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.

Fires play an important role in ecosystem dynamics. Long-term controls on global burned area include fuel continuity and moisture, with ignitions and human activity becoming dominant in specific ecosystems. Changes in fuel continuity and moisture are the main drivers of changes of fire globally.

A soil–plant–atmosphere model was used to estimate gross primary productivity (GPP) and evapotranspiration (ET) of a tropical savanna in Australia. This paper describes model modifications required to simulate the substantial C4 grass understory together with C3 trees. The model was further improved to include a seasonal distribution of leaf area and foliar nitrogen through 10 canopy layers. Model outputs were compared with a 5‐year eddy covariance dataset. Adding the C4 photosynthesis component improved the model efficiency and root‐mean‐squared error (RMSE) for total ecosystem GPP by better emulating annual peaks and troughs in GPP across wet and dry seasons. The C4 photosynthesis component had minimal impact on modelled values of ET. Outputs of GPP from the modified model agreed well with measured values, explaining between 79% and 90% of the variance and having a low RMSE (0.003–0.281 g C m−2 day−1). Approximately, 40% of total annual GPP was contributed by C4 grasses. Total (trees and grasses) wet season GPP was approximately 75–80% of total annual GPP. Light‐use efficiency (LUE) was largest for the wet season and smallest in the dry season and C4 LUE was larger than that of the trees. A sensitivity analysis of GPP revealed that daily GPP was most sensitive to changes in leaf area index (LAI) and foliar nitrogen (Nf) and relatively insensitive to changes in maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax) and minimum leaf water potential (ψmin). The modified model was also able to represent daily and seasonal patterns in ET, (explaining 68–81% of variance) with a low RMSE (0.038–0.19 mm day−1). Current values of Nf, LAI and other parameters appear to be colimiting for maximizing GPP. By manipulating LAI and soil moisture content inputs, we show that modelled GPP is limited by light interception rather than water availability at this site.

Daily and seasonal patterns of tree water use were measured for the two dominant tree species, Angophora bakeri E.C.Hall (narrow-leaved apple) and Eucalyptus sclerophylla (Blakely) L.A.S. Johnson & Blaxell (scribbly gum), in a temperate, open, evergreen woodland using sap flow sensors, along with information about soil, leaf, tree and micro-climatological variables. The aims of this work were to: (a) validate a soil–plant–atmosphere (SPA) model for the specific site; (b) determine the total depth from which water uptake must occur to achieve the observed rates of tree sap flow; (c) examine whether the water content of the upper soil profile was a significant determinant of daily rates of sap flow; and (d) examine the sensitivity of sap flow to several biotic factors. It was found that: (a) the SPA model was able to accurately replicate the hourly, daily and seasonal patterns of sap flow; (b) water uptake must have occurred from depths of up to 3 m; (c) sap flow was independent of the water content of the top 80 cm of the soil profile; and (d) sap flow was very sensitive to the leaf area of the stand, whole tree hydraulic conductance and the critical water potential of the leaves, but insensitive to stem capacitance and increases in root biomass. These results are important to future studies of the regulation of vegetation water use, landscape-scale behaviour of vegetation, and to water resource managers, because they allow testing of large-scale management options without the need for large-scale manipulations of vegetation cover.

Abstract. Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspiration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley–Taylor coefficient, are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.

17 18The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil 19 moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy 20 conductance has then often been used to predict transpiration using the Penman-Monteith (PM) 21 model. We previously suggested an alternative approach in which the JS model is modified to 22 2 directly estimate transpiration rather than canopy conductance. In the present study we used this 23 alternative approach to model tree water fluxes from an Australian native forest over an annual cycle. 24For comparative purposes we also modelled canopy conductance and estimated transpiration via the 25 PM model. Finally we applied an artificial neural network as a statistical benchmark to compare the 26 performance of both models. Both the PM and modified JS models were parameterised using solar 27 radiation, vapour pressure deficit and soil moisture as inputs with results that compare well with 28 previous studies. Both models performed comparably well during the summer period. However, 29during winter the PM model was found to fail during periods of high rates of transpiration. In 30 contrast, the modified JS model was able to replicate observed sapflow measurements throughout the 31 year although it too tended to underestimate rates of transpiration in winter under conditions of high 32 rates of transpiration. Both approaches to modelling transpiration gave good agreement with hourly, 33 daily and total sums of sapflow measurements with the modified JS and PM models explaining 87% 34 and 86% of the variance respectively. We conclude that these three approaches have merit at 35 different time-scales. 36 37

script developed incorporates a function to connect directly a digital camera, or high 6 resolution webcam, from a laptop to obtain cover photographs and LAI analysis in 7 real time. The later is a novel feature which is not available on commercial LAI 8 analysis softwares for cover photography. This script is available for interested 9 researchers. 10 11

Kato introduces the concept of a strictly singular operator, a generalization of the concept of a compact operator. He proves that for X and Y B-spaces the strictly singular operators form a closed subspace in the space of all bounded linear operators from X to F and that the product of a strictly singular operator with a bounded operator is strictly singular, so when X = F they form a twosided ideal. He further shows that the Riesz-Schauder theorem holds for the spectrum of a strictly singular operator on a B-space.