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"en": "The purpose of the Biosoil soil inventory (ICP Forests - level I - test plots) was to assess the chemical state of the soil and its changes, and secondly to assess the soil properties that affect the functioning of the forest land. In addition to the fact that the Biosoil data provides soil information for the study of the effects of atmospheric deposition on a larger scale, the soil inventory serves other purposes as it provides data for both research diciplines, climate change mitigation (e.g. the amount of carbon and its changes) and sustainable forest management (e.g., in addition to acidification, also, for example, studies on nutrient cycles and imbalances). \n\nSoil profile data was collected as part of the BioSoil project, Natural Resources Institute Finland, Luke (former Finnish Forest Research Institute, METLA). The BioSoil project was implemented as part of ICP Forests (International Cooperative Program on the Assessment and Monitoring of Air Pollution Effects on Forests; icp-forests.net/) and the EU Forest Focus program (Tamminen and Ilvesniemi 2013). The aim of the project was to collect information on soil properties, composition and changes in carbon, nutrients, acidity and heavy metals in Finnish forest lands. The material was collected in the so-called From the network of ICP Forests Forest Focus Level I experimental area in 2006-2007, which were first sampled for soil samples in 1986-1995 (Tamminen and Starr 1994, Tamminen 2009). This network is part of the so-called 3,000 permanent sample plot data. In Finland, the BioSoil database contains 631 experimental plots, while the total number of the plots in Europe is around 6000 (icp-forests.net/) A detailed description of all the collected data and variables is given in BioSoil Kuvio- ja puusto-ohjeet (2006). \n\nIn the laboratory, the particle size categories (clay, silt and sand) of the soil profile samples were determined. Approximate content of soil organic matter for the mineral soils was determined for different layers based on loss on ignition at a temperature of 550 °C for about two hours. In addition, the concentrations of several elements were determined from the samples. \n\nThe basic data of the experimental area include: latitude, longitude, altitude from sea level, soil moisture, slope, topographical location, bare rock cover (%), soil type, parent material, coarse particle content (%), soil texture, site type and Sphagnum cover (%). \n\nInformation was collected from the mineral soils by the EU funded Biosoil project during 2006-2007 (Tamminen, 2006; Tamminen ja Ilvesniemi, 2013). \n\nData have been used in several research projects (Heiskanen ym. 2018, Heiskanen ym. 2020, Launiainen ym. 2022, Lehtonen ym. 2016, Mäkelä ym. 2022, Rantakari ym. 2012). \n\n## 3,000 permanent sample plots established 1985-86 \n\nIn connection with the 8th national forest inventory in 1985-1986, approximately 3,000 permanent experimental plots were established for the purpose of monitoring the nature of the forest and the state of the environment. The plots were located in a network of forest inventory covering the entire country. The distances between the clusters of plots in southern Finland are 16 km both in the south-north direction and in the east-west direction. In northern Finland, the distances are 24 km in the south-north direction and 32 km in the east-west direction. Each cluster has a group of plots in the direction from south to north including 4 plots every 400 meters in Southern Finland and 3 plots every 600 meters in Northern Finland.\n\nFor the BioSoil project, one plot was selected and measured from each cluster. The data collection of the forest inventories and the assessment of surface areas are based on the division of each plot on the forestry land into management units. Management units have been formed based on the properties of the tree stand. A management unit is a homogeneous area in terms of soil type and trees, as well as the forest management measures that have been carried out in the area. 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The abundance of each plant species was evaluated as projected coverage, i.e. the percentage covered by aerial shoots and mixed stems on the sample plot. Coverages were estimated with an accuracy of 1%, coverage below 1% with an accuracy of 0.1%. The biologists of the inventory groups received uniform training for the field work. A large number of tree stand and growth location codes have been inventoried from the plots. Soil samples have also been taken from the inventory plots.",
