privathaushalte-total-anz

title_for_slug: privathaushalte-total-anz

de: bezirke haushalte gemeinden bevoelkerungsstatistik kantonzuerich bevoelkerung privathaushalte

de: Privathaushalte Total [Anz.]

de: Anzahl Privathaushalte (ohne Kollektivhaushalte)

bevoelkerungsstatistik

display_name: bevoelkerungsstatistik

privathaushalte

display_name: privathaushalte

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich


maintainer: Statistisches Amt des Kantons Zürich, Data Shop

de: bezirke alter kantonzuerich bevoelkerung gemeinden altersstruktur

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

state: active

type: dataset

de: Bevölkerung: Anteil 65-79-Jährige [%]

media_type: text/csv

format: CSV

mimetype: text/csv

de: Anteil 65-79-Jähriger an der Gesamtbevölkerung nach zivilrechtlichem Wohnsitz(ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

alter

display_name: alter

altersstruktur

display_name: altersstruktur

bevoelkerung

display_name: bevoelkerung

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

statistisches-amt-kanton-zuerich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

political_level: canton

kanton-zuerich

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: ZH-Kt Statistisches Amt - DCAT Harvester


wegzuge-pers

title_for_slug: wegzuge-pers

name: Statistisches Amt des Kantons Zürich, Data Shop

de: gemeinden zuzuege-wegzuege kantonzuerich wanderungen bevoelkerung bezirke

de: Wegzüge [Pers.]

de: Anzahl weggezogene Personen. Hinweis: Ab 2011 Wechsel des Produktionsverfahrens und neue Definition der ständigen Wohnbevölkerung, die zusätzlich Personen im Asylprozess mit einer Gesamtaufenthaltsdauer von mindestens 12 Monaten umfasst. Inkl. innerkantonaler Wanderungen.

wanderungen

display_name: wanderungen

zuzuege-wegzuege

display_name: zuzuege-wegzuege


wahlarchiv-kantonsratswahlen

maintainer: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

title_for_slug: wahlarchiv-kantonsratswahlen

de: wahlergebnisse kantonsratswahlen kantonzuerich politik kantonsrat wahlen panaschierstimmen politischeparteien

label: Codebook/Dokumentation der Daten

de: Listenresultate Erneuerungswahl Kantonsrat 2023

de: Anzahl erhaltener Stimmen pro Liste und Gebiet

de: Listenresultate Erneuerungswahl Kantonsrat 2019

de: Panaschierstatistik Erneuerungswahl Kantonsrat 2019

de: Stimmen nach Herkunft für alle Kandidierenden der Kantonsratswahl 2019 pro Gemeinde

de: Listenresultate Erneuerungswahl Kantonsrat 2011

de: Parteiresultate Erneuerungswahl Kantonsrat 2015

de: Anzahl erhaltener Stimmen pro Partei und Gebiet. Die Zuteilung der Listen zu einer Partei erfolgt gemäss der Ressource "Zuordnungstabelle Listen – Parteien" dieses Datasets.

de: Parteiresultate Erneuerungswahl Kantonsrat 2011

de: Parteiresultate Erneuerungswahl Kantonsrat 2007

de: Kandidierende Erneuerungswahl Kantonsrat 2007

de: Informationen zu den Kandidierenden der Kantonsratswahl 2007

de: Kandidierende Erneuerungswahl Kantonsrat 2011

de: Informationen zu den Kandidierenden der Kantonsratswahl 2011

de: Gemeindeinformationen Erneuerungswahl Kantonsrat 2019

de: Gemeindespezifische Informationen wie BFS-Nummer und Stimmbeteiligung für die Kantonsratswahl 2019

de: Gemeindeinformationen Erneuerungswahl Kantonsrat 2011

de: Gemeindespezifische Informationen wie BFS-Nummer und Stimmbeteiligung für die Kantonsratswahl 2011

de: Listenresultate Erneuerungswahl Kantonsrat 2007

de: Panaschierstatistik Erneuerungswahl Kantonsrat 2023

de: Stimmen nach Herkunft für alle Kandidierenden der Kantonsratswahl 2023 pro Gemeinde

de: Panaschierstatistik Erneuerungswahl Kantonsrat 2015

de: Stimmen nach Herkunft für alle Kandidierenden der Kantonsratswahl 2015 pro Gemeinde

de: Parteiresultate Erneuerungswahl Kantonsrat 2023

de: Panaschierstatistik Erneuerungswahl Kantonsrat 2007

de: Stimmen nach Herkunft für alle Kandidierenden der Kantonsratswahl 2007 pro Gemeinde

de: Panaschierstatistik Erneuerungswahl Kantonsrat 2011

de: Stimmen nach Herkunft für alle Kandidierenden der Kantonsratswahl 2011 pro Gemeinde

de: Kandidierende Erneuerungswahl Kantonsrat 2015

de: Informationen zu den Kandidierenden der Kantonsratswahl 2015

de: Listenresultate Erneuerungswahl Kantonsrat 2015

de: Kandidierende Erneuerungswahl Kantonsrat 2023

de: Informationen zu den Kandidierenden der Kantonsratswahl 2023

format: XLS

de: Kandidierende Erneuerungswahl Kantonsrat 2019

de: Informationen zu den Kandidierenden der Kantonsratswahl 2019

de: Zuordnungstabelle Listen – Parteien

de: Tabelle für die Zuordnung von Listen zu Parteien bei Zürcher Kantonsratswahlen. Die ausgewiesenen Parteien sind an die vom Bundesamt für Statistik (BFS) in Zeitreihen separat ausgewiesenen Parteien angelehnt.

de: Gemeindeinformationen Erneuerungswahl Kantonsrat 2007

de: Gemeindespezifische Informationen wie BFS-Nummer und Stimmbeteiligung für die Kantonsratswahl 2007

de: Parteiresultate Erneuerungswahl Kantonsrat 2019

de: Gemeindeinformationen Erneuerungswahl Kantonsrat 2023

de: Gemeindespezifische Informationen wie BFS-Nummer und Stimmbeteiligung für die Kantonsratswahl 2023

de: Gemeindeinformationen Erneuerungswahl Kantonsrat 2015

de: Gemeindespezifische Informationen wie BFS-Nummer und Stimmbeteiligung für die Kantonsratswahl 2015

de: Ergebnisse der Erneuerungswahlen der Mitglieder des Kantonsrates


bevolkerung-heimat-schweiz-pers

title_for_slug: bevolkerung-heimat-schweiz-pers

de: gemeinden heimat kantonzuerich schweiz bevoelkerung bezirke nationalitaet

de: Bevölkerung: Heimat Schweiz [Pers.]

de: Einwohnerbestand Heimat Schweiz nach zivilrechtlichem Wohnsitz (ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

heimat

display_name: heimat

nationalitaet

display_name: nationalitaet

schweiz

display_name: schweiz

soci

de: Bevölkerung und Gesellschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


zuzuge

title_for_slug: zuzuge

de: gemeinden bezirke wanderungen kantonzuerich bevoelkerung zuzuege-wegzuege

de: Zuzüge [%]

de: Zuzüge in Bezug auf die Einwohnerzahl (gemäss Kantonaler Erhebung) Ende des vorhergehenden Jahres. Beispiel: Die "Zuzüge [%] 2003" beziehen sich auf die Einwohnerzahl von Ende 2002. Hinweis: Ab 2011 Wechsel des Produktionsverfahrens und neue Definition der ständigen Wohnbevölkerung, die zusätzlich Personen im Asylprozess mit einer Gesamtaufenthaltsdauer von mindestens 12 Monaten umfasst. Inkl. innerkantonaler Wanderungen.


