ALBERT

Description: Studying the temporal pattern of savanna gross primary productivity (GPP) is essential for predicting the response of the biome to global environmental changes. In this study, MODIS satellite data coupled with eddy covariance based flux measurements were used to estimate GPP using a remote sensing based light use efficiency model across a significant rainfall gradient in the Northern Territory (NT) region of Australia. Closed forest that occurred in wet and often fireproof environments assimilated (GPP) 4–6 times more carbon than grasslands and Acacia woodlands that grow in arid environments (〈600 mm annual rainfall). However, due to their small spatial extent, closed forests contributed 〈0.5% of the regional budget compared to savanna woodlands (86%) and grasslands (32%). Annual rainfall was found to exert a significant influence on GPP for different vegetation types except for closed forest which was less sensitive to above-average rainfall. Interannual variability in GPP showed that arid ecosystems had a higher variation (〉20%) compared to woodlands and forest (~5%). This variation in GPP was correlated with that of rainfall (R 2 = 0.88, p〈0.05). Analysis of the impact of wettest and driest years on GPP showed a strong positive correlation between the magnitude of the relative maxima in rainfall and maxima in GPP (R 2 = 0.89, p〈0.05). In contrast, the relative rainfall minima exhibited an insignificant relationship with relative GPP minima (R 2 = 0.45, p = 0.07). These findings provide valuable information on the carbon uptake across the savanna biome and show the sensitivity of different vegetation systems to rainfall, a variable that may change in quantity and variability with projected climate change. Such data also show regions of high levels of carbon that could be linked with savanna management to protect the resources in the Australian savannas.

Description: Seasonally dry ecosystems present a challenge to plants to maintain water relations. While native vegetation in seasonally dry ecosystems have evolved specific adaptations to the long dry season, there are risks to introduced exotic species. African mahogany, Khaya senegalensis Desr. (A. Juss.), is an exotic plantation species that has been introduced widely in Asia and northern Australia, but it is unknown if it has the physiological or phenotypic plasticity to cope with the strongly seasonal patterns of water availability in the tropical savanna climate of northern Australia. We investigated the gas exchange and water relations traits and adjustments to seasonal drought in K. senegalensis and native eucalypts ( Eucalyptus tetrodonta F. Muell. and Corymbia latifolia F. Muell.) in a savanna ecosystem in northern Australia. The native eucalypts did not exhibit any signs of drought stress after 3 months of no rainfall and probably had access to deeper soil moisture late into the dry season. Leaf water potential, stomatal conductance, transpiration and photosynthesis all remained high in the dry season but osmotic adjustment was not observed. Overstorey leaf area index (LAI) was 0.6 in the native eucalypt savanna and did not change between wet and dry seasons. In contrast, the K. senegalensis plantation in the wet season was characterized by a high water potential, high stomatal conductance and transpiration and a high LAI of 2.4. In the dry season, K. senegalensis experienced mild drought stress with a predawn water potential –0.6 MPa. Overstorey LAI was halved, and stomatal conductance and transpiration drastically reduced, while minimum leaf water potentials did not change (–2 MPa) and no osmotic adjustment occurred. Khaya senegalensis exhibited an isohydric behaviour and also had a lower hydraulic vulnerability to cavitation in leaves, with a P50 of –2.3 MPa. The native eucalypts had twice the maximum leaf hydraulic conductance but a much higher P50 of –1.5 MPa. Khaya senegalensis has evolved in a wet–dry tropical climate in West Africa (600–800 mm) and appears to be well suited to the seasonal savanna climate of northern Australia. The species exhibited a large phenotypic plasticity through leaf area adjustments and conservative isohydric behaviour in the 6 months dry season while operating well above its critical hydraulic threshold.

Description: 1. We investigated the relative importance of CH4 and CO2 fluxes from soil and termite mounds at four different sites in the tropical savannas of Northern Australia near Darwin and assessed different methods to indirectly predict CH4 fluxes based on CO2 fluxes and internal gas concentrations. 2. The annual flux from termite mounds and surrounding soil was dominated by CO2 with large variations among sites. On a CO2-e basis, annual CH4 flux estimates from termite mounds were 5- to 46-fold smaller than the concurrent annual CO2 flux estimates. Differences between annual soil CO2 and soil CH4 (CO2-e) fluxes were even greater, soil CO2 fluxes being almost three orders of magnitude greater than soil CH4 (CO2-e) fluxes at site. 3. There were significant relationships between mound CH4 flux and mound CO2 flux, enabling the prediction of CH4 flux from measured CO2 flux, however, these relationships were clearly termite species specific. 4. We also observed significant relationships between mound flux and gas concentration inside mound, for both CH4 and CO2, and for all termite species, thereby enabling the prediction of flux from measured mound internal gas concentration. However, these relationships were also termite species specific. Using the relationship between mound internal gas concentration and flux from one species to predict mound fluxes from other termite species (as has been done in past) would result in errors of more than 5-fold for CH4 and 3-fold for CO2. 5. This study highlights that CO2 fluxes from termite mounds are generally more than one order of magnitude greater than CH4 fluxes. There are species-specific relationships between CH4 and CO2 fluxes from a~mound, and between the inside mound concentration of a gas and the mound flux emission of the same gas, but these relationships vary greatly among termite species. Consequently, there is no generic relationship that will allow for the prediction of CH4 fluxes from termite mounds of all species.

Description: Strong seasonal variability of hygric and thermal soil conditions are a defining environmental feature in Northern Australia. However, how such changes affect the soil–atmosphere exchange of nitrous oxide (N2O), nitric oxide (NO) and dinitrogen (N2) is still not well explored. By incubating intact soil cores from four sites (3 savanna, 1 pasture) under controlled soil temperatures (ST) and soil moisture (SM) we investigated the release of the trace gas fluxes of N2O, NO and carbon dioxide (CO2). Furthermore, the release of N2 due to denitrification was measured using the helium gas flow soil core technique. Under dry pre-incubation conditions NO and N2O emission were very low (

Description: Savanna ecosystems cover 20 % of the global land surface and account for 25 % of global terrestrial carbon uptake. They support one fifth of the world's human population and are one of the most important ecosystems on our planet. Savanna productivity is a product of the interplay between trees and grass that co-dominate savanna landscapes and are maintained through interactions with climate and disturbance (fire, land use change, herbivory). In this study, we evaluate the temporally dynamic partitioning of overstory and understory carbon dioxide fluxes in Australian tropical savanna using overstory and understory eddy covariance measurements. Over a two year period (September 2012 to October 2014) the overall net ecosystem productivity (NEP) of the savanna was 506.2 (±22 SE) g C m−2 yr−1. The total gross primary productivity (GPP) was 2267.1 (±80 SE) g C m−2 yr−1, of which the understory contributed 32 %. The understory contribution was strongly seasonal, with most GPP occurring in the wet season (40 % of total ecosystem in the wet season and 18 % in the dry). This study is the first to elucidate the temporal dynamics of savanna understory and overstory carbon flux components explicitly using observational information. Understanding grass productivity is crucial for evaluating fuel loads, as is tree productivity for quantifying the tree carbon sink. This information will contribute to a significant refinement of the representation of savannas in models, as well as improved understanding of relative tree-grass productivity and competition for resources.

Description: The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change.

Description: The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change.