de: Datenstruktur auf Englisch

en: Data cube in German

de: Hotellerie nach Jahr, Kennzahl, Herkunftsland und Monat

en: Hotels and similar accommodation by Year, Key figure, Country of residence and Month

tourism

display_name: tourism

tourismus

display_name: tourismus

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Hotellerie - Gästeankünfte und Logiernächte nach Herkunftsland und Monat seit 2008

en: Hotels and similar accommodation – Arrivals and nights spent by country of residence and month since 2008


state: active

type: dataset

de: Datenwürfel auf Englisch

en: Data cube in English

media_type: text/html

format: HTML

de: Datenwürfel auf Deutsch

en: Data structure in English

media_type: application/json

format: JSON

de: Datenstruktur auf Deutsch

en: Data structure in German

de: Lebendgeburten bei Staatsbürgerschaft des Vaters und Jahr

en: Live births by Father's citizenship and Year

births-deaths

display_name: births-deaths

geburten-todesfalle

display_name: geburten-todesfalle

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

political_level: other

liechtenstein

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: DCAT Harvester Amt für Statistik FL

de: Lebendgeborene nach Staatsbürgerschaft des Vaters seit 1999

en: Live births by fathers citizenship since 1999


de: Einzelbasis - Zinsertrag und -aufwand nach Jahr, Zinsertrag / -aufwand und Liechtenstein / natürliche Personen in Liechtenstein

en: Individual basis - Interest income and expense by Year, Interest income / expense and Liechtenstein / natural persons in Liechtenstein

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

fr: Économie et finances

it: Economia e finanze

de: Einzelbasis - Zinsertrag und -aufwand in Liechtenstein seit 2017

en: Individual basis - Interest income and expense in Liechtenstein since 2017


de: Abschlüsse von Studierenden aus Liechtenstein an Universitäten nach Jahr, Studienland, Fächergruppe, Geschlecht und Exemensstufe

en: Graduates form Liechtenstein at universities by Year, Country of study, Fields of study, Sex and Level of graduation

hochschulen

display_name: hochschulen

tertiary-education

display_name: tertiary-education

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: Abschlüsse von Studierenden aus Liechtenstein an Universitäten nach Examensstufe, Fächergruppe, Studienland und Geschlecht seit 2014

en: Graduates from Liechtenstein at universities by level of graduation, fields of study, country of study and sex since 2014


en: Data cube in German

de: Datenstruktur auf Englisch

de: Kennzahlen und Resultate der Abstimmungen auf Landesebene bei Abstimmung, Gemeinde und Kennzahl

en: Key figures and results of referendums on national level by Referendum, Municipality and Key figure

elections-referendums

display_name: elections-referendums

wahlen-abstimmungen

display_name: wahlen-abstimmungen

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

de: Kennzahlen und Resultate der Abstimmungen auf Landesebene nach Abstimmung und Gemeinde seit 1919

en: Key figures and results of referendums at national level, by referendum, municipality and key figure since 1919


en: Data cube in English

de: Erwerbstätige Bevölkerung nach Stichtag, Verkehrsmittelkombinationen und Wohngemeinde

en: Population in gainful employment by Reference date, Combinations of means of transport and Municipality of residence

passenger-transport

display_name: passenger-transport

personenverkehr

display_name: personenverkehr

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Erwerbstätige Bevölkerung nach Verkehrsmittelkombination für den Arbeitsweg und Wohngemeinde

en: Population in gainful employment by combination of means of transport to work and municipality of residence


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Datenwürfel auf Deutsch

de: Datenwürfel auf Englisch

en: Data structure in English

de: Alle Beherbergungsarten nach Jahr, Kennzahl, Region, Betriebsstandort und Monat

en: All types of accommodation by Year, Key figure, Region, Place of establishment and Month

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Alle Beherbergungsarten - Gästeankünfte, Logiernächte und Aufenthaltsdauer nach Region, Betriebsstandort und Monat seit 2012

en: All types of accommodation - Arrivals, nights spent and length of stay by region, place of establishment and month since 2012


de: Internationale Indikatoren der öffentlichen Finanzen nach Jahr und Indikator/ Quote

en: Public finance indicators by Year and Indicator/ Ratio

offentliche-finanzen

display_name: offentliche-finanzen

public-finance

display_name: public-finance

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Internationale Indikatoren der öffentlichen Finanzen seit 2011

en: Public finances indicators since 2011


en: Data cube in German

de: Datenstruktur auf Englisch

de: Verlust des Landesbürgerrechts durch ausdrücklichen Verzicht nach Jahr, Wohnsitz und Altersklasse

en: Loss of national citizenship through explicit renunciation by Year, Residence and Age group

einburgerungen

display_name: einburgerungen

naturalisations

display_name: naturalisations

soci

de: Bevölkerung und Gesellschaft

en: Population and society

intr

fr: Questions internationales

de: Internationale Themen

en: International issues

it: Tematiche internazionali

de: Verlust des Landesbürgerrechts durch ausdrücklichen Verzicht nach Wohnsitz und Altersklassen seit 2008

en: Loss of national citizenship through explicit renunciation by residence and age group since 2008


en: Data cube in English

de: Einkommen (Privathaushalte) bei Jahr, Haushaltsgrösse, Einkommen und Kennzahl

en: Income (private households) by Year, Household size, Income and Key figure

vermogens--und-einkommensverteilung

display_name: vermogens--und-einkommensverteilung

wealth-and-income-distribution

display_name: wealth-and-income-distribution

de: Einkommen (Privathaushalte) nach Haushaltsgrösse seit 2020

en: Income (private households) by households size since 2020


en: Data structure in German

de: Lebendgeborene bei Jahr, Kennzahl, Geschlecht und Wohngemeinde

en: Live births by Year, Indicator, Sex and Municipality

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Lebendgeborene nach Geschlecht und Wohngemeinde der Mutter seit 1999

en: Live births by sex and municipality of residence of the mother since 1999


en: Data structure in English

de: Datenwürfel auf Englisch

de: Datenwürfel auf Deutsch

de: Datenstruktur auf Deutsch

de: Wegpendelnde nach Jahr, Voll-/ Teilzeit, Wirtschaftszweig, Altersklasse und Geschlecht

en: Outward commuters by Year, Part-/ full-time, Economic activity, Age group and Sex

erwerbstatigkeit

display_name: erwerbstatigkeit

population-in-gainful-employment

display_name: population-in-gainful-employment

econ

en: Economy and finance

de: Wegpendelnde nach Voll-/ Teilzeit, Wirtschaftszweig, Altersklasse und Geschlecht seit 2008

en: Outward commuters by part-/ full-time, economic activity, age group and sex since 2008


de: Vermögensbilanz Staat nach Jahr, Bilanzposition, Teilsektor und Institutionelle Einheit

en: Government balance sheet by Year, Balance sheet item, Subsectur and Institutional unit

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Vermögensbilanz Staat nach Bilanzposition, Teilsektor und institutionelle Einheit seit 2011

en: Government balance sheet by balance sheet item, subsector and institutional unit since 2011


en: Data cube in German

de: Datenstruktur auf Englisch

de: Eintragungen und Auflösungen von Partnerschaften bei Jahr, Geschlecht, Partnerschaften und Kennzahl

en: Registrations and dissolutions of partnerships by Year, Sex, Partnerships and Indicator

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Eintragungen und Auflösungen von Partnerschaften seit 2011

en: Registrations and dissolutions of partnerships since 2011


en: Data cube in English

de: Privathaushalte bei Jahr, Haushaltsgrösse, Einkommen und Einkommensklasse

en: Private households by Year, Household size, Income and Income category

de: Privathaushalte nach Einkommensklasse und Haushaltsgrösse seit 2020

en: Private households by Income category and household size since 2020


en: Data structure in German

de: 463.003 Betriebsrechnung bei Jahr, Kennzahl und Versicherungszweig

accident-insurers

display_name: accident-insurers

unfallversicherer

display_name: unfallversicherer

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

econ

de: Wirtschaft und Finanzen

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: 463.003 Betriebsrechnung in CHF nach Bilanzposition und Versicherungszweig seit 2005


de: Datenstruktur auf Deutsch

de: Datenwürfel auf Deutsch

de: Datenwürfel auf Englisch

en: Data structure in English

de: Erstzugelassene Fahrzeuge bei Jahr, Fahrzeuggruppe/-art und Gemeinde

en: Vehicles registered for the first time by Year, Vehicle group/ type and Municipality

fahrzeug-erstzulassungen

display_name: fahrzeug-erstzulassungen

mobility-and-transport

display_name: mobility-and-transport

tran

de: Verkehr

en: Transport

de: Erstzugelassene Fahrzeuge nach Fahrzeuggruppe/-art und Gemeinde

en: Vehicles registered for the first time by vehicle group/ type and municipality


de: Datenstruktur auf Englisch

de: Einbürgerungen nach Jahr, Wohnsitz und Einbürgerungsart nach Jahr, Wohnsitz und Einbürgerungsart

en: Naturalisations by Year, Residence and Type of naturalisation by Year, Residence and Type of naturalisation

intr

de: Internationale Themen

en: International issues

amt-fuer-statistik-fl

de: Amt für Statistik

de: Einbürgerungen nach Einbürgerungsart und Wohnsitz seit 1970

en: Naturalisations by type of naturalisation and place of residence since 1970


de: 463.007 Rentenzahlungen bei Jahr, Versicherungszweig, Rentenart und Rententeil

econ

en: Economy and finance

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: 463.007 Rentenzahlungen nach Versicherungszweig, Rentenart und Rententeil seit 2005


en: Data cube in German

de: Hauptaggregate und -indikatoren der VGR 1998 - 2013 by Jahr and Aggregat / Indikator

en: Main aggregates and main indicators of national accounts 1998 - 2013 by Year and Aggregate / indicator

national-accounts

display_name: national-accounts

volkswirtschaftliche-gesamtrechnungen

display_name: volkswirtschaftliche-gesamtrechnungen


en: Data cube in English

de: Einzelbasis - Zinskonditionen (Jahresdurchschnitt) nach Jahr und Kredit / Anlage

en: Individual basis - Interest rate conditions (annual average) by Year and Loan / Investment

banking-interests

display_name: banking-interests

bankzinsen

display_name: bankzinsen

econ

de: Wirtschaft und Finanzen

de: Einzelbasis - Zinskonditionen (Jahresdurchschnitt) für die Aufnahme von Krediten und die Anlage von Geldern in CHF in Liechtenstein seit 1980

en: Individual basis - Interest rate conditions (annual average) for borrowing and investing funds in CHF in Liechtenstein since 1980


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Einnahmen und Ausgaben Staat nach Jahr, Art, Teilsektor und Institutionelle Einheit

en: Government revenue and expenditure by Year, Kind, Subsector and Institutional unit

offentliche-finanzen

display_name: offentliche-finanzen

public-finance

display_name: public-finance

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Einnahmen und Ausgaben Staat nach Art, Teilsektor und institutionelle Einheit seit 2011

en: Government revenue and expenditure by kind, subsector and institutional unit since 2011


de: Datenwürfel auf Englisch

en: Data structure in English

de: Datenwürfel auf Deutsch

de: Bauprojekte nach Bewilligungsjahr, Art der Arbeiten, Kategorie der Bauwerke und Gemeinde

en: Construction projects by Year of approval, Type of work, Building categories and Municipality

bautatigkeit

display_name: bautatigkeit

construction-activity

display_name: construction-activity

de: Bauprojekte nach Kategorie der Bauwerke, Art der Arbeiten und Gemeinde seit 2010

en: Construction projects type of work, building category and municipality since 2010


de: Datenstruktur auf Englisch

de: Migration bei Jahr, Richtung, Staatsbürgerschaft, Geschlecht und Altersklasse

en: Migration by Year, Direction, Citizenship, Sex and Age group by Year, Direction, Citizenship, Sex and Age group

migration-binnenwanderung

display_name: migration-binnenwanderung

migration-internal-migration

display_name: migration-internal-migration

soci

de: Bevölkerung und Gesellschaft

en: Population and society

intr

de: Internationale Themen

en: International issues

amt-fuer-statistik-fl

de: Amt für Statistik

de: Migration nach Richtung, Staatsbürgerschaft, Geschlecht und Altersklasse seit 2011

en: Migration by direction, citizenship and age group since 2011


de: Personenwagenbestand nach Stichtag, Hubraumklasse und Gemeinde

fahrzeugbestand

display_name: fahrzeugbestand

licensed-vehicles

display_name: licensed-vehicles

tran

de: Verkehr

en: Transport

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Personenwagenbestand nach Hubraumklasse und Gemeinde seit 2013


de: Datenstruktur auf Deutsch

en: Data cube in English

en: Data cube in German

de: Bauprojekte nach Bewilligungsjahr, Art der Arbeiten, Kategorie der Bauwerke und Kategorie der Auftraggeber

en: Construction projects by Year of approval, Type of work, Building categories and Client categories

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Bauprojekte nach Art der Arbeiten, Kategorie der Bauwerke und Kategorie der Auftraggeber seit 2010

en: Construction projects by type of work, building categories and client categories since 2010


en: Data structure in German

de: Datenwürfel auf Englisch

de: Gebäude nach Stichtag, Anzahl Wohneinheiten und Gemeinde

en: Buildings by Reference date, Number of housing units and Municipality

buildings-dwellings

display_name: buildings-dwellings

gebaude-wohnungen

display_name: gebaude-wohnungen

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Gebäude nach Anzahl Wohneinheiten und Gemeinde

en: Buildings by number of housing units and municipality


de: Datenstruktur auf Englisch

en: Data structure in English

de: Datenwürfel auf Deutsch

de: Erstzugelassene Anhänger bei Jahr, Fahrzeugart, Gesamtgewichtsklasse, Anzahl Achsen und Nutzlastklasse

en: Trailers registered for the first time by Year, Type of vehicle, Maximum gross weight class, Number of axles and Load weight class

de: Erstzugelassene Anhänger nach Fahrzeugart, Gesamtgewichtsklasse, Anzahl Achsen und Nutzlastklasse

en: Trailers registered for the first time by maximum gross weight class, number of axles and load weight class


de: Berufsunfallversicherung: Verteilung der Lohnsumme, Unfälle und Leistungen in % nach Jahr, Geschlecht (Anteil in %), Versicherungszweig (Anteil in %) und Kennwerte der Risikodaten (Anteil in %)

accident-insurers

display_name: accident-insurers

unfallversicherer

display_name: unfallversicherer

heal

de: Gesundheit

en: Health

de: Amt für Statistik

de: Berufsunfallversicherung: Verteilung der Lohnsumme, Unfälle und Leistungen in Prozent nach Versicherungszweig und Geschlecht seit 2005


de: Heiratende Personen bei Jahr, Geschlecht, Staatsbürgerschaft und Staatsbürgerschaft des Partners

en: Marrying persons by sex, citizenship and partner's citizenship by Year, Sex, Citizenship and Partner's citizenship

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

soci

de: Bevölkerung und Gesellschaft

en: Population and society

de: Heiratende Personen nach Geschlecht, Staatsbürgerschaft und Staatsbürgerschaft des Partners seit 1999

en: Marrying persons by sex, age group, citizenship and partners citizenship since 1999


de: Datenstruktur auf Deutsch

de: Ausgesteuerte Arbeitslose nach Jahr und Monat

en: Non-entitled unemployed persons by Year and Month

arbeitslosigkeit

display_name: arbeitslosigkeit

unemployment

display_name: unemployment

econ

de: Wirtschaft und Finanzen

amt-fuer-statistik-fl

en: Office of Statistics

de: Ausgesteuerte Arbeitslose nach Monat seit 2006

en: Non-entitled unemployed persons by month since 2006


en: Data cube in German

de: Nutztierhalter und Nutztierbestand nach Jahr, Kennzahl, Tierkategorie und Zone | Region

landwirtschaft

display_name: landwirtschaft

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Nutztierhalter und Nutztierbestände nach Tierkategorie, Zone und Region seit 2005


de: Datenwürfel auf Englisch

en: Data cube in English

de: Datenwürfel auf Deutsch

de: Datenstruktur auf Englisch

de: Erwerbstätige Bevölkerung nach Stichtag, Erwerbsstatus, Heimat, Geschlecht und Wohngemeinde

en: Population in gainful employment by Reference date, Status in employment, Citizenship, Sex and Municipality of residence

employment-structure

display_name: employment-structure

erwerbsstruktur-berufe

display_name: erwerbsstruktur-berufe

econ

en: Economy and finance

de: Erwerbstätige Bevölkerung nach Erwerbsstatus, Heimat, Geschlecht und Wohngemeinde

en: Population in gainful employment by status in employment, citizenship, sex and municipality of residence


en: Data structure in English

en: Data structure in German

de: Demografische Indikatoren nach Szenario, Kennzahl und Jahr

en: Demographic indicators by Scenario, Indicator and Year

bevolkerungsszenarien

display_name: bevolkerungsszenarien

population-scenarios

display_name: population-scenarios

amt-fuer-statistik-fl

de: Amt für Statistik

de: Demografische Indikatoren nach Szenario und Kennzahl von 2023 bis 2060

en: Demographic indicators by Scenario and Indicator from 2023 to 2060


de: Berufsunfallversicherung: Beschäftigte, Lohnsumme, Unfälle und Leistungen in % nach Jahr, Wirtschaftszweig und Kennwerte der Risikodaten

heal

de: Gesundheit

en: Health

de: Berufsunfallversicherung: Beschäftigte, Lohnsumme, Unfälle und Leistungen in % nach Wirtschaftszweig seit 2008


de: Datenstruktur auf Deutsch

de: Arbeitslose nach Jahr, Geschlecht, Heimat und Monat

en: Unemployed persons by Year, Sex, Citizenship and Month

econ

de: Wirtschaft und Finanzen

de: Arbeitslose nach Heimat, Geschlecht und Monat seit 2006

en: Unemployed persons by citizenship, sex and month since 2006


de: Kennzahlen der Luftqualität bei Jahr, Standort und Kennzahl

en: Key figures on air quality by Year, Location and Key figure

air-climate

display_name: air-climate

luft-klima

display_name: luft-klima

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Kennzahlen der Luftqualität nach Standort und Kennzahl seit 1990

en: Key figures on air quality by location and key figure since 1990


de: Datenwürfel auf Deutsch

en: Data cube in German

de: Motorräderbestand nach Stichtag, Hubraumklasse und Gemeinde

fahrzeugbestand

display_name: fahrzeugbestand

tran

de: Verkehr

en: Transport

en: Office of Statistics

de: Motorräderbestand nach Hubraumklasse und Gemeinde seit 2013


de: Datenwürfel auf Englisch

en: Data cube in English

de: Datenstruktur auf Englisch

de: Kennzahlen des Grundwassers bei Jahr, Standort und Kennzahl

en: Key figures on groundwater by Year, Location and Key figure

wasser

display_name: wasser

water

display_name: water

amt-fuer-statistik-fl

de: Amt für Statistik

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Kennzahlen des Grundwassers nach Standort und Kennzahl seit 1988

en: Key figures on groundwater by location and key figure since 1988


en: Data structure in English

de: Datenstruktur auf Deutsch

de: Obligatorische Krankenpflegeversicherung - Versicherte per 31. Dezember nach Jahr, Personengruppe und Geschlecht

en: Compulsory health care insurance - Insured persons as of December 31st by Year, Group of persons and Sex

health-insurers

display_name: health-insurers

krankenversicherer

display_name: krankenversicherer

heal

de: Gesundheit

econ

en: Economy and finance

de: Obligatorische Krankenpflegeversicherung - Versicherte per 31. Dezember nach Personengruppe seit 2001

en: Compulsory health care insurance - Insured persons as of December 31st by group of persons since 2001


en: Data structure in German

de: Kennzahlen der Vorsteherwahlen nach Jahr, Kennzahl und Gemeinde

en: Key figures on mayorial elections by Year, Key figure and Municipality by Year, Key figure and Municipality

elections-referendums

display_name: elections-referendums

wahlen-abstimmungen

display_name: wahlen-abstimmungen

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

de: Kennzahlen der Vorsteherwahlen nach Gemeinde seit 1975

en: Key figures on mayoral elections by municipality and political party since 1975


de: Landwirtschaftliche Förderleistungen nach Jahr, Beitragstyp und Kennzahl

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

econ

de: Wirtschaft und Finanzen

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Landwirtschaftliche Förderleistungen nach Beitragstyp seit 2010


de: Datenwürfel auf Deutsch

de: Datenwürfel auf Englisch

de: Strompreise für Haushalte und Kleingewerbe nach Stichtag, Tarif, Preiskategorie und Jährlicher Stromverbrauch

en: Electricity prices for households and small businesses by Reference date, Rate, Price category and Annual electricity consumption

energiepreise

display_name: energiepreise

energy-prices

display_name: energy-prices

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

de: Strompreise für Haushalte und Kleingewerbe nach Stichtag, Tarif, Preiskategorie und jährlicher Stromverbrauch von 2007 bis 2015

en: Electricity prices for households and small businesses by reference date, rate, price category and annual electricity consumption from 2007 to 2015


de: Datenstruktur auf Englisch

de: Datenstruktur auf Deutsch

en: Data cube in German

de: Bevölkerungsbewegung nach Jahr, Wohnsitz und Kennzahl bei Jahr, Wohnsitz und Kennzahl

en: Population change by Year, Place of residence and Key figure by Year, Place of residence and Key figure by Year, Place of residence and Key figure

bevolkerungsbewegung

display_name: bevolkerungsbewegung

population-change

display_name: population-change

soci

de: Bevölkerung und Gesellschaft

en: Population and society

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Bevölkerungsbewegung der ständigen Bevölkerung nach Wohnsitz seit 2011

en: Population change of the permanent population by place of residence since 2011


en: Data structure in English

en: Data cube in English

de: Luftqualitätsuntersuchung mit Flechten bei Jahr und Luftqualität

en: Air quality analysis with lichens by Year and Air quality

envi

de: Umwelt

en: Environment

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Luftqualitätsuntersuchung mit Flechten nach Luftqualität seit 1989

en: Air quality analysis with lichens by air quality since 1989


en: Data structure in German

de: Steuereinnahmen bei Rechnungsjahr und Steuerkategorie

en: Tax revenue by Fiscal year and Tax category

steuern-abgaben

display_name: steuern-abgaben

taxes-levies

display_name: taxes-levies

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

de: Steuereinnahmen nach Steuerkategorie und Rechnungsjahr seit 1998

en: Tax revenue by tax category and fiscal year since 1998


de: Datenwürfel auf Deutsch

de: Einzelbasis - Forderungen gegenüber Kunden und Hypothekarforderungen nach Jahr, Bilanzposition und Deckungsart

en: Individual basis - Claims against clients and mortgage loans by Year, Balance sheet item and Type of collateral

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

de: Wirtschaft und Finanzen

en: Economy and finance

amt-fuer-statistik-fl

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

de: Einzelbasis - Forderungen gegenüber Kunden und Hypothekarforderungen nach Deckungsart seit 2017

en: Individual basis - Claims against clients and mortgage loans by type of collateral since 2017


en: Data cube in German

de: Datenstruktur auf Englisch

de: Datenwürfel auf Englisch

de: Scheidende Personen bei Jahr, Geschlecht und Altersklasse

en: Divorcing persons by Year, Sex and Age group

ehen-partnerschaften

display_name: ehen-partnerschaften

marriages-partnerships

display_name: marriages-partnerships

de: Scheidende Personen nach Geschlecht und Altersklasse seit 1999

en: Divorcing persons by sex and age group since 1999


de: Datenstruktur auf Deutsch

de: Erwerbstätige ständige Bevölkerung nach Jahr, Wirtschaftszweig, Heimat, Stellung im Beruf und Geschlecht

en: Permanent resident population in gainful employment by Year, Economic activity, Citizenship, Occupational status and Sex

erwerbstatigkeit

display_name: erwerbstatigkeit

population-in-gainful-employment

display_name: population-in-gainful-employment

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

de: Erwerbstätige ständige Bevölkerung nach Wirtschaftszweig, Heimat, Stellung im Beruf und Geschlecht seit 2006

en: Permanent resident population in gainful employment by economic activity, citizenship, occupational status and sex since 2006


maintainer: Anita C. Risch

en: non-native-plant weed-management grassland native-plant herbivory

en: Correction: Data file native and non-native plant interactions in Australian grasslands

en:
taxa tab:	list and overview of all the recorded species

* family:                 family of the plant

* genus:                genus of the plant

* species:                plant species name

* origin:                indicates whether the plant is native to Australia or not (non-native)

* common name:	        common name of the plant species

* functional group:	        functional group of the plant species: forb, graminoid, fern, tree

* functional group detailed:	gives more detail about the type of graminoid and forb: legume, forb (non-leguminous),
                        grass, sedge, rush, fern, tree

* lifeform:                annual or perennial lifeform (species which can have both of these lifeforms where
                        considered as annuals)

plot tab:	list of species found in each plot and their cover (%)

* sampling.session:        provides information about the sampling time:
                        May2020 = data that was collected in May 2020
                        Nov2020 = data that was collected in November 2020

* farm.name:	            name of the farms where the sampling took place:
                        SF = farm of the Southern group
                        NF = farm of the Northern group
                        numbers 1-3 = randomly allocated to the Southern group of farms
                        numbers 4-6 = randomly allocated to the Northern group of farms

* site.type:	                KG: Kangaroo grass dominated site
                        ALG: ALG+KG site (Kangarooo grass and African lovegrass co-dominated site)

* plot.no:                plot number: 9-12

* scientific.name:	        scientific name of the plant species found in a certain plot

* functional group:	        indicates whether the species found is a tree, forb, graminoid or fern

* functional group detailed:	indicates whether the species found is a tree, legume, forb (non-leguminous),
                        grass, sedge, rush, fern

* lifeform:                specifies the lifeform of the species: annual or perennial lifeform
                        (species which can have both of these lifeforms where considered as annuals)

corrections tab:	Detailed description of corrections made in plot.data tab

format: XLS

en:
This dataset contains all data, on which the following publication below is based.

Paper Citation:

_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._

Please cite this paper together with the citation for the datafile.

Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).

Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.

References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

value: Envidat Harvester

en: Native and no-native plant interactions in Australian grasslands


maintainer: EnviDat Support

en: perception-of-ecosystem-services online-questionnaire-survey visual-attractiveness adults-and-teenagers nfi-photos

en: Questionnaire Italian

format: SERVICE

en: Questionnaire French

en: SPSS-Dataset

en: Codebook to SPSS-file

media_type: application/pdf

format: PDF

mimetype: application/pdf

en: Dataset in csv-format

media_type: text/csv

format: CSV

mimetype: text/csv

en: Questionnaire German

en: This questionnaire survey was conducted as an online survey and aimed at investigating the relationship between physical forest characteristics, visual attractiveness of forest and the perception of ecological and cultural ecosystem services in urban forests. Each participant was shown 6 photos out of a pool of 50 photos taken from the Swiss National Forest Inventory (NFI) database. Physical forest characteristics were derived from the photos. The study was conducted as part of the "WaMos meets LFI" (WML) project.

adults-and-teenagers

display_name: adults-and-teenagers

nfi-photos

display_name: nfi-photos

online-questionnaire-survey

display_name: online-questionnaire-survey

perception-of-ecosystem-services

display_name: perception-of-ecosystem-services

visual-attractiveness

display_name: visual-attractiveness

en: Relationship between physical forest characteristics, visual attractiveness and perception of ecosystem services in urban forests


maintainer: Frank Techel

en: avalanche-forecasting avalanche-forecast avalanche-danger-level avalanche-bulletin verification

en: D_QC for forecasting seasons 2020/2021 - 2022/2023.

en: D_QC for forecasting seasons 2001/2002 until 2019/2020.

en: Data for the 2023/2024 forecasting season. It was added on 26 Aug 2024 by F. Techel.

en:
The data set contains the re-analyzed (or quality-checked) regional avalanche danger levels (D_QC) for Switzerland.

D_QC relates to dry-snow avalanche conditions only. Measuring the avalanche danger level D is not possible; forecast, nowcast, and hindcast assessments of D are judgments by humans interpreting data. However, combining several pieces of information indicating the same D, it can be expected that it is more likely that D_QC represents the avalanche conditions well.

For the **forecasting seasons 2001/2002 until 2019/2020**, the approach to obtain D_QC is described in detail in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

For the **forecasting seasons 2020/2021 and later**, D_QC is derived using the following approach:
1. *Combination of forecast (D_forecast) and nowcast (D_nowcast)*: If there was only one assessment available by an observer after a day in the field for a region, and if D_forecast = D_nowcast --> D_QC = D_forecast.
2. *Combination of several nowcast assessments (D_nowcast)*: If two (or more) observers agreed (or majority opinion) in their (independent) assessments of D_nowcast after a day in the field in the same warning region. --> D_QC = D_nowcast.
3. *Hindcast analysis (D_hindcast)*: In Switzerland, avalanche forecasters re-evaluate all situations when D = 4 (high) or D = 5 (very high) were either forecast, should have been forecast, or when forecasters discussed given one of these two levels but had not given them. Generally, two forecasters assess each situation. In these cases, D_QC = D_hindcast. The hindcast analysis, only available since the forecasting season 2020/2021, replaces what was step (2) in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

All other cases - ties in case of (1) or (2), no new information from the warning region in question, or if no D_hindcast was available - are not considered quality-checked, and are, thus, not contained in the data set.

In addition to D_QC, the file contains information on the elevation and aspect, where D_QC likely prevails.
- The indicated elevation is the mean of the respective elevations in (1), (2), or (3). At danger level 1 (low), when no elevation is indicated in the Swiss forecast, a value of 1500 m is set.
- For the four cardinal aspects N, E, S, and W, a value of 1 means that there was agreement that D was reached in this aspect and a value of 0 means that there was agreement that D was not reached in this aspect. Intermediate values correspondingly mark disagreements in the assessments.

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forecast

display_name: avalanche-forecast

avalanche-forecasting

display_name: avalanche-forecasting

verification

display_name: verification

en: Re-analyzed regional avalanche danger levels in Switzerland


maintainer: M. Carol Resch

en: grassland long-term-experiment nematodes vegetation restoration topsoil-removal diversity

en: Nemadotes and vegetation

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

X: X-Coordinate

Y: Y-Coordinate

Ri.veg: Total number of plant species

Div.veg: Shannon diversity of plant species

Ri.nem: Total number of nematode families

Div.nem: Shannon diversity of nematode families

abund: Total nematode abundance (individuals per 100g dry soil)

MI: Maturity index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI: Plant parasite index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI.MI: Plant parasite to Maturity index according to Bongers, van der Meulen, & Korthals 1997; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

CI: Channel index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

EI: Enrichment index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

SI: Structure index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

He.a: Herbivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.Ca.a	Sum of omnivorous and carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014
CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001

CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001

CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP3-5.a: Sum of C-P3, C-P4 and C-P5 nematode abundance (individuals per 100g dry soil) equivalent to structure indicators according to Ferris, Bongers, & de Goede 2001

protect.sp.pro: plant species categorized into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002)

tar.sp: Number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species)

Indi.moist: Plant indicator values for soil moisture according to Landolt et al. 2010

Indi.nutri: Plant indicator values for soil nutrients according to Landolt et al. 2010

Management: level of mowing and manuring frequency (35-40 kg N ha-1 application-1); intensity1 = mowing once and no manure; intensity2 = 2-3 times mowing and no manure; intensity3 = 2-3 times mowing and manuring; intensity4 = 4-5 times mowing and manuring

Tillage: last time of tillage

Land.use.history: for Initial plots = recent agricultural use; for all restored sites = agricultural use before restoration
Mowing	earliest date of biomass harvesting (excluding “Initial”) based on contracts between farmers and the Nature Protection Agency of Zurich

Soil.type: based on soil mapping survey 1991 (before restoration)

Soil.texture: determined by the sediment method (Gee & Bauder 1986) and classified into soil textural classes according to FAO (1990)

pH: soil pH (CaCl2)

Slope: slope gradient classes according to FAO (1990; %)

en: Nematode families

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-41: Nematode abundance (individuals per 100g dry soil) per family; nomenclature according to Bongers 1988

en: Plant community composition (plant species)

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-252: Plant abundance per species (in total 252 plant species) expressed as cover percentage estimation according to van der Maarel (vdM 1979; 7 classes: 1-7); nomenclature according to Lauber & Wagner (1996)

en: Nematode colonizer-persister classes

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001
CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001
CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

en: Coordinates of one research plot were wrong. This was corrected in the current version of the file.

en: Nematode feeding types

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:
 > Resch, M.C., Schütz, M., Graf, U., Wagenaar, R., van der Putten, W.H., Risch, A.C. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56: 1782-1793.

Please cite this paper together with the citation for the datafile.

 Methods
 Study area and experimental settings
The study was conducted in a nature reserve (Eigental: 47° 27’ to 47° 29’ N, 8° 37’ E, 461 to 507 m a.s.l.) that is located on the Swiss Central plateau close to Zurich airport (Canton Zurich, Switzerland). The mean annual temperature in this area ranges from 8.9 to 10.6 °C, mean annual precipitation from 910 to 1260 mm [10-year average (2007-2017); MeteoSchweiz, 2018]. The main soil types are calcaric to gleyic Cambisol and Gleysols. The reserve was established in 1967 to protect small remnants of oligotrophic semi-natural grasslands (roughly 12 ha). The plant community can be characterized as Molinion and Mesobromion (semi-wet to semi-dry), depending on the site-specific groundwater level and slope inclination (Delarze, Gonseth, Eggenberg, & Vust, 2015). These remnants represent species-rich islands in an otherwise intensively managed agricultural landscape. Semi-natural grasslands covered an area of 60,000 ha in the Canton Zurich in 1939, however, by 2005 only roughly 600 ha remained (Baudirektion Kanton Zürich, 2007). In 1990, the government of Canton Zurich decided to enlarge the nature reserve Eigental. The goal was to incorporate eleven patches of 20 ha adjacent intensively farmed land and transform these patches into semi-natural grasslands. The patches had a different agricultural history, ranging from permanent (no tillage for >50 years) to temporary grassland (as part of crop rotation; last tillage <5 years). On all freshly integrated patches fertilization was stopped in 1992 and from then on biomass was harvested three times a year and removed. After 5 years without noticeable effects on vegetation composition, the Nature Conservation Agency of Canton Zurich decided to increase the restoration efforts. In 1995, a large-scale experiment was initialized to evaluate if certain treatments can facilitate restoration within a reasonable timeframe of 5 to 10 years after treatment implementation.
The three restoration treatments used were:
i. “Harvest only”: Plots are being mowed two to three times a year and the biomass is removed.
ii. “Topsoil”: Topsoil was removed to a depth of 10 to 20 cm, depending on the depth of the O and A horizon, in four randomly selected areas within each of the eleven patches in late autumn 1995. The size of each topsoil removal area depended on individual patch size and was between 2700 and 7000 m2.
iii. “Topsoil+Propagules”: Propagules from target vegetation were added on half of the area where topsoil was removed, using fresh, seed-containing hay originating from a mixture of semi-dry to semi-wet species-rich grasslands of local provenance (within a radius of 7 km). Hay applications were conducted twice in 1995 and 1996. Repeated applications were chosen to account for the low quantity of available plant material per transfer, since area ratio between receptor and donor sites was roughly 1:1. In addition, hand-collected propagules from 15 selected target species of regional provenance (within a radius of 30 km) were equally applied in 1996 and 1997.
“Topsoil” and “Topsoil+Propagules” plots are mowed once a year, and the biomass is removed. Mowing on these plots started five years after the treatment was implemented.
Eleven permanent plots of 5 m x 5 m were randomly established in each treatment to monitor the vegetation development. The experiment was complemented with 11 control plots that represent the initial state of intensively managed grasslands, further referred to as “Initial”, and 11 control plots that represent the targeted state of donor sites for “Topsoil+Propagules”, further referred to as “Target”. Consequently, the experiment consists of 55 plots (5 treatments x 11 replicates). Management of intensively used grasslands includes mowing and fertilizing (manure) between two to five times a year, as well as different tillage regimes (no tillage for >50 years; last time of tillage <5 years).

