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- Titel:
Root traits of grasslands rapidly respond to climate change, while community biomass mainly depends on functional composition
- Dokumenttyp:
- Forschungsdaten
- Veröffentlichungsdatum:
- 19.04.2023
- Verantwortlich:
- Rojas-Botero, Sandra Liliana
- Autorinnen / Autoren:
- Rojas-Botero, Sandra Liliana; Teixeira, Leonardo H.; Prucker, Paula; Kloska, Veronika; Kollmann, Johannes; Le Stradic, Soizig
- Institutionszugehörigkeit:
- TUM
- Herausgeber:
- TUM
- Identifikator:
- doi:10.14459/2023mp1706017
- Enddatum der Datenerzeugung:
- 18.08.2022
- Fachgebiet:
- RPL Raumplanung, Raumordnung; UMW Umweltwissenschaften
- zusätzliche Fachgebiete:
- Ecology, Climate change, Ecosystem functioning
- Quellen der Daten:
- Experimente und Beobachtungen / experiments and observations
- Datentyp:
- Tabellen / tables
- Methode der Datenerhebung:
- By the endpoint of the experiment, young mesocosm grasslands were harvested: above- and belowground biomass were collected considering two soil depths: 0 – 6 cm and 6 – 15 cm. Additionally, morphological traits of absorptive roots were measured: root diameter, root tissue density, specific root length, and root length density.
- Beschreibung:
- Collected data from an ecotron experiment conducted in the facility TUMmesa. Mesocosm grasslands were established and the allocation of biomass above- and belowground, as well as absorptive root traits were assessed under climate change conditions (i.e., two RCP scenarios and two precipitation regimes).
- Links:
- This dataset relates to the publication: https://doi.org/10.1111/1365-2435.14345
- Schlagworte:
- Belowground responses, climate change, grassland restoration, plant functional types, biomass allocation, root functional traits
- Technische Hinweise:
- View and download (32 KB total, 4 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1706017):
rsync rsync://m1706017@dataserv.ub.tum.de/m1706017/ - Sprache:
- en
- Rechte:
- by, http://creativecommons.org/licenses/by/4.0
- Horizon 2020:
- Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst (F.7-F5121.14.2.3/14/9) Deutsche Forschungsgemeinschaft (INST 95/1184- FUGG)
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