Using remote sensing to assess peatland resilience by estimating soil surface moisture and drought recovery.

Peatland areas provide a range of ecosystem services, including biodiversity, carbon storage, clean water, and flood mitigation, but many areas of peatland in the UK have been degraded through human land use including drainage. Here, we explore whether remote sensing can be used to monitor peatland resilience to drought. We take resilience to mean the rate at which a system recovers from perturbation; here measured literally as a recovery timescale of a soil surface moisture proxy from drought lowering. Our objectives were (1) to assess the reliability of Sentinel-1 Synthetic Aperture Radar (SAR) backscatter as a proxy for water table depth (WTD); (2) to develop a method using SAR to estimate below-ground (hydrological) resilience of peatlands; and (3) to apply the developed method to different sites and consider the links between resilience and land management. Our inferences of WTD from Sentinel-1 SAR data gave results with an average Pearson's correlation of 0.77 when compared to measured WTD values. The 2018 summer drought was used to assess resilience across three different UK peatland areas (Dartmoor, the Peak District, and the Flow Country) by considering the timescale of the soil moisture proxy recovery. Results show clear areas of lower resilience within all three study sites, which often correspond to areas of high drainage and may be particularly vulnerable to increasing drought severity/events under climate change. This method is applicable to monitoring peatland resilience elsewhere over larger scales, and could be used to target restoration work towards the most vulnerable areas.

A model of gross primary productivity based on satellite data suggests formerly afforested peatlands undergoing restoration regain full photosynthesis capacity after five to ten years.

Peatlands are an important terrestrial carbon store, but disturbance has resulted in the degradation of many peatland ecosystems and caused them to act as a net carbon source. Restoration work is being undertaken but monitoring the success of these schemes can be difficult and costly using traditional field-based methods. A landscape-scale alternative is to use satellite data to assess the condition of peatlands and to estimate gaseous carbon fluxes. In this study we used Moderate Resolution Imaging Spectroradiometer (MODIS) products to model Gross Primary Productivity (GPP) over peatland sites at various stages of restoration. We found that the MOD17A2H GPP product overestimates GPP modelled from data collected by eddy covariance towers situated at two ex-forestry sites undergoing restoration towards blanket bog at the Forsinard Flows RSPB reserve, Scotland, UK (one full year of data), and a near-natural Atlantic blanket bog site in Glencar, Ireland (ten-year data series). We calibrated a Temperature and Greenness (TG) model for the Forsinard sites and found it to be more accurate than the MODIS GPP product at local scale. We also found that inclusion of a wetness factor using the Normalised Difference Water Index (NDWI) improved inter-annual accuracy of the model. This TGWa (annual Temperature, Greenness and Wetness) model was then applied to six control sites comprising near-natural bog across the reserve, and to six sites on which restoration began between 1998 and 2006. GPP from 2005 to 2016 was estimated for each site using the model. The resulting modelled trends are positive at all six restored sites, increasing by approximately 5.5 g C/m2/yr every year since restoration began in the Forsinard Flows reserve. The results suggest that peatland sites undergoing restoration at Forsinard Flows reach the carbon assimilation potential of near-natural bog sites between 5 and 10 years after restoration was begun.

Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review.

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration.