Land use affects evapotranspiration rates and is a primary driver of the catchment water balance. The water balance of two catchments in southeastern Australia dominated by either grazed pasture or blue gum ( Eucalyptus globulus ) plantation was studied, focusing on the patterns of evapotranspiration (ET) throughout the year. Rainfall, streamflow, and groundwater levels measured between 2015-2019 were combined to estimate annual ET using a water balance equation. In the pasture, eddy covariance was used to measure ET from the catchment. Sap flow measurements were used to estimate tree transpiration in May 2017 – May 2018 and Feb 2019 – Feb 2021 in two different plots within the plantation. The tree transpiration rates were added to direct evaporation, estimated as a percentage of annual rainfall, to calculate ET from the plantation catchment. ET in the pasture showed strong seasonal cycles with very low ET rates in summer and ET rates in spring that were larger than the transpiration rates in the plantation, where trees transpired consistently throughout the year. The estimated annual ET from the water balance equation were comparable to ET estimated from other measurements. In the pasture, ET on average accounted for 88% of annual rainfall, while ET in the plantation was on average 93% of rainfall, exceeding it in the years with annual rainfall lower than 500 mm. The difference between the ET rates in the plantation and the pasture were approximately 30 to 50 mm y­ . The larger ET rates in the plantation are reflected in a gradual decrease in the groundwater storage. The differences in ET rates were thus enough to cause a decrease in groundwater storage in the plantation, while the groundwater levels in the pasture remained stable.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

The establishment and expansion of commercial plantations for timber production and carbon sequestration raises concerns because of their large water use. Eucalyptus globulus (blue gum) is one of the most planted species globally, as it grows rapidly and is adaptable to a range of climatic conditions. The dearth of experimental observations on water use and growth in blue gum plantations in their early years after establishment makes it difficult to develop management practices. This study quantified the trade-offs between water use and carbon assimilation in a blue gum plantation in the first 4 years after establishment. The study site is located in southwest Victoria, Australia, where energy, water and CO2 fluxes were continuously measured above the tree canopy for 4 years after the trees were planted. During the first year after establishment, understory vegetation and ecosystem respiration had a major impact on the net ecosystem exchange (NEE), with the plantation being a net carbon source. Subsequently, the trees started dominating the contributions to NEE, and after approximately 2 years the plantation became a consistent carbon sink. These shifts in NEE were accompanied by smaller increases in annual evapotranspiration rates, which was 70% of the annual precipitation in the first year and 74% in the 3rd year of measurements. As a result, yearly averages of water use efficiency increased from 2.86 gC kg(-1)H(2)O in 2018 to 4.3 gC kg(-1)H(2)O in 2020, following tree development. This shows a remarkable increase in productivity at the expense of a small amount of water.

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

The errors and uncertainties associated with gap-filling algorithms of water, carbon, and energy fluxes data have always been one of the main challenges of the global network of microclimatological tower sites that use the eddy covariance (EC) technique. To address these concerns and find more efficient gap-filling algorithms, we reviewed eight algorithms to estimate missing values of environmental drivers and nine algorithms for the three major fluxes typically found in EC time series. We then examined the algorithms' performance for different gap-filling scenarios utilising the data from five EC towers during 2013. This research's objectives were (a) to evaluate the impact of the gap lengths on the performance of each algorithm and (b) to compare the performance of traditional and new gap-filling techniques for the EC data, for fluxes, and separately for their corresponding meteorological drivers. The algorithms' performance was evaluated by generating nine gap windows with different lengths, ranging from a day to 365 d. In each scenario, a gap period was chosen randomly, and the data were removed from the dataset accordingly. After running each scenario, a variety of statistical metrics were used to evaluate the algorithms' performance. The algorithms showed different levels of sensitivity to the gap lengths; the Prophet Forecast Model (FBP) revealed the most sensitivity, whilst the performance of artificial neural networks (ANNs), for instance, did not vary as much by changing the gap length. The algorithms' performance generally decreased with increasing the gap length, yet the differences were not significant for windows smaller than 30 d. No significant differences between the algorithms were recognised for the meteorological and environmental drivers. However, the linear algorithms showed slight superiority over those of machine learning (ML), except the random forest (RF) algorithm estimating the ground heat flux (root mean square errors – RMSEs – of 28.91 and 33.92 for RF and classic linear regression – CLR, respectively). However, for the major fluxes, ML algorithms and the MDS showed superiority over the other algorithms. Even though ANNs, random forest (RF), and eXtreme Gradient Boost (XGB) showed comparable performance in gap-filling of the major fluxes, RF provided more consistent results with slightly less bias against the other ML algorithms. The results indicated no single algorithm that outperforms in all situations, but the RF is a potential alternative for the MDS and ANNs as regards flux gap-filling.

