Delineating the distribution of mineral and peat soils at the landscape scale in northern boreal regions

Abstract

Abstract. To meet the sustainable development goals and enable sustainable management and protection of peatlands, there is a strong need for improving the mapping of peatlands. Here we present a novel approach to identify peat soils based on a high-resolution digital soil moisture map that was produced by combining airborne laser scanning-derived terrain indices and machine learning to model soil moisture at 2 m spatial resolution across the Swedish landscape. As soil moisture is a key factor in peat formation, we fitted an empirical relationship between the thickness of the organic layer (measured at 5479 soil plots across the country) and the continuous SLU (Swedish University of Agricultural Science) soil moisture map (R2= 0.66, p < 0.001). We generated categorical maps of peat occurrence using three different definitions of peat (30, 40, and 50 cm thickness of the organic layer) and a continuous map of organic layer thickness. The predicted peat maps had a higher overall quality (MCC = 0.69–0.73) compared to traditional Quaternary deposits maps (MCC = 0.65) and topographical maps (MCC = 0.61) and captured the peatlands with a recall of ca. 80 % compared to 50 %–70 % on the traditional maps. The predicted peat maps identified more peatland area than previous maps, and the areal coverage estimates fell within the same order as upscaling estimates from national field surveys. Our method was able to identify smaller peatlands resulting in more accurate maps of peat soils, which was not restricted to only large peatlands that can be visually detected from aerial imagery – the historical approach of mapping. We also provided a continuous map of the organic layer, which ranged 6–88 cm organic layer thickness, with an R2 of 0.67 and RMSE (root mean square error) of 19 cm. The continuous map exhibits a smooth transition of organic layers from mineral soil to peat soils and likely provides a more natural representation of the distribution of soils. The continuous map also provides an intuitive uncertainty estimate in the delineation of peat soils, critically useful for sustainable spatial planning, e.g., greenhouse gas or biodiversity inventories and landscape ecological research.

Tree growth potential and its relationship with soil moisture conditions across a heterogeneous boreal forest landscape

“…Similar findings for soil moisture conditions and soil types have been observed in studies of the relationship between normalised mean annual increment in relation to soil properties across Sweden 48 . Previous studies have also proven the utility of soil moisture maps in comparison to other terrain indices 49 , as well as the ability to predicting thick organic soil layers based on soil moisture 50 . Lower site quality is expected in these areas because the saturated soil conditions decrease tree growth 48 , 51 .…”

The ongoing lateral expansion of peatlands in Finland

“…We used stereomicroscope to detect macroscopic plant remains in the peat samples and categorized the peat as either woody/ Carex type or Sphagnum type. In many international, especially geological, classifications the peat depth requirement for a peatland varies but is commonly considered to be ≥30 cm (Ågren et al., 2022). However, as these requirements are seldom fulfilled in the thin peat layers of peatland margins and other “cryptic wetlands”, we used the presence of the peatland vegetation, in particular Sphagnum mosses, as further evidence of our study locations to be classified as a peatland.…”

Challenges and Limitations of Remote Sensing Applications in Northern Peatlands: Present and Future Prospects

“…Accurate estimation of carbon stocks is essential for assessing peatlands' climate change mitigation potential [41,101,102]. Airborne-based remote sensing, combined with LiDAR technology, has been employed to estimate above-ground biomass and carbon stocks in peatland ecosystems.…”