"fi": "Biosoil maaperäinventaarion (ICP forests - taso I - koealat) tarkoituksena oli arvioida maaperän kemiallista tilaa ja sen muutoksia ja toiseksi arvioida maaperän ominaisuuksia, jotka vaikuttavat metsämaan toimintaan ja käyttöön. Sen lisäksi, että Biosoil aineisto tarjoaa maaperätietoa ilmakehän laskeumavaikutusten tutkimukseen laajemmassa mittakaavassa, maaperäinventaario palvelee muitakin tarkoituksia, sillä se tuo aineistoa sekä ilmastonmuutoksen (esim. hiilen määrä ja sen muutokset), että kestävään metsänhoidon (esim. happamoitumisen lisäksi mm. typpitutkimukset ja ravinteiden epätasapaino, maan viljavuus, maan kantavuus) tutkimukseen.\n\nMaaperäprofiilitiedot kerättiin osana BioSoil-projektia, Luonnonvarakeskus, Luke (entinen Metsäntutkimuslaitos, METLA). BioSoil-projekti toteutettiin osana ICP Forests -ohjelmaa (International Cooperative Program on the Assessment and Monitoring of Air Pollution Effects on Forests; icp-forests.net/) ja EU Forest Focus -ohjelmaa (Tamminen ja Ilvesniemi 2013). Hankkeen tavoitteena oli kerätä tietoa maaperän ominaisuuksista, koostumuksesta sekä hiilen, ravinteiden, happamuuden ja raskasmetallien muutoksista Suomen metsämaissa. Aineisto kerättiin ns. ICP Forests Forest Focus Level I koealan verkostosta vuosina 2006–2007, joista otettiin ensimmäisen kerran maaperänäytteet vuosina 1986–1995 (Tamminen ja Starr 1994, Tamminen 2009). Tämä koealaverkosto on osa ns. 3000 pysyvän koealan aineistoa. Suomessa BioSoil-tietokanta sisältää 631 koealaa, kun taas koko Euroopassa koealojen kokonaismäärä on noin 6000 (icp-forests.net/) Yksityiskohtainen kuvaus kaikista kerätyistä tiedoista ja muuttujista on annettu BioSoil Kuvio- ja puusto-ohjeet (2006).\n\nLaboratoriossa maaperän profiilinäytteistä määritettiin näytteiden hiukkaskokoluokat (savi, siltti ja hiekka). Maaperän orgaanisen aineksen likimääräinen pitoisuus kivennäismaakerrokselle määritettiin eri kerroksille perustuen polttohäviöön 550 °C lämpötilassa noin kahden tunnin ajan. Lisäksi näytteistä määritettiin useiden alkuaineiden pitoisuudet. \n\nKoealan perustiedot sisältävät: leveysaste, pituusaste, korkeus merenpinnan yläpuolella maaperän kosteus, kaltevuus, topografinen sijainti, paljas kivipeite (%), maaperätyyppi, lähtöaine, karkean aineksen pitoisuus (%), maaperän rakenne, kasvupaikan tyyppi ja Sphagnum-peittävyys (%). \n\nKangasmaiden maaperästä ja -kohteista kerättiin tietoja EU:n rahoittaman Biosoil-projektin puitteissa kaudella 2006–2007 (Tamminen, 2006; Tamminen ja Ilvesniemi, 2013). \n\nAineistoa on käytetty useissa tutkimuksissa (Heiskanen ym. 2018, Heiskanen ym. 2020, Launiainen ym. 2022, Lehtonen ym. 2016, Mäkelä ym. 2022, Rantakari ym. 2012). \n\n## Vuonna 1985–86 perustetut noin 3000 pysyvää koealaa \n\nValtakunnan metsien 8. inventoinnin yhteydessä vuosina 1985–1986 perustettiin metsäluonnon ja ympäristön tilan seurantaa varten noin 3000 pysyvää koealaa. Koealat on sijoitettu koko maan kattavaan inventointilohkojen verkostoon. Lohkojen etäisyydet toisistaan ovat Etelä-Suomessa sekä etelä-pohjoissuunnassa että itä-länsisuunnassa 16 km. Pohjois-Suomessa etäisyydet ovat etelä-pohjoissuunnassa 24 km ja itä-länsisuunnassa 32 km. Kullakin lohkolla on etelä-pohjoissuuntainen koealaryväs, joka käsittää Etelä-Suomessa 4 koealaa 400 metrin välein ja Pohjois-Suomessa 3 koealaa 600 metrin välein. \n\nBioSoil-hanketta varten kultakin lohkolta valittiin ja mitattiin 1 koeala. Valtakunnan metsien