Aquatic carbon exports are an understudied component of catchment carbon budgets. For drained agroecosystems, the role of this aquatic pathway in offsetting the terrestrial carbon sink is unknown. Here, we present findings on the complete annual carbon budget of a subtropical agricultural floodplain in Australia. We quantified net ecosystem exchange (NEE) using eddy covariance, and aquatic carbon fluxes from drainage canals over an annual cycle, including atmospheric exchange of aquatic CO2 and CH4, as well as lateral exports of dissolved organic, inorganic and particulate carbon. The floodplain was a large atmospheric CO2 sink, with an annual NEE of - 900 g C m(-2) yr(-1) driven by the sugarcane growing season. Aquatic carbon fluxes were estimated at 24, 16, and 0.05 g C m(-2) yr(-1) for lateral export, CO2 and CH4 evasion, respectively. Between 70% and 91% of aquatic carbon was lost during flood events which occurred only 12% of the time. From these measurements and estimates of other carbon inputs and outputs from farm operations, the net ecosystem carbon budget was close to neutral at -100 (error range -289 to 215) g C m(-2) yr(-1). Compared to other drained wetlands, the aquatic carbon flux was a minor component of the carbon budget.

Changing climates have extended growing seasons and increased vegetation productivity in many northern ecosystems, but less is known about Southern Hemisphere counterparts. Among the more dramatic changes are reductions in winter snow cover in mountainous ecosystems in southeastern Australia; some forecasts predict almost complete absence of snow by 2050. We used the eddy covariance technique in a montane grassland (Nimmo) of the Snowy Mountains, which was a carbon sink of 26-185 g C m(-2) yr(-1) from 2007-2014 but was temperature- and moisture-limited. Higher soil temperatures increased net productivity at a rate of about 2.2 g C m(-2)month(-1) per 1 degrees C, when soil water content was not limiting. Carbon uptake of Australian mountain grasslands may therefore increase in a warming climate, provided growing season precipitation remains adequate. We used the MODIS normalized difference vegetation index (NDVI) to monitor phenology at Nimmo from 2001-2016. We also recorded daily estimates of greenness from digital imagery (i.e. PhenoCam) and found close correspondence between satellite and near-surface greenness indices in 2015, suggesting that remote sensing can reliably extend PhenoCam records. Mean growing season length (244 days) did not change over the study period and was two weeks longer than mountain grasslands in the Northern Hemisphere. The longer Australian growing season is not correlated with productivity and is likely attributable to the lower latitude of the Snowy Mountains (36 degrees S) and mild Australian climate. Green-up of the grassland advanced by 16 days over the past 15 years, seemingly as a result of increasing August (late winter) temperature. Grass senescence (i.e. yellowing) was most closely related to vapor pressure deficit in March (early autumn). When high temperatures (14 C) and low rainfall (<= 50 mm) resulted in high March VPD (similar to 0.7 kPa), grass yellowed nearly 3 months early and the growing season was < 200 days. These results suggest there is a tipping point beyond which high summer VPD prevents late-season recovery of Australian mountain grasslands.

Standardised, quality-controlled and robust data from flux networks underpin the understanding of ecosystem processes and tools necessary to support the management of natural resources, including water, carbon and nutrients for environmental and production benefits. The Australian regional flux network (OzFlux) currently has 23 active sites and aims to provide a continental-scale national research facility to monitor and assess Australia's terrestrial biosphere and climate for improved predictions. Given the need for standardised and effective data processing of flux data, we have developed a software suite, called the Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO), that enables gap-filling and partitioning of the primary fluxes into ecosystem respiration (Fre) and gross primary productivity (GPP) and subsequently provides diagnostics and results. We outline the processing pathways and methodologies that are applied in DINGO (v13) to OzFlux data, including (1) gap-filling of meteorological and other drivers; (2) gap-filling of fluxes using artificial neural networks; (3) the u* threshold determination; (4) partitioning into ecosystem respiration and gross primary productivity; (5) random, model and u* uncertainties; and (6) diagnostic, footprint calculation, summary and results outputs. DINGO was developed for Australian data, but the framework is applicable to any flux data or regional network. Quality data from robust systems like DINGO ensure the utility and uptake of the flux data and facilitates synergies between flux, remote sensing and modelling.

Measurement of the exchange of energy and mass between the surface and the atmospheric boundary-layer by the eddy covariance technique has undergone great change in the last 2 decades. Early studies of these exchanges were confined to brief field campaigns in carefully controlled conditions followed by months of data analysis. Current practice is to run tower-based eddy covariance systems continuously over several years due to the need for continuous monitoring as part of a global effort to develop local-, regional-, continental- and global-scale budgets of carbon, water and energy. Efficient methods of processing the increased quantities of data are needed to maximise the time available for analysis and interpretation. Standardised methods are needed to remove differences in data processing as possible contributors to observed spatial variability. Furthermore, public availability of these data sets assists with undertaking global research efforts. The OzFlux data path has been developed (i) to provide a standard set of quality control and post-processing tools across the network, thereby facilitating inter-site integration and spatial comparisons; (ii) to increase the time available to researchers for analysis and interpretation by reducing the time spent collecting and processing data; (iii) to propagate both data and metadata to the final product; and (iv) to facilitate the use of the OzFlux data by adopting a standard file format and making the data available from web-based portals. Discovery of the OzFlux data set is facilitated through incorporation in FLUXNET data syntheses and the publication of collection metadata via the RIF-CS format. This paper serves two purposes. The first is to describe the data sets, along with their quality control and post-processing, for the other papers of this Special Issue. The second is to provide an example of one solution to the data collection and curation challenges that are encountered by similar flux tower networks worldwide.

Forest ecosystems play a crucial role in the global carbon cycle by sequestering a considerable fraction of anthropogenic CO2, thereby contributing to climate change mitigation. However, there is a gap in our understanding about the carbon dynamics of eucalypt (broadleaf evergreen) forests in temperate climates, which might differ from temperate evergreen coniferous or deciduous broadleaved forests given their fundamental differences in physiology, phenology and growth dynamics. To address this gap we undertook a 3-year study (2010–2012) of eddy covariance measurements in a dry temperate eucalypt forest in southeastern Australia. We determined the annual net carbon balance and investigated the temporal (seasonal and inter-annual) variability in and environmental controls of net ecosystem carbon exchange (NEE), gross primary productivity (GPP) and ecosystem respiration (ER). The forest was a large and constant carbon sink throughout the study period, even in winter, with an overall mean NEE of −1234 ± 109 (SE) g C m−2 yr−1. Estimated annual ER was similar for 2010 and 2011 but decreased in 2012 ranging from 1603 to 1346 g C m−2 yr−1, whereas GPP showed no significant inter-annual variability, with a mean annual estimate of 2728 ± 39 g C m−2 yr−1. All ecosystem carbon fluxes had a pronounced seasonality, with GPP being greatest during spring and summer and ER being highest during summer, whereas peaks in NEE occurred in early spring and again in summer. High NEE in spring was likely caused by a delayed increase in ER due to low temperatures. A strong seasonal pattern in environmental controls of daytime and night-time NEE was revealed. Daytime NEE was equally explained by incoming solar radiation and air temperature, whereas air temperature was the main environmental driver of night-time NEE. The forest experienced unusual above-average annual rainfall during the first 2 years of this 3-year period so that soil water content remained relatively high and the forest was not water limited. Our results show the potential of temperate eucalypt forests to sequester large amounts of carbon when not water limited. However, further studies using bottom-up approaches are needed to validate measurements from the eddy covariance flux tower and to account for a possible underestimation in ER due to advection fluxes.

While the eddy covariance technique has become an important technique for estimating long-term ecosystem carbon balance, under certain conditions the measured turbulent flux of CO2 at a given height above an ecosystem does not represent the true surface flux. Profile systems have been deployed to measure periodic storage of CO2 below the measurement height, but have not been widely adopted. This is most likely due to the additional expense and complexity and possibly also the perception, given that net storage over intervals exceeding 24 h is generally negligible, that these measurements are not particularly important. In this study, we used a 3-year record of net ecosystem exchange of CO2 and simultaneous measurements of CO2 storage to ascertain the relative contributions of turbulent CO2 flux, storage, and advection (calculated as a residual quantity) to the nocturnal CO2 balance and to quantify the effect of neglecting storage. The conditions at the site are in relative terms highly favourable for eddy covariance measurements, yet we found a substantial contribution (∼ 40 %) of advection to nocturnal turbulent flux underestimation. The most likely mechanism for advection is cooling-induced drainage flows, the effects of which were observed in the storage measurements. The remaining ∼ 60 % of flux underestimation was due to storage of CO2. We also showed that substantial underestimation of carbon uptake (approximately 80 gC m−2 a−1, or 25 % of annual carbon uptake) arose when standard methods (u∗ filtering) of nocturnal flux correction were implemented in the absence of storage estimates. These biases were reduced to approximately 40–45 gC m−2 a−1 when the filter was applied over the entire diel period, but they were nonetheless large relative to quantifiable uncertainties in the data. Neglect of storage also distorted the relationships between the CO2 exchange processes (respiration and photosynthesis) and their key controls (light and temperature respectively). We conclude that the addition of storage measurements to eddy covariance sites with all but the lowest measurement heights should be a high priority for the flux measurement community.

As a result of climate change warmer temperatures are projected through the 21st century and are already increasing above modelled predictions. Apart from increases in the mean, warm/hot temperature extremes are expected to become more prevalent in the future, along with an increase in the frequency of droughts. It is crucial to better understand the response of terrestrial ecosystems to such temperature extremes for predicting land-surface feedbacks in a changing climate. While land-surface feedbacks in drought conditions and during heat waves have been reported from Europe and the US, direct observations of the impact of such extremes on the carbon and water cycles in Australia have been lacking. During the 2012/2013 summer, Australia experienced a record-breaking heat wave with an exceptional spatial extent that lasted for several weeks. In this study we synthesised eddy-covariance measurements from seven woodlands and one forest site across three biogeographic regions in southern Australia. These observations were combined with model results from BIOS2 (Haverd et al., 2013a, b) to investigate the effect of the summer heat wave on the carbon and water exchange of terrestrial ecosystems which are known for their resilience toward hot and dry conditions. We found that water-limited woodland and energy-limited forest ecosystems responded differently to the heat wave. During the most intense part of the heat wave, the woodlands experienced decreased latent heat flux (23 % of background value), increased Bowen ratio (154 %) and reduced carbon uptake (60 %). At the same time the forest ecosystem showed increased latent heat flux (151 %), reduced Bowen ratio (19 %) and increased carbon uptake (112 %). Higher temperatures caused increased ecosystem respiration at all sites (up to 139 %). During daytime all ecosystems remained carbon sinks, but carbon uptake was reduced in magnitude. The number of hours during which the ecosystem acted as a carbon sink was also reduced, which switched the woodlands into a carbon source on a daily average. Precipitation occurred after the first, most intense part of the heat wave, and the subsequent cooler temperatures in the temperate woodlands led to recovery of the carbon sink, decreased the Bowen ratio (65 %) and hence increased evaporative cooling. Gross primary productivity in the woodlands recovered quickly with precipitation and cooler temperatures but respiration remained high. While the forest proved relatively resilient to this short-term heat extreme the response of the woodlands is the first direct evidence that the carbon sinks of large areas of Australia may not be sustainable in a future climate with an increased number, intensity and duration of heat waves.

OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national research facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. This paper describes the evolution, design, and current status of OzFlux as well as provides an overview of data processing. We analyse measurements from all sites within the Australian portion of the OzFlux network and two sites from New Zealand. The response of the Australian biomes to climate was largely consistent with global studies except that Australian systems had a lower ecosystem water-use efficiency. Australian semi-arid/arid ecosystems are important because of their huge extent (70 %) and they have evolved with common moisture limitations. We also found that Australian ecosystems had a similar radiationuse efficiency per unit leaf area compared to global values that indicates a convergence toward a similar biochemical efficiency. The two New Zealand sites represented extremes in productivity for a moist temperate climate zone, with the grazed dairy farm site having the highest GPP of any OzFlux site (2620 gC m−2 yr−1) and the natural raised peat bog site having a very low GPP (820 gC m−2 yr−1). The paper discusses the utility of the flux data and the synergies between flux, remote sensing, and modelling. Lastly, the paper looks ahead at the future direction of the network and concludes that there has been a substantial contribution by OzFlux, and considerable opportunities remain to further advance our understanding of ecosystem response to disturbances, including drought, fire, land-use and land-cover change, land management, and climate change, which are relevant both nationally and internationally. It is suggested that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing the delicately balanced ecosystems in Australasia.

