Southern Finland Research Articles

Abstract. The identification and delineation of geographic objects, a fundamental yet subjective aspect of topographic mapping, forms the basis for creating abstract models of our surrounding physical environment and has captivated researchers due to its complexity and conceptual challenges. Although topographic maps and databases of the National Mapping and Cadastral Agencies (NMCAs) often represent objects with sharp boundaries, this is usually the result of practical reasons and user needs for modelling the data, rather than our know knowledge of inherent vagueness of many geographic objects and the associated cognitive processes involved in their recognition. The main objective of this article is to increase our understanding of the role of vague geographic objects as part of the topographic data production of NMCAs and to develop a generic TDB Change Detection tool to help the analysis of changed features in topographic databases (TDBs). The experimental part of this work is focused on the TDB versions produced by the National Land Survey of Finland (NLS) in 2021–2024 and it provides answers to (a) what kind and how many changes are made to the vague features in the NLS TDB within the observation period, and (b) how are the changes distributed by feature class and region. The selected vague feature classes were outcrops of bedrock, cliffs, young and other bogs, lakes and ponds, and contours. Buildings were used as a reference when analysing the total number of changes over the whole of Finland. The results show that the number of changes made for analysed feature classes was much higher than expected. The largest number of changes occurred in bogs, outcrops and contours. In general, the largest amount of modified features appeared to be concentrated in southern Finland and in the northernmost parts of Finland. The spatial variation in changes is explained both by the spatial variation in topography and by the individual characteristics of different topographers operating in different parts of Finland. Based on the results, the work made it possible to make a number of recommendations to 1) improve the understanding of the nature and significance of topographic interpreted data within NMCAs, 2) clarify NMCAs own position on the quality requirements for the geometry and timeliness of vague topographic features, 3) develop precise guidelines and guidance for the data collection process, 4) to develop tools to monitor the topographic data collection work done, and 5) for NMCAs to regularly archive frozen versions of their TDBs to enable efficient monitoring of data production process afterwards.

Large independently evolved supergenes control colony social organization and queen reproductive strategies in several ant lineages. Their independent origins, as well as the similarities of the associated phenotypes, make ant supergenes a promising system for studying the parallel evolution of genome organization and adaptability. However, the genetic basis of differences in social organization and queen phenotypes remains unknown in many ant species, limiting the potential power of this system for comparative studies. We investigated the genetic basis of colony social organization in the queen-size dimorphic ant Myrmica ruginodis by sampling 95 queens from 31 colonies in southern Finland. Whole-genome sequencing revealed a novel 9 Mb supergene associated with both queen size and social organization. Queens homozygous for the AA haplotype were larger and found only in single-queen colonies, while queens in multiple-queen colonies were smaller and carried only AB and BB genotypes. This supergene is not homologous to previously identified supergenes in ants, suggesting it arose through a distinct evolutionary pathway.

Enhancing Residential Load Forecasting Accuracy through Dynamic Feature Selection and Ensemble Machine Learning Models: A Real-World Scenario in Southern Finland

IntroductionClimatic conditions have been associated with cardiovascular health, but most studies focus on short term exposure and individual weather parameters. The aim of the present work is to explore the use of longitudinal multidimensional clustering in studying the relationship between climate exposure over the life-course and adult blood pressure (BP).MethodsAn array of 7 climate parameters (annual averages) was linked to health data from the Northern Finland Birth Cohort 1966, using geolocations from their residential history. Only participants living in Finland during the entire study period (1970-2011) were included (n = 4191). Individual climate trajectories were clustered using the kml3d algorithm across youth (4-24y) and adult (25-46y) life stages. Generalized linear models were used to assess the relationship between climate clusters and clinically measured systolic BP (SBP) and diastolic BP (DBP) at 46 years. All models were adjusted for known predictors of environmental exposure and BP.ResultsTwo youth climate clusters (A and B) were identified, while three clusters (A, B and C) emerged in adulthood. Compared to reference cluster A, B describes a colder northern climate, while C represents a transition to a warmer southern climate. Preliminary results show that adult exposure to this warmer southern climate (C) is associated with lower SBP (-4.63 mmHg, 95%CI -6.01,-3.25) and DBP (-1.98mmHg, 95%CI -2.93,-1.03). Likewise, growing up in a colder climate (B) was suggested to be associated with lower SBP (-1.21mmHg, 95%CI -2.28,-0.15) but not DBP (-0.37 95%CI -2.25,-0.15).ConclusionsYouth and adult climate exposure were independently associated with adult BP. Studies including individuals raised in southern Finland are needed to assess whether changes in climate exposure play a role. Our results show that kml3d clustering can identify distinct climate clusters at country level, facilitating observational studies on climate exposure.Key messages• We analyzed climate exposure clusters with blood pressure in a Finnish birth cohort. Results suggest that youth and adulthood exposure are associated with adult blood pressure independently.• The kml3d algorithm identified distinct climate exposure clusters at the national level in 7 climate variables over 42 years, enabling future studies on long-term climate exposure.

