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DOI	10.1016/j.rse.2020.111855
	Spatiotemporal partitioning of savanna plant functional type productivity along NATT
	Ma X.; Huete A.; Moore C.E.; Cleverly J.; Hutley L.B.; Beringer J.; Leng S.; Xie Z.; Yu Q.; Eamus D.
发表日期	2020
ISSN	00344257
卷号	246
英文摘要	Realistic representations and simulation of mass and energy exchanges across heterogeneous landscapes can be a challenge in land surface and dynamic vegetation models. For mixed life-form biomes such as savannas, plant function is very difficult to parameterise due to the distinct physiological characteristics of tree and grass plant functional types (PFTs) that vary dramatically across space and time. The partitioning of their fractional contributions to ecosystem gross primary production (GPP) remains to be achieved at regional scale using remote sensing. The objective of this study was to partition savanna gross primary production (GPP) into tree and grass functional components based on their distinctive phenological characteristics. Comparison of the remote sensing partitioned GPPtree and GPPgrass against field measurements from eddy covariance (EC) towers showed an overall good agreement in terms of both GPP seasonality and magnitude. We found total GPP, as well as its tree and grass components, decreased dramatically with rainfall over the North Australian Tropical Transect (NATT), from the Eucalyptus forest and woodland in the northern humid coast to the grasslands, Acacia woodlands and shrublands in the southern xeric interior. Spatially, GPPtree showed a steeper decrease with precipitation along the NATT compared to GPPgrass, thus tree/grass GPP ratios also decreased from the northern mesic region to the arid south region of the NATT. However, results also showed a second trend at the southern part of the transect, where tree-grass ratios and total GPP increased with decreasing mean annual precipitation, and this occurred in the physiognomic transition from hummock grasslands to Acacia woodland savannas. Total GPP and tree-grass GPP ratios across climate extremes were found to be primarily driven by grass layer response to rainfall dynamics. The grass-containing xeric savannas exhibited a higher hydroclimatic sensitivity, whereas GPP in the northern mesic savannas was fairly stable across years despite large variations in rainfall amount. The pronounced spatiotemporal variations in savanna vegetation productivity encountered along the NATT study area suggests that the savanna biome is particularly sensitive and vulnerable to predicted future climate change and hydroclimatic variability. © 2020 Elsevier Inc.
英文关键词	EVI; GPP; MODIS; NATT; Phenology; Plant functional types; Tree-grass ratio
语种	英语
scopus关键词	Climate change; Ecosystems; Productivity; Rain; Remote sensing; Sensitivity analysis; Space optics; Vegetation; Dynamic vegetation model; Gross primary production; Heterogeneous landscapes; Hydroclimatic variability; Mean annual precipitation; Physiological characteristics; Spatio-temporal variation; Vegetation productivity; Forestry; climate variation; evergreen forest; functional response; grass; grassland; heterogeneity; parameterization; phenology; physiology; primary production; remote sensing; savanna; seasonality; shrubland; spatiotemporal analysis; woodland; Acacia; Eucalyptus
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179276
作者单位	School of Life Sciences, University of Technology Sydney, Ultimo, NSW, Australia; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu, China; Genomic Ecology of Global Change, Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana, IL, United States; School of Environment, Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, NT, Australia; School of Agriculture and Environment, University of Western Australia, Crawley, WA, Australia; Centre for Biodiversity and Conservation Science, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD, Australia; State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shanxi, China
推荐引用方式 GB/T 7714	Ma X.,Huete A.,Moore C.E.,et al. Spatiotemporal partitioning of savanna plant functional type productivity along NATT[J],2020,246.
APA	Ma X..,Huete A..,Moore C.E..,Cleverly J..,Hutley L.B..,...&Eamus D..(2020).Spatiotemporal partitioning of savanna plant functional type productivity along NATT.Remote Sensing of Environment,246.
MLA	Ma X.,et al."Spatiotemporal partitioning of savanna plant functional type productivity along NATT".Remote Sensing of Environment 246(2020).