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 2-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.

Reliable estimation of evapotranspiration is important for many hydrological applications, including agriculture, climatology, and assessment of stormwater control measures. An automated chamber system was constructed to measure field evapotranspiration. The system consists of six chambers, sampled consecutively by means of a dynamic closed-chamber design, and is fully automated to allow replicable long-term measurements. However, the use of such a system is subject to measurement errors due to vapor adsorption along the sampling tubes and inappropriate internal ventilation. Because these issues are rarely addressed in the literature on flux chambers, a laboratory calibration was performed to estimate errors in evapotranspiration rates measured by the system. The effects of the sampling tube length and air mixing were investigated. A correction factor for evapotranspiration rates relative to the tube length was established. Appropriate air mixing induced by small fans ensured that the measured rates were representative of the internal conditions of the chambers. With appropriate internal ventilation and correction factors, the relative error of measurements was less than 5% for high evapotranspiration rates. (C) 2014 American Society of Civil Engineers.

Evaporation from the land surface, averaged over successive 8 day intervals and at 0.05° (∼5 km) spatial resolution, was calculated using the Penman‐Monteith (PM) energy balance equation, gridded meteorology, and a simple biophysical model for surface conductance. This conductance is a function of evaporation from the soil surface, leaf area index, absorbed photosynthetically active radiation, atmospheric water vapor pressure deficit, and maximum stomatal conductance ( g sx ). The novelty of this paper is the use of a “Budyko‐curve” hydrometeorological model to estimate mean annual evaporation rates and hence a unique value of g sx for each grid cell across the Australian continent. First, the hydrometeorological model was calibrated using long‐term water balances from 285 gauged catchments. Second, gridded meteorological data were used with the calibrated hydrometeorological model to estimate mean annual average evaporation ( ) for each grid cell. Third, the value of g sx for each cell was adjusted to equate calculated using the PM equation with from the hydrometeorological model. This closes the annual water balance but allows the PM equation to provide a finer temporal resolution for evaporation than is possible with an annual water balance model. There was satisfactory agreement (0.49 < R 2 < 0.80) between 8 day average evaporation rates obtained using remotely sensed leaf area indices, the parameterized PM equation, and observations of actual evaporation at four Australian eddy covariance flux sites for the period 2000–2008. The evaporation product can be used for hydrological model calibration to improve runoff prediction studies in ungauged catchments.

Soils are responsible for storing up to 75% of forest carbon uptake making them extremely large carbon pools. However, soil carbon is eventually released to the atmosphere by below ground respiration, consisting of soil respiration (microbial activity) and root respiration, which is influenced by environmental climate variables (soil temperature and moisture), soil characteristics (chemical and physical properties) and stand characteristics (stand age). We investigated the impact of stand age of cool temperate mountain ash forests (E. regnans) in Wallaby Creek, Victoria on carbon cycling between the soil and atmosphere using a chronosequence of three sites of different ages (regrowth from bushfires in 1730, 1926 and 1983). Below ground respiration was measured between January (Summer) and May (Autumn) in 2005 across all three sites, with the highest rates found in the old growth forest (5.3μmolCO2m−2s−1) and with lowest rates in the youngest site (2.9μmolCO2m−2s−1). Within sites, below ground respiration rates increased with temperature, with Q10 values ranging between 1.42 and 1.55. Rates were further influenced by soil moisture, and soil physical and chemical properties, including root biomass and levels of soil carbon. Litterfall was also measured and was highest at the youngest site (140gbiomassm−2month−1) and lowest (92gbiomassm−2month−1) at the old growth site. Greater understanding of forest carbon cycling will result in an improved understanding of forests and their influence on global warming.