schweine-anz

title_for_slug: schweine-anz

de: landwirtschaft bezirke gemeinden nutztiere kantonzuerich viehbestand

de: Schweine [Anz.]

de: Anzahl Schweine

landwirtschaft

display_name: landwirtschaft

nutztiere

display_name: nutztiere

viehbestand

display_name: viehbestand

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


auslanderanteil

title_for_slug: auslanderanteil

de: bezirke gemeinden bevoelkerungsstatistik bevoelkerung kantonzuerich auslaender

de: Ausländeranteil [%]

de: Ausländeranteil in Prozent der Gesamtbevölkerung (zivilrechtlicher Wohnsitz; ab 2010 inkl. vorläufig Aufgenommene, die über einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

auslaender

display_name: auslaender


neuerstellte-efh-whg

title_for_slug: neuerstellte-efh-whg

de: immobilien gemeinden einfamilienhaus kantonzuerich wohnbautaetigkeit bezirke

de: Neuerstellte EFH [Whg.]

de: Neu erstellte Einfamilienhäuser

einfamilienhaus

display_name: einfamilienhaus

immobilien

display_name: immobilien

wohnbautaetigkeit

display_name: wohnbautaetigkeit


krw-wahleranteil-bdp

title_for_slug: krw-wahleranteil-bdp

de: kantonzuerich wahlen parteien gemeinden politik kantonsratswahlen bezirke

label: Übersicht über alle Listen der Kantonsratswahlen

de: Kantonsratswahlen: Wähleranteil BDP [%]

de: Wähleranteil aller Listen der Partei BDP bei den Kantonsratswahlen

kantonsratswahlen

display_name: kantonsratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico


kuhe-anz

title_for_slug: kuhe-anz

de: bezirke gemeinden

de: Kühe [Anz.]

de: Anzahl Kühe

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


steuerfuss-juristische-personen

title_for_slug: steuerfuss-juristische-personen

de: gemeinden kantonzuerich steuern gemeindesteuerfuesse gemeindesteuern steuerfuss

de: Steuerfuss juristische Personen [%]

de: Steuerfuss für juristische Personen. Details zu angewendeten Steuerfüssen sind direkt bei den jeweiligen Gemeinden einzuholen.

gemeindesteuerfuesse

display_name: gemeindesteuerfuesse

gemeindesteuern

display_name: gemeindesteuern

kantonzuerich

display_name: kantonzuerich

steuerfuss

display_name: steuerfuss

steuern

display_name: steuern

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze


reformierte-kirchensteuerpflichtige-anz

title_for_slug: reformierte-kirchensteuerpflichtige-anz

de: kantonzuerich kirchensteuer steuerpflichtige gemeinden bezirke oeffentlichefinanzen

de: Reformierte Kirchensteuerpflichtige

kirchensteuer

display_name: kirchensteuer

oeffentlichefinanzen

display_name: oeffentlichefinanzen

steuerpflichtige

display_name: steuerpflichtige


maintainer: Fachstelle Open Government Data des Kantons Zürich

de: vereine einzelfirmen zefix shab wirtschaft gmbh unternehmensdaten ehra branchen firmen konkurse handelsregister stiftungen genossenschaften unternehmen

label: Neugründungs- und Konkursstatistik Kanton Zürich

label: Zentraler Firmenindex Zefix (Eidgenössisches Amt für das Handelsregister)

de: Konkurseröffnungen nach Branchen im Kanton Zürich und der Schweiz insgesamt, wöchentlich aktualisiert

de: Anzahl der Eröffnungen von Konkursverfahren gegen Unternehmen und weitere Rechtseinheiten, wie sie im Zentralen Firmenindex (Zefix) mit Mutationstyp "KE Auflösung inf. Konkurs" ausgewiesenen sind. Die Meldungen werden mit den Branchenklassifikationen gemäss der Allgemeinen Systematik der Wirtschaftszweige (NOGA) angereichert und nach Branchen-Abschnitten (Grossbuchstaben) aggregiert. Aufgrund von Unterschieden bei der Datenerhebung kann es zu Abweichungen von anderen Auswertungen (zB. von kantonalen Handelsregisterämtern) kommen. Variabeln: 'br_abschnitt_red' = Auswahl von Branchen-Abschnitten (Grossbuchstaben) gemäss der Allgemeinen Systematik der Wirtschaftszweige (NOGA); 'location' = Kantonskürzel oder 'CH' für die Schweiz insgesamt; 'date' = Datum der Publikation im Schweizerischen Handelsamtsblatt (SHAB), die im Normalfall einige Tage nach der Publikation durch die kantonalen Ämter erfolgt; 'value' = Anzahl erstmaliger Konkursverfahrenseröffnungen per SHAB-Publikationsdatum; 'cumsum_diff' = Differenz der Anzahl Konkursverfahrenseröffnungen am SHAB-Publikationsdatum verglichen mit dem Durchschnitt Konkurseröffnungen der Vergleichsperiode 2017 bis 2019.

de: Neugründungen nach Branchen im Kanton Zürich und der Schweiz insgesamt, wöchentlich aktualisiert

de: keine

de: Wöchentlich aktualisierte Informationen zu den im Firmenzentralregister (Zefix) des Eidgenössischen Amts für das Handelsregister (EHRA) eingetragenen Unternehmen und weiteren Rechtseinheiten mit Sitz (Domiziladresse) im Kanton Zürich. Die Daten (Ressourcen) enthalten wöchentlich aktualisierte Konkurseröffnungen und Neugründungen nach Branche. Die Brancheninformation stammt aus dem Betriebs- und Unternehmensregister (BUR), dort sind NOGA-Codes hinterlegt. Das Statistische Amt plant weitere Daten als weitere Ressourcen zu veröffentlichen.

branchen

display_name: branchen

ehra

display_name: ehra

einzelfirmen

display_name: einzelfirmen

firmen

display_name: firmen

genossenschaften

display_name: genossenschaften

gmbh

display_name: gmbh

handelsregister

display_name: handelsregister

konkurse

display_name: konkurse

shab

display_name: shab

stiftungen

display_name: stiftungen

unternehmen

display_name: unternehmen

unternehmensdaten

display_name: unternehmensdaten

vereine

display_name: vereine

wirtschaft

display_name: wirtschaft

zefix

display_name: zefix

de: Tagesregistereinträge zum Kanton Zürich und der Schweiz aus dem Zentralen Firmenindex (Zefix) des Bundes


de: gemeinden kantonzuerich steuern steuerkraft bezirke

de: Steuerkraft ber. (arith. Mittel 3 Jahre) [Mio.Fr.]

de: Berichtigte Steuerkraft (Steuerkraft nach Finanzausgleich): arithm. Mittel der letzten 3 Jahre.

