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"fi": "Koesarjan avulla selvitetään, miten lannoituksilla voitaisiin lieventää ilman epäpuhtauksista, bioottisista tekijöistä yms. aiheutuvia vaurioita ja turvata metsien kasvukunto. Kokeet on perustettu v. 1991-1993 keski-ikäisiin kasvatusmetsiin. Koesarjaan kuuluu 13 männikkö- ja 5 kuusikkokoetta sekä 1 koivikkokoe. Koejärjestelynä on satunnaistetut lohkot. Ravinteita on lisätty ensisijaisesti hidasvaikutteisina lannoitteina, joilla parannetaan tasapainoista ravinteiden saantia ja lievennetään maan happamuutta. Kolmelle kokeelle on perustettu 2000-luvulla puittaisia hakkuutähdekäsittelyjä.\n\nKokeilla on suoritettu puustonmittauksia, neulasnäytteenottoja, kaatokoepuiden mittauksia, maanäytteenottoja, karikenäytteenottoja sekä sade- ja vajovesimittauksia.\n\n### TL375 Loppi\n\nLopen ja Karkkilan välillä sijaitseva tutkimusmetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990 , 1994, 1998, 2004 ja 2015. 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Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1990 ja 1995.\n\n\n### TL407 Rovaniemi\n\nRovaniemen ja Kemijärven välillä sijaitseva koemetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990, 1995, 2000, 2005, 2010 ja 2020. Koeasetelmana 18 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1990 ja 1995.\n\n\n### TL408 Oulu\n\nOulussa Ylikiimingin itäpuolella sijaitseva koemetsikkö (≈6 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1991, 1996, 2001, 2006 ja 2012. Koeasetelmana 21 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1996.\n\n\n### TL409 Salo\n\nSalon Kiikalassa sijaitseva koemetsikkö (≈5 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990, 1995, 2000 ja 2005. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1995.\n\n\n### TL410 Jämijärvi\n\nJämijärven ja Ikaalisten välillä sijaitseva koemetsikkö (≈5 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990, 1995, 2000, 2005, 2012 ja 2017. Koeasetelmana 18 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1990, 1995 ja 2000. Lisäksi koealojen vaipoilta (ulkorajoilta brutto- ja nettokoealan rajojen väliseltä alueelta) vuonna 1994.\n\n\n### TL411 Harjavalta\n\nHarjavallassa sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1991, 1996 ja 2002. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1996. Lisäksi koealojen vaipoilta (ulkorajoilta brutto- ja nettokoealan rajojen väliseltä alueelta) vuonna 1994.\n\n### TL412 Harjavalta\n\nHarjavallassa sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1991, 1996, 2002 ja 2006. Koeasetelmana 16 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1996. \n\n### TL413 Harjavalta\n\nHarjavallassa sijaitseva koemetsikkö (≈6 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1991, 1996, 2002 ja 2007. Koeasetelmana 16 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1996. Lisäksi koealojen vaipoilta (ulkorajoilta brutto- ja nettokoealan rajojen väliseltä alueelta) vuonna 1994.\n\n### TL414 Kokemäki\n\nKokemäellä sijaitseva koemetsikkö (≈5 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1991, 1996, 2001 ja 2006. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1991 ja 1996. Lisäksi koealojen vaipoilta (ulkorajoilta brutto- ja nettokoealan rajojen väliseltä alueelta) vuonna 1994.\n\n### TL415 Sonkajärvi\n\nSonkajärvellä sijaitseva koemetsikkö (≈5 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1992, 1997, 2002 ja 2007. Koeasetelmana 21 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1992 ja 1997.\n\n\n### TL416 Jämsä\n\nJämsässä sijaitseva koemetsikkö (≈6 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1992, 1997, 2002, 2007 ja 2016. Koeasetelmana 18 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1992 ja 1997.\n\n\n### TL417 Savonlinna\n\nSavonlinnassa Punkaharjulla sijaitseva koemetsikkö (≈9 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1993, 1997, 2002 ja 2007. Koeasetelmana 16 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuosina 1992 ja 2002.\n\n### TL418 Suonenjoki\n\nSuonenjoella sijaitseva koemetsikkö (≈8 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1993, 1997 ja 2002. Koeasetelman 20 puustokoealasta seurattu mittauksin 16 alaa.\n\n#### Kaatokoepuut\n\nKaatokoepuita kaadettu ja mitattu koealoilta vuonna 1992.\n\n##### ______________________________________________________________________________________________________________________ \n\n### Puustonmittausaineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.\n\n### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm), yläläpimitta ilmoitetulta korkeudelta(mm), tuoreoksaraja(dm, kuivaoksaraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
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"en": "<jats:p>Resumo Este artigo discute um modelo de triangulação de análise quantitativa de dados para investigar a agência profissional do estudante de pedagogia (APEP), já utilizado na Finlândia e em aplicação no Brasil. A APEP pode ser compreendida como o engajamento do estudante no próprio processo contínuo de aprendizagem, por meio de mecanismos individuais e interações sociais com outros e com recursos do ambiente. A literatura mostra que a APEP se desenvolve de acordo com a construção da identidade profissional do professor, a coerência curricular do curso de pedagogia e o seu ambiente de aprendizagem. Este estudo utilizou os resultados obtidos com ajuda de questionário aplicado a 362 estudantes do curso de pedagogia de uma universidade finlandesa. Duas análises quantitativas de dados foram aplicadas: a Modelagem de Equações Estruturais (MEE), representando o modelo reflexivo da psicometria tradicional, aliada à análise de redes pertencente ao modelo formativo da psicometria. Os resultados mostraram que, enquanto o modelo reflexivo oferece medidas mais robustas de validação e confiança nos resultados, o modelo formativo amplia o modo de compreender a complexa relação entre as dimensões da agência profissional dos estudantes de pedagogia, assim como os construtos individuais e fatores ambientais que a influenciam durante a formação inicial de docentes. Essa triangulação quantitativo-analítica permitiu compreender de forma mais abrangente os processos interativos dos fatores investigados e pode ser utilizada por educadores e formuladores de currículo para desenvolverem uma formação inicial de professores que melhor prepare os estudantes de pedagogia a se engajarem no contínuo processo profissional ao longo de suas carreiras.</jats:p>",
"fi": "<jats:p>Resumo Este artigo discute um modelo de triangulação de análise quantitativa de dados para investigar a agência profissional do estudante de pedagogia (APEP), já utilizado na Finlândia e em aplicação no Brasil. A APEP pode ser compreendida como o engajamento do estudante no próprio processo contínuo de aprendizagem, por meio de mecanismos individuais e interações sociais com outros e com recursos do ambiente. A literatura mostra que a APEP se desenvolve de acordo com a construção da identidade profissional do professor, a coerência curricular do curso de pedagogia e o seu ambiente de aprendizagem. Este estudo utilizou os resultados obtidos com ajuda de questionário aplicado a 362 estudantes do curso de pedagogia de uma universidade finlandesa. Duas análises quantitativas de dados foram aplicadas: a Modelagem de Equações Estruturais (MEE), representando o modelo reflexivo da psicometria tradicional, aliada à análise de redes pertencente ao modelo formativo da psicometria. Os resultados mostraram que, enquanto o modelo reflexivo oferece medidas mais robustas de validação e confiança nos resultados, o modelo formativo amplia o modo de compreender a complexa relação entre as dimensões da agência profissional dos estudantes de pedagogia, assim como os construtos individuais e fatores ambientais que a influenciam durante a formação inicial de docentes. Essa triangulação quantitativo-analítica permitiu compreender de forma mais abrangente os processos interativos dos fatores investigados e pode ser utilizada por educadores e formuladores de currículo para desenvolverem uma formação inicial de professores que melhor prepare os estudantes de pedagogia a se engajarem no contínuo processo profissional ao longo de suas carreiras.</jats:p>",
"und": "<jats:p>Resumo Este artigo discute um modelo de triangulação de análise quantitativa de dados para investigar a agência profissional do estudante de pedagogia (APEP), já utilizado na Finlândia e em aplicação no Brasil. A APEP pode ser compreendida como o engajamento do estudante no próprio processo contínuo de aprendizagem, por meio de mecanismos individuais e interações sociais com outros e com recursos do ambiente. A literatura mostra que a APEP se desenvolve de acordo com a construção da identidade profissional do professor, a coerência curricular do curso de pedagogia e o seu ambiente de aprendizagem. Este estudo utilizou os resultados obtidos com ajuda de questionário aplicado a 362 estudantes do curso de pedagogia de uma universidade finlandesa. Duas análises quantitativas de dados foram aplicadas: a Modelagem de Equações Estruturais (MEE), representando o modelo reflexivo da psicometria tradicional, aliada à análise de redes pertencente ao modelo formativo da psicometria. Os resultados mostraram que, enquanto o modelo reflexivo oferece medidas mais robustas de validação e confiança nos resultados, o modelo formativo amplia o modo de compreender a complexa relação entre as dimensões da agência profissional dos estudantes de pedagogia, assim como os construtos individuais e fatores ambientais que a influenciam durante a formação inicial de docentes. Essa triangulação quantitativo-analítica permitiu compreender de forma mais abrangente os processos interativos dos fatores investigados e pode ser utilizada por educadores e formuladores de currículo para desenvolverem uma formação inicial de professores que melhor prepare os estudantes de pedagogia a se engajarem no contínuo processo profissional ao longo de suas carreiras.</jats:p>"
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"en": "Using nonsoluble, partly soluble or soluble K-fertilizers with slowly soluble P or by using foliar analysis (on polluted sites)vitality of young pine stands growing on peatlands are tried to return.",
"fi": "Suomänniköissä esiintyneiden tuhojen hoitamiseen tarkoitettujen liukoisuudeltaan erilaisten kaliumyhdisteiden koesarja. \n\n### LATER501 Raasepori\n\nRaaseporin Tammisaaren länsipuolella sijaitseva tutkimusmetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1991 ja 1996. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 24.10.1991**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 23-25.9.1996**\n- Mitattu kaikki koealat.\n\n\n### LATER502 Eurajoki\n\nPorin ja Rauman puolivälissä Eurajoella sijaitseva tutkimusmetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990 ja 1996. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 18.10.1990**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 13.-14.8.1996**\n- Puuston mittaus harvennuksen jälkeen. Mitattu kaikki koealat.\n\n\n### LATER503 Kankaanpää\n\nKankaanpään kaakkoispuolella sijaitseva koemetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990-1991 ja 1999. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 1.11.1990-16.5.1991**\n- Mitattu kaikki koealat. Koealat 1-10 syksyllä ja 11-15 keväällä.\n\n**Puuston mittaus 21.-23.9.1999**\n- Mitattu kaikki koealat.\n\n\n### LATER504 Hyvinkää\n\nHyvinkään ja Mäntsälän puolivälissä sijaitseva koemetsikkö (≈7 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990 ja 1995. Koeasetelmana 20 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 1.12.1990**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 3.-11.10.1995**\n- Mitattu kaikki koealat.\n\n\n### LATER506 Kouvola\n\nKouvolan itäpuolella sijaitseva koemetsikkö (≈7 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1992 ja 1999. 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Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 22.5.1992**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 12.10.-17.11.1999**\n- Mitattu kaikki koealat.\n\n\n### LATER509 Posio\n\nPosion eteläpuolella sijaitseva koemetsikkö (≈4 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 5.11.1990**\n- Mitattu kaikki koealat.\n\n\n### LATER510 Ylitornio\n\nYlitornion Meltosjärven itäpuolella sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1990. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 23.10.1990**\n- Mitattu kaikki koealat.\n\n\n### LATER511 Pelkosenniemi\n\nPelkosenniemen Luiron pohjoispuolella sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 1991. Koeasetelmana 15 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 8.10.1991**\n- Mitattu kaikki koealat.\n\n\n### LATER512 Pyhtää\n\nPyhtään pohjoispuolella sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2022. Koeasetelmana 23 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 2.8.-26.9.2022**\n- Mitattu kaikki koealat, paitsi 6, 7 ja 21.\n\n\n### HARJAV505 Harjavalta/Nakkila\n\nHarjavallassa sekä Nakkilassa sijaitsevat 5 koemetsikköä (≈3/15 ha).\n\n#### Puuston mittaukset\n\nPuustot mitattu 1992 ja 1998. Koeasetelmana 25 puustokoealaa viidessä eri koemetsikössä (5 koealaa/metsikkö).\n\n**Puuston mittaus 15.10.-26.10.1992**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 1.6.-5.6.1998**\n- Mitattu kaikki koealat.\n\n\n##### ______________________________________________________________________________________________________________________ \n\n### Aineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.\n\n### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm), yläläpimitta ilmoitetulta korkeudelta(mm), tuoreoksaraja(dm, kuivaoksaraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
