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Drone-derived canopy height predicts biomass across non-forest ecosystems globally

Cunliffe, A. M.; Anderson, K.; Boschetti, F.; Graham, H. A.; Brazier, R. E.; Myers-Smith, I. H.; Astor, T.; Boer, M. M.; Calvo, L.; Clark, P. E.; Cramer, M. D.; Encinas-Lara, M. S.; Escarzaga, S. M.; Fernandez-Guisuraga, J. M.; Fisher, A. G.; Gdulov, K.; Gillespie, B. M.; Griebel, A.; Hanan, N. P.; Hanggito, M. S.; Haselberger, S.; Havrilla, C. A.; Heilman, P.; Ji, W.; Karl, J. W.; Kirchhoff, M.; Kraushaar, S.; Lyons, M. B.; Marzolff, I.; Mauritz, M. E.; McIntire, C. D.; Metzen, D.; Mendez-Barroso, L. A.; Power, S. C.; Prosek, J.; Sanz-Ablanedo, E.; Sauer, K. J.; Schulze-Bruninghoff, D.; Simov

2020-07-17 ecology
10.1101/2020.07.16.206011 bioRxiv
Show abstract

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.

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