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

steuerkraft

display_name: steuerkraft

steuern

display_name: steuern


de: bevoelkerung kantonzuerich haushaltsgroesse gemeinden bezirke haushalte haushalt-typ

de: Anteil 3-Personenhaushalte [%]

de: Anteil Dreipersonenhaushalte an allen Privathaushalten

bevoelkerung

display_name: bevoelkerung

haushalt-typ

display_name: haushalt-typ

haushalte

display_name: haushalte

haushaltsgroesse

display_name: haushaltsgroesse

soci

de: Bevölkerung und Gesellschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


de: gemeinden vermoegen bezirke kantonzuerich steuerbaresvermoegen natuerlichepersonen

de: Steuerb. Vermögen natürl. Pers. 75%-Quantil [Fr.]

de: Steuerbares Vermögen natürlicher Personen des Kantonalen Steueramts. Das 75%-Quantil ist ein Schwellenwert: Drei Viertel der Bevölkerung liegt unter, das andere Viertel über diesem Wert.

natuerlichepersonen

display_name: natuerlichepersonen

steuerbaresvermoegen

display_name: steuerbaresvermoegen

vermoegen

display_name: vermoegen

econ

de: Wirtschaft und Finanzen


schul-kindergarten-anz

title_for_slug: schul-kindergarten-anz

de: schueler bezirke schuelerinnen schulen kantonzuerich gemeinden kindergarten

de: Schül. Kindergarten [Anz.]

de: Anzahl KindergartenschülerInnen inkl. Grundstufe (nach Wohnort)

kindergarten

display_name: kindergarten

schueler

display_name: schueler

schuelerinnen

display_name: schuelerinnen

schulen

display_name: schulen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport


bauzonen-uberbaut-ha

title_for_slug: bauzonen-uberbaut-ha

de: bezirke kantonzuerich bauzonen bauzonenverbrauch zonenart gemeinden bodennutzung

de: Bauzonen überbaut [ha]

de: Total überbaute Bauzonenfläche

bauzonen

display_name: bauzonen

bauzonenverbrauch

display_name: bauzonenverbrauch

bodennutzung

display_name: bodennutzung

zonenart

display_name: zonenart


de: gemeinden kantonzuerich sterbefaelle bevoelkerung bevoelkerungsbewegungen bezirke

de: Sterberate (5-J.-mittel) [pro 1000 Einw.]

de: Durchschnittliche Zahl von Sterbefällen im Fünfjahresmittel pro 1000 Einw. Beispiel: Die Zahl von 2003 entspricht dem Mittelwert der Sterbefällen von 1999-2003 in Bezug auf die Einwohnerzahl von 1998.

bevoelkerungsbewegungen

display_name: bevoelkerungsbewegungen

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

sterbefaelle

display_name: sterbefaelle


nrw-wahleranteil-bdp

title_for_slug: nrw-wahleranteil-bdp

de: parteien nationalratswahlen wahlen bezirke gemeinden kantonzuerich politik

label: Übersicht über alle Listen der Nationalratswahlen

de: Nationalratswahlen: Wähleranteil BDP [%]

de: Wähleranteil BDP bei Nationalsratswahlen. Hinweis: 2015 werden alle Auslandschweizer zur Stadt Zürich gezählt.

nationalratswahlen

display_name: nationalratswahlen

parteien

display_name: parteien

politik

display_name: politik

wahlen

display_name: wahlen

gove

de: Regierung und öffentlicher Sektor


bevolkerung-manner-pers

title_for_slug: bevolkerung-manner-pers

de: maenneranteil bezirke gemeinden geschlecht kantonzuerich bevoelkerung

de: Bevölkerung: Männer [Pers.]

de: Einwohnerbestand Männer nach zivilrechtlichem Wohnsitz (ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

bevoelkerung

display_name: bevoelkerung

geschlecht

display_name: geschlecht

maenneranteil

display_name: maenneranteil

soci

de: Bevölkerung und Gesellschaft

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


verkaufe-efh-anz

title_for_slug: verkaufe-efh-anz

de: kantonzuerich einfamilienhaus immobilien bezirke gemeinden eigentum handaenderungen

de: Verkäufe EFH [Anz.]

de: Anzahl verkaufter Einfamilienhäuser (EFH). Die letzten drei Jahre sind provisorisch.

eigentum

display_name: eigentum

einfamilienhaus

display_name: einfamilienhaus

handaenderungen

display_name: handaenderungen

immobilien

display_name: immobilien


de: strassen gemeinden verkehrsinfrastruktur bauinvestitionen strassenbau kantonzuerich bautaetigkeit bezirke

de: Bauinv. Strassen, PP 5 Jahre [Fr./Einw.]

de: Durchschnittliche Bauinvestitionen der letzten 5 Jahre im Bereich Strassen (Bauinv. für Strassen inkl. Parkplätze, ohne Nationalstrassenbau und ohne Strassenunterhalt), in Franken pro Einwohner.

bauinvestitionen

display_name: bauinvestitionen

bautaetigkeit

display_name: bautaetigkeit

strassen

display_name: strassen

strassenbau

display_name: strassenbau

verkehrsinfrastruktur

display_name: verkehrsinfrastruktur


leerwohnungen-total-anz

title_for_slug: leerwohnungen-total-anz

de: gemeinden wohnungen zimmerzahl bezirke kantonzuerich wohnungsbestand

de: Leerwohnungen Total [Anz.]

de: Leerstehende Wohnungen am 1. Juni des Erhebungsjahres

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand

zimmerzahl

display_name: zimmerzahl


de: bezirke kantonzuerich juristischepersonen eigenkapital gemeinden

de: Ø Eigenkapital steuerpfl. jur. Pers. [1000 Fr.]

de: Durchschnittliches Eigenkapital (ehem. Kapital) steuerpflichtiger juristischer Personen. Hinweis: Sehr hohe Beträge einiger weniger Steuerpflichtigen wirken sich entsprechend stark auf den Mittelwert aus.

eigenkapital

display_name: eigenkapital

juristischepersonen

display_name: juristischepersonen

econ

de: Wirtschaft und Finanzen


de: gemeinden freizeit bezirke oeffentlichefinanzen kantonzuerich kultur gemeindefinanzen nettoaufwendungen

de: Nettoaufwand Kultur, Sport und Freizeit [Fr./Einw.]

de: Bruttoaufwand - Bruttoertrag (der Laufenden Rechnung). Aussage: Durch Steuern zu finanzierender Anteil des betreffenden Hauptaufgabenbereichs. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Umstellung des Rechnungsmodells von HRM1 auf HRM2 ab Rechnungsjahr 2019.

freizeit

display_name: freizeit

gemeindefinanzen

display_name: gemeindefinanzen

kultur

display_name: kultur

nettoaufwendungen

display_name: nettoaufwendungen

oeffentlichefinanzen

display_name: oeffentlichefinanzen


de: oeffentlicherverkehr verkehrsmittelwahl bezirke gemeinden kantonzuerich

de: ÖV-Wege Quell-, Ziel- und Binnenverkehr [Anz.]

de: Das ÖV-Verkehrsaufkommen ist die Summe aller ÖV-Personenwege im Quell-, Ziel- und Binnenverkehr an einem durchschnittlichen Werktag (DWV). Mit Prognosezustand. Anzahl Wege pro Gemeinde, pro Planungsregion und ganzer Kanton.

oeffentlicherverkehr

display_name: oeffentlicherverkehr

verkehrsmittelwahl

display_name: verkehrsmittelwahl

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


bauzonen-nicht-uberbaut-ha

title_for_slug: bauzonen-nicht-uberbaut-ha

de: bodennutzung zonenart kantonzuerich bauzonen bauzonenverbrauch gemeinden bezirke nutzungsreserven

de: Bauzonen nicht überbaut [ha]

de: Total nicht überbaute Bauzonenfläche

bauzonen

display_name: bauzonen

bauzonenverbrauch

display_name: bauzonenverbrauch

bodennutzung

display_name: bodennutzung

nutzungsreserven

display_name: nutzungsreserven

zonenart

display_name: zonenart

soci

de: Bevölkerung und Gesellschaft


steuerertrag-kirchgemeinden-mio-fr

title_for_slug: steuerertrag-kirchgemeinden-mio-fr

de: gemeindefinanzen steuerertrag gemeinden kirchgemeinden bezirke steuern kantonzuerich

de: Steuerertrag Kirchgemeinden [Mio.Fr.]

de: Steuerertrag Kirchgemeinden (Nettoertrag Rechnungsjahr).