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"en": "The survey charted Finnish opinions on and experiences of welfare and inequality. The study was part of a project entitled Tackling Inequalities in Time of Austerity (TITA) funded by the Strategic Research Council of the Academy of Finland (decision numbers: 293103 and 314250), as well as the Inequalities, Interventions and a New Welfare State (INVEST) project funded by the Academy of Finland (decision number: 320162). First, the respondents were asked about their life satisfaction, mood, ability to achieve goals, perceived status in society and trust in other people. Feelings of loneliness, depression, failure, and happiness in the previous 12 months were also charted. Regarding income and personal finance, net income of the household and the ease of covering usual expenses with the income were surveyed. The respondents were asked whether they had received social assistance (minimum income scheme) in the previous year. The respondents' sense of safety was examined with questions on how often they interacted with or helped their neighbours, how safe they felt it was to walk outside in their own neighbourhood or in the population centre of the municipality late at night, and whether they had recently been concerned about becoming the victim of certain crimes (e.g. burglary, assault, sexual harassment). The respondents' views on how safe Finland is in general were also investigated. A number of statements about social assistance and social security were presented (e.g. all Finns are treated equally, the funding of social security is not sustainable, and that EU membership is a disadvantage to social security). Finally, the respondents were asked to what extent they agreed with statements about their own welfare and well-being, and how satisfied they were with their lives overall. Background variables included the respondent's gender, year of birth, household composition, household characteristics, housing tenure, type of accommodation, level of education, household income and expenses, and NUTS3 region of residence.",
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"description": {
"en": "This national survey examined the health and health-related behaviour of university and university of applied sciences (polytechnic) students in Finland. Questions covered, among other topics, physical, mental and dental health, health-related behaviour, social interaction, and eating habits. General state of health was charted with a number of questions relating to long-term illnesses, disabilities or disorders, and current well-being in general. The respondents were asked if they had suffered from a variety of symptoms in the previous month. Birth control methods used by the respondent and her/his partner within the previous month were surveyed. Some questions covered the respondents' weight, height, and attitude toward food. Psychological or social symptoms causing problems were investigated. Psychosocial health was further studied using items of the General Health Questionnaire (GHQ-12). Use of healthcare services by different types of service providers and satisfaction with the services of the Finnish Student Health Service (FSHS) were surveyed, along with reasons for using the services of other healthcare service providers. The respondents were also asked if they had used smartphone applications related to health and well-being, and what type of guidance they would have liked in certain issues (e.g. stress or weight management, study skills, alcohol use, smoking cessation). Time spent sitting during the day as well as engagement in sporting activities and less vigorous physical activities were surveyed. Eating habits were investigated with a number of questions based on the Index of Diet Quality (IDQ), for instance, asking where the respondents ate their main meals, if they skipped meals, and the consumption of dairy products, fish, bread, fruit, vegetables, etc. The respondents were also asked how often they brushed or flossed their teeth and used toothpaste or xylitol products, and whether they had problems with teeth grinding (or used a bite guard), facial pain or jaw locking. Health-related behaviour was further studied by asking the respondents about their use of drugs, alcohol and tobacco products (amount, frequency). Drinking habits were further charted using the Alcohol Use Disorders Identification Test (AUDIT). Some questions covered gambling and possible problems caused by it. One theme pertained to the respondents' studies. The survey examined the number of years the respondents had been enrolled as 'present' for current studies, credits earned, study success, and confidence of having chosen the right field of study, as well as hours spent on study and hours spent on paid work during the study year. The sufficiency of study guidance and advice provided by the institution were investigated as well as positive and negative feelings (e.g. enthusiasm, burnout) related to their studies. Internet use was examined with questions regarding the purposes for which respondents used the internet and how many hours per week, and if it had caused problems with their circadian rhythm, studying or relationships. The respondents' participation in paid work during the academic year was also surveyed, and they were asked to evaluate their financial situation. The survey also studied interpersonal relationships. The respondents were asked about their household composition and living arrangements, partnerships, sexual orientation, spending time with friends, whether they felt lonely or part of a group, and whether they had someone close to them with whom they could discuss their affairs. Some questions charted whether the respondents had been subjected to bullying or discrimination during their higher education studies or had themselves bullied or discriminated against others. The respondents were also asked whether they had been subjected to stalking or violence, and by whom. The final theme pertained to family life, and questions covered the number of children, whether the respondents would want to have (more) children, reasons for having or not having children, and support for combining studies and family life (from the university, from other people, or from society). Background variables included the respondent's age, gender, field of study, and university/university of applied sciences.",
"fi": "Tutkimuksessa kartoitettiin korkeakouluopiskelijoiden fyysistä, psyykkistä ja sosiaalista terveydentilaa, keskeisiä terveyskäyttäytymisen piirteitä sekä terveyspalvelujen käyttöä ja mielipiteitä palvelujen laadusta. Lisäksi selvitettiin terveyteen, terveyskäyttäytymiseen ja opiskelukykyyn liittyviä tekijöitä, kuten sosiaalisia suhteita, opiskelua ja toimeentuloa. Kysymykset käsittelivät terveydentilaa, mm. lääkärin toteamia sairauksia, oppimisvaikeuksia, henkistä hyvinvointia, oireita, ehkäisyä, ruokailutottumuksia ja suhtautumista ruokaan. Lisäksi kysyttiin millaisia tunteita vastaajat olivat kokeneet viikon aikana ja kysyttiin, miten hyvin vastaajat olivat keskittymään ja suoriutumaan tehtävistään sekä olivatko he tunteneet itsensä hyödyllisiksi. Terveyspalveluita tutkittiin kysymällä, mitä terveyspalveluja oli käytetty, miltä palveluntarjoajilta ne oli hankittu ja miksi. Kysyttiin myös erilaisten terveyteen ja hyvinvointiin liittyvien mobiilisovellusten käytöstä sekä tiedusteltiin, olisiko vastaajilla tarvetta terveyteen liittyvälle neuvonnalle, ryhmäkokoontumisille, kursseille tai luennoille. Liikuntatottumuksia kartoitettiin kysymällä hyöty- ja kuntoliikuntaan käytettyä aikaa sekä tiedusteltiin, kuinka paljon vastaajat keskimäärin istuivat arkipäivinä. Lisäksi kysyttiin, kenen järjestämään liikuntatoimintaan vastaajat osallistuivat. Ravintoa käsittelevissä kysymyksissä tiedusteltiin, ajattelivatko vastaajat ruokaa hankkiessaan sen terveellisyyttä ja kuinka usein he söivät lounaan opiskelijaravintolassa opiskeluviikon aikana. Lisäksi kysyttiin kuinka usein erilaisia ravintoaineita nautittiin viikossa, millaista leipää syötiin ja millaista rasvaa leivän päälle laitettiin. Kysyttiin myös, millaisia maitovalmisteita vastaajilla oli tapana nauttia. Hampaiden hoitoa käsiteltiin kysymällä, kuinka usein hampaita harjattiin, käytettiinkö fluorihammastahnaa, hammaslankaa ja ksylitolipurukumia. Kysymykset käsittelivät myös hampaiden narskuttelua ja purentakiskojen käyttöä. Tupakointi, alkoholia ja huumeita käsiteltiin kysymällä mitä aineita ja kuinka usein vastaajilla oli tapana käyttää. Alkoholin käyttöä kartoitettiin vielä useilla tarkentavilla kysymyksillä. Rahapelaamista tutkittiin kysymällä, olivatko vastaajat tunteneet tarvetta käyttää pelaamiseen entistä enemmän rahaa ja olivatko he valehdelleet läheisilleen pelaamisestaan. Opiskeluun liittyvissä kysymyksissä kysyttiin mm. läsnäolovuosien määrää ja suoritettuja opintopisteitä sekä pyydettiin omaa arviota opintomenestyksestä. Lisäksi esitettiin opintoihin liittyviä väittämiä. Kysyttiin myös kuinka paljon vastaajat käyttivät nettiä ja kuinka paljon siihen kului aikaa. Seuraavaksi kysyttiin, kävivätkö vastaajat töissä opintojen ohessa ja millaiseksi he kokivat taloudellisen tilanteensa. Ihmissuhteita käsittelivät kysymykset koskivat perhemuotoa, ystäviä ja ystävyyttä, parisuhdetta ja seksuaalista käyttäytymistä. Tämän jälkeen kysyttiin, kokivatko vastaajat tulleensa kiusatuiksi, vainotuiksi tai olivatko he joutuneet väkivallan kohteeksi ja kenen taholta. Lopuksi kysymykset käsittelivät opiskelun ja perheen yhteensovittamista, lapsien lukumäärää, aikovatko vastaajat hankkia tulevaisuudessa lapsen tai lisää lapsia. Kysyttiin myös, mitkä syyt vaikuttivat siihen, jos lapsen hankinta ei tuntunut ajankohtaiselta. Taustamuuttujina olivat mm. ikä, sukupuoli, korkeakoulu ja opiskelupaikkakunta."
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"description": {
"en": "The dataset contains 149 sexual life histories written by Finnish men and women for a national writing competition, advertised in popular magazines in 1992. The autobiographies were collected as part of the FINSEX research project studying Finnish sexuality. In the writing competition invitation, participants were asked to describe significant events, issues, experiences and feelings related to their sexual history, sexual life at that moment, and own sexuality in general, including sexual identity. While the participants were asked to write freely, they were also given a broad schema they could use to direct their narratives. The length of the autobiographies varied from one to 46 pages. Background information included the participant's gender, age, occupation or other economic activity, and involvement in and type of couple relationship. The dataset is only available in Finnish, with the exception of one autobiography available in Swedish.",
"fi": "Aineisto sisältää suomalaisten omakohtaisia kirjoituksia seksuaalisuudesta ja seksielämästä. Kirjoitukset on kerätty valtakunnallisella kirjoituskilpailulla, jossa vastaajaa on pyydetty vapaamuotoisesti kertomaan oman seksuaalisuuden ja sukupuolielämän kannalta merkityksellisistä asioista ja kokemuksista elämän varrelta. Aineisto on kerätty osana suomalaisten sukupuolielämää kartoittavaa FINSEX-tutkimushanketta vuonna 1992. Seksuaalisen omaelämänkerran kilpailukutsussa vastaajia on ohjeistettu kirjoittamaan vapaamuotoisesti, mutta heille annettiin väljä neljän kohdan runko, jota noudattamalla omaa kirjoitustaan voi ohjata. Aluksi kirjoittajaa pyydettiin kuvaamaan sen hetkistä elämäntilannetta: miten seksuaalinen elämä on muokkautunut siihenastiseen elämäntilanteeseen ja millaisia tyytyväisyyden tai tyytymättömyyden kokemuksia siihen liittyy. Toiseksi kirjoittajaa pyydettiin kertomaan elämänhistoriastaan ja siitä, miten lapsuudenkoti ja vanhemmat suhtautuivat seksuaalisuuteen sekä millaisia seksuaalisuuden kokemuksia esiintyi lapsuuden ja nuoruuden vuosina sekä myöhemmin aikuisuuden sukupuolikokemuksissa. Kirjoittajaa pyydettiin kertomaan erilaisista suhteista, seikkailuista sekä seksuaalisuuteen kohdistuvien ajatusten muuttumisesta elämän kuluessa. Kolmanneksi kirjoittajaa pyydettiin arvioimaan seksuaalista elämäänsä kokonaisuutena, kuten mitkä ovat merkittävimmät ja traumaattisimmat kokemukset sekä mitä asioita toivoo vielä seksiltä. Neljännessä kohdassa kirjoittajaa pyydetään vielä kertomaan muun muassa, minkä ulkoisten asioiden hän uskoo elämässä vaikuttaneen eniten suhtautumiseensa seksuaalisuuteen, mitä elämä on opettanut ja mistä on saanut sosiaalista tukea vaikeissa tilanteissa. Kirjoituksissa esiintyy hyvin monipuolisesti seksuaalisuuteen liittyviä aihealueita ja niitä ovat muun muassa seksuaalinen häirintä ja hyväksikäyttö, seksuaaliset häiriöt, masturbaatio, eroottiset leikit, seksuaalinen halukkuus, ryhmäseksi, seksuaalivalistus, sukupuolimoraali, pornografia, prostituutio ja erilaiset seksuaaliset identiteetit. Kirjoituksen ovat kaikki suomenkielisiä lukuun ottamatta yhtä ruotsinkielistä kirjoitusta. Aineistossa kirjoituksia on yhteensä 149 kappaletta. Taustatietoina on kerrottu vastaajan sukupuoli, ikä, pääasiallinen toimi ja parisuhdetyyppi. Aineistosta on tehty html-versio, jonka hakemiston avulla kirjoituksia on helppo selata. Kirjoitukset on numeroitu tutkijan alkuperäisen numeroinnin mukaisesti, siksi ne eivät noudata ns. normaalia numerointijärjestystä."
},
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"fi": "Koesarjan tavoitteena on seurata ravinnelisäyksen vaikutuksia kasvupaikkaan, kasvillisuuteen ja puustoon ojitusalueilla. Koejärjestelyt ja käsittelyt ovat vaihtelevia: lannoituskäsittelyjä on tehty eri metsänkäsittelyvaiheisiin liittyen ja perustettu usein \"tavanomaisista\" käsittelyistä poiketen esikokeiksi mm. tutkimushypoteesien testaamiseksi.\n\nTestattu kaupallisten lannoitteiden (PK, K) vaikutusta. Tärkeimpänä varttuneisiin metsiin 2000-luvun alussa perustetut kokeet. Aineisto sisältää muun muassa puustomittauksien datoja ja neulasnäytteiden tuloksia.\n\n### HANNULAPK Tornio\n\nTornion koillispuolella sijaitseva tutkimusmetsikkö (≈9 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu kevään ja syksyn 2021 aikana. Koeasetelmana 27 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 1.5.-4.6.2021**\n- Mitattu koealat 1, 3, 4, 7, 12, 15, 16, 18, 19, 21 ja 22.\n\n**Puuston mittaus 11.8.-7.9.2021**\n- Mitattu koealat 8-11 ja 25-27.\n\n\n### HANNU1.01 Tornio\n\nTornion koillispuolella sijaitseva tutkimusmetsikkö (≈2 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2001, 2008 ja 2020. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 6.9.2001**\n- Mitattu kaikkien koealojen valtapuusto.\n\n**Puuston mittaus 20.-21.10.2008**\n- Puuston mittaus ylispuiden poiston jälkeen. Mitattu kaikkien koealojen alikasvos.\n\n**Puuston mittaus 25.-29.5.2020**\n- Mitattu kaikki koealat.\n\n\n### RUSKO1.01 Oulu\n\nOulun Ruskossa sijaitseva koemetsikkö (≈2 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2008 ja 2021. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 7.11.2008**\n- Mitattu kaikkien koealojen alikasvos.\n\n**Puuston mittaus 20.5.2021**\n- Mitattu kaikki koealat. Myös ylispuut.\n\n\n### AHTAA2.01 Raahe\n\nRaahen Vihannissa sijaitseva koemetsikkö (≈0,5 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2008. Koeasetelmana 6 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 13.-17.11.2008**\n- Mitattu kaikki koealat. Koealoilta mitattu kaikki alikasvoskuuset ja -männyt.\n\n\n### OTANNEVA1 Kajaani\n\n Kajaanin Otanmäessä sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2018. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 8.10.-8.11.2018**\n- Mitattu kaikki koealat.\n\n\n### OTANNEVA2 Kajaani\n\nKajaanin Otanmäessä sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2020. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 29.9.-9.10.2020**\n- Mitattu kaikki koealat.\n\n\n### MUSTIKKA1 Pyhäntä\n\nPyhännällä sijaitseva koemetsikkö (≈2 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2021. Koeasetelmana 9 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 22.10.2021**\n- Mitattu kaikki koealat.\n\n\n### MUSTIKKA2 Pyhäntä\n\n Pyhännällä sijaitseva koemetsikkö (≈3 ha).\n\n#### Puuston mittaukset\n\nPuusto on mitattu 2022. Koeasetelmana 12 puustokoealaa puustotilavuuden muutoksen mittaukseen eri lannoituskäsittelyjen kesken.\n\n**Puuston mittaus 11.11.2022**\n- Mitattu kaikki koealat.\n\n\n\n\n##### ______________________________________________________________________________________________________________________ \n\n### Aineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.\n\n### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm), yläläpimitta ilmoitetulta korkeudelta(mm), tuoreoksaraja(dm, kuivaoksaraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
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"fi": "# Ränskälänkorpi\n\nRänskälänkorven tutkimusinfrastruktuuri (≈25 ha) sijaitsee Etelä-Suomessa, Asikkalassa. Kohteella tutkitaan jatkuvapeitteisen ja avohakkuisiin perustuvan metsänkäsittelyn vaikutusta puuston kehitykseen, vesitalouteen sekä ojitetun suometsäekosysteemin ja ilmakehän väliseen kasvihuonekaasujen vaihtoon boreaalisella kasvillisuusvyöhykkeellä.\n\n\nPuuston mittauksia kohteella on tehty vuosina 2019, 2020, 2021 ja 2024. \n\n### Puuston mittaukset:\n\n**Puusto mitattu 4.-15.7.2019**\n-\tMitattu linjat 1 (koealat 11-15), 2 (koealat 21-25), 3 (koealat 31-35), 4 (koealat 41-45) ja 5 (koealat 51-55)\n\n**Puusto mitattu 4.-8.5.2020**\n-\tMitattu EC-koeala (sisältää koealan 61), avohakkuu (koealat 1-6) sekä linjat 6 (koealat 62-65), 7 (koealat 71-74) ja 8 (koealat 81-84)\n\n**Puusto mitattu osittaishakkuiden jälkeen 18.-19.5.2021**\n-\tMitattu EC-koeala (sisältää koealan 61) sekä linjat 1(koealat 11-15), 5(koealat 51-55), 6(koealat 62-65), 7(koealat 71-74) ja 8(koealat 81-84)\n-\tMitattu hakkuusta jäljelle jääneet puut\n-\tPituus ja latvusraja mitattu vain EC-koealalta\n\n**Puusto mitattu 21.-24.10.2024**\n-\tMitattu EC-koeala (sisältää koealan 61) sekä linjat 1 (koealat 11-15), 2 (koealat 21-25), 3 (koealat 31-35), 4 (koealat 41-45) ja 5 (koealat 51-55), 6(koealat 62-65), 7(koealat 71-73) ja 8(koealat 81-84)\n-\tKoealat 85 ja 74 poistettu, koska ne ovat kartasta poiketen mittausalueiden ulkopuolelta. Koeala 55 mitattiin, vaikka sitä ei ole hakattu. \n-\tKaikki yli rinnankorkeuden kasvaneet havupuut on otettu uusina puina mukaan. Uusien koivujen läpimittarajana oli 10 mm.\n\n\n**Aineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.**\n\n#### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
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"en": "The experiment aims to detect the impacts of tree stand cuttings on carbon and nutrient dynamics. Pools of C and nutrients before and 3, 5, and 10 years after cutting are measured in the tree stand, other vegetation, and surface peat soil. Also CO2, methane, and N2O fluxes, decomposition rates of various kinds of litter,as well as environmental factors such as PAR, air and soil T, precipitation, and soil moisture are monitored to enable modeling of carbon and nutrient balance.",
"fi": "Kokeissa selvitetään hiilen ja eri ravinteiden dynamiikkaa suo- ja suometsäekosysteemeissä (CRAVSUO), ja useissa kokeissa hakkuun tai muiden ympäristömuutosten vaikutuksia niihin. Puustosta, kasvillisuudesta sekä kasvupaikan aktiivisesta pintaosasta selvitetään hiilen ja ravinteiden varastot (ja niiden muutokset mahdollisen hakkuun jälkeen). Lisäksi mitataan orgaanisen aineksen hajotukseen liittyviä kaasuvirtauksia, eri kariketyyppien hajotusnopeutta ja hajotukseen liittyvää karikedynamiikkaa sekä kasvupaikan ravinnevarastomuutoksia. Useilla kokeilla toimitaan yhteistyössä Ilmatieteenlaitoksen (kasvihuonekaasumittaukset eddy covariance -menetelmällä, meteorologiset havainnot) ja Helsingin yliopiston kanssa.\n\n\n\n## LETTOSUO Tammela\n\nLettosuon tutkimusmetsikkö (≈65 ha) sijaitsee Etelä-Suomessa, Tammelassa. Kohteella tutkitaan jatkuvapeitteisen ja avohakkuisiin perustuvan metsänkäsittelyn vaikutusta puuston kehitykseen, vesitalouteen sekä ojitetun suometsäekosysteemin ja ilmakehän väliseen kasvihuonekaasujen vaihtoon boreaalisella kasvillisuusvyöhykkeellä.\n\nKohteella mitataan intensiivisesti kasvihuonekaasupäästöjä ja määritetään hiilitaseen eri komponentteja sekä maaperästä että koko ekosysteemitasolla. Lisäksi mitataan maaperän hydrologisia tunnuksia, puuston ja pintakasvillisuuden haihduntaa, puuston sekä kasvillisuuden kasvua ja muutoksia sekä vedenlaatua ja miten hakkuut vaikuttavat niihin. Alueen seuranta aloitettiin vuonna 2009 ja kummankin hakkuukäsittelyn mukainen puunkorjuu toteutettiin helmi-maaliskuussa 2016.\n\nKohteella tutkimusta suorittavat yhteistyössä Ilmatieteen laitos, Luonnonvarakeskus ja Helsingin Yliopiston Metsätieteiden laitos. Lettosuo on osa ICOS-verkostoa (Associated Ecosystem Station).\n\nTieteellisiä artikkeleita ja lisätietoa \"Tunnisteet ja tapahtumat\" -välilehden alta.\n\n \n\n\n\n### Puuston mittaukset\n\nPuusto on mitattu 2014, 2016, 2020 ja 2024. Koeasetelmana 40 puustokoealaa puustotilavuuden ja biomassan muutoksen mittaukseen säteittäisillä linjoilla keskellä olevasta eddy covariance -mittaustornista 200m etäisyydelle.\n\n**Puuston mittaus 15.10.2014**\n- Mitattu kaikki koealat.\n- Puuston mittauksessa ei lainkaan pituuskoepuita. Aineiston käsittelyssä mahdollista käyttää myöhempien mittausten pituuskoepuita.\n\n**Puuston mittaus 15.5.2016**\n- Puuston mittaus hakkuun jälkeen tehty vain harvennetuille koealoille.\n\n**Puuston mittaus 20.10.2020**\n- Mitattu kaikki koealat.\n\n**Puuston mittaus 30.10.2024**\n- Mitattu kaikki koealat.\n\n\n##### ______________________________________________________________________________________________________________________ \n\n## VESIJRAVD Vesijako\n\nPadasjoen Vesijaon tutkimusmetsiin kuuluva koemetsikkö (≈2 ha), jossa tutkitaan harvennuksen ja avohakkuun vaikutusta hiilen ja ravinteiden kiertoon ojitetulla rämeellä. Kohteella on tehty puustomittausten lisäksi kasvihuonekaasujen mittauksia kannettavalla analysaattorilla, turve- ja karikenäytteenottoja sekä kasvillisuuskartoitus.\n\n### Puuston mittaukset\n\nPuusto on mitattu 2001, 2004 ja 2020.\n\n**Puuston mittaus 13.11.2001-17.1.2002**\n- Mitattu koealat 1, 1a, 1b, 2, 3, 4 ja 7.\n\n**Puuston mittaus 15.10.2004-21.10.2004**\n- Mitattu koealat 1, 1a, 1b, 2 ja 3.\n\n**Puuston mittaus 27.8.2020**\n- Mitattu aikaisempia mittauksia pienemmät ympyräkoealat koealoista 1, 2, ja 4.\n\n##### ______________________________________________________________________________________________________________________ \n\n### Aineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.\n\n### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
},
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{
"id": "9c2c445d-5aa2-4ada-9529-f5e74bcec131",
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"en": "Set-up and instrumentation of the greenhouse gas measurements on experimental sites of continuous cover forestry"
},
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"en": "A set of experimental study sites was established to monitor greenhouse gas (GHG) emissions from drained peatland forests under different harvesting regimes in Finland. The purpose of these experimental sites is to study the effects of continuous cover forestry (CCF) and clear-cutting (CC) on ecosystem processes including GHG emissions and stand development on drained peatland forests. The sites represent fertile Norway spruce dominated peatland forests, where soil GHG emissions are high due to drainage that has exposed peat to decomposition in aerobic conditions. Two “flagship” sites for greenhouse gas (GHG) monitoring have been established and instrumented by the Natural Resources Institute Finland (Luke), University of Helsinki (UH) and the Finnish Meteorological Institute (FMI). The sites host continuous GHG monitoring with Eddy Covariance (EC) towers and with automatic chambers. In addition, greenhouse gas (CO2, CH4, and N2O) emissions are monitored with manually operated chambers at four sites, where effects of selection (CCF) harvests are studied with replicated treatments. These data will be used to calculate the ecosystem and soil GHG balances of the sites by using methodologies standardized earlier and compatible with the IPCC guidelines. On all experimental sites, ground water table (WT), tree growth and regeneration are monitored in different management trials. These data will form the basic data needed for designing and demonstrating optimal harvesting cycles and evaluating and generalizing the climate impacts. The results including the biological drainage capacity (evapotranspiration) of different-sized tree stands as well as the soil GHG balance of different tree stand – WT combinations will be incorporated into existing models that can be used to estimate the mitigation obtained with different management options and in different site and climatic conditions. The study sites are actively used for training and demonstration of alternative peatland management practices by host projects and by multiple stakeholders. The host projects and organizations also promote further extensions for the measurements and all complementary research activities are welcome to these study sites."
