Eija Hyvönen

Soil-Driven Timberline of Spruce (Picea abies) in Tanaelv Belt–Lapland Granulite Transition, Finland

Abstract Climate-driven northern limits of cold-hardy conifers, Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.), reach latitude 70°N in Fennoscandia. Spruce timberline is located at significantly lower latitudes than pine timberline, but factors contributing to this exceptional pattern have remained obscure. We assessed soil-water and soil-nutrient regimes across the spruce timberline in Finnish Lapland through the use of terrestrial electromagnetic (EM) measurements. These included soil dielectric permittivity (ϵ), which is positively correlated to soil-water content (θv); gamma radiation (γ), which is negatively correlated to soil-water content (θv); and electrical conductivity (σa), which is a measure of solute content of a soil. The soil EM data were acquired at 15 sites carrying mature (older than 150 yr) stands dominated by either spruce or pine; the sites fall along a 50-km-long transect that crosses the spruce timberline. The correlation and artificial neural network (ANN) analyses revealed that the soil-moisture and solute content were significantly higher in glacial tills of Norway spruce stands compared to those of stands formed by Scots pine. The stands dominated by spruce were associated with mesic-wet and nutrient-rich tills derived from mafic amphibole and hornblende gneisses of the Tanaelv Belt. Dry and nutrient-poor till derived from felsic garnet gneisses of the Lapland Granulite appeared to constitute an edaphic dispersal barrier for Norway spruce.

Geological controls on conifer distributions and their implications for forest management in Finnish Lapland

Abstract Soil water and nutrient regimes of naturally established old-growth conifer stands and those of intensively managed Norway spruce [Picea abies (L.) Karst.] sites were assessed over a range of lithological provinces in Finnish Lapland. Soil dielectric permittivity (ϵ), as a measure of soil water content (θ v) and soil electrical conductivity (σ a), as a measure of soil solute content, were species specific, such that high soil θ v>0.27 cm3cm−3 (ϵ>15) constitutes an edaphic constraint for Scots pine (Pinus sylvestris L.) and low soil solute content (σ a<0.5 mS m−1) is constraining for Norway spruce. The spatial pattern of the soil θ v was temporally stabile, such that intraseasonal and interseasonal soil θ v was significantly higher in silty tills of spruce stands compared to sandy tills of pine stands. Scots pine was the only conifer on tills derived from felsic rocks of Hetta granite (HG) and Lapland granulite (LG). Norway spruce dominated on tills derived from the mafic rocks of Lapland greenstone belt (LGB), but tills of LG and HG constitute a dispersal barrier for spruce. Mechanical site preparation (MSP) with ploughing (Marttiini) was not able to amend soil θ v to meet site requirements of Scots pine at former spruce sites. MSP resulted in significant reduction in soil nutrient content such that untreated control σ a>tilt/shoulder σ a>trench σ a. The results imply that MSP treatments through which cross-contour tracks are created pose a risk to the sustainability of soil quality in Lapland.

Central boreal mire plant communities along soil nutrient potential and water content gradients

Peatlands have traditionally been exploited in forestry and agriculture over the boreal region, yet they also provide substantial source of fuel production. The large-scale exploitation of peatlands has raised a concern about the diversity of mire plant communities. We studied composition of mire plant communities along soil nutrient potential and water content gradients, to recognize the areas with the high plant diversity. Soil electrical conductivity (ECb) was measured to characterise soil nutrient regimes and soil dielectric permittivity (DP) the soil (volumetric) water regimes. A total of 115 mire sites were studied in the central boreal region of south-western Finnish Lapland. We found that Ward’s hierarchical cluster analysis produced eight stable ECb and DP clusters with discrete vegetation compositions. On the basis of a locally weighted regression analysis (Loess), Carex dioica L., Comarum palustre L., Equisetum fluviatile L., Menyanthes trifoliata L., and Scorpidium scorpioides (Hedw.) Limpr. were found as indicator species for nutrient-rich regimes as designated by high soil ECb. The soil ECb is a diagnostic measure of plant diversity as ECb > 7 mSm−1 resulted in a considerable increase in species richness. Our classification method, based on electrical measurements, provides a simple way to classify mires and focus detailed research to areas with potentially high conservation value.

Arctic Soil Hydraulic Conductivity and Soil Type Recognition Based on Aerial Gamma-Ray Spectroscopy and Topographical Data

A central characteristic of soil in the arctic is its load bearing capacity since that property influences forest harvester mobility, flooding dynamics and infrastructure potential. The hydraulic conductivity has the greatest dynamical influence to bearing capacity and hence is essential to measure or estimate. In addition, the arctic soil type information is needed in many cases, e.g. in roads and railways building planning. In this paper we propose a method for hydraulic conductivity estimation via linear regression on aerial gamma-ray spectroscopy and publicly available topographical data with derived elevation based features. The same data is also utilized for the arctic soil type recognition, both logistics regression and nearest neighbor classification results are reported. The classification results for logistic regression resulted in 44.5% prediction performance and 50.5% for 8-nearest neighbor classifier respectively. Linear regression results for estimating the hydraulic conductivity of the soil resulted in C-index value of 0.63. The hydraulic conductivity and soil type estimation results are promising and the proposed topographic elevation features are apparently new for remote sensing community and should also have a wider general interest.

Predicting Water Permeability of the Soil Based on Open Data

Water permeability is a key concept when estimating load bearing capacity, mobility and infrastructure potential of a terrain. Northern sub-arctic areas have rather similar dominant soil types and thus prediction methods successful at Northern Finland may generalize to other arctic areas. In this paper we have predicted water permeability using publicly available natural resource data with regression analysis. The data categories used for regression were: airborne electro-magnetic and radiation, topographic height, national forest inventory data, and peat bog thickness. Various additional features were derived from original data to enable better predictions. The regression performances indicate that the prediction capability exists up to 120 meters from the closest direct measurement points. The results were measured using leave-one-out cross-validation with a dead zone between the training and testing data sets.