ABSTRACT This study evaluates the potential of low-altitude airborne laser scanning (ALS) and terrestrial laser scanning (TLS) for characterizing structural complexity in Southern Finland. Unlike species diversity, structural complexity reflects realized niche occupancy by describing how vegetation utilizes light, water, and space, providing key insights into ecosystem functioning. We analyzed 99 circular sample plots (r = 20 m) scanned with helicopter-borne ALS at 80 m altitude and TLS data from nine scan locations per plot. Structural complexity metrics were derived at both grid level (variability in canopy height models and voxel occupancy) and object level (variability in individual tree attributes). High-density ALS effectively captured vertical and horizontal complexity through object-level analysis, showing close agreement with TLS. However, differences in measurement geometry affected volumetric complexity, with ALS and TLS characterizing tree architecture and vegetation occupancy differently. Object-level approaches captured a broader range of horizontal and vertical complexity, while grid-level approaches better captured volumetric variability, facilitating the identification of forest stand properties and biodiversity hotspots. The strongest agreement between ALS and TLS occurred for variation in tree height (R² = 0.66, Spearman = 0.80), while lowest agreement was found for fractal dimensions of tree architecture (R² = 0.04, Spearman = 0.25).

ABSTRACT This study investigates the accumulation of social risks among psychiatric patients based on register-based data in Southern Finland. We apply a mixed methods approach to study the differences between different demographic patient groups. First, we transformed patient case record data quantitatively using inductive category analysis. Then, we used cross-tabulation to explore the connections between social risks and patients’ demographic variables. Finally, we created nine imaginary story models, based on category analysis and cross-tabulation results. We identified social risks across nine categories: capacity to work, social relations, addictions, subsistence, violence and crime, ability to function, intergenerational transmission, housing, and renouncement and death of a loved one. Results highlight that social risks are prevalent throughout the patient case record data, regardless of patients’ backgrounds. Although there are some variations in the prevalence of demographic variables and social risks, they are relatively small. However, diagnoses of substance abuse disorders and psychosis were connected to several social risk categories. Therefore, social risks accumulate among the most vulnerable population, thus forming complex and intertwining networks.

General practitioner hospitalists in psychiatry – may we help you?

ABSTRACT Urban catchments face high flood risks caused by heavy rainfall, largely because of altered hydrology and high imperviousness. Estimating the runoff response to such rainfall events is crucial for effective stormwater management. This study utilizes modified python version of the Short Term Ensemble Prediction System (pySTEPS) to generate stochastic design storms, mimicking spatiotemporal properties of an observed thunderstorm over an urban catchment in southern Finland. The model is parametrized using weather radar data with altered rain field advections. Simulated rainfall ensembles are fed into a storm water management model (SWMM) to assess the hydrological response across advection scenarios. Results show notable differences in rainfall accumulations depending on orientation of rainfall structures and varying advection magnitude. Changes in advection properties translate to increased peak stormwater flows and urban flooding risk for slowly moving rain structures and for rain structures with an elongated shape along the direction they are advancing. The presented approach gives insight to the effects of spatial variability of heavy rainfall on runoff generation across advection scenarios.

Cardiac manifestations are associated with Lewy body disease, but studies addressing the underlying histopathological mechanisms at the myocardial level are sparse. Here, we generated an artificial intelligence-based algorithm to quantify tyrosine hydroxylase (TH)-immunoreactive sympathetic distal axons at the myocardial level. This novel tool was applied to septal samples of the Vantaa 85 + study (n = 138), which is a population-based autopsy study representing all subjects aged 85years or older living in the city of Vantaa (southern Finland) in 1991. In addition, the tool was applied to left ventricle samples of the Helsinki Biobank (n = 87) and the forensic Tampere Sudden Death Study (TSDS, n = 127). The level of myocardial TH reactivity was compared between subjects with and without Lewy pathology in the central nervous system in all datasets. In the Vantaa 85 + study, TH reactivity was also compared between subjects with caudo-rostral and amygdala-based subtypes, and potential confounding factors (age at death, sex, myocardial infarction, senile systemic amyloidosis, and diabetes medication) were controlled for using multiple linear regression models. Presence of Lewy pathology was strongly associated with loss of TH reactivity at the myocardial level in all three autopsy cohorts (Vantaa 85 + p = 0.001, Helsinki Biobank p < 0.001, TSDS p < 0.001)). In the Vantaa 85 + study, the caudo-rostral subtype (p < 0.001), but not the amygdala-based subtype (p = 0.60), was associated with myocardial denervation/dysfunction, and this association was independent of other known causes of sympathetic denervation/dysfunction. Caudo-rostral subtype and myocardial infarction were the strongest predictors of myocardial sympathetic denervation/dysfunction in the oldest-old population (Vantaa 85 +). In conclusion, our results show that Lewy pathology in the central nervous system, and particularly its caudo-rostral subtype, is strongly associated with loss of sympathetic distal axons at the myocardial level. We also provide evidence that the caudo-rostral subtype is one of the strongest predictors of myocardial sympathetic denervation/dysfunction in the oldest-old population.

Abstract Understanding the spatial distribution of individuals is essential for effective species conservation. We investigated the spatio-temporal distribution of Aquila chrysaetos (Golden Eagle) in Finland using nest surveys, citizen science observations, and environmental data from 1982–2021. We extended a popular N-mixture model to estimate population abundance while accounting for the number of recently hatched nestlings, the spatial distribution, and correcting for biases in the observation process, all integrated into a two-stage Bayesian hierarchical model. Results of our model aligned with the previously known north-oriented distribution of A. chrysaetos in Finland, supporting its applicability to A. chrysaetos and other species with similar ecological requirements and life-history traits. Furthermore, we observed the highest densities of successful nests near open landscapes, such as marshes and peat bogs, whereas dense forests, port areas, and areas of high human population density had a strong negative effect. While the temporal trend of nest abundance has remained constant over the years, the overall population abundance showed an increasing trend until 2007, after which it stabilized. Finally, we detected a larger number of A. chrysaetos movements in southern and southwestern Finland than elsewhere in Finland, opening up new possible areas for conservation targets.

Due to the lack of complete taxonomic inventories and revisions for nearly 120 years and a high number of chaotic and conflicting species descriptions in the times of the primary biodiversity exploration, the actual diversity of apomictic species of Hieracium in Finland is currently unknown. The existing nomenclatural and bibliographic inventory, published in 2002, does not include taxonomic evaluations. To compensate for this deficiency, there is an urgent need for a new taxonomic revision. The operative foundation for this revision is an inventory of the taxonomic diversity and distribution patterns on the basis of primary sources, i.e. herbarium collections identified by major taxonomic authorities. A complete checklist of Hieracium species occurring in Finland, which were accepted in major authoritative sources (recently or in the past) and identified in herbarium collections, includes 137 accepted species, which are deemed mostly apomictic. These taxa are considered taxonomically evaluated and are recommended for current use in national checklists and manuals. Brief species descriptions are provided as the basis for a new identification key. Species distributions in Finland are recorded on the basis of herbarium specimens according to the traditional biogeographic provinces of Eastern Fennoscandia. The distribution patterns revealed in the hierarchical cluster analysis highlight a largely isolated position of the Åland Islands, with strong phytogeographical connections to Sweden; the presence of taxa with strictly oceanic distributions in south-western Finland; and a high level of taxonomic dissimilarity between the north (Lapland and neighbouring territories) and the east (southern and central mainland Finland and neighbouring territories) of Finland. The eastern floristic element is considered autochthonously developed in Finland during the postglacial colonisation of Northern Europe by Hieracium plants and contains numerous endemics or near-endemics of the country. Two species are established aliens, which were introduced as park ornamentals over 100 years ago. A new synonymy is established: Hieraciumschmidtiisubsp.residuum is reduced to a synonym of H.crinellum; its only record in Finland is a local relic of the postglacial period, remotely isolated from the main populations in Norway and southern Sweden. Numerous further province-level and country-level records are expected in Finland in the course of a new taxonomic revision, with a total to reach or exceed 200 species.

Wetlands are the largest natural source of atmospheric methane (CH4), but substantial uncertainties remain in the global CH4 budget, partly due to a mismatch in spatial scale between detailed insitu flux measurements and coarse-resolution land surface models. In this study, we evaluated the importance of capturing small-scale spatial heterogeneity within a patterned bog to better explain seasonal variation in ecosystem-scale CH4 emissions. We conducted chamber-based flux measurements and pore water sampling on vegetation removal plots across different microtopographic features (microforms) of Siikaneva bog, southern Finland, during seasonal field campaigns in 2022. Seasonal and spatial patterns in CH4 fluxes were analyzed in relation to key environmental and ecological drivers. High-resolution (6 cm ground sampling distance) drone-based land cover mapping enabled the extrapolation of microscale (< 0.1 m2) fluxes to the ecosystem scale (0.75 km2). Methane emissions from wetter microforms (mud bottoms and hollows) closely followed seasonal changes in peat temperature and green leaf area of aerenchymatous plants, while emissions from drier microforms (high lawns and hummocks) remained seasonally stable. This constancy was attributed to persistently low water tables, which moderated environmental fluctuations and reduced seasonality of CH4 production, CH4 oxidation and plant-mediated transport. The strong spatial pattern in CH4 emissions and their seasonal dynamics made both the magnitude and seasonal cycle of ecosystem-scale emissions highly sensitive to the areal distribution of microforms. Our findings underscore the need to integrate microscale spatial variability into CH4 modelling frameworks, as future shifts in peatland hydrology due to climate change may alter the balance between wet and dry microforms-and with it, the seasonal and annual CH4 budget.

Girls on the Move: Late Medieval Social Networks, Economic Conditions and Peasant Geographic Mobility between Southern Finland and Reval (Tallinn), c. 1350–1560

The Svecofennian orogeny in southern Finland has traditionally been divided into two broadly defined compressional stages, the 1.89–1.87 Ga “synorogenic” stage and the ca 1.84–1.81 Ga “lateorogenic” stage. The term “intraorogenic” is used to describe a less studied stage that occurred between these two, with some overlap with both. Mafic and intermediate intrusions collectively named as the Kaiplot gabbros are situated on a number of islands and islets in Nagu (Nauvo) in the southwestern archipelago of Finland. The outcrops occur as dykes as well as plutonic bodies and have been emplaced in at least two separate pulses. Net-veining and other structures suggesting incomplete mixing between mafic and felsic magmas are found. The main plutonic body is a hornblende gabbronorite. U-Pb dating (TIMS, zircon) gives it an age of 1865 ± 2 Ma. Geochemically, the most primitive Kaiplot gabbros are tholeiitic and show affinity to back-arc basin basalts, indicating generation in an extensional tectonic environment. Their parental magmas appear to have originated from relatively high-degree partial melting of a shallow spinel-bearing and slightly subduction-modified depleted mantle. During transport and emplacement, both differentiation and assimilation of crustal material have taken place. The Kaiplot gabbros endorse an extensional tectonic episode of the Svecofennian orogeny at around 1865 Ma, possibly as a result of tectonic switching propagating southwestwards.

IntroductionDiet contributes substantially to one’s carbon footprint. Climate impact of diet varies between certain sociodemographic groups, but no studies have comprehensively compared the climate impact of diet between sociodemographic groups and regions in Finland. Aims of this study were to compare absolute and energy-adjusted dietary climate impacts between sociodemographic groups and to illustrate their regional distributions on maps.MethodsThe FinHealth 2017 Study data (n = 5,123) comprising individuals aged 18–99 years, and additionally for the spatial analyses, FINRISK 2012 and Health 2011 survey data were utilized (combined n = 14,692). Dietary intake information was collected using validated food frequency questionnaires. Products’ climate impacts, produced with the life cycle assessment, were linked to the ingredient groups used in food consumption data, and individual-level climate impacts/day [kg CO2 equivalents (eq)/day and kg CO2 eq/megajoule/day] were estimated. Statistical analyses for maps were based on 10×10 km square data and on spatial Besag-York-Mollie model. Linear regression model was used to study differences between sociodemographic groups.Results and discussionMen had higher absolute and energy-adjusted dietary climate impacts than women did. In women and in men, the climate impacts were the highest in the 35–54-year-olds, and those living with underage children, and the lowest in the 75–99-year-olds and those living alone. Women living in remote rural areas, and men in the highest income quintile had high dietary climate impacts. On maps, the climate impacts were low in southern Finland near the capital region. Higher levels appeared in men especially in parts of central Finland. Results of absolute and energy-adjusted climate impacts showed mainly similar patterns. Information on the differences between sociodemographic groups can be used when targeting policies concerning transition towards more climate-friendly diets to sociodemographic groups with high dietary climate impacts.