inventointien tiedonkeruu ja pinta-alojen arviointi perustuu kunkin metsätalouden maalle sijoittuvan koealan jakamiseen metsikkökuvioihin. Kuviointi muodostetaan kasvupaikan ja puuston ominaisuuksien perusteella. Metsikkökuvio on kasvupaikkatekijöiden ja puuston sekä metsässä tehtyjen ja tarvittavien hakkuu- ja hoitotoimien suhteen homogeeninen metsäalue. Inventoinnissa käytetty 4 aarin suuruinen pysyvä ympyräkoeala voi jakaantua useampaan metsikkökuvioon. Esimerkiksi jos osa koealasta kuuluu eri maaluokkaan, kasvupaikkatyyppiin tai koeala sattuu suon ja kankaan rajaan tai puuston kehitysluokkarajaan, se jaetaan metsikkökuvioiden mukaan kuvioihin. \n\nBiologit tarkensivat tarvittaessa inventoinnin ryhmänjohtajien arvioimaa em. koealakuviointia erottamalla tyyppikuviot koealasta tehtyyn peitepiirrokseen. Tyyppikuviot rajattiin kasvupaikkatyypin perusteella. Pienimmän erotettavan tyyppikuvion tuli olla vähintään 5 % 4 aarin täyskoealan pinta-alasta. Inventoinnissa kenttä- ja pohjakerroslajien peittävyydet arvioitiin neljältä 4 aarin koealalle systemaattisesti sijoitetulta 2 m2 suuruiselta näyteruudulta. Kunkin kasvilajin runsautta arvioitiin projektiopeittävyytenä, eli ilmaversojen ja sekovarsien kattamana prosenttipeittävyytenä näyteruudulla. Peittävyydet arvioitiin prosentin tarkkuudella, alle 1 % peittävyydet 0,1 % tarkkuudella. Inventointiryhmien biologit saivat pysyvillä koealoilla suoritettaviin maastotöihin yhtenäisen koulutuksen. Koealoilta on inventoitu runsaasti puusto- ja kasvupaikkatunnuksia. Koealoilta on otettu myös maaperänäytteitä."
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"en": "Launiainen, Kieloaho, Lindroos, Salmivaara, Ilvesniemi, Heiskanen: Water Retention Characteristics of Mineral Forest Soils in Finland: Impacts for Modeling Soil Moisture",
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"en": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>",
"fi": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>",
"und": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>"
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"en": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>",
"fi": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>",
"und": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>"
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"en": "The purpose of the Biosoil soil inventory (ICP Forests - level I - test plots) was to assess the chemical state of the soil and its changes, and secondly to assess the soil properties that affect the functioning of the forest land. In addition to the fact that the Biosoil data provides soil information for the study of the effects of atmospheric deposition on a larger scale, the soil inventory serves other purposes as it provides data for both research diciplines, climate change mitigation (e.g. the amount of carbon and its changes) and sustainable forest management (e.g., in addition to acidification, also, for example, studies on nutrient cycles and imbalances). \n\nSoil profile data was collected as part of the BioSoil project, Natural Resources Institute Finland, Luke (former Finnish Forest Research Institute, METLA). The BioSoil project was implemented as part of ICP Forests (International Cooperative Program on the Assessment and Monitoring of Air Pollution Effects on Forests; icp-forests.net/) and the EU Forest Focus program (Tamminen and Ilvesniemi 2013). The aim of the project was to collect information on soil properties, composition and changes in carbon, nutrients, acidity and heavy metals in Finnish forest lands. The material was collected in the so-called From the network of ICP Forests Forest Focus Level I experimental area in 2006-2007, which were first sampled for soil samples in 1986-1995 (Tamminen and Starr 1994, Tamminen 2009). This network is part of the so-called 3,000 permanent sample plot data. In Finland, the BioSoil database contains 631 experimental plots, while the total number of the plots in Europe is around 6000 (icp-forests.net/) A detailed description of all the collected data and variables is given in BioSoil Kuvio- ja puusto-ohjeet (2006). \n\nIn the laboratory, the particle size categories (clay, silt and sand) of the soil profile samples were determined. Approximate content of soil organic matter for the mineral soils was determined for different layers based on loss on ignition at a temperature of 550 °C for about two hours. In addition, the concentrations of several elements were determined from the samples. \n\nThe basic data of the experimental area include: latitude, longitude, altitude from sea level, soil moisture, slope, topographical location, bare rock cover (%), soil type, parent material, coarse particle content (%), soil texture, site type and Sphagnum cover (%). \n\nInformation was collected from the mineral soils by the EU funded Biosoil project during 2006-2007 (Tamminen, 2006; Tamminen ja Ilvesniemi, 2013). \n\nData have been used in several research projects (Heiskanen ym. 2018, Heiskanen ym. 2020, Launiainen ym. 2022, Lehtonen ym. 2016, Mäkelä ym. 2022, Rantakari ym. 2012). \n\n## 3,000 permanent sample plots established 1985-86 \n\nIn connection with the 8th national forest inventory in 1985-1986, approximately 3,000 permanent experimental plots were established for the purpose of monitoring the nature of the forest and the state of the environment. The plots were located in a network of forest inventory covering the entire country. The distances between the clusters of plots in southern Finland are 16 km both in the south-north direction and in the east-west direction. In northern Finland, the distances are 24 km in the south-north direction and 32 km in the east-west direction. Each cluster has a group of plots in the direction from south to north including 4 plots every 400 meters in Southern Finland and 3 plots every 600 meters in Northern Finland.\n\nFor the BioSoil project, one plot was selected and measured from each cluster. The data collection of the forest inventories and the assessment of surface areas are based on the division of each plot on the forestry land into management units. Management units have been formed based on the properties of the tree stand. A management unit is a homogeneous area in terms of soil type and trees, as well as the forest management measures that have been carried out in the area. The 4-acre permanent circular sample plot area used in the inventory can be divided into several forest management units. For example, if a part of the test area belongs to a different land class, forest type, or sample plot locates to be on the border of a peatland and a forest or on the border of a tree development class, it is divided into different management units according to the stand properties. \n\nIf necessary, the biologists refined the management unit borders assessed by the inventory team by refining management units borders by the cover drawing made from the sample plot. The refinement of the management unit was based on the site types. The smallest distinguishable management unit had to be at least 5% of the area of the of the sample plot (4 acres). In the inventory, the coverage of field and understory species was estimated from four 2 m2 sample squares systematically placed in the 4-acre experimental area. The abundance of each plant species was evaluated as projected coverage, i.e. the percentage covered by aerial shoots and mixed stems on the sample plot. Coverages were estimated with an accuracy of 1%, coverage below 1% with an accuracy of 0.1%. The biologists of the inventory groups received uniform training for the field work. A large number of tree stand and growth location codes have been inventoried from the plots. Soil samples have also been taken from the inventory plots.",
"fi": "Biosoil maaperäinventaarion (ICP forests - taso I - koealat) tarkoituksena oli arvioida maaperän kemiallista tilaa ja sen muutoksia ja toiseksi arvioida maaperän ominaisuuksia, jotka vaikuttavat metsämaan toimintaan ja käyttöön. Sen lisäksi, että Biosoil aineisto tarjoaa maaperätietoa ilmakehän laskeumavaikutusten tutkimukseen laajemmassa mittakaavassa, maaperäinventaario palvelee muitakin tarkoituksia, sillä se tuo aineistoa sekä ilmastonmuutoksen (esim. hiilen määrä ja sen muutokset), että kestävään metsänhoidon (esim. happamoitumisen lisäksi mm. typpitutkimukset ja ravinteiden epätasapaino, maan viljavuus, maan kantavuus) tutkimukseen.\n\nMaaperäprofiilitiedot kerättiin osana BioSoil-projektia, Luonnonvarakeskus, Luke (entinen Metsäntutkimuslaitos, METLA). BioSoil-projekti toteutettiin osana ICP Forests -ohjelmaa (International Cooperative Program on the Assessment and Monitoring of Air Pollution Effects on Forests; icp-forests.net/) ja EU Forest Focus -ohjelmaa (Tamminen ja Ilvesniemi 2013). Hankkeen tavoitteena oli kerätä tietoa maaperän ominaisuuksista, koostumuksesta sekä hiilen, ravinteiden, happamuuden ja raskasmetallien muutoksista Suomen metsämaissa. Aineisto kerättiin ns. ICP Forests Forest Focus Level I koealan verkostosta vuosina 2006–2007, joista otettiin ensimmäisen kerran maaperänäytteet vuosina 1986–1995 (Tamminen ja Starr 1994, Tamminen 2009). Tämä koealaverkosto on osa ns. 3000 pysyvän koealan aineistoa. Suomessa BioSoil-tietokanta sisältää 631 koealaa, kun taas koko Euroopassa koealojen kokonaismäärä on noin 6000 (icp-forests.net/) Yksityiskohtainen kuvaus kaikista kerätyistä tiedoista ja muuttujista on annettu BioSoil Kuvio- ja puusto-ohjeet (2006).\n\nLaboratoriossa maaperän profiilinäytteistä määritettiin näytteiden hiukkaskokoluokat (savi, siltti ja hiekka). Maaperän orgaanisen aineksen likimääräinen pitoisuus kivennäismaakerrokselle määritettiin eri kerroksille perustuen polttohäviöön 550 °C lämpötilassa noin kahden tunnin ajan. Lisäksi näytteistä määritettiin useiden alkuaineiden pitoisuudet. \n\nKoealan perustiedot sisältävät: leveysaste, pituusaste, korkeus merenpinnan yläpuolella maaperän kosteus, kaltevuus, topografinen sijainti, paljas kivipeite (%), maaperätyyppi, lähtöaine, karkean aineksen pitoisuus (%), maaperän rakenne, kasvupaikan tyyppi ja Sphagnum-peittävyys (%). \n\nKangasmaiden maaperästä ja -kohteista kerättiin tietoja EU:n rahoittaman Biosoil-projektin puitteissa kaudella 2006–2007 (Tamminen, 2006; Tamminen ja Ilvesniemi, 2013). \n\nAineistoa on käytetty useissa tutkimuksissa (Heiskanen ym. 2018, Heiskanen ym. 2020, Launiainen ym. 2022, Lehtonen ym. 2016, Mäkelä ym. 2022, Rantakari ym. 2012). \n\n## Vuonna 1985–86 perustetut noin 3000 pysyvää koealaa \n\nValtakunnan metsien 8. inventoinnin yhteydessä vuosina 1985–1986 perustettiin metsäluonnon ja ympäristön tilan seurantaa varten noin 3000 pysyvää koealaa. Koealat on sijoitettu koko maan kattavaan inventointilohkojen verkostoon. Lohkojen etäisyydet toisistaan ovat Etelä-Suomessa sekä etelä-pohjoissuunnassa että itä-länsisuunnassa 16 km. Pohjois-Suomessa etäisyydet ovat etelä-pohjoissuunnassa 24 km ja itä-länsisuunnassa 32 km. Kullakin lohkolla on etelä-pohjoissuuntainen koealaryväs, joka käsittää Etelä-Suomessa 4 koealaa 400 metrin välein ja Pohjois-Suomessa 3 koealaa 600 metrin välein. \n\nBioSoil-hanketta varten kultakin lohkolta valittiin ja mitattiin 1 koeala. Valtakunnan metsien inventointien tiedonkeruu ja pinta-alojen arviointi perustuu kunkin metsätalouden maalle sijoittuvan koealan jakamiseen metsikkökuvioihin. Kuviointi muodostetaan kasvupaikan ja puuston ominaisuuksien perusteella. Metsikkökuvio on kasvupaikkatekijöiden ja puuston sekä metsässä tehtyjen ja tarvittavien hakkuu- ja hoitotoimien suhteen homogeeninen metsäalue. Inventoinnissa käytetty 4 aarin suuruinen pysyvä ympyräkoeala voi jakaantua useampaan metsikkökuvioon. Esimerkiksi jos osa koealasta kuuluu eri maaluokkaan, kasvupaikkatyyppiin tai koeala sattuu suon ja kankaan rajaan tai puuston kehitysluokkarajaan, se jaetaan metsikkökuvioiden mukaan kuvioihin. \n\nBiologit tarkensivat tarvittaessa inventoinnin ryhmänjohtajien arvioimaa em. koealakuviointia erottamalla tyyppikuviot koealasta tehtyyn peitepiirrokseen. Tyyppikuviot rajattiin kasvupaikkatyypin perusteella. Pienimmän erotettavan tyyppikuvion tuli olla vähintään 5 % 4 aarin täyskoealan pinta-alasta. Inventoinnissa kenttä- ja pohjakerroslajien peittävyydet arvioitiin neljältä 4 aarin koealalle systemaattisesti sijoitetulta 2 m2 suuruiselta näyteruudulta. Kunkin kasvilajin runsautta arvioitiin projektiopeittävyytenä, eli ilmaversojen ja sekovarsien kattamana prosenttipeittävyytenä näyteruudulla. Peittävyydet arvioitiin prosentin tarkkuudella, alle 1 % peittävyydet 0,1 % tarkkuudella. Inventointiryhmien biologit saivat pysyvillä koealoilla suoritettaviin maastotöihin yhtenäisen koulutuksen. Koealoilta on inventoitu runsaasti puusto- ja kasvupaikkatunnuksia. Koealoilta on otettu myös maaperänäytteitä."
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"en": "Launiainen, Kieloaho, Lindroos, Salmivaara, Ilvesniemi, Heiskanen: Water Retention Characteristics of Mineral Forest Soils in Finland: Impacts for Modeling Soil Moisture",
"fi": "Launiainen, Kieloaho, Lindroos, Salmivaara, Ilvesniemi, Heiskanen: Water Retention Characteristics of Mineral Forest Soils in Finland: Impacts for Modeling Soil Moisture"
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"en": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>",
"fi": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>",
"und": "<jats:p>Soil hydraulic properties are central for soil quality and affect forest productivity and the impacts of climate change on forests. The water retention characteristics (WRC) of mineral forest soils in Finland are not well known, and practical tools to predict them for hydrological, biogeochemical and forest models are lacking. We statistically analyzed mineral forest soils WRC from over 130 sites in Finland, focusing on the humus layer and main root zone (0–19 cm depth). We showed that mineral forest soils can be grouped into five WRC classes that are well predictable from soil bulk density, organic matter content and clay fraction. However, the majority of the forest soils are hydrologically rather similar. We found that neither topsoil maps nor any combination of open geospatial data were able to predict WRC. Thus, in the absence of site-specific soil data, parameterizing WRC as a function of forest site fertility type was proposed. We demonstrated the approach in soil moisture modeling at a small forest headwater catchment and showed that the soil moisture response to weather conditions is jointly affected by WRC, stand attributes and topography. We showed that drought risks are highest for dense mature forests at nutrient-poor, coarse-textured sites and lower for young stands on peatlands and lowland herb-rich sites with groundwater influence. The results improve hydrological predictions for Finnish forests, and the open dataset can contribute to the larger synthesis and development of boreal forest soil pedo-transfer functions.</jats:p>"
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"en": "Lehtonen, Linkosalo, Peltoniemi, Sievänen, Mäkipää, Tamminen, Salemaa, Nieminen, Ťupek, Heikkinen, Komarov: Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland",
"fi": "Lehtonen, Linkosalo, Peltoniemi, Sievänen, Mäkipää, Tamminen, Salemaa, Nieminen, Ťupek, Heikkinen, Komarov: Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland"
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"en": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>",
"fi": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>",
"und": "<jats:p>Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.\n </jats:p>"
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"fi": "Vapaasti käytettäväksi tarkoitettu näyteaineisto. Sisältää kahdenkeskisen videoidun keskustelun ”Reitti A-siipeen”, jossa selvitetään reittiä tiettyyn Helsingin yliopiston Metsätalossa sijaitsevaan huoneeseen.\n\nAineisto on saatavilla Kielipankin latauspalvelussa, ks. Access location. Ladattavaan aineistoon sisältyy sama materiaali, joka oli vuoden 2020 loppuun saakka käytettävissä ja ladattavissa Kielipankin LAT-alustan kautta."
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