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"en": "Leppä, Korkiakoski, Nieminen, Laiho, Hotanen, Kieloaho, Korpela, Laurila, Lohila, Minkkinen, Mäkipää, Ojanen, Pearson, Penttilä, Tuovinen, Launiainen: Vegetation controls of water and energy balance of a drained peatland forest: Responses to alternative harvesting practices",
"fi": "Leppä, Korkiakoski, Nieminen, Laiho, Hotanen, Kieloaho, Korpela, Laurila, Lohila, Minkkinen, Mäkipää, Ojanen, Pearson, Penttilä, Tuovinen, Launiainen: Vegetation controls of water and energy balance of a drained peatland forest: Responses to alternative harvesting practices"
},
"description": {
"fi": "Abstract. We quantified the response of peatland water table level (WTL) and energy fluxes to harvesting of a drained peatland forest. Two alternative harvests (clear-cut and partial harvest) were carried out in a mixed-species ditch-drained peatland forest in southern Finland, where water and energy balance components were monitored for six pre-treatment and three post-treatment growing seasons. To explore the responses caused by harvestings, we applied a mechanistic multi-layer soil-plant-atmosphere transfer model. At the clear-cut site, the mean growing season WTL rose by 0.18 ± 0.02 m (error estimate based on measurement uncertainty), while net radiation, and sensible and latent heat fluxes decreased after harvest. On the contrary, we observed only minor changes in energy fluxes and mean WTL (0.05 ± 0.03 m increase) at the partial harvest site, although as much as 70% of the stand basal area was removed and leaf-area index was reduced to half. The small changes were mainly explained by increased water use of spruce undergrowth and field layer vegetation, as well as increased forest floor evaporation. The rapid establishment of field layer vegetation had a significant role in energy balance recovery at the clear-cut site. At partial harvest, chlorophyll fluorescence measurements and model-data comparison suggested the shade-adapted spruce undergrowth was suffering from light stress during the first post-harvest growing season. We conclude that in addition to stand basal area, species composition and stand structure need to be considered when controlling WTL in peatland forests with partial harvesting. Our results have important implications on the operational use of continuous cover forestry on drained peatlands. A continuously maintained tree cover with significant evapotranspiration capacity could enable optimizing WTL from both tree growth and environmental perspectives."
},
"entity_identifier": "https://doi.org/10.1016/j.agrformet.2020.108198",
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"en": "Rautakoski, Korkiakoski, Mäkelä, Koskinen, Minkkinen, Aurela, Ojanen, Lohila: Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data",
"fi": "Rautakoski, Korkiakoski, Mäkelä, Koskinen, Minkkinen, Aurela, Ojanen, Lohila: Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data"
},
"description": {
"en": "<jats:p>Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.\n </jats:p>",
"fi": "Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.",
"und": "<jats:p>Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.\n </jats:p>"
},
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"en": "Korkiakoski, Ojanen, Tuovinen, Minkkinen, Nevalainen, Penttilä, Aurela, Laurila, Lohila: Partial cutting of a boreal nutrient-rich peatland forest causes radically less short-term on-site CO2 emissions than clear-cutting",
"fi": "Korkiakoski, Ojanen, Tuovinen, Minkkinen, Nevalainen, Penttilä, Aurela, Laurila, Lohila: Partial cutting of a boreal nutrient-rich peatland forest causes radically less short-term on-site CO2 emissions than clear-cutting"
},
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"fi": "Abstract. Wide-spread harvesting of forests growing on drained peatlands is foreseen to take place in Finland in the near future. A hot question is if continuous cover forestry utilizing partial cuttings could be used to mitigate carbon dioxide (CO2) emissions and the consequent climatic impact compared to traditional clear-cutting and even-aged forest management. To assess the impact of clear-cutting vs. partial cutting, we first measured CO2 exchange with the eddy covariance (EC) method for six years in a mature, nutrient-rich peatland forest in southern Finland. Part of the forest was then partially cut (74% of the stem volume), and part of it was clear-cut, and CO2 exchange of both areas was measured for another six years. Tree growth was recorded before and after the cuttings to separate the contributions of tree stand and forest floor to CO2 exchange. Before the cuttings, the site had an annual CO2 exchange close to zero, but both cutting methods turned it into a CO2 source. However, the first-year emissions from the partial cutting area (800 g CO2 m−2 yr−1) were markedly lower than the emissions after clear-cutting (3100 g CO2 m−2 yr−1). The partial cutting area remained a CO2 source during the first three years but turned into a CO2 sink after that, while the clear-cut area acted as a large, although diminishing, CO2 source for the whole measurement period. The total six-year CO2 balances before and after partial cutting did not differ significantly, while the emissions after clear-cutting were on average 2240 g CO2 m−2 yr−1 larger than before it. Combining the EC data with the tree growth measurements showed that the forest floor was losing C both before and after harvestings. In conclusion, partial cutting resulted in clearly smaller CO2 emissions than clear-cutting at least in the short term."