bezirke

display_name: bezirke

gemeinden

display_name: gemeinden

kantonzuerich

display_name: kantonzuerich

kirchgemeinden

display_name: kirchgemeinden

steuerertrag

display_name: steuerertrag

steuern

display_name: steuern


bevolkerung-heimat-ausland-pers

title_for_slug: bevolkerung-heimat-ausland-pers

de: kantonzuerich bevoelkerung heimat bezirke nationalitaet auslaender gemeinden

de: Bevölkerung: Heimat Ausland [Pers.]

de: Einwohnerbestand Ende Jahr Heimat Ausland nach zivilrechtlichem Wohnsitz (ab 2010 inkl. vorläufig Aufgenommene, die seit mehr als einem Jahr in der Gemeinde leben, aber ohne Wochenaufenthalter und Asylbewerber).

auslaender

display_name: auslaender

bevoelkerung

display_name: bevoelkerung

heimat

display_name: heimat

nationalitaet

display_name: nationalitaet


total-quellensteuerpflichtige-anz

title_for_slug: total-quellensteuerpflichtige-anz

de: bezirke oeffentlichefinanzen kantonzuerich steuerpflichtige gemeinden

de: Total Quellensteuerpflichtige [Anz.]

de: Anzahl Quellensteuerpflichtige

oeffentlichefinanzen

display_name: oeffentlichefinanzen

steuerpflichtige

display_name: steuerpflichtige

econ

de: Wirtschaft und Finanzen


de: nettoaufwendungen gemeindefinanzen gemeinden gemeindesteuern steuern kantonzuerich oeffentlichefinanzen bezirke

de: Nettoaufwand Finanzen und Steuern [Fr./Einw.]

de: Bruttoaufwand - Bruttoertrag (der Laufenden Rechnung). Aussage: Durch Steuern zu finanzierender Anteil des betreffenden Hauptaufgabenbereichs. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Umstellung des Rechnungsmodells von HRM1 auf HRM2 ab Rechnungsjahr 2019.

gemeindefinanzen

display_name: gemeindefinanzen

gemeindesteuern

display_name: gemeindesteuern

nettoaufwendungen

display_name: nettoaufwendungen


neuerstellte-mfh-wohnungen-whg

title_for_slug: neuerstellte-mfh-wohnungen-whg

de: wohnbautaetigkeit immobilien mehrfamilienhaus kantonzuerich gemeinden bezirke

de: Neuerstellte MFH-Wohnungen [Whg.]

de: Neu erstellte Wohnungen in Mehrfamilienhäusern

immobilien

display_name: immobilien

mehrfamilienhaus

display_name: mehrfamilienhaus

wohnbautaetigkeit

display_name: wohnbautaetigkeit

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.


beschaftigte-im-gastgewerbe-anteil

title_for_slug: beschaftigte-im-gastgewerbe-anteil

de: bezirke gemeinden gastgewerbe kantonzuerich wirtschaftssektor beschaeftigte

de: Beschäftigte im Gastgewerbe: Anteil [%]

de: Anteil der im Bereich Beherbergung/Gastgewerbe Beschäftigten (ohne Gastronomie) an den Beschäftigten des 2. und 3. Sektors. Beherbergung/Gastgewerbe: ab 2008: I55 (NOGA2008); bis 2005: HA55 (NOGA2002). Bruch in der Reihe zwischen 2008 und 2011 aufgrund des Übergangs von der alten BZ-Methodik auf STATENT. Daten des aktuellsten Jahres provisorisch.

beschaeftigte

display_name: beschaeftigte

bezirke

display_name: bezirke

gastgewerbe

display_name: gastgewerbe

gemeinden

display_name: gemeinden

wirtschaftssektor

display_name: wirtschaftssektor


motorrader-anz

title_for_slug: motorrader-anz

de: privatverkehr motorfahrzeugbestand fahrzeuge motorfahrzeuge gemeinden bezirke kantonzuerich motorraeder

de: Motorräder [Anz.]

de: Am 30. September eingelöste Motorräder. Hinweis: Der Wert für den ganzen Kanton umfasst alle Motorräder mit einem Zürcher Kennzeichen; diese können auch Personen oder Unternehmen gehören, die ihr Domizil nicht im Kanton Zürich haben.

fahrzeuge

display_name: fahrzeuge

kantonzuerich

display_name: kantonzuerich

motorfahrzeugbestand

display_name: motorfahrzeugbestand

motorfahrzeuge

display_name: motorfahrzeuge

motorraeder

display_name: motorraeder

privatverkehr

display_name: privatverkehr

tran

de: Verkehr


gemeindebeitrag-an-zvv-fr-einw

title_for_slug: gemeindebeitrag-an-zvv-fr-einw

de: oeffentlichefinanzen bezirke gemeinden kantonzuerich zvv oeffentlicherverkehr

de: Gemeindebeitrag an ZVV [Fr./Einw.]

de: Der Beitrag errechnet sich aus dem auf die Gemeinden entfallenden Defizit und wird anteilsmässig nach Angebot (Anzahl Abfahrten, Ant. 80%) und der absoluten, berichtigten Steuerkraft (Ant. 20%) verteilt. Der Gemeindebeitrag wird gemessen an der Einwohnerzahl Ende Vorjahr.

oeffentlichefinanzen

display_name: oeffentlichefinanzen

oeffentlicherverkehr

display_name: oeffentlicherverkehr

zvv

display_name: zvv


ertrags-aufwanduberschuss-fr-einw

title_for_slug: ertrags-aufwanduberschuss-fr-einw

de: nettoaufwendungen oeffentlichefinanzen gemeindefinanzen bezirke gemeinden kantonzuerich

de: Ertrags- (+) / Aufwandüberschuss (-) [Fr./Einw.]

de: Jahresergebnis Erfolgsrechnung. Ertragsüberschuss (positives Vorzeichen) oder Aufwandüberschuss (negatives Vorzeichen). Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Grundlage ist die Konsolidierte Gemeinde. Der Haushalt der Schulgemeinde wird dabei anteilsmässig in den Haushalt der poltischen Gemeinden umgelegt. Umstellung des Rechnungsmodells von HRM1 auf HRM2 ab Rechnungsjahr 2019.

gemeindefinanzen

display_name: gemeindefinanzen

nettoaufwendungen

display_name: nettoaufwendungen

econ

de: Wirtschaft und Finanzen


o-reingewinn-steuerpfl-jur-pers-fr

title_for_slug: o-reingewinn-steuerpfl-jur-pers-fr

de: gemeinden bezirke juristischepersonen kantonzuerich reingewinn

de: Ø Reingewinn steuerpfl. jur. Pers. [Fr.]

de: Durchschnittlicher Reingewinn (ehem. Ertrag) steuerpflichtiger juristischer Personen. Hinweis: Sehr hohe Beträge einiger weniger Steuerpflichtigen wirken sich entsprechend stark auf den Mittelwert aus.

juristischepersonen

display_name: juristischepersonen

reingewinn

display_name: reingewinn


name: Statistisches Amt des Kantons Zürich, Wahlen & Abstimmungen

de: politischegemeinden kantonzuerich politischeparteien gemeindewahlen wahlergebnisse politik gemeinden wahlen

label: Gemeindewahlen

de: Ergebnisse der Erneuerungswahlen der Zürcher Gemeindeparlamente. Abgebildet sind sämtliche über die den Gemeinden vom Kanton Zürich zur Verfügung gestellte Wahl- und Abstimmungssoftware abgewickelten Gemeindeparlamentswahlen 2022. Gemeinden sind nicht verpflichtet, die Wahlen mit besagter Software abzuwickeln. Ausserdem ist es möglich, dass gewählte Personen die Wahl ablehnen. Der rechtskräftig gewordene Ausgang einer Wahl wird lediglich von der entsprechenden Gemeinde publiziert.

