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  • The technical harvesting potential of small-diameter trees can be defined as the maximum potential procurement volume of small-diameter trees available from the Finnish forests based on the prevailing guidelines for harvesting of energy wood. The potentials of small-diameter trees from early thinnings have been calculated for fifteen NUTS3-based Finnish regions covering the whole country (Koljonen et al. 2017). To begin with the estimation of the region-level potentials, technical harvesting potentials were estimated using the sample plots of the eleventh national forest inventory (NFI11) measured in the years 2009–2013. First, a large number of sound and sustainable management schedules for five consecutive ten-year periods were simulated for each sample plot using a large-scale Finnish forest planning system known as MELA (Siitonen et al. 1996; Redsven et al. 2013). MELA simulations consisted of natural processes and human actions. The ingrowth, growth, and mortality of trees were predicted based on a set of distance-independent tree-level statistical models (e.g. Hynynen et al. 2002) included in MELA and the simulation of the stand (sample plot)-level management actions was based on the current Finnish silvicultural guidelines (Äijälä et al. 2014) and the guidelines for harvesting of energy wood (Koistinen et al. 2016). Simulated management actions for the small-tree fraction consisted of thinnings that fulfilled the following stand criteria: • mean diameter at breast height ≥ 8 cm • number of stems ≥ 1500 ha-1 • mean height < 10.5 m (in Lapland) or mean height < 12.5 m (elsewhere). Energy wood was harvested as delimbed (i.e. including the stem only) in spruce-dominated stands and peatlands and as whole trees (i.e. including stem and branches) elsewhere. When harvested as whole trees, a total of 30% of the original crown biomass was left onsite (Koistinen et al. 2016). Energy wood thinnings could be integrated with roundwood logging or carried out independently. Second, the technical energy wood potential of small trees was operationalized in MELA by maximizing the removal of thinnings in the first period. In this way, it was possible to pick out all small tree fellings simulated in the first period despite, for example, the profitability of the operation. However, a single logging event was rejected if the energy wood removal was lower than 25 m³ha-1 or the industrial roundwood removal of pine, spruce, or birch exceeded 45 m³ha-1. The potential calculated in this way contained also timber suitable for industrial roundwood. Therefore, two estimates are given: • potential of trees below 10.5 cm in breast-height diameter • potential of trees below 14.5 cm in breast-height diameter. Subsequently, the region-level potentials were spread on a raster grid at 1 km × 1 km resolution. Only grid cells on Forests Available for Wood Supply (FAWS) were considered in this operation. In this study, FAWS was defined as follows: First, forest land was extracted from the Finnish Multi-Source National Forest Inventory (MS-NFI) 2013 data (Mäkisara et al. 2016). Second, restricted areas were excluded from forest land. The restricted areas consisted of nationally protected areas (e.g. nature parks, national parks, protection programme areas) and areas protected by the State Forest Enterprise. In addition, some areas in northernmost Lapland restricted by separate agreements between the State Forest Enterprise and stakeholders were left out from the final data. Furthermore, for small trees, FAWS was further constrained by the stand criteria presented above to represent similar stand conditions for small-tree harvesting as in MELA. Finally, the region-level potentials were distributed to the grid cells by weighting with MS-NFI stem wood biomasses. References Äijälä O, Koistinen A, Sved J, Vanhatalo K, Väisänen P (2014) Metsänhoidon suositukset [Guidelines for sustainable forest management]. Metsätalouden kehittämiskeskus Tapion julkaisuja. Hynynen J, Ojansuu R, Hökkä H, Salminen H, Siipilehto J, Haapala P (2002) Models for predicting the stand development – description of biological processes in MELA system. The Finnish Forest Research Institute Research Papers 835. Koistinen A, Luiro J, Vanhatalo K (2016) Metsänhoidon suositukset energiapuun korjuuseen, työopas [Guidelines for sustainable harvesting of energy wood]. Metsäkustannus Oy, Helsinki. Koljonen T, Soimakallio S, Asikainen A, Lanki T, Anttila P, Hildén M, Honkatukia J, Karvosenoja N, Lehtilä A, Lehtonen H, Lindroos TJ, Regina K, Salminen O, Savolahti M, Siljander R (2017) Energia ja ilmastostrategian vaikutusarviot: Yhteenvetoraportti. [Impact assessments of the Energy and Climate strategy: The summary report.] Publications of the Government´s analysis, assessment and research activities 21/2017. Mäkisara K, Katila M, Peräsaari J, Tomppo E (2016) The Multi-Source National Forest Inventory of Finland – methods and results 2013. Natural resources and bioeconomy studies 10/2016. Redsven V, Hirvelä H, Härkönen K, Salminen O, Siitonen M (2013) MELA2012 Reference Manual. Finnish Forest Research Institute. Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O, Teuri M (1996) MELA Handbook. Metsäntutkimuslaitoksen tiedonantoja 622. ISBN 951-40-1543-6.