 Nematode and plant sampling
Soil nematodes were sampled in 2 m x 2 m plots, randomly established at least 2 m away from the vegetation plots. We collected eight soil cores with a 2.2 cm diameter soil core sampler (Giddings Machine Company, Windsor, CO, USA) to a depth of 12 cm (representing the majority of the plant rooting system) in each plot at the beginning of July 2017. The eight cores within each replicate plot were combined, gently homogenized, placed in coolers and transported to the laboratory of NIOO in Wageningen, the Netherlands, within one week. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink, 1960) and concentrated, resulting in 6 mL nematode solution. The nematode solution was subdivided into three subsamples, two for morphological identification and quantification, and one for molecular work (not used in this study). For morphological identification and quantification, nematodes were heat-killed at 90 °C and fixed in 4 % formaldehyde solution (final volume 10 mL per subsample). All nematodes in 1 mL of formaldehyde solution were counted, and a minimum of 150 individuals per 1 mL sample (or all if less nematodes were present) were identified to family level using Bongers (1988). We then extrapolated the numbers of each nematode taxa identified to the entire sample and expressed them per 100 g dry soil for further analyses.
We calculated number of nematode taxa and Shannon diversity and assessed nematode community composition. In addition, we classified the nematode taxa into feeding types (herbivores, bacterivores, fungivores, omni-carnivores), structural and functional guilds (Table S4). Structural guilds assign nematode taxa according to life-history traits into five colonizer-persister (C-P) classes, ranging from one (early colonizers of new resources) to five (persisters in undisturbed habitats; Bongers 1990). C-P classes can be categorized as indicators for nutrient-enriched (C-P1), stressed (C-P2) and structured (C-P3 + C-P4 + C-P5) soil conditions (Ferris, Bongers, & de Goede, 2001). Functional guilds assign nematode taxa according to their C-P classification combined with their feeding habits (Ferris, Bongers, & de Goede, 2001). Based on the structural and functional guild classification we calculated five additional indices to assess soil nutrient status, disturbance and food web characteristics using NINJA (Sieriebriennikov, Ferris, & de Goede, 2014). 1) The Maturity index indicates the degree of different environmental perturbations (e.g., tillage, nutrient enrichment, pollution) and is used to monitor colonization and subsequent succession after disturbances (Bongers, 1990). 2) The ratio between the Plant Parasite (C-P of herbivorous nematodes only) to Maturity index is used to monitor the recovery of disturbed habitats incorporating information of life-history traits for all feeding types (Bongers, van der Meulen, & Korthals, 1997). 3) The Enrichment index indicates nutrient-enriched soils and agricultural management practices (Ferris, Bongers, & de Goede, 2001). 4) The Structure index provides information about the succession stage of the soil food web and therefore correlates with the degree of maturity of an ecosystem (Ferris, Bongers, & de Goede, 2001). 5) The Channel index provides information about the predominant decomposition pathways, where higher values stand for a higher proportion of energy transformed through the slow fungal decomposition channel (Ferris, Bongers, & de Goede, 2001). In addition, the Structure and Enrichment indices can be displayed in a biplot where nematode assemblages are plotted along a structure (x-axis) and enrichment (y-axis) trajectory (increasing index values). Each biplot quadrat reflects different levels of disturbance, soil nutrient pools and decomposition pathways (Ferris, Bongers, & de Goede, 2001).
The plant surveys were conducted on the 25 m2 permanent plots in June 2017. Plant species cover was visually assessed according to the semi-quantitative cover-abundance scale of Braun-Blanquet (1964; nomenclature: Lauber & Wagner, 1996). We calculated number of species and Shannon diversity, and assessed plant community composition. We also counted the number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species) and categorized plant species into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002). Furthermore, we calculated indicator values for soil moisture and soil nutrients for each species according to Landolt et al. (2010).

 References
Baudirektion Kanton Zürich (2007). 10 Jahre Naturschutz-Gesamtkonzept für den Kanton Zürich 1995-2005 – Stand der Umsetzung. Zürich: Baudirektion Kanton Zürich.
Bongers, T. (1988). De nematoden van Nederland. Utrecht: Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging.
Bongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia, 83, 14-19. doi:10.1007/BF00324627
Bongers, T., van der Meulen, H., & Korthals, G. (1997). Inverse relationship between the nematode maturity index and plant parasite index under enriched nutrient conditions. Applied Soil Ecology, 6, 195-199. doi:10.1016/S0929-1393(96)00136-9
Braun-Blanquet, J. (1964). Pflanzensoziologie, Grundzüge der Vegetationskunde (3rd ed.). Wien: Springer.
Delarze, R., Gonseth, Y., Eggenberg, S., & Vust, M. (2015). Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten (3rd ed.). Bern: Ott.
Ferris, H., Bongers, T., & de Goede, R.G.M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 13-29. doi:10.1016/S0929-1393(01)00152-4
Landolt, E., Bäumler, B., Erhardt, A., Hegg, O., Klötzli, F., Lämmler, W., … Wohlgemuth, T. (2010). Flora indicativa. Ecological indicator values and biological attributes of the Flora of Switzerland and the Alps (2nd ed.). Bern: Haupt.
Lauber, K., & Wagner, G. (1996). Flora Helvetica. Flora der Schweiz. Bern: Haupt.
MeteoSchweiz (2018). Klimabulletin Jahr 2017, Zürich: MeteoSchweiz.
Moser, D., Gygax, A., Bäumler, B., Wyler, N., & Palese, R. (2002) Rote Liste der gefährteten Farn- und Blütenpflanzen der Schweiz. Bern: BUWAL.
Oostenbrink, M. (1960). Estimating nematode populations by some selected methods. In N.J. Sasser & W.R. Jenkins (Eds.), Nematology (pp. 85-101). Chapel Hill: University of North Carolina Press.
Sieriebriennikov, B., Ferris, H., & de Goede, R.G.M (2014). NINJA: An automated calculation system for nematode-based biological monitoring. European Journal of Soil Biology, 61, 90-93. doi:10.1016/j.ejsobi.2014.02.004

diversity

display_name: diversity

long-term-experiment

display_name: long-term-experiment

nematodes

display_name: nematodes

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

vegetation

display_name: vegetation

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Grassland restoration: nematodes and plant communities


dataset-on-new-snow-water-equivalent

title_for_slug: dataset-on-new-snow-water-equivalent

en: precipitation new-snow snowfall data-assimilation snow-modelling

media_type: application/zip

en: The .zip file contains all data as described in this repository and associated publication. The .zip file contains a readme file describing its content in detail.

format: ZIP

en:
This dataset includes quality-controlled measurements of new snow depth (HN), new snow water equivalent (HNW), snow depth (HS), and snow water equivalent (SWE) from 41 stations located in Switzerland for the period from 2016-09-01 to 2022-08-31.
These data are the basis of the following publication: Magnusson J., Cluzet B., Quéno L., Mott R., Oberrauch M., Mazzotti G., Marty C., Jonas T., 2025, Evaluating methods to estimate the water equivalent of new snow from daily snow depth recordings, Cold Regions Science and Technology, https://doi.org/10.1016/j.coldregions.2025.104435.
Abstract
The water equivalent of new snow (HNW) plays a crucial role in various fields, including hydrological modeling, avalanche forecasting, and assessing snow loads on structures. However, in contrast to snow depth (HS), obtaining HNW measurements is challenging as well as time-consuming and is hence rarely measured. Therefore, we assess the reliability of two semi-empirical methods, HS2SWE and ΔSNOW, for estimating HNW. These methods are designed to simulate continuous water equivalent of the snowpack (SWE) from daily HS only, with changes in SWE yielding daily HNW estimates. We compare both parametric methods against HNW predictions from a physics-based snow model (FSM2oshd) that integrates daily HS recordings using data assimilation. Our findings reveal that all methods exhibit similar performance, with relative biases of less than ~3 % in replicating SWE observations commonly used for model evaluations. However, the ΔSNOW model tends to underestimate daily HNW by ~17 %, whereas HS2SWE and FSM2oshd combined with a particle filter data assimilation scheme provide nearly unbiased estimates, with relative biases below ~5 %. In contrast to the parsimonious parametric methods, we show that the physics-based approach can yield information about unobserved variables, such as total solid precipitation amounts, that may differ from HNW due to concurrent melt. Overall, our results underscore the potential of utilizing commonly available daily HS data in conjunction with appropriate modeling techniques to provide valuable insights into snow accumulation processes. Our study demonstrates that daily SWE observations or supplementary measurements like HNW are important for validating the day-to-day accuracy of simulations and should ideally already be incorporated during the calibration and development of models.
Acknowlegements
These data were recorded by SLF observers and staff members. Their contribution is gratefully acknowledged.

data-assimilation

display_name: data-assimilation

new-snow

display_name: new-snow

precipitation

display_name: precipitation

snow-modelling

display_name: snow-modelling

snowfall

display_name: snowfall

en: Dataset on new snow water equivalent


en: flora-change zurich plant-species uetliberg occurrence

en:
The list gives the clearly identifiable plant species from Schinz (1775). Die Reise auf den Uetliberg. Verlag des Waysenhauses, Zürich). Several species given in Schinz (1775) are not identifiable to the species level and are not included in the list. Similarly, Vicia pisiformis, Erbsenartige Wicke, given by Schinz (1775) is probably a misidentification and also not included in the list.