de: Dokumentation Gemeindeparlamentswahlen

de: Erklärungen und Definitionen der einzelnen Variablen für die Ressourcen dieses Datensatzes

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Listen

de: Ergebnisse der kommunalen Parlamentswahlen 2022 auf Ebene Kandidierende

gemeindewahlen

display_name: gemeindewahlen

politik

display_name: politik

politischegemeinden

display_name: politischegemeinden

politischeparteien

display_name: politischeparteien

wahlen

display_name: wahlen

wahlergebnisse

display_name: wahlergebnisse

gove

de: Regierung und öffentlicher Sektor

statistisches-amt-kanton-zuerich

de: Statistisches Amt Kanton Zürich

de: Das Statistische Amt ist das Kompetenzzentrum für die öffentliche Statistik im Kanton Zürich. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Informationen und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

de: Archiv Wahlresultate Gemeindeparlamentswahlen im Kanton Zürich


maintainer: Frank Techel

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

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

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

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

educ

de: Bildung, Kultur und 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.

political_level: other

value: Envidat Harvester

en: Re-analyzed regional avalanche danger levels in Switzerland


maintainer: EnviDat Support

en: snowmicropen terrestrial-laser-scanning antarctica mass-flux meteorological-data drifting-snow

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: Dataset

en: Links to the dataset

format: SERVICE

en:
This dataset contains the data acquired during the expedition to Princess Elisabeth Antarctica Station in December 2016 and January 2017. The dataset consits of meterorological data, drifting snow mass flux data, SnowMicroPen data and Terrestrial Laser Scanning data.

Please refer to the README for more information about the data.

This dataset is the basis of the following publication:

Sommer, C. G., Wever, N., Fierz, C., and Lehning, M.: Wind-packing of snow in Antarctica, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-36, in review, 2018.

antarctica

display_name: antarctica

drifting-snow

display_name: drifting-snow

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

snowmicropen

display_name: snowmicropen

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

en: Expedition to Princess Elisabeth Antarctica Station, 2016/2017


maintainer: Joan Casanelles Abella

en: paris angiospermae zurich floral-resources poznan antwerp tartu urban floral-inventories plants

en: Floral units, mean number of flowers per floral unit and floral abundance of the different plants counted in quadrats in the study sites in Zurich during the four sampling periods

en: Trait values for the sampled plants

en: List of plant species sampled in the five cities (Antwerp, Paris, Poznan, Tartu and Zurich) during the different sampling perionds (four for Zurich, three for the other cities) with their frequency (oc1-oc16) within a 100 m radius

en: Data of a survey of flowering plants in 80 sites in five European cities and urban agglomerations (Antwerp, Belgium; greater Paris, France; Poznan, Poland; Tartu, Estonia; and Zurich, Switzerland) sampled between April and July 2018.

angiospermae

display_name: angiospermae

antwerp

display_name: antwerp

floral-inventories

display_name: floral-inventories

floral-resources

display_name: floral-resources

paris

display_name: paris

plants

display_name: plants

poznan

display_name: poznan

tartu

display_name: tartu

urban

display_name: urban

zurich

display_name: zurich

en: Flowering Plants (Angiospermae) in Urban Green Areas in five European Cities


en: natural-avalanches avalanche-size snowpack-model avalanche machine-learning

en: Data set AV2 used for training the avalanche-size estimator (Sections 2.1.2 and 3.2 in Mayer et al.)

en: Data set DL was used for validation of the avalanche-day classifier and the avalanche-size estimator. The data set contains the quality-checked danger levels merged with the respective SNOWPACK simulations (Sections 2.3 and 3.3(2) in Mayer et al.).

en: Data set AV1 was used for training the avalanche-day classifier (Sections 2.1.1, 2.2, and 3.1 in Mayer et al.).

en: Data set AV3 was used for validation of the avalanche-day classifier (Sections 2.1.3 and 3.3(1) in Mayer et al.).

en:
The data set contained in this repository was used in the analysis by Mayer et al. (2023):
Mayer, S. I., Techel, F., Schweizer, J., and van Herwijnen, A.: Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations, EGUsphere, https://doi.org/10.5194/egusphere-2023-646, 2023.

avalanche

display_name: avalanche

avalanche-size

display_name: avalanche-size

machine-learning

display_name: machine-learning

natural-avalanches

display_name: natural-avalanches

snowpack-model

display_name: snowpack-model

educ

en: Education, culture and sport

en: Data-set for prediction of natural dry-snow avalanche activity and avalanche size using physics-based snowpack simulations


en: climate-change-impact snow-water-equivalent cryosphere rain-on-snow natural-climate-variability uncertainty

en: climate realizations

en: The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty

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: Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century


maintainer: Henning Löwe

en: spherical-model-snow discrete-element-modelling 3d-ct-images unconfined-compression-experiments snow-mechanics microstructure

en: Data Structure (Python Notebook)

en: Data Access

en: Data Structure (Python Notebook - view online)

en:
For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles.
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).

discrete-element-modelling

display_name: discrete-element-modelling

microstructure

display_name: microstructure

snow-mechanics

display_name: snow-mechanics

spherical-model-snow

display_name: spherical-model-snow

unconfined-compression-experiments

display_name: unconfined-compression-experiments

en: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples


en: albedo winter-energy-production shortwave-radiation photovoltaic snow

en: Data Forward Scattering

en: GROUNDEYE model for multiple forward scattering in snow-covered terrain. Meteorological and topographical input data set for the Meierhofertäli near Davos, Switzerland, September 2017 - August 2018. Output data for September 2017 - August 2018 at hourly resolution and every pixel. Post-processing scripts for plotting and analysis.

en:
 Overview
We present GROUNDEYE, a new model of radiative transfer over mountainous terrain, which considers for the first time the forward scattering properties of snow.
Embedded in the surface process model Alpine3D, the new terrain radiation model GROUNDEYE receives interpolated real weather data with diffuse and direct broadband shortwave radiation for each pixel as well as a spatially variable plane albedo from the module SNOWPACK.

 Format
The GROUNDEYE model is written in c++, as is the entire environment of Alpine3d. The input and output data sets are .xlsx or .txt format, pre- and postprocessing including the generation of all figures is in .R format.

 Structure
In Data_Forward_Scattering.zip you will find all necessary data and model details to
reproduce the results of the JGR publication "How forward-scattering snow and terrain change the Alpine radiation balance with application to solar panels"

 - 	Model Input Data contains the meteorological and topographic input data sets, the BRDF, and preprocessing scripts.
 - Model Code contains the full model Alpine3d including the radiative transfer module GROUNDEYE.
 - Model Output Data contains the results of the simulation of terrain irradiance and irradiance of solar panels; hourly resolution, 1. Sptember 2017 - 31. August 2018.
 - Measurements Solar Testsite contains information and measurements of the solar testsite at the Totalp near Davos, Switzerland.
 - Postprocessing contains all R-Scripts used for the analysis and
plotting of the corresponding data.

