Articles | Volume 14, issue 1
https://doi.org/10.5194/bg-14-111-2017
https://doi.org/10.5194/bg-14-111-2017
Research article
 | 
10 Jan 2017
Research article |  | 10 Jan 2017

Tree–grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna

Caitlin E. Moore, Jason Beringer, Bradley Evans, Lindsay B. Hutley, and Nigel J. Tapper

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Cited articles

Andrew, M. H., and Mott, J. J.: Annuals with transient seed banks: the population biology of indigenous Sorghum species of tropical north-west Australia, Aust. J. Ecol., 8, 265–276, 1983.
Baret, F., de Solan, B., Lopez-Lozano, R., Ma, K., and Weiss, M.: GAI estimates of row crops from downward looking digital photos taken perpendicular to rows at 57.5° zenith angle: Theoretical considerations based on 3D architecture models and application to wheat crops, Agr. Forest Meteorol., 150, 1393–1401, https://doi.org/10.1016/j.agrformet.2010.04.011, 2010.
Beringer, J., Hutley, L. B., Tapper, N. J., and Cernusak, L. A.: Savanna fires and their impact on net ecosystem productivity in North Australia, Glob. Change Biol., 13, 990–1004, 2007.
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Short summary
Separating tree and grass productivity dynamics in savanna ecosystems is vital for understanding how they function over time. We showed how tree-grass phenology information can improve model estimates of gross primary productivity in an Australian tropical savanna. Our findings will contribute towards improved modelling of productivity in savannas, which will assist with their management into the future.
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