Latin plant species name Schinz 1775: Latin plant name (if) given by Schinz (1775); na: not available
German plant species name Schinz 1775: German plant name given by Schinz (1775)
Latin plant species name Info Flora 2024: Latin plant name according to www.infoflora.ch in 2024
German plant species name Info Flora 2024: German plant name according to www.infoflora.ch in 2024
Plant species still occurring in 2020: Plant species given in Schinz (1775) still occurring at the Uetliberg in 2020 (Zürcherische Botanische Gesellschaft. 2020. Flora des Kanton Zürich. Haupt, Bern); occurrence of Thesium alpinum, Alpen-Bergflachs, according to floristic knowledge of Rolf Holderegger and Michèle Büttner; 1: still occurring; 0: no longer occurring / extinct.

en:
The list gives the clearly identifiable plant species from Schinz (1775). Die Reise auf den Uetliberg. Verlag des Waysenhauses, Zürich). Several species given in Schinz (1775) are not identifiable to the species level and are not included in the list. Similarly, *Vicia pisiformis*, Erbsenartige Wicke, given by Schinz (1775) is probably a misidentification and also not included in the list.
Latin plant species name Schinz 1775: Latin plant name (if) given by Schinz (1775); na: not available
German plant species name Schinz 1775: German plant name given by Schinz (1775)
Latin plant species name Info Flora 2024: Latin plant name according to www.infoflora.ch in 2024
German plant species name Info Flora 2024: German plant name according to www.infoflora.ch in 2024
Plant species still occurring in 2020: Plant species given in Schinz (1775) still occurring at the Uetliberg in 2020 (Zürcherische Botanische Gesellschaft. 2020. Flora des Kanton Zürich. Haupt, Bern); occurrence of *Thesium alpinum*, Alpen-Bergflachs, according to floristic knowledge of Rolf Holderegger and Michèle Büttner; 1: still occurring; 0: no longer occurring / extinct.

flora-change

display_name: flora-change

occurrence

display_name: occurrence

plant-species

display_name: plant-species

uetliberg

display_name: uetliberg

zurich

display_name: zurich

en: Plant species list from 1775 and 2020 for Uetliberg Zürich


maintainer: Rebecca Mott

en: terrestrial-laser-scanning tls patchy-snow-covers snow-ablation-rates riegl-vz6000

en: Snowmask 2015

mimetype: application/zip

en: Digital Elevation Modell 2015

en: Digital Elevation Modell 2014

en: Snowmask 2016

en: Gletschboden test site

en: Snowmask 2014

en: Digital Elevation Modell 2016

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


en: sediment-transport mars model erosion snow

media_type: text/plain

en: Datasets of Figure 3a

format: TXT

mimetype: text/plain

en: Datasets of Figure 3b

en: Datasets of Figure 4a

en: Datasets of Figure 4b

en: Datasets of Figure 2

en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).

 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation


maintainer: Loïc Pellissier Pellissier

en: alps elevation community-indices plant-herbivore-interactions environmental-gradients functional-traits herbivores-communities

en: Orthoptera surveys

en: Species inventories of Orthoptera

en: Orthoptera traits

en: Orthoptera functional traits (incisive mandibular strength averaged by species)

en: Vegetion surveys

en: Species inventories of plants

en: Study sites

en: Coordinates and elevation of the study sites

en: Nematode surveys

en: Surveys of soil nematode along elevation

en: Plant traits

en: Plant functional traits (SLA, LDMC, carbon and nitrogen content, punch strenght; averaged by species)

en: Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017.

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions

en: Above- and below-ground herbivore communities along elevation


en: high-resolution evapotranspiration snow-simulation snow oshd land-use land-cover clm5 forest-productivity

en:
12 gridded CLM5 simulations over the spatial extent of Switzerland:
- 1km, 0.25deg, 0.5deg
- 3 different meteorological forcings (Clim_CRU, CLIM_CRU*, CLIM_OSHD)
- 2 different land use forcings
each with the following outputs:
- daily snow depth (file SNOW_DEPTH.nc)
- monthly summed gross primary production (file FPSN_MONTH_SUM.nc)
- monthly summed evapotranspiration (file QFLX_EVAP_TOT_MONTH_SUM.nc).
Temporal extent of all simulations: 01/01/2015 - 31/12/2020.

en: Point-scale CLM5 simulation output of snow depth and snow water equivalent for 9 different simulation scenarios, each performed at 36 snow station locations across Switzerland. Please have a look at table A1 in the appendix of the linked publication for coordinates of the stations. Additional information on the setup, and the differences between simulation setups can also be found in the linked publication.

en: Forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution. For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR) are provided.

en:
This dataset contains Community Land Model 5 (CLM5) simulation output over the spatial extent of Switzerland at different resolutions and based on a range of input datasets. It further contains land-use surface data used for the CLM5-simulations.

**Detailed description of the CLM5 simulation setup and the various input datasets can be found in the accompanying publication: https://doi.org/10.5194/egusphere-2023-1832.**

 CLM5 simulation output

This dataset includes gridded CLM5 simulations of snow depth, gross primary productivity (GPP) and evapotranspiration at different resolutions ( 1km, 0.25° and 0.5°) and based on a range of input datasets over the spatial extent of Switzerland (see folder *gridded_CLM5_simulations*). Additionally, point-scale CLM5 simulations of snow depth and snow-water-equivalent at 36 snow-station locations (see folder *point_scale_CLM5_simulations*) are included. Latitude, longitude and elevation for these station locations can be found in table A1 of the above-mentioned publication. All simulation output spans from 01/01/2015 - 31/12/2019.

Included CLM5 simulation results are based on 3 different meteorological forcing datasets:
* Clim_CRU: standard global dataset, we used the recent state-of-the-art standrd global dataset CRU-JRA (https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad)

* Clim_CRU*: ClimCRU upraded by downscaling temperature data using a temperature lapse rate of -6.5K/1000m and a high-resolution DEM

* Clim_OSHD: highest level of detail, meteorological forcing generated according to methods developed by the Operational Snow Hydrological Service (OSHD), at 1km spatial and 1hour temporal resolution</li>

 Land-use surface data

This dataset further includes forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution (see folder *surface_landuse_datasets*). For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR), which includes a higher level of detail and is based on a more up-to-date land use datase, are provided. More details on these two datasets can be found in the above-mentioned publication.

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow-simulation

display_name: snow-simulation

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Multi-resolution CLM5 simulations across Switzerland


wind-lidar-davos-wolfgang

title_for_slug: wind-lidar-davos-wolfgang

en: raclets profiles wind wolfgangpass lidar

en: Wind LIDAR data Wolfgang

en: A Leosphere WidCube 100S was deployed at Davos Wolfang, measuring wind profiles as well as performing PPI and RHI scans. Time format is in UTC with highest time resolution of 5 seconds.

en: Scanning wind Lidar from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 200 m above ground to 8100 m. The time resolution is up to 5 seconds. The Lidar was measuring wind profiles but also performed plan position indicator (PPI) and range height indicator (RHI) scans.

lidar

display_name: lidar

profiles

display_name: profiles

raclets

display_name: raclets

wind

display_name: wind

wolfgangpass

display_name: wolfgangpass

en: Wind LIDAR Davos Wolfgang


en: snow vapor-transport pattern-formation numerical-model python

en:
Data and code v1.0 downloaded from the git.