In each of these folders you will find detailed information in
the file 'About this Folder.txt'.

albedo

display_name: albedo

photovoltaic

display_name: photovoltaic

shortwave-radiation

display_name: shortwave-radiation

snow

display_name: snow

winter-energy-production

display_name: winter-energy-production

en: Data, Code Link and Metadata on Forward Scattering of Snow at Totalp


backward-trajectories

maintainer: Michael Sprenger

title_for_slug: backward-trajectories

en: raclets alps complex-topopgraphy cosmo lagrangian-analysis backward-trajectories atmospheric-dynamics

en: Backward Trajectories

media_type: application/zip

en: The trajectories are started from surface up to 5000 m altitude, with an equidistant vertical spacing of 200 m, and calculated 120 h backward in time. As long as the trajectories stay in the COSMO1 domain (essentially the Alpine region), as run operationally at MeteoSwiss, the COSMO analysis wind fields are used. When the trajectories leave this domain, they are extended further backward in time based on ECMWF analysis data. The following fields are traced along the trajectories: longitude, latitude, geopotential height, pressure, specific humidity, temperature and surface topography. Furthermore, it is indicated for each trajectory time instance on which model data, COSMO or ECMWF, the trajectory time is based. Finally, the trajectories are started every hour in the specified time period, and positions and fields are available every 10 min. Each day is saved as a separate file. The last 8 digits of the file names indicate the starting date of the trajectories.

format: ZIP

mimetype: application/zip

en: Backward trajectories were calculated from two positions: Davos Wolfgang (LON: 9.85361, LAT: 46.83551) and Weissfluhjoch (LON: 9.80646 LAT: 46.83304) for the time period February 2 until March 27 2019 using COSMO or ECMWF, respectively.

alps

display_name: alps

atmospheric-dynamics

display_name: atmospheric-dynamics

backward-trajectories

display_name: backward-trajectories

complex-topopgraphy

display_name: complex-topopgraphy

cosmo

display_name: cosmo

lagrangian-analysis

display_name: lagrangian-analysis

raclets

display_name: raclets

educ

en: Education, culture and sport

en: Backward  Trajectories


en: microclimate climate-change ecology statistical-interpolation radiation-transfer forest biodiversity

en: Predicted microclimate air temperatures at 100 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate topsoil temperatures at 5 cm below ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate air temperatures at 5 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate-change impacts on biodiversity and ecosystem functioning. Here we combine a national network of microclimate temperature measurements with a novel radiative transfer model to map monthly minimum, mean and maximum temperatures during the vegetation period at a 10 meter spatial resolution across Switzerland. The temperature measurements took place in 107 sampling plots distributed across different habitat types, with 62 plots in forests, 22 below trees outside forests, and 23 in open grasslands. In each plot we measured temperature in the topsoil (-5cm), as well as in the air at 5cm and 100cm height above ground. Spatial interpolation was achieved by using a hybrid approach based on linear mixed effects models with input from detailed radiation estimates that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography and vegetation height. Our data reveals strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 °C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 °C. We also found that in open grasslands, maximum temperatures at 5 cm above ground are on average 3.4 °C warmer than that of macroclimate, suggesting that in such habitats heat exposure close to the ground is often underestimated when using macroclimatic data. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by RSME’s ranging from 1.18 to 3.43 °C, with minimum temperatures generally being predicted more accurately than maximum temperatures. The microclimate maps presented here enable a more biologically relevant perspective when analysing climate-species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change.

biodiversity

display_name: biodiversity

climate-change

display_name: climate-change

ecology

display_name: ecology

forest

display_name: forest

microclimate

display_name: microclimate

radiation-transfer

display_name: radiation-transfer

statistical-interpolation

display_name: statistical-interpolation

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: Monthly topsoil and near surface microclimate temperature data for Switzerland


en: phylogenetic-diversity species-distribution-models plants global-change european-alps conservation zonation taxonomic-diversity functional-diversity migclim land-use-change beta-diversity

en: Data Access

format: GeoTIFF

en:
This repository contains extensive data for the European Alps:
  - Observations of ~3,500 plant species
  - Climate (1-km), soil (100-m) and land cover predictors (1km); current and future scenarios (28 CMIP6-GCMs, 2 land cover change and 3 dispersal scenarios i.e., unlimited, no and realistic vegetation dispersal)
  - Flora migration rates (categorical) and ecological preferences (continuous indicator values)
  - Regional maps of barriers to migration and water bodies at 100-m resolution
  - Sampling effort, distance to roads and cities predictors at 100-m resolution
  - Present and future abundances over the study region at 1-km resolution (~2,000 species)
  - Present and future multifaceted and uniqueness of the European Alps' Flora at 1-km resolution
  - Present and future conservation recommendations at 1-km resolution (26 current and future strategies)
  - Phylogenetic data and functional traits of ~2,000 plants (raw data and classification trees)
  - All scripts, data and plots used for the analyses, including a singularity container (mini-linux) to run them

beta-diversity

display_name: beta-diversity

conservation

display_name: conservation

european-alps

display_name: european-alps

functional-diversity

display_name: functional-diversity

global-change

display_name: global-change

land-use-change

display_name: land-use-change

migclim

display_name: migclim

phylogenetic-diversity

display_name: phylogenetic-diversity

plants

display_name: plants

species-distribution-models

display_name: species-distribution-models

taxonomic-diversity

display_name: taxonomic-diversity

zonation

display_name: zonation

en: Present and future multifaceted plant diversity, uniqueness and conservation in the European Alps


en: wind precipitation radiation atmospheric-conditions temperature-profiles

en: README

en: This description is outdated and has been replaced with an updated version (see description).

en: Site photo 2

en: This site photo is outdated and has been replaced with an updated version (see description).

en: Latest data from Stillberg climate station

en: This dataset is outdated and has been replaced with an updated version (see description).

en: STB2 CSV

en: Site photo 1

en: DATA ACCESS

en: This data access is outdated and has been replaced with an updated version (see description).

en: Site photo 3

en: Overview plot

media_type: image/png

en: This overview plot is outdated and has been replaced with an updated version (see description).

format: PNG

en:
 Important

This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.." The entry can be found under this link <https://www.envidat.ch/dataset/meteo-stillberg> and with this DOI https://doi.org/10.16904/envidat.396.

atmospheric-conditions

display_name: atmospheric-conditions

precipitation

display_name: precipitation

radiation

display_name: radiation

temperature-profiles

display_name: temperature-profiles

wind

display_name: wind

en: Long-term meteorological and snow station at 2090 m a.s.l., Stillberg, Davos, Switzerland (1975 - present)


maintainer: Chunhong Zhao

en: urban-morphology austin landscape land-use land-dynamics

en: Land use dynamics in Austin since 1992

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

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: Land use/cover dynamics in Austin metropolitan area since 1992


maintainer: James W. Kirchner

en: plynlimon precipitation catchment stable-water-isotopes tracer deuterium chloride streamflow

en: Weekly stable water isotopes

en: Data set of weekly stable water isotope data collected at Carreg Wen (precipitation) and Lower Hafren and Tanllwyth (streamflow).

en: Data Set Documentation

media_type: application/pdf

en: This file contains a documentation of the data sets, including references to other helpful documentations.

format: PDF

mimetype: application/pdf

en: 7-hourly stable water istopes

en: Data set of 7-hourly stable water isotope data measured at Carreg Wen (precipitation) and Upper Hafren (streamflow).

en: The data base contains timeseries of stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK. One data set contains weekly stable water isotope data from the Lower Hafren and Tanllwyth catchments, and the other data set contains 7-hourly stable water isotope data from Upper Hafren. Both data sets also include chloride concentrations in precipitation and streamflow.

catchment

display_name: catchment

chloride

display_name: chloride

deuterium

display_name: deuterium

plynlimon

display_name: plynlimon

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow

tracer

display_name: tracer

en: Stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK


maintainer: Matthias Haeni

en: climate-change relative-humidity meteo precipitation par swiss-forest-lab temperature long-term meteorology wind-speed

en: Site aerial photo (Visp)

en: Site aerial photo from both Visp stations. Source: Google. 2016. Site aerial photo from both Visp stations. Retrieved November 11, 2016, from https://www.google.ch/maps

mimetype: image/jpeg

en: Data plot of the field station (VSF)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the forest station (VSB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Site photo of the field station (VSF)

en: Site photo of the field station from the side.

en: Data plot of the forest station (VSB)

en: Forest station data (VSB)

en: Data file.

