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The magnitude of the terrestrial carbon (C) sink may be overestimated globally due to the difficulty of accounting for all C losses across heterogeneous landscapes. More complete assessments of net landscape C balances (NLCB) are needed that integrate both emissions by fire and transfer to aquatic systems, two key loss pathways of terrestrial C. These pathways can be particularly significant in the wet–dry tropics, where fire plays a fundamental part in ecosystems and where intense rainfall and seasonal flooding can result in considerable aquatic C export (ΣFaq). Here, we determined the NLCB of a lowland catchment (~140 km2) in tropical Australia over 2 years by evaluating net terrestrial productivity (NEP), fire‐related C emissions and ΣFaq (comprising both downstream transport and gaseous evasion) for the two main landscape components, that is, savanna woodland and seasonal wetlands. We found that the catchment was a large C sink (NLCB 334 Mg C km−2 year−1), and that savanna and wetland areas contributed 84% and 16% to this sink, respectively. Annually, fire emissions (−56 Mg C km−2 year−1) and ΣFaq (−28 Mg C km−2 year−1) reduced NEP by 13% and 7%, respectively. Savanna burning shifted the catchment to a net C source for several months during the dry season, while ΣFaq significantly offset NEP during the wet season, with a disproportionate contribution by single major monsoonal events—up to 39% of annual ΣFaq was exported in one event. We hypothesize that wetter and hotter conditions in the wet–dry tropics in the future will increase ΣFaq and fire emissions, potentially further reducing the current C sink in the region. More long‐term studies are needed to upscale this first NLCB estimate to less productive, yet hydrologically dynamic regions of the wet–dry tropics where our result indicating a significant C sink may not hold. [ABSTRACT FROM AUTHOR]

Understanding effects of climate change on ecosystems will require a diverse range of approaches. We proposed using downscaled climate models to generate realistic weather scenarios as experimental treatments. Kreyling et al. propose a gradient approach to determine the shape of response functions. These approaches are different, but highly complementary. [ABSTRACT FROM AUTHOR]

We used highly realistic temperature treatments based on down-scaled global circulation models for 1990-2000 (control) and 2100 (warming treatment) to experimentally assess the impacts of altered temperature regimes on the emerging adults of aquatic insect communities. Experiments were run for 6 weeks and emerging adults of insects were identified and measured for length. There were clear responses to the warming treatment, but responses were taxa- and gender-specific. Males of mayfly Ulmerophlebia pipinna Suter 1986 (Leptophlebiidae) emerged faster under 2100 temperatures. This resulted in a change in the sex ratio that could compromise populations. Mean body size of some insects decreased under warming conditions, which is in agreement with the general hypothesis of reduced body size in response to climate change. However, the degree to which organism size was affected by temperature varied within and between taxa. These changes show the potential for changed temperature regimes to impact ecological systems at individual, population, and community levels. Changes in body size and species composition of emerging insects are likely to impact different levels in both the aquatic and terrestrial communities, for example through disruption of interactions between emerging insects and riparian predators which rely on those resources. [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP) plays a critical role in the regulation of photosynthesis, evapotranspiration, and energy fluxes. Significant progress has been made in extracting LSP information over large areas using satellite data, yet LSP retrievals remain a challenge over vast arid and semi-arid ecosystems because of sparse greenness, high variability and the lack of distinct annual patterns; for example, the MODerate Imaging Spectrometer (MODIS) Land Cover Dynamics Product MCD12Q2 that provides LSP metrics globally often failed to provide LSP information in these ecosystems. In this study, we used a modified threshold algorithm to extract LSP timing metrics, including the start, peak, and end of growing seasons, using the 16-day composite Enhanced Vegetation Index (EVI) time series from MODIS data. We applied this regionally customized algorithm across all arid and semi-arid climate regions of Australia (75% of the continental land area) encompassing shrublands, grasslands, savannas, woodlands, and croplands, extracting LSP metrics annually from 2003 to 2018, with up to two (phenology) seasons accounted for in each year. Our algorithm yielded an average of 64.9% successful rate of retrieval (proportion of pixels with retrieved LSP metrics) across 16 years in Arid and Semi-arid AUStralia (AS-AUS), which was a significant increase compared to the 14.5% rate of retrieval yielded in our study area by the global product and the major cause of the different performances between these two approaches was the different EVI amplitude restrictions utilized to avoid spurious peaks (i.e. EVI amplitude ≥ 0.1 used by the global product and peak EVI ≥ time series average EVI used by our algorithm). Gross primary productivity (GPP) measurements at OzFlux eddy covariance (EC) tower sites were used to cross-compare with the presence/absence of growing seasons detected by our algorithm, and 97% of our retrieved seasons matched with those extracted using EC data. Preliminary tests at five OzFlux sites showed that our algorithm was robust to view angle-induced sensitivity of the input data and showed similar performance when using EVI data calculated using MODIS Nadir BRDF-Adjusted Reflectance product. Our retrieved LSP metrics revealed that vegetation growth in arid ecosystems is highly irregular and can occur at any time of the year, more than once in a year, or can skip a year. The proportion of pixels with two growing seasons was found to be correlated with the average annual precipitation of the study area (p < 0.01), providing an estimation approach of LSP via rainfall. Our study improves the detection and measurement of vegetation phenology in arid and semi-arid regions by improving the spatial extend of LSP retrievals, which contributes to studies on LSP variations and dryland ecosystem resilience to climate change. More evaluation is planned for future work to assess and further improve the accuracy of the retrieved LSP metrics. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) of wooded ecosystems (forests and savannas) is central to the global carbon cycle, comprising 67%–75% of total global terrestrial GPP. Climate change may alter this flux by increasing the frequency of temperatures beyond the thermal optimum of GPP (Topt). We examined the relationship between GPP and air temperature (Ta) in 17 wooded ecosystems dominated by a single plant functional type (broadleaf evergreen trees) occurring over a broad climatic gradient encompassing five ecoregions across Australia ranging from tropical in the north to Mediterranean and temperate in the south. We applied a novel boundary‐line analysis to eddy covariance flux observations to (a) derive ecosystem GPP–Ta relationships and Topt (including seasonal analyses for five tropical savannas); (b) quantitatively and qualitatively assess GPP–Ta relationships within and among ecoregions; (c) examine the relationship between Topt and mean daytime air temperature (MDTa) across all ecosystems; and (d) examine how down‐welling short‐wave radiation (Fsd) and vapour pressure deficit (VPD) influence the GPP–Ta relationship. GPP–Ta relationships were convex parabolas with narrow curves in tropical forests, tropical savannas (wet season), and temperate forests, and wider curves in temperate woodlands, Mediterranean woodlands, and tropical savannas (dry season). Ecosystem Topt ranged from 15℃ (temperate forest) to 32℃ (tropical savanna—wet and dry seasons). The shape of GPP–Ta curves was largely determined by daytime Ta range, MDTa, and maximum GPP with the upslope influenced by Fsd and the downslope influenced by VPD. Across all ecosystems, there was a strong positive linear relationship between Topt and MDTa (Adjusted R2: 0.81; Slope: 1.08) with Topt exceeding MDTa by >1℃ at all but two sites. We conclude that ecosystem GPP has adjusted to local MDTa within Australian broadleaf evergreen forests and that GPP is buffered against small Ta increases in the majority of these ecosystems. [ABSTRACT FROM AUTHOR]

