Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Biogeosciences, 14, 111-129, 2017
https://doi.org/10.5194/bg-14-111-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
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. Moore1,2, Jason Beringer1,2, Bradley Evans3,4, Lindsay B. Hutley5, and Nigel J. Tapper1 1School of Earth, Atmosphere and Environment, Monash University, Clayton, VIC, 3800, Australia
2School of Earth and Environment, University of Western Australia, Crawley, WA, 6009, Australia
3Department of Environmental Sciences, University of Sydney, Eveleigh, NSW, 2015, Australia
4Terrestrial Ecosystem Research Network Ecosystem Modelling and Scaling Infrastructure, University of Sydney, Eveleigh, NSW, 2015, Australia
5School of Environment, Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, NT, 0909, Australia
Abstract. The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom–bust seasonal pattern of productivity that follows the wet–dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to understand how the tree–grass relationship may shift in response to climate change. This study investigated the relationship between productivity and phenology for trees and grasses in an Australian tropical savanna. Productivity, estimated from overstory (tree) and understory (grass) eddy covariance flux tower estimates of gross primary productivity (GPP), was compared against 2 years of repeat time-lapse digital photography (phenocams). We explored the phenology–productivity relationship at the ecosystem scale using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and flux tower GPP. These data were obtained from the Howard Springs OzFlux/Fluxnet site (AU-How) in northern Australia. Two greenness indices were calculated from the phenocam images: the green chromatic coordinate (GCC) and excess green index (ExG). These indices captured the temporal dynamics of the understory (grass) and overstory (trees) phenology and were correlated well with tower GPP for understory (r2 =  0.65 to 0.72) but less so for the overstory (r2 =  0.14 to 0.23). The MODIS enhanced vegetation index (EVI) correlated well with GPP at the ecosystem scale (r2 =  0.70). Lastly, we used GCC and EVI to parameterise a light use efficiency (LUE) model and found it to improve the estimates of GPP for the overstory, understory and ecosystem. We conclude that phenology is an important parameter to consider in estimating GPP from LUE models in savannas and that phenocams can provide important insights into the phenological variability of trees and grasses.

Citation: Moore, C. E., Beringer, J., Evans, B., Hutley, L. B., and Tapper, N. J.: Tree–grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna, Biogeosciences, 14, 111-129, https://doi.org/10.5194/bg-14-111-2017, 2017.
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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.
Separating tree and grass productivity dynamics in savanna ecosystems is vital for understanding...
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