR-based PLS models for C:N ratios and carbohydrate signatures was adequate to allow for their use as initial screening tools in the evaluation of the present and future organic matter composition of peat during monitoring of restoration efforts.
Peatlands are important reservoirs of carbon (C) but our understanding of C cycling on cutover peatlands is limited. We investigated the decomposition over 18 months of five types of plant litter ...(Calluna vulgaris, Eriophorum angustifolium, Eriophorum vaginatum, Picea sitchensis and Sphagnum auriculatum) at a cutover peatland in Scotland, at three water tables. We measured changes in C, nitrogen (N) and phosphorus (P) in the litter and used denaturing gradient gel electrophoresis to investigate changes in fungal community composition. The C content of S. auriculatum litter did not change throughout the incubation period whereas vascular plant litters lost 30-40% of their initial C. There were no differences in C losses between low and medium water tables, but losses were always significantly less at the high water table. Most litters accumulated N and E. angustifolium accumulated significant quantities of P. C, N and P were significant explanatory variables in determining changes in fungal community composition but explained <25% of the variation. Litter type was always a stronger factor than water table in determining either fungal community composition or turnover of C, N and P in litter. The results have implications for the ways restoration programmes and global climate change may impact upon nutrient cycling in cutover peatlands.
Estimates of peatland carbon fluxes based on remote sensing data are a useful addition to monitoring methods in these remote and precious ecosystems, but there are questions as to whether large-scale ...estimates are reliable given the small-scale heterogeneity of many peatlands. Our objective was to consider the reliability of models based on Earth Observations for estimating ecosystem photosynthesis at different scales using the Forsinard Flows RSPB reserve in Northern Scotland as our study site. Three sites across the reserve were monitored during the growing season of 2017. One site is near-natural blanket bog, and the other two are at different stages of the restoration process after removal of commercial conifer forestry. At each site we measured small (flux chamber) and landscape scale (eddy covariance) CO2 fluxes, small scale spectral data using a handheld spectrometer, and obtained corresponding satellite data from MODIS. The variables influencing GPP at small scale, including microforms and dominant vegetation species, were assessed using exploratory factor analysis. A GPP model using land surface temperature and a measure of greenness from remote sensing data was tested and compared to chamber and eddy covariance CO2 fluxes; this model returned good results at all scales (Pearson's correlations of 0.57 to 0.71 at small scale, 0.76 to 0.86 at large scale). We found that the effect of microtopography on GPP fluxes at the study sites was spatially and temporally inconsistent, although connected to water content and vegetation species. The GPP fluxes measured using EC were larger than those using chambers at all sites, and the reliability of the TG model at different scales was dependent on the measurement methods used for calibration and validation. This suggests that GPP measurements from remote sensing are robust at all scales, but that the methods used for calibration and validation will impact accuracy.
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•Peatlands have heterogeneous microtopography that challenges large-scale monitoring.•Remote sensing has the potential to monitor peatland GPP over large areas.•Flux chambers and eddy covariance were compared to spectrometer and satellite data.•A Temperature and Greenness model correlated with GPP at small and large scales.•Microtopography had minimal influence, model calibration was important.
Extracellular phenol oxidases play an important role in the soil carbon cycle. The effects of a field-scale summer drought manipulation on extracellular litter and soil phenol oxidase activity, ...soluble phenolic compounds and dissolved organic carbon concentrations were examined for an upland Calluna heathland on a peaty podsol in North Wales. Litter and organic soil phenol oxidase activity was found to be positively correlated with moisture content. Thus in shallow organic soils, which are sensitive to drying during periods of low rainfall, drought may inhibit soil phenol oxidase activity as a result of water limitations. The release of soluble phenolic compounds and DOC from the droughted plots was found to be lowered during the drought period and elevated outside of the drought period. It is hypothesized that these changes may be a result of the reduced ability of extracellular phenol oxidases to process recalcitrant polyphenolic material under drought conditions. A drying incubation carried out with litter and soil cores from the same site suggests that extracellular phenol oxidase activity displays an optimal moisture level. This reconciled the observed water limitation of phenol oxidase activity at the heathland experimental site with previously observed stimulation of phenol oxidase activity by water table drawdown in deeper peats.
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