en: Field station data (VSF)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Visp in Switzerland where one station is located within a natural mixed forest stand (VSB) with Scots pine (_Pinus sylvestris_; 40-80 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, VSF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Visp is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Visp, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Marcia Phillips

en: permafrost ritigraben permos meteo-station borehole

en: DATA ACCESS

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

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: RIT2: Meteorological station at Ritigraben borehole site


en: restoration plants grassland topsoil-removal biodiversity soil soil-chemistry soil-biodiversity bacteria soil-biology fungi nematodes

en: Soil properties

en:
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)
N.pool	Soil nitrogen pool (June 2017); corrected for bulk density and 12 cm sampling depth [kg ha-1 12cm-1]
Corg.pool	Soil organic carbon pool (June 2017); corrected for bulk density and 12 cm sampling depth [kg ha-1 12cm-1]
pH	soil pH [CaCl2]
BD	Bulk density [g cm-3]
FC	Field capacity [%]
Veg.1	principle coordinate axis 1 (vegetation)
Veg.1	principle coordinate axis 2 (vegetation)
Nem.1	principle coordinate axis 1 (nematoda)
Nem.2	principle coordinate axis 2 (nematoda)
Fun.1	principle coordinate axis 1 (fungi)
Fun.2	principle coordinate axis 2 (fungi)
Prok.1	principle coordinate axis 1 (prokaryota)
Prok.2	principle coordinate axis 2 (prokaryota)
Veg.H	Shannon diversity (vegetation)
Nem.H	Shannon diversity (nematoda)
Fun.H	Shannon diversity (fungi)
Prok.H	Shannon diversity (prokaryota)

en: Networks

en:
Treatment	Treatment groups; Y.4-18 = restored grasslands; Initial = intensively managed grasslands; Target = species-rich semi-wet to semi-dry grasslands
Correlation	non-parametric Spearman rank correlations
Vertex.1+2	Comparison between network components; N.pool = total soil nitrogen pool [kg ha-1 12 cm-1]; Corg.pool = soil organic carbon pool [kg ha-1 12 cm-1], pH = soil pH [CaCl2]; BD = bulk density [g cm-3]; FC = field capacity [%]
	PCoA 1 + 2 biotic communities [Veg = vegetation; Nem = nematoda; Fun = fungi; Prok = prokaryota]
Type	Interactions type; A.A = abiotic.abiotic; A.B = abiotic.biotic; B.B = biotic.biotic

en: Nematode data

en:
Sample.data
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)

Taxonomy
ASV.ID	unit number.letter code per amplicon sequence variant (in total 904)
Taxonomic rank	Phylum, Class, Order, Family, Genus, Species

Abundance
columns	Plot.ID (see Sample.data)
rows	ASV.ID (see Taxonomy)

en: Distance to target results

en:
Community	biotic community (vegetation, nematoda, fungi, prokaryota)
Treatment	Treatment groups; Y.4-30= restored grasslands (time since restoration); Initial=intensively managed grasslands (I)
Comparison	within- or between-community Bray-Curtis dissimilarity distance comparison
Label	within-community distances of initial/restored grasslands: treatment abbreviation; between-communities distances of initial/restored-to-target grasslands: treatment abbreviation plus Target (T; species-rich grasslands)
mean	Mean distance to Target (6 plots per treatment group)
sd	Standard deviation of distances to Target (6 plots per treatment group)

en: Ecosystem coupling_interactions

en:
Treatment	Treatment groups; Y.4-18 = restored grasslands; Initial = intensively managed grasslands; Target = species-rich semi-wet to semi-dry grasslands
Type	Interactions type; A.A = abiotic.abiotic; A.B = abiotic.biotic; B.B = biotic.biotic
Correlation	non-parametric Spearman rank correlations between biotic and abiotic parameters (ecological interactions)

en: Vegetation data

en:
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)
column I-LW	Plant abundance per species (in total 327 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: Fungi data

en:
Sample.data
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)

Taxonomy
OTU.ID	consecutive numbers for operational taxonomic units (OTUe 1-7794)
Taxonomic rank	Domain, Phylum, Class, Order, Family, Genus, Species

Abundance
columns	Plot.ID (see Sample.data)
rows	OTU.ID (see Taxonomy)

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

Paper Citation:

_Resch, M.C., Schütz, M., Ochoa-Hueso, R., Buchmann, N., Frey, B., Graf, U., van der Putten, W.H., Zimmermann, S., Risch, A.C. (in review). Long-term recovery of above- and belowground interactions in restored grassland after topsoil removal and seed addition. Journal of Applied Ecology_

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

Study area and experimental design
The study was conducted in and around two nature reserves, Eigental and Altläufe der Glatt, which were located approximately 5 km apart (47°27´ to 47°29´ N, 8°37´ to 8°32´ E, 417 to 572 m a.s.l., Canton of Zurich, Switzerland; Figure S1 and S2, Table S1). Mean annual temperature and precipitation are 9.8 ± 0.6 °C and 990 ± 168 mm (Kloten climate station 1988-2018; MeteoSchweiz, 2019). TFor this study, we used a space-for-time approach based on eight restoration sites that were between 3 and 32 years old. We measured recovery and restoration success by comparing the restored grasslands with intensively managed and semi-natural grasslands. Using a space-for-time approach requires high similarities in historical properties of the site, such as soil conditions and management regimes, to assure that temporal processes are appropriately represented by spatial patterns (Walker et al., 2010). This was the case in our study. The restored sites had similar soil conditions (i.e., soil type, structure, water availability) as the targeted semi-natural grasslands, while they shared the same agricultural legacy with intensively managed grasslands, i.e., biomass harvest and fertilization (manure and/or slurry) three to five times a year as well as tillage. We randomly established three 5 m x 5 m (25-m2) plots for plant identification and three 2 m x 2 m (4-m2) subplots for soil biotic and abiotic data collection at least 2 m away from the 25-m2 plots in each restoration site. Sites of similar age were grouped into four age classes: Y.4 (3 & 4 years after restoration), Y.18 (17 & 19 years), Y.24 (23 & 25 years), and Y.30 (27 & 32 years). Six intensively managed (Initial) and six semi-natural grassland (Target) sites complemented the experimental set-up, for a total of 36 plots. All plots were sampled under similar conditions, i.e., day of the year, air temperature, soil moisture, and time since last rain event, in June/July 2017 (intensively managed and semi-natural plots) and 2018 (restored plots).

