Effect of forest management choices on carbon sequestration and biodiversity at national scale

Forest management methods and harvest intensities influence wood production, carbon sequestration and biodiversity. We devised different management scenarios by means of stakeholder analysis and incorporated them in the forest growth simulator PREBAS. To analyse impacts of harvest intensity, we used constraints on total harvest: business as usual, low harvest, intensive harvest and no harvest. We carried out simulations on a wall-to-wall grid in Finland until 2050. Our objectives were to (1) test how the management scenarios differed in their projections, (2) analyse the potential wood production, carbon sequestration and biodiversity under the different harvest levels, and (3) compare different options of allocating the scenarios and protected areas. Harvest level was key to carbon stocks and fluxes regardless of management actions and moderate changes in proportion of strictly protected forest. In contrast, biodiversity was more dependent on other management variables than harvesting levels, and relatively independent of carbon stocks and fluxes.

Quantification of the effect of environmental changes on the brownification of Lake Kukkia in southern Finland

The browning of surface waters due to the increased terrestrial loading of dissolved organic carbon is observed across the northern hemisphere. Brownification is often explained by changes in large-scale anthropogenic pressures (including acidification, and climate and land-use changes). We quantified the effect of environmental changes on the brownification of an important lake for birds, Kukkia in southern Finland. We studied the past trends of organic carbon loading from catchments based on observations taken since the 1990s. We created hindcasting scenarios for deposition, climate and land-use change in order to simulate their quantitative effect on brownification by using process-based models. Changes in forest cuttings were shown to be the primary reason for the brownification. According to the simulations, a decrease in deposition has resulted in a slightly lower leaching of total organic carbon (TOC). In addition, runoff and TOC leaching from terrestrial areas to the lake was smaller than it would have been without the observed increasing trend in temperature by 2 °C in 25 years.

Input data resolution affects the conservation prioritization outcome of spatially sparse biodiversity features

Detailed spatial data are an essential part of land use planning and decision-making. Their spatial resolution sets limitations to their use, as coarse datasets are not suitable for detecting small-scale phenomena. In this study, we explored the effects of spatial resolution on the ecological outcome of a conservation prioritization process in Zonation software. Our study area was in Evo, southern Finland, covering a mosaic of managed and conserved forests. We produced the feature layers describing the forest characteristics using high-resolution remote sensing datasets, object-based mapping methods, and forest site type data. We found that increasing the resolution above the 16 m baseline resolution resulted in substantial errors. The conservation errors were the highest for rare features related to European Aspen, whereas the common features related to dominant tree species could benefit from the growth of cell size. We conclude that adequate spatial resolution is a prerequisite for efficient conservation prioritization, and that the size and spatial distribution of the features affect the resolution requirements.

Role of land cover in Finland's greenhouse gas emissions

We present regionally aggregated emissions of greenhouse gases (GHG) from five land cover categories in Finland: artificial surfaces, arable land, forest, waterbodies, and wetlands. Carbon (C) sequestration to managed forests and unmanaged wetlands was also assessed. Models FRES and ALas were applied for emissions (CO2, CH4, N2O) from artificial surfaces and agriculture, and PREBAS for forest growth and C balance. Empirical emission coefficients were used to estimate emissions from drained forested peatland (CH4, N2O), cropland (CO2), waterbodies (CH4, CO2), peat production sites and undrained mires (CH4, CO2, N2O). We calculated gross emissions of 147.2 ± 6.8 TgCO2eq yr-1 for 18 administrative units covering mainland Finland, using data representative of the period 2017-2025. Emissions from energy production, industrial processes, road traffic and other sources in artificial surfaces amounted to 45.7 ± 2.0 TgCO2eq yr-1. The loss of C in forest harvesting was the largest emission source in the LULUCF sector, in total 59.8 ± 3.3 TgCO2eq yr-1. Emissions from domestic livestock production, field cultivation and organic soils added up to 12.2 ± 3.5 TgCO2eq yr-1 from arable land. Rivers and lakes (13.4 ± 1.9 TgCO2eq yr-1) as well as undrained mires and peat production sites (14.7 ± 1.8 TgCO2eq yr-1) increased the total GHG fluxes. The C sequestration from the atmosphere was 93.2 ± 13.7 TgCO2eq yr-1. with the main sink in forest on mineral soil (79.9 ± 12.2 TgCO2eq yr-1). All sinks compensated 63% of total emissions and thus the net emissions were 53.9 ± 15.3 TgCO2eq yr-1, or a net GHG flux per capita of 9.8 MgCO2eq yr-1.

Role of data uncertainty when identifying important areas for biodiversity and carbon in boreal forests

Forest conservation plays a central role in meeting national and international biodiversity and climate targets. Biodiversity and carbon values within forests are often estimated with models, introducing uncertainty to decision making on which forest stands to protect. Here, we explore how uncertainties in forest variable estimates affect modelled biodiversity and carbon patterns, and how this in turn introduces variability in the selection of new protected areas. We find that both biodiversity and carbon patterns were sensitive to alterations in forest attributes. Uncertainty in features that were rare and/or had dissimilar distributions with other features introduced most variation to conservation plans. The most critical data uncertainty also depended on what fraction of the landscape was being protected. Forests of highest conservation value were more robust to data uncertainties than forests of lesser conservation value. Identifying critical sources of model uncertainty helps to effectively reduce errors in conservation decisions.

Utilizing historical maps in identification of long-term land use and land cover changes

Knowledge in the magnitude and historical trends in land use and land cover (LULC) is needed to understand the changing status of the key elements of the landscape and to better target management efforts. However, this information is not easily available before the start of satellite campaign missions. Scanned historical maps are a valuable but underused source of LULC information. As a case study, we used U-Net to automatically extract fields, mires, roads, watercourses, and water bodies from scanned historical maps, dated 1965, 1984 and 1985 for our 900 km[Formula: see text] study area in Southern Finland. We then used these data, along with the topographic databases from 2005 and 2022, to quantify the LULC changes for the past 57 years. For example, the total area of fields decreased by around 27 km[Formula: see text], and the total length of watercourses increased by around 2250 km in our study area.