Abstract Iron (Fe) concentrations are increasing in lakes on a wide geographical scale, contributing to recent browning of lake waters. As available time series on lake-water Fe concentrations are relatively short, covering the past few decades only, varved lake sediments may provide extended and precisely dated records to study temporal Fe dynamics in lakes in response to environmental drivers, such as changes in catchment land use and atmospheric sulphur deposition. Here, we present and discuss temporal changes in Fe speciation and accumulation rates during the last three centuries as revealed by sub-annually resolved X-ray absorption spectroscopy analyses of varved sediments from three lakes in southern Finland. Iron speciation in sediments is dominated by Fe-bearing silicate fractions in two of the lakes, while the third lake has contributions of organically complexed Fe and Fe-(oxy)hydroxides. Long-term changes in sediment Fe accumulation correspond with documented shifts in land use from agriculture to spruce forestry in the lake catchments, and in one of the lakes with water-level lowering. An overall poor correspondence between monitored aqueous Fe concentrations and sediment-inferred Fe accumulation rates is likely linked to the dominance in the sediments of particulate Fe phases that are not prevalent in suspended form in the water column. This suggests that sediment records are unsuitable for reconstructions of past lake-water Fe concentrations in these lakes. However, the study provides valuable insight into how major land-use changes in the past have affected both the supply and speciation of Fe accumulated in lake sediments.

Abstract. In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate and trigger road maintenance operations. Urban climate and road weather models have specialized in simulating these conditions in cities or in the countryside, respectively. In this study, we intend to bridge the gap between road weather models and urban climate models in terms of cold region urban modelling and artificial surface condition predictions in any environment. We have refined the modelling of road surface processes related to winter conditions in the Town Energy Balance (TEB), an urban climate model designed for complex environments. We have developed an ice content prediction to account for the freezing and melting of the water content on the surface. Additionally, we have enhanced the TEB representation of snow on road, moving from a single-layer snow model (1-L), to a more precise multi-layer snow model known as Explicit Snow (ES). We have isolated the winter surface processes from other physical interactions by limiting the evaluation of the experiments to open environments. The experiments are carried out at two locations: the Col de Porte in the Alps and a road weather station in southern Finland. Our findings show that the enhanced TEB model (named TEB-ES) outperforms TEB, as well as a benchmark model, ISBA-Route/CROCUS, but with mixed results against a multiple linear regression in-sample algorithm. For roads with high traffic and/or winter maintenance operations, future modelling work should focus on the representation of anthropic effects.

Abstract Complex Land Surface Models (LSMs) rely on a plethora of parameters. These parameters and the associated process formulations are often poorly constrained, which hampers reliable predictions of ecosystem dynamics and climate feedbacks. Robust and uncertainty‐aware parameter estimation with observations is complicated by, for example, the high dimensionality of the model parameter space and the computational cost of LSM simulations. Herein, we adapt a novel Bayesian data assimilation (DA) and machine learning framework termed “calibrate, emulate, sample” (CES) to infer parameters in a widely‐used LSM coupled with a demographic vegetation model (CLM‐FATES). First, an iterative ensemble Kalman smoother provides an initial estimate of the posterior distribution (“calibrate”). Subsequently, a machine‐learning‐based emulator is trained on the resulting model‐observation mismatches to predict outcomes for unseen parameter combinations (“emulate”). Finally, this emulator replaces CLM‐FATES simulations in an adaptive Markov Chain Monte Carlo approach enabling computationally feasible posterior sampling with enhanced uncertainty quantification (“sample”). We test our implementation with synthetic and real observations representing a boreal forest site in southern Finland. We estimate a total of six plant‐functional‐type‐specific photosynthetic parameters by assimilating evapotranspiration (ET) and gross primary production (GPP) flux data. CES provided the best estimates of the synthetic truth parameters when compared to data‐blind emulator sampling designs while all approaches reduced model‐observation errors compared to a default parameter simulation (GPP: % to %, ET: % to %). Although errors were also consistently reduced with real data, comparing the emulator designs was less conclusive, which we mainly attribute to equifinality, structural uncertainty within CLM‐FATES, and/or unknown errors in the data that are not accounted for.

Abstract This study presents a novel method to assess the freeze-thaw exposure of concrete structures. The new Relative Freeze-Thaw Exposure index (RFE) is based on regression model that considers location-related actual freeze-thaw damage observations, number of freeze-thaw cycles and both annual and cycle-related amount of wind-driven rain (WDR) before cycles. The RFE index is then used to compare location-, direction- and climate-related freeze-thaw exposure levels. It can be concluded that the amount of WDR before each cycle has the most significant effect on freeze-thaw damage. Freeze-thaw exposure level is highest in present climate and remains the highest in Finland’s coastal area regardless of the used climate change scenario. In Finland’s coastal area and southern Finland, the exposure level increases more from eastern and western directions than southern which indicates that the exposure level is getting more evenly distributed. However, the southern direction remains with the most severe exposure in almost every studied case in every location. Freeze-thaw exposure for outdoor concrete structures is not getting less severe with the changing climate in Finland. The quality of concrete (e.g. success of air-entrainment) and protecting concrete from free water remain the main methods against the initiation of freeze-thaw damage.

Introduction Cosmic-ray neutron sensors (CRNSs) have been used worldwide to assess soil moisture changes continuously and non-destructively at scales of less than kilometers. The method is based on inverse correlation between cosmic-ray neutron intensity and soil moisture, as low-energy neutron intensity above the soil depends greatly on the hydrogen content of the soil (Zreda 2008). On the field scale, the effective range of the sensor is from 130 to 240 m and penetration depth from 15 to 83 cm depending on soil moistness, decreasing exponentially with distance from the sensor (Köhli 2015). CRNSs have been used in diverse environments, such as grasslands, agricultural fields and forest ecosystems, various climatic zones and more than ten years in Europe (Bogena 2022). Here we attempt to calibrate the CRNS soil moisture estimation process for three boreal coniferous forests stands in southern and northern Finland and compare the results with data from point measurements of soil moisture sensors. Since most of the CRNS research has been conducted further south in Europe, these will be novel results from CRNS measurements of boreal forests in northern Europe, partly even further north than the Arctic Circle. Materials and methods Three CRNSs (StyX Neutronica Black Puppet SP; Fig. 1) were installed in 2022 at two University of Helsinki field sites, two at the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II (61.51°N, 24.17°E, 181 a.s.l) near Hyytiälä forest station in southern Finland and one at SMEAR I (67°46’N, 29°35’E, 390 a.s.l) on Kotovaara hill, near Värriö subarctic research station in eastern Finnish Lapland. SMEAR II in southern Finland has two sensors, one located to call “hill” and other called “hollow” sites. The forest around CRNS “hill” is a 63-years-old Scots pine (Pinus sylvestris L.) stand with undergrowth of Norway spruce (Picea abies (L.) Karst.), and around “hollow” is dominated by 60–100-years-old Norway spruces (Kolari 2022). The soil above the bedrock around “hill” sensor is haplic podsol on glacial till (FAO 1988), and the soil depth is approximately 0.5–1.0 m. “Hollow” site has a small a stream flowing in wet seasons near the sensor. Forest around SMEAR I in northern Finland is naturally generated Scots pine stand, which has estimated to be on average approximately 70–80 years old (Matkala 2021). Soil type is haplic podsol on sandy till (FAO 1988), and the soil depth is approximately 0.5 m. Moisture calibration was conducted by taking volumetric soil samples from different directions, distances and various depths from the sensors, based on Schrön (2017). Moisture content of the samples was determined gravimetrically. Soil samples from SMEAR II “hill” were collected from six different directions at 7, 40 and 100 meters from the sensor in August 2022. Soil samples from SMEAR II “hollow” were collected from four different directions at 4, 24 and 70 meters from the sensor in August 2023. Humus layer was sampled, and soil samples were sampled from 5 or 6 different depths up to 30 cm. Soil samples from SMEAR I were collected from six different directions at 3.5, 49 and 114 meters from the sensor in June 2023. Humus layer height was measured, and soil samples were collected from 6 different depths up to 30 cm. Additionally, soil organic matter (SOM) and carbon (SOC) were determined for soil samples. Calculations were conducted with an open-source Python tool “crspy” (Power 2021). Results Preliminary results from the assessment of soil moisture using CRNS from the first measurement years 2022–2024 are shown in the eLTER conference. We aim to evaluate the performance of CRNS in our measurement areas by comparing the results with environmental variables, such as, soil moisture measured continuously with soil sensors at different depths and different locations near the CRNSs, precipitation and snow depth in the area. The purpose is to detect whether the results of CRNS and point measurements are in line or if there are divergent patterns during the year(s) or discrepancies in some conditions that might affect the validity of either measurement method.