TY  - INPR
A1  - Cunliffe, Andrew M.
A1  - Anderson, Karen
A1  - Boschetti, Fabio
A1  - Brazier, Richard E.
A1  - Graham, Hugh A.
A1  - Myers-Smith, Isla H.
A1  - Astor, Thomas
A1  - Boer, Matthias M.
A1  - Calvo, Leonor
A1  - Clark, Patrick E.
A1  - Cramer, Michael D.
A1  - Encinas-Lara, Miguel Sebastián
A1  - Escarzaga, Stephen M.
A1  - Fernández-Guisuraga, José Manuel
A1  - Fisher, Adrian G.
A1  - Gdulová, Kateřina
A1  - Gillespie, Breahna M.
A1  - Griebel, Anne
A1  - Hanan, Niall P.
A1  - Hanggito, Muhammad S.
A1  - Haselberger, Stefan
A1  - Havrilla, Caroline A.
A1  - Heilman, Philip
A1  - Ji, Wenjie
A1  - Karl, Jason W.
A1  - Kirchhoff, Mario
A1  - Kraushaar, Sabine
A1  - Lyons, Mitchell B.
A1  - Marzolff, Irene
A1  - Mauritz, Marguerite E.
A1  - McIntire, Cameron D.
A1  - Metzen, Daniel
A1  - Méndez-Barroso, Luis Arturo
A1  - Power, Simon C.
A1  - Prošek, Jiří
A1  - Sanz-Ablanedo, Enoc
A1  - Sauer, Katherine J.
A1  - Schulze-Brüninghoff, Damian
A1  - Šı́mová, Petra
A1  - Sitch, Stephen
A1  - Smit, Julian L.
A1  - Steele, Caitriana M.
A1  - Suárez-Seoane, Susana
A1  - Vargas Zesati, Sergio A.
A1  - Villarreal, Miguel L.
A1  - Visser, Fleur
A1  - Wachendorf, Michael
A1  - Wirnsberger, Hannes
A1  - Wojcikiewicz, Robert
T1  - Drone-derived canopy height predicts biomass across non-forest ecosystems globally
T2  - bioRxiv
N2  - Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, yet are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely-sensed biomass products and are undersampled by in-situ monitoring. Current global change threats emphasise the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we assess whether canopy height inferred from drone photogrammetry allows the estimation of aboveground biomass (AGB) across low-stature plant species sampled through a global site network. We found mean canopy height is strongly predictive of AGB across species, demonstrating standardised photogrammetric approaches are generalisable across growth forms and environmental settings. Biomass per-unit-of-height was similar within, but different among, plant functional types. We find drone-based photogrammetry allows for monitoring of AGB across large spatial extents and can advance understanding of understudied and vulnerable non-forested ecosystems across the globe.
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72794
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-727949
UR  - https://www.biorxiv.org/content/10.1101/2020.07.16.206011v1
IS  - 2020.07.16.206011v1
PB  - bioRxiv
ER  -