Collection of plants and selected soil biota data
Plant species cover (in %) was visually estimated in each 25-m2 plot in mid-June (Braun-Blanquet, 1964; nomenclature: Lauber & Wagner, 1996). We calculated Shannon diversity and assessed plant community structure. We included soil microbial (fungi, procaryotes) and nematodes in our study as they represent the majority of soil biotic diversity and abundance (Bardgett & van der Putten, 2014), cover various trophic levels of the soil food web (Bongers & Ferris, 1999), and play key roles in soil functioning and ecosystem processes (Bardgett & van der Putten, 2014). In particular, soil nematodes were found to be well suited belowground indicators to evaluate recovery/development after restoration (e.g. Frouz, et al. 2008; Kardol et al., 2009; Resch et al., 2019). We randomly collected ten soil cores (2.2 cm diameter x 12 cm depths; sampler from Giddings Machine Company, Windsor, USA) in the 4-m2 subplots to assess soil nematode and microbial (fungal, prokaryotic) diversities and community structures. For soil nematodes, eight of the soil cores were combined and gently homogenized, placed in coolers and stored at 4 °C and transported to the laboratory (Netherlands Institute of Ecology, NIOO, Wageningen, Netherlands) within three days after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriators (Oostenbrink, 1960). After extraction, each sample was divided into three subsamples, two for molecular identification and one to determine nematode abundance (see Resch et al., 2019). For the molecular work, two subsamples were stored in 70% ethanol (final volume 10 mL each) and transported to the laboratory at the Swiss Federal Research Institute WSL (Birmensdorf, Switzerland). Each subsample was reduced to roughly 200 μL by centrifugation and removal of the supernatant. The remaining ethanol was vaporized (65 °C for 3 h). Thereafter, 180 μL ATL buffer solution (Qiagen, Hilden, Germany) was immediately added and samples were stored at 4 °C until further processing. From these samples, nematode metagenomic DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer`s protocol, except for the incubation step which was run at 56 °C for 4 h. PCR amplification of the V6-V8 region of the eukaryotic small-subunit (18S) was performed with 7.5 μL of genomic DNA template (ca. 1 ng/μL) in 25 μL reactions containing 5 μL PCR reaction buffer, 2.5 mM MgCL2, 0.2 mM dNTPs, 0.8 μM of each primer (NemF: Sapkota & Nicolaisen, 2015; 18Sr2b: Porazinska et al., 2009), 0.5 μL BSA, and 0.25 μL GoTaq G2 Hot Start Polymerase (Promega Corporation, Madison, USA). Amplification was using an initial DNA denaturation step of 95 °C for 2 min, followed by 35 cycles at 94 °C for 40 sec, 58 °C for 40 sec, 72 °C for 1 min, and a final elongation step at 72 °C for 10 min. Filtering, dereplication, sample inference, chimera identification, and merging of paired-end reads was implemented using the DADA2 pipeline (v.1.12; Callahan et al., 2016) to finally assign amplicon sequence variants (ASVs) as taxonomic units.
We combined and homogenized the remaining two soil cores to assess soil microbes, placed them in coolers (4 °C) and transported them to the laboratory at WSL. Metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNAeasy PowerMax Soil Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol. PCR amplification of the V3-V4 region of the small-subunit (16S) of prokaryotes (i.e., bacteria and archaea) and the ribosomal internal transcribed spacer region (ITS2) of fungi was performed with 1 ng of template DNA using PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates, pooled and sent to the Genome Quebec Innovation Centre (Montreal, QC, Canada) for barcoding using the Fluidigm Access Array technology (Fluidigm) and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, USA). Quality filtering, clustering into operational taxonomic units (OTUs, 97% similarity cutoffs) and taxonomic assignment were performed as previously described (Resch et al., 2021).Taxonomic classification of nematode, prokaryotic and fungal sequences was conducted querying against the most recent versions of PR2 (v.4.11.1; Guillou et al., 2013), SILVA (v.132; Quast et al., 2013), and UNITE (v.8; Nilsson et al., 2019) reference sequence databases. Taxonomic assignment cutoffs were set to confidence rankings ≥ 0.8 (below ranked as unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as OTUs or ASVs assigned to other than Fungi or Nematoda were manually removed prior to data analysis. The three datasets were filtered to discard singletons and doubletons. Taxonomic abundance matrices were rarefied to the lowest number of sequences per community to achieve parity of the total number of reads between samples (Prokaryotes: 10,929 reads; Fungi: 18,337 reads; Nematodes: 6,662 reads). We calculated Shannon diversity and assessed community structures for soil nematodes, prokaryotes and fungi based on their relative abundances of ASV or OTU at the taxon level.

Collection of soil physical and chemical properties
We randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) per 4-m2 subplot using a steel cylinder that fit into the soil corer. The cylinders were capped to avoid disturbance during transport and used to measure field capacity, rock content and fine earth density as previously described (Resch et al., 2021). We randomly collected another three soil cores (5 cm diameter, 12 cm depths) in each 4-m2 subplot to determine soil chemical properties. The cores were pooled, dried at 60 °C for 48 h and passed through a 2 mm sieve. We measured soil pH (CaCl2) on dried samples, total nitrogen (N) and organic carbon (C) concentration on dried and fine-ground samples (≤ 0.5 mm; for details see Resch et al., 2021). We calculated total N and organic C pools after correcting its concentration for soil depth, rock content and fine earth density.

bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

fungi

display_name: fungi

grassland

display_name: grassland

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil

display_name: soil

soil-biodiversity

display_name: soil-biodiversity

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

topsoil-removal

display_name: topsoil-removal

en: Long-term recovery of above-and belowground interactions in restored grasslands


lwf-tea-bag-sites

maintainer: Marcus Schaub

title_for_slug: lwf-tea-bag-sites

en: carbon decomposition roiboos modeling forest litter verification green-tea tea-bag

en: Site Information

en: Descriptive information on sites

en:
Decomposition of plant litter is a key process for the transfer of carbon and nutrients in ecosystems. Carbon contained in the decaying biomass is released to the atmosphere as respired CO2, and may contribute to global warming. Litterbag studies have been used to improve our knowledge of the drivers of litter decomposition, but they lack comparability because litter quality is plant species-specific. The use of commercial tea bags as a standard substrate was suggested in order to harmonize studies, where green tea and rooibos represent more labile and more recalcitrant C compounds as surrogates of local litter.
The tea bag approach was implemented on eight sites of the Swiss long-term Forest Ecosystem Research (LWF) network (https://www.wsl.ch/LWF). This allowed us to take advantage from the existing infrastructure and data from a previous litterbag study with local litter. In Beatenberg and Schaenis, additional elevation transects were established (1200-1800 m and 540-1150 m, respectively) to examine particularly the effect of temperature on decomposition. In Pfynwald (https://www.wsl.ch/de/ueber-die-wsl/versuchsanlagen-und-labors/flaechen-im-wald/pfynwald.html) and Salgesch, infrastructure of running projects was used to examine the effect of drought and understory removal, respectively. In Novaggio, tea bags were incubated in summer and winter to study the effect of seasonality particularly precipitation. Tea bags are collected after 3, 12, 24, and 36 months; for the two time-shifted experiments additionally after 6 and 9 months.
The study has two primary objectives. Firstly, it contributes to TeaComposition initiative (http://teacomposition.org/) which aims at investigating long-term litter decomposition and its key drivers at present as well as under different future climate scenarios using a common protocol and standard litter (tea) across nine terrestrial biomes. Secondly, the data are used to further develop decomposition models such as Yasso (http://en.ilmatieteenlaitos.fi/yasso) which is used by several countries, including Switzerland to estimate the annual carbon fluxes in dead wood, litter, and soil for reporting in National Greenhouse Gas Inventories under the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

carbon

display_name: carbon

decomposition

display_name: decomposition

forest

display_name: forest

green-tea

display_name: green-tea

litter

display_name: litter

modeling

display_name: modeling

roiboos

display_name: roiboos

tea-bag

display_name: tea-bag

verification

display_name: verification

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: LWF-Tea bag sites


en: temperature meteorology wind-speed par long-term climate-change relative-humidity meteo precipitation swiss-forest-lab

en: Field station data (OTF)

en: Data file.

en: Site photo of the forest station (OTB)

en: Site photo of the forest station from above (viewing downwards the slope).

en: Data plot of the forest station (OTB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Forest station data (OTB)

en: Data plot of the field station (OTF)

en: Site photo of the field station (OTF)

en: Site photo of the field station from below (viewing upwards the slope).

en: Site aerial photo (Othmarsingen)

en: Site aerial photo from both Othmarsingen stations. Source: Google. 2016. Site aerial photo from both Othmarsingen stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Othmarsingen, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


en: snow-depth boundary-layer-winds saltation snow-cover vertical-wind-motion

en: Data Compilation

en: Compressed TXT files

en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.

Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

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: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: envidat research-data-management open-science wsl juypter-notebooks

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

en: EnviDat Supports Open Science