  • The Baltic Sea Pressure Index is a calculation of quantity and spatial distribution of potential cumulative impacts on the Baltic Sea. The BSII is based on georeferenced datasets of human activities (36 datasets), pressures (18 datasets) and ecosystem components (36 datasets), and on sensitivity estimates of ecosystem components (so-called sensitivity scores) that combine the pressure and ecosystem component layers, created in <a href="http://www.helcom.fi/helcom-at-work/projects/holas-ii" target="_blank">HOLAS II</a> project. The assessment can be applied with a focus on pressures only by using the Baltic Sea Pressure Index (BSPI) which shows the anthropogenic pressures/human activities in the defined assessment units without including ecosystem components. The BSPI however includes a weighting component in order to grade the effect of the pressures on the ecosystem in a generalized perspective. Cumulative impacts are calculated for each assessment unit (1 km2 grid cells) by summing all impacts occurring in the unit. All datasets and methodologies used in the index calculations are approved by all HELCOM Contracting Parties in review and acceptance processes. This dataset covers the time period 2011-2016. Please scroll down to "Lineage" and visit <a href="http://stateofthebalticsea.helcom.fi/cumulative-impacts/" target="_blank">State of the Baltic Sea website</a> for more info.

  • Seabed substrate 1:100 000 is one of the products produced in the EMODnet (European Marine Observation and Data network) Geology III EU project. Project provided seabed geological material from the European maritime areas. The EMODnet Geology III project (http://www.emodnet-geology.eu/) collects and harmonizes geological data from the European sea areas to support decision-making and sustainable marine spatial planning. The EMODnet Geology partnership has included 39 marine organizations from 30 countries. This data includes the EMODnet seabed substrate map at a scale of 1:100 000 from the Finnish marine areas. It is based on the data produced on a scale of 1:20 000 by the Geological Survey of Finland (GTK). The data has been harmonized and reclassified into five Folk substrate classes (clay + silt (mud), sandy clays, clayey sands, coarse sediments, mixed sediments) and bedrock. The data describes the seabed substrate from the uppermost 30 cm of the sediment column. The data have been generalized into a target scale (1:100 000). The smallest smallest cartographic unit within the data is 0.05 km2 (5 hectares). Further information about the EMODnet-Geology project III is available on the portal (http://www.emodnet-geology.eu/). Permission (AN17367) to publish the material was obtained from the Finnish Defence Office 29.9.2017.

  • The EMODnet (European Marine Observation and Data network) Geology project collects and harmonizes marine geological data from the European sea areas to support decision making and sustainable marine spatial planning. The partnership includes 39 marine organizations from 30 countries. The partners, mainly from the marine departments of the geological surveys of Europe (through the Association of European Geological Surveys-EuroGeoSurveys), have assembled marine geological information at various scales from all European sea areas (e.g. the White Sea, Baltic Sea, Barents Sea, the Iberian Coast, and the Mediterranean Sea within EU waters). This dataset includes EMODnet seabed substrate maps at a scale of 1:15 000 from the European marine areas. Traditionally, European countries have conducted their marine geological surveys according to their own national standards and classified substrates on the grounds of their national classification schemes. These national classifications are harmonised into a shared EMODnet schema using Folk's sediment triangle with a hierarchy of 16, 7 and 5 substrate classes. The data describes the seabed substrate from the uppermost 30 cm of the sediment column. Further information about the EMODnet Geology project is available on the portal (http://www.emodnet-geology.eu/).

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    FTIA INSPIRE Transport Networks Theme Dataset is a dataset depicting the Transport Networks covering the whole of Finland. It contains the following INSPIRE feature types: Road network, Rail network, Waterway network and Air transport network. The dataset is available via the FTIA INSPIRE Download Service (WFS) for Transport Networks and it can be viewed via the FTIA INSPIRE View Service (WMS) for Transport Networks.

