Catchment characteristics control boreal mire nutrient regime and vegetation patterns over ~5000 years of landscape development.

Vegetation holds the key to many properties that make natural mires unique, such as surface microtopography, high biodiversity values, effective carbon sequestration and regulation of water and nutrient fluxes across the landscape. Despite this, landscape controls behind mire vegetation patterns have previously been poorly described at large spatial scales, which limits the understanding of basic drivers underpinning mire ecosystem services. We studied catchment controls on mire nutrient regimes and vegetation patterns using a geographically constrained natural mire chronosequence along the isostatically rising coastline in Northern Sweden. By comparing mires of different ages, we can partition vegetation patterns caused by long-term mire succession (<5000 years) and present-day vegetation responses to catchment eco-hydrological settings. We used the remote sensing based normalized difference vegetation index (NDVI) to describe mire vegetation and combined peat physicochemical measures with catchment properties to identify the most important factors that determine mire NDVI. We found strong evidence that mire NDVI depends on nutrient inputs from the catchment area or underlying mineral soil, especially concerning phosphorus and potassium concentrations. Steep mire and catchment slopes, dry conditions and large catchment areas relative to mire areas were associated with higher NDVI. We also found long-term successional patterns, with lower NDVI in older mires. Importantly, the NDVI should be used to describe mire vegetation patterns in open mires if the focus is on surface vegetation, since the canopy cover in tree-covered mires completely dominated the NDVI signal. With our study approach, we can quantitatively describe the connection between landscape properties and mire nutrient regime. Our results confirm that mire vegetation responds to the upslope catchment area, but importantly, also suggest that mire and catchment aging can override the role of catchment influence. This effect was clear across mires of all ages, but was strongest in younger mires.

Using machine learning to generate high-resolution wet area maps for planning forest management: A study in a boreal forest landscape.

Comparisons between field data and available maps show that 64% of wet areas in the boreal landscape are missing on current maps. Primarily forested wetlands and wet soils near streams and lakes are missing, making them difficult to manage. One solution is to model missing wet areas from high-resolution digital elevation models, using indices such as topographical wetness index and depth to water. However, when working across large areas with gradients in topography, soils and climate, it is not possible to find one method or one threshold that works everywhere. By using soil moisture data from the National Forest Inventory of Sweden as a training dataset, we show that it is possible to combine information from several indices and thresholds, using machine learners, thereby improving the mapping of wet soils (kappa = 0.65). The new maps can be used to better plan roads and generate riparian buffer zones near surface waters.

Identifying and assessing the potential hydrological function of past artificial forest drainage.

Drainage of forested wetlands for increased timber production has profoundly altered the hydrology and water quality of their downstream waterways. Some ditches need network maintenance (DNM), but potential positive effects on tree productivity must be balanced against environmental impacts. Currently, no clear guidelines exist for DNM that strike this balance. Our study helps begin to prioritise DNM by: (1) quantifying ditches by soil type in the 68 km2 Krycklan Catchment Study in northern Sweden and (2) using upslope catchment area algorithms on new high-resolution digital elevation models to determine their likelihood to drain water. Ditches nearly doubled the size of the stream network (178-327 km) and 17% of ditches occurred on well-draining sedimentary soils, presumably making DNM unwarranted. Modelling results suggest that 25-50% of ditches may never support flow. With new laser scanning technology, simple mapping and modelling methods can locate ditches and model their function, facilitating efforts to balance DNM with environmental impacts.