},
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"en": "Rautakoski, Korkiakoski, Mäkelä, Koskinen, Minkkinen, Aurela, Ojanen, Lohila: Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data",
"fi": "Rautakoski, Korkiakoski, Mäkelä, Koskinen, Minkkinen, Aurela, Ojanen, Lohila: Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data"
},
"description": {
"en": "<jats:p>Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.\n </jats:p>",
"fi": "Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.",
"und": "<jats:p>Abstract. The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A Random forest with conditional inference trees was used to find immediate and time-lagged relationships between N2O flux and environmental conditions across seasons and years with different environmental conditions. The temporal variation of N2O flux was large, and the daily mean flux varied between –11 and 1760 µg N2O m⁻² h⁻¹. Three of the six measurement chambers had a maximum N2O flux of less than 400 µg N2O m⁻² h⁻¹, while the fluxes in the other three chambers exceeded 1000 µg N2O m⁻² h⁻¹. Spatial differences in the flux persisted over time, and despite the high small-scale spatial variability, the temporal patterns of the fluxes were relatively similar across the chambers. Soil moisture as well as air and soil surface temperature were the most important variables in the random forest, with lagged soil moisture also considered important. N2O flux responded to soil wetting with a time lag of 1–7 days, but the length of the time lag varied spatially and between seasons indicating interactions with other spatially and temporally variable environmental conditions. The high temporal variation in N2O flux was related to a) seasonally variable environmental conditions, with the highest N2O fluxes measured after summer dry-wet cycles and winter soil freezing, and b) to annually variable seasonal weather conditions, which lead to high year-to-year variability in N2O budget. Changes especially in the frequency of summer precipitation events and in winter temperature and snow conditions may increase the variability of annual N2O emissions if the variability in summer and winter weather conditions increases due to climate change.\n </jats:p>"
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"fi": "Aineistossa (SVESITASE) on seurattu pieniä valuma-alueita, jotka on perustettu ojitetuille rämeille. Rovaniemellä on 2 koetta (Sattasuo ja Koiraoja) ja sen lisäksi on viisi muuta koetta (Muhos, Sievi, Parkano, Mänttä-Vilppula ja Tuusula). Koekohteilla on tehty 2006-2007 kaksinkertainen ojitus, jossa ulommalla ojalla estetään ulkopuolisten vesien pääsy alueelle ja toisaalta sisempää ojaa pitkin alueelta kertyvä valumavesi kulkeutuu mittapadon kautta ulos. Valuma-alueen muodostaa käytännössä yksi sarka. Pinta-ala vaihtelee kohteen mukaan 0,5 – 4 ha. Rovaniemen Sattasuolla, Vilppulan Jaakkoinsuolla ja Tuusulan Katilassa on ollut yksi valuma-alue seurannassa. Muilla kohteilla on ollut 2-3 valuma-aluetta seurannassa. Intensiivisintä seurantaa on tehty 2006 – 2015. Valuma-alueilla on mitattu seuraavia tietoja:\n-\tPohjaveden syvyyttä kasvukaudella, 30 – 50 pohjavesiputken hila, manuaalimittaukset ja joillakin alueilla myös yksi dataloggeri\n-\tValuntamittaukset mittapadolla: Rovaniemen Sattasuolla, Vilppulassa ja Tuusulassa mittakaivo, jossa dataloggeri valunnan jatkuvaan seurantaan, muualla valuntaa mitattu mittauskampanjoin\n-\tOjaveden korkeutta manuaalimittauksin \n-\tMetsikkösadantaa sadesuppiloilla\n-\tLumen paksuutta\n-\tSääasema Rovaniemen Sattasuolla ja Vilppulassa\n-\tPuutason haihduntaa Granier-menetelmällä Rovaniemen Sattasuon kokeella ja Vilppulassa (josta huono data)\n-\tTurpeen vedenläpäisevyys, turpeen paksuus, turpeen laatu\n-\tPuuston kartoitusmittaus koko valuma-alueella (joillakin lisäksi xyz-tarkkuuspaikannus)\n-\tPuustomittaukset, katso alla\n-\tPuuston neulasten ravinnepitoisuus useana vuonna\n-\tKokeista lopetettu Tuusula, Vilppula ja Parkano 2017-2018, Rovaniemen Koiraojan koe 2022 (muutettu eri käyttöön keväällä 2025)\n-\tSievissä tehty harvennushakkuu toisella valuma-alueella keväällä 2009 ja Muhoksella samoin toisella valuma-alueella keväällä 2010. Kummatkin harvennetut valuma-alueet on tuhkalannoitettu (5t/ha) keväällä 2014.\n-\tPohjavesi- ja puustomittauksia jatkettu Muhoksella ja Sievissä 2024 saakka\n\n**Puustonmittauksia alueille tehty seuraavasti:**\n\n**SATTASUO Rovaniemi**\n- 1.9.2009 ja 17.10.2018\n\n**KOIRASUO Rovaniemi**\n- 29.5.2007, 15.6.2009 (koeala 3), 1.7.2010 (koeala 2), 30.5.2016 (koeala 2) ja 27.9.2023\n\n**NEVAJÄRVI Sievi**\n- 2.5.2006, 2.5.2009 (koeala 2), 9.6.2011, 7.10.2014 (koealojen osittainen mittaus), 8.5.2019 ja 6.10.2023\n\n**KIIMAKEI Parkano**\n- 18.12.2006, 10.5.2010 (koeala 3) ja 8.3.2017\n\n**JAAKKOINS Mänttä-Vilppula**\n- 1.4.2006 ja 6.5.2011\n\n**KATILA Tuusula**\n- 6.11.2006 ja 4.6.2013\n\n**ANSASAARI Muhos**\n- 1.8.2007, 1.6.2010 (koeala 1), 1.9.2014 (koealojen osittainen mittaus), 3.5.2019 ja 8.9.2023\n\n\n**Puustonmittausaineistot ovat Excel-pohjaisia 20- ja 71-lomakkeita.**\n\n#### Tärkeimmät tallennetut muuttujat:\n\ntietuetunnus(20, 71), kokeen numero, mittauskerta, koealan numero, koealan pinta-ala(neliömetri), mittausajankohta(vuosi, kuukausi, päivä), puun numero, konepiste(mittauspiste koealan sisällä, -5--10), suunta(0-360), etäisyys(cm), puulaji(1-9), puujakso(0-3), puustoryhmä(1-4), läpimitta rinnankorkeudelta(mm), latvuskerros(1-6), tekninen laatu(1-9), tuhon ilmiasu(0-8), tuhon syy(0-13), tuhon aste (0-3), koepuukoodi(0-3), puun pituus(dm), puun latvusraja(dm).\n\nAineiston keruussa ja tallennuksessa noudatetut standardit ja menetelmäohjeet: Metsikkökokeiden maastotyöohjeet"
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"metadata_repository": "Fairdata"
}
]
}