  • This dataset contains borders of the HELCOM MPAs (former Baltic Sea Protected Areas (BSPAs). The dataset has been compiled from data submitted by HELCOM Contracting Parties. It includes the borders of designated HELCOM MPAs stored in the http://mpas.helcom.fi. The designation is based on the HELCOM Recommendation 15/5 (1994). The dataset displays all designated or managed MPAs as officially reported to HELCOM by the respective Contracting Party. The latest related HELCOM publication based on MPA related data is http://www.helcom.fi/Lists/Publications/BSEP148.pdf The dataset contains the following information: MPA_ID: Unique ID of the MPA as used in HELCOM Marine Protected Areas database Name: Name of the MPA Country: Country where MPA is located Site_link: Direct link to site's fact sheet in the http://mpas.helcom.fi where additional information is available MPA_status: Management status of the MPA Date_est: Establishment date of the MPA Year_est: Establishment year of the MPA

  • This dataset represents the Integrated biodiversity status assessment for pelagic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. Open sea areas were assessed based on the core indicators ‘Zooplankton mean size and total stock’ and ‘Chlorophyll-a’, as well as the pre-core indicator ‘Cyanobacterial bloom index’ . Coastal areas were assessed by national indicators. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "BQR" = Biological Quality Ratio "Confidence" = Confidence of the assessment "HELCOM_ID" = Code of the HELCOM assessment unit "Country" = Country of coastal assessment unit/ open sea "Level2" = HELCOM sub-basins (name of the scale 2 assessment unit) "Name" = Name of the HELCOM scale 4 assessment unit "Area_km2" = Area of assessment unit "AULEVEL" = scale of the assessment unit "HID" = assessment unit ID by country "SAUID" = ID number for the spatial assessment unit "EcosystemC" = Ecosystem component assessed "Confiden_1" = Confidence of the assessment (0-1, higher values mean higher confidence) "Total_numb" = Number of indicators used in assessment "STATUS" = Integrated status category (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

  • Maatalousmaa vuonna 2020 aineisto kuvaa mahdollisimman kattavasti maankäytöltään maatalouteen kuuluvia alueita vuonna 2020, sisältäen sekä maataloustukia saavat alueet, että tukien ulkopuoliset alueet. Aineisto on koostettu käyttäen Ruokaviraston tuottamia perus- ja kasvulohkoaineistoja sekä Maanmittauslaitoksen tuottamaa maastotietokantaa. Peruslohkoaineisto on komission asetuksen 796/2004 ja neuvoston asetuksen (EY) N:o 1782/2003 20 artiklassa tarkoitettu viljelylohkojen tunnistusjärjestelmä. Järjestelmää käytetään EU:n pinta-alaperusteisen maataloustuen hallinnoinnissa. Aineisto käsittää vuoden 2020 peruslohkojen tilanteen 31.12.2020. Kasvulohkolla tarkoitetaan yhteen peruslohkoon kuuluvaa yhtenäistä aluetta, jossa kasvatat yhtä kasvilajia, useamman kasvilajin seosta tai jota kesannoidaan tai joka on erityiskäytössä. Yhdellä peruslohkolla voi olla yksi tai useampia kasvulohkoja. Kasvulohko voi kuulua vain yhteen peruslohkoon. Kasvulohkojen rajat ja samalla niiden pinta-alat voivat vaihdella peruslohkon sisällä vuosittain. Peltolohkorekisteristä on aineistoon otettu mukaan ne lohkot joihin yhdistyy kasvulohkoista tieto viljellystä kasvista. Aineistosta on tiputettu pois ei-maatalousaluetta olevat lohkot, esimerkiksi metsäiset alueet. Maanmittauslaitoksen Maastotietokanta on koko Suomen kattava maastoa kuvaava aineisto ja se koostuu erilaisista kohderyhmistä. Maastotietokannan Maatalousmaa -aineisto sisältää Maastotietokannan pellot, ja puutarhat. Niityt ovat erillinen kohdeluokka. Mammuttiprojektia varten MTK kohdeluokat Maatalousmaa (pellot ja puutarhat) ja Niitty yhdistettiin yhdeksi aineistoksi. Kohdeluokat on poimittu vuoden 2020 Maastotietokannasta, joka on saatavissa Paituli-palvelusta (poiminta tehty 19.04.2021). Kohdeluokat ja niiden kuvaukset löytyvät: https://www.maanmittauslaitos.fi/sites/maanmittauslaitos.fi/files/attachments/2018/03/Maastotietokohteet_0.pdf Peruslohkoaineistosta ja maastotietokannasta poimitut kohteet on yhdistetty siten, että maatalousmaa muodostetaan ensisijaisesti käyttämällä peruslohkoaineistosta poimittuja peruslohkoja. Tämän joukon ulkopuolelle jäävä maatalousmaa tulee maastotietokannasta. Aineistojen yhdistäminen on kuvattu tarkemmin tuotantokuvauksessa. https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/maatalousmaa2020.pdf https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/Metatietokuvaus_peltolohkorekisteri.pdf Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0).