Running the code requires an installation of FEniCS via docker.

en:
This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format.

The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication:

_Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical
instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_

The code and potential updates can be accessed directly through git via:

https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics

numerical-model

display_name: numerical-model

pattern-formation

display_name: pattern-formation

python

display_name: python

snow

display_name: snow

vapor-transport

display_name: vapor-transport

en: A numerical solver for heat and mass transport in snow based on FEniCS


en: wrf antarctica topography landuse cryowrf

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


maintainer: Leo Gallus Bont

en: cable-yarding qgis-plugin swiss-geo-downloader seilaplan digital-planning open-source digital-elevation-model swiss-geodata geoinformation-system

en: Herunterladen des DHM mit SwissGeoDownloader

en: View video on youtube!

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link to Seilaplan website: https://seilaplan.wsl.ch

*********************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.

Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader

Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

seilaplan

display_name: seilaplan

swiss-geo-downloader

display_name: swiss-geo-downloader

swiss-geodata

display_name: swiss-geodata

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Seilaplan Tutorial: DTM download with SwissGeoDownloader


maintainer: Alexandre Buttler

en: soil silvopastoral-systems biogeochemisty climate-change transplantation-experiment

en: Dataset

en: Zip archive of all datasets detailed in study.

en:
Silvopastoral systems are highly productive and combine long-term wood production with annual provision of forage for livestock. In the Swiss Jura Mountains these systems are a key component of the landscape. As in other cold biomes, climate change can potentially accelerate landscape change within these historically sustainable systems.

In order to anticipate the evolution of subalpine wooded pasture ecosystems under future climate and land-use changes, this project focused on the interplay between soil, vegetation and climate. It was aimed at providing experimental evidence for chief ecosystem processes, with emphasis on the quality of the ecosystem services provided. The main interest was placed on vegetation turf resistance to climate change along an unwooded – sparsely wooded - densely wooded pasture gradient (land-use intensity), where plant productivity, diversity and succession along with rates of carbon cycling and microbial activity provided measures of ecosystem functioning at both plot and landscape level.

Experimental transplantation of monolith soil turfs to lower altitudes allowed to simulate soil warming and reduced annual precipitation. In order to simulate a year-round warmer and drier climate the natural climate variation along an altitudinal gradient was used as a proxy. The aim was to simulate realistic climate change scenarios for the second half of the 21st century predicted by the IPCC report and downscaled for Switzerland providing regionalized interpolated projections integrating therein trends for temperature increase and precipitation decrease. By using permanent meteorological stations within the network of the Federal Office of Meteorology and Climatology (MeteoSwiss), we obtained high resolution regional data on the variation of mean annual temperature (MAT) and mean annual precipitation (MAP) in relation to altitude in the Swiss Jura Mountains. We observed a general increase of +0.5 K in MAT and a decrease of -20 % MAP for each 100 m decrease in altitude along the SE slope of the Swiss Jura Mountains. These relationships served for the selection of the transplantation sites such that in comparison to a control site at 1350 m a.s.l. (Combe des Amburnex, N 46°54’, E 6°23’) a +2 K MAT and -20 % MAP was achieved at 1010 m a.s.l. (Saint-George, N 46°52’, E 6°26’), a +4 K MAT and -40 % MAP at 570 m a.s.l., (Arboretum d’Aubonne, N 46°51’, E 6°37’), and a +5 K MAT and -50 % MAP at 395 m a.s.l. (Les Bois Chamblard, N 46°47’, E 6°41’). The two stations at 1010 m a.s.l. and 570 m a.s.l. corresponded to the IPCC scenario A1B for a moderate increase in greenhouse gas emissions and to scenario A2 for a high increase in greenhouse gas emissions, respectively. The station at 395 m a.s.l. was chosen to represent an extreme scenario with climate variables lying at the positive tail distribution of model predictions under the A2 scenario.

Soil cores were assembled into rectangular PVC boxes of 60  80 cm2 size and of 35 cm height. All mesocosms were dug down to surface level into previously prepared trenches in the ground thus preventing lateral heat exchange with the atmosphere. Since at each site the mesocosms were placed in a common garden with no light interception, mesocosms with turfs from the two wooded pastures were shaded from direct sun light to simulate the natural light conditions in the corresponding habitats. Each mesocosm was equipped with a drainage system and was connected to a water tank thus representing a zero potential lysimeter collecting soil solution and precipitation/snowmelt runoff. ECH2O EC-TM sensor probes coupled to Em50 data-loggers (Decagon Devices, Inc., USA) recorded soil temperature and volumetric water content in each mesocosm at the top-soil (0 to -3 cm) every minute and data were averaged over one hour intervals. Climate parameters at each transplantation site were monitored continuously throughout the experiment by means of automated weather stations (Sensor Scope Sàrl, Switzerland), measuring rain precipitation (non-heated tipping bucket gauges) and air temperature and humidity 2 m above the ground surface at one minute intervals.

A list of above- and belowground variables were measured to assess the resilience of biogeochemical processes, plant productivity, tree regeneration, and carbon sequestration for each respective land-use practice. Furthermore, the experimental data were used to improve on (parameterization) the existing spatially explicit, dynamic model WoodPaM and refine the modelʼs climatic and land-use variables so that different scenarios of climate change and land use change could be simulated. Natural and management induced disturbance patterns were incorporated into the model.
The data have been made available within the project CCES Mounted. The climate stations Sensorscope are still in use within the project CLIMARBRE (Wald und Klimawandel, WSL/BAFU).

#References

1. Puissant, J., Cécillon, L., Mills, R.T.E., Robroek, B.J.M. Gavazov, K., De Danieli, S., Spiegelberger, T., Buttler, A., Brun, J.J. 2015. Seasonal influence of climate manipulation on microbial community structure and function in mountain soils. Soil Biology and Biochemistry 80: 296–305.
2. Mills, R., K. Gavazov, T. Spiegelberger, D. Johnson and A. Buttler 2014. Diminished soil functions occur under simulated climate change in a sup-alpine pasture, but heterotrophic temperature sensitivity indicates microbial resilience. Science of the Total Environment, vol. 473–474(0): 465-472.
3. Gavazov, K., Spiegelberger, T. and Buttler, A. 2014. Transplantation of subalpine wood-pasture turfs along a natural climatic gradient reveals lower resistance of unwooded pastures to climate change compared to wooded ones. Oecologia (174) : 1425-1435.
4. Peringer A., Siehoff S., Chételat J., Spiegelberger T., Buttler A. & Gillet F. 2013. Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change. Ecology and Society, 18, 3: 11. DOI: 10.5751/ES-05600-180311. [online] URL: http://www.ecologyandsociety.org/vol18/iss3/art11/
5. Gavazov, K. S., A. Peringer, A. Buttler, F. Gillet and T. Spiegelberger. 2013. Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios. Ecology and Society 18 (1): 38. [online] URL: http://www.ecologyandsociety.org/vol18/iss1/art38/

biogeochemisty

display_name: biogeochemisty

climate-change

display_name: climate-change

silvopastoral-systems

display_name: silvopastoral-systems

soil

display_name: soil

transplantation-experiment

display_name: transplantation-experiment

en: Biogeochemical data from a transplantation experiment of monolith soil turfs along an altitudinal gradient to simulate climate change scenarios


rorcc

maintainer: Tobias Wechsler

title_for_slug: rorcc

en: climate-change hydropower environmental-flow design-discharge run-of-river-power-plants

en: RoRCC

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants