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• W2254548579 abstract "Abstract. The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil-water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe that this study is the first to assess how well TBMs simulate savanna ecosystems and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies." @default.
• W2254548579 created "2016-06-24" @default.
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• W2254548579 date "2016-06-03" @default.
• W2254548579 modified "2023-10-16" @default.
• W2254548579 title "A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas" @default.
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• W2254548579 cites W16269152 @default.
• W2254548579 cites W1874808789 @default.
• W2254548579 cites W1888540468 @default.
• W2254548579 cites W1898496237 @default.
• W2254548579 cites W1966913183 @default.
• W2254548579 cites W1968883173 @default.
• W2254548579 cites W1979793013 @default.
• W2254548579 cites W1980030918 @default.
• W2254548579 cites W1980853261 @default.
• W2254548579 cites W1980854310 @default.
• W2254548579 cites W1985591768 @default.
• W2254548579 cites W1988144647 @default.
• W2254548579 cites W1989994082 @default.
• W2254548579 cites W1998157234 @default.
• W2254548579 cites W2014473959 @default.
• W2254548579 cites W2021259565 @default.
• W2254548579 cites W2026958447 @default.
• W2254548579 cites W2027921754 @default.
• W2254548579 cites W2029074727 @default.
• W2254548579 cites W2036687720 @default.
• W2254548579 cites W2039295317 @default.
• W2254548579 cites W2044054848 @default.
• W2254548579 cites W2045719405 @default.
• W2254548579 cites W2046857879 @default.
• W2254548579 cites W2047608969 @default.
• W2254548579 cites W2048839121 @default.
• W2254548579 cites W2055158641 @default.
• W2254548579 cites W2073951769 @default.
• W2254548579 cites W2085382913 @default.
• W2254548579 cites W2090023908 @default.
• W2254548579 cites W2095906789 @default.
• W2254548579 cites W2096090184 @default.
• W2254548579 cites W2096682311 @default.
• W2254548579 cites W2100174116 @default.
• W2254548579 cites W2100321473 @default.
• W2254548579 cites W2101493446 @default.
• W2254548579 cites W2104968988 @default.
• W2254548579 cites W2107212943 @default.
• W2254548579 cites W2107814890 @default.
• W2254548579 cites W2107888302 @default.
• W2254548579 cites W2109771788 @default.
• W2254548579 cites W2116991286 @default.
• W2254548579 cites W2118203740 @default.
• W2254548579 cites W2126860661 @default.
• W2254548579 cites W2127110926 @default.
• W2254548579 cites W2129531078 @default.
• W2254548579 cites W2134289299 @default.
• W2254548579 cites W2134307851 @default.
• W2254548579 cites W2136066577 @default.
• W2254548579 cites W2137961132 @default.
• W2254548579 cites W2141125076 @default.
• W2254548579 cites W2141408144 @default.
• W2254548579 cites W2145422581 @default.
• W2254548579 cites W2148341336 @default.
• W2254548579 cites W2148750799 @default.
• W2254548579 cites W2151646838 @default.
• W2254548579 cites W2151652327 @default.
• W2254548579 cites W2153322439 @default.
• W2254548579 cites W2153828129 @default.
• W2254548579 cites W2156892295 @default.
• W2254548579 cites W2163008571 @default.
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• W2254548579 cites W2166550920 @default.
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• W2254548579 doi "https://doi.org/10.5194/bg-13-3245-2016" @default.
• W2254548579 hasPublicationYear "2016" @default.
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