Latent heat flux (LE) and corresponding water loss in non-moisture-limited ecosystems are well correlated to radiation and temperature. By contrast, in savannahs and arid and semi-arid lands LE is mostly driven by available water and the vegetation exerts a strong control over the rate of transpiration. Therefore, LE models that use optical vegetation indices (VIs) to represent the vegetation component (transpiration as a function of surface conductance, G s ) generally overestimate water fluxes in water-limited ecosystems. In this study, we evaluated and compared optical and passive microwave index based retrievals of G s and LE derived using the Penman-Monteith (PM) formulation over the North Australian Tropical Transect (NATT). The methodology was evaluated at six eddy covariance (EC) sites from the OzFlux network. To parameterize the PM equation for retrievals of LE (PM-G s ), a subset of G s values was derived from meteorological and EC flux observations and regressed against individual and combined satellite indices, from (1) MODIS AQUA: the Normalized Difference Water Index (NDWI) and the Enhanced Vegetation Index (EVI); and from (2) AMSR-E passive microwave: frequency index (FI), polarization index (PI), vegetation optical depth (VOD) and soil moisture (SM) products. Similarly, we combined optical and passive microwave indices (multi-sensor model) to estimate weekly G s values, and evaluated their spatial and temporal synergies. The multi-sensor approach explained 40–80% of LE variance at some sites, with root mean square errors (RMSE) lower than 20 W/m 2 and demonstrated better performance to other satellite-based estimates of LE. The optical indices represented potential G s associated with the phenological status of the vegetation (e.g. leaf area index, chlorophyll content) at finer spatial resolution. The microwave indices provided information about water availability and moisture stress (e.g. water content in leaves and shallow soil depths, atmospheric demand) at a high temporal resolution, thereby providing a scaling factor for potential G s . We applied the newly proposed G s model to estimate LE at regional scale using global meteorological data. Our derivation could be extended to continental scales providing equally robust estimates of LE in arid and semi-arid biomes. A more accurate estimation of G s and LE across different savannah classes will improve the analysis of water use efficiency under drought conditions, which is of importance to climate change studies of water, carbon and energy cycling. [ABSTRACT FROM AUTHOR]

Accurate measurements of energy fluxes between land and atmosphere are important for understanding and modeling climatic patterns. Several methods are available to measure heat fluxes, and scintillometers are becoming increasingly popular because of their ability to measure sensible ( H ) and latent ( L v E ) heat fluxes over large spatial scales. The main motivation of this study was to test the use of different methods and technologies to derive surface heat fluxes. Measurements of H and L v E were carried out with an eddy covariance (EC) system, two different makes of optical large aperture scintillometers (LAS) and two microwave scintillometers (MWS) with different frequencies at a pasture site in a semi-arid environment of New South Wales, Australia. We used the EC measurements as a benchmark. Fluxes derived from the EC system and LAS systems agreed ( R 2 > 0.94), whereas the MWS systems measured lower H (bias ∼60 W m −2 ) and larger L v E (bias ∼65 W m −2 ) than EC. When the scintillometers were compared against each other, the two LASs showed good agreement of H ( R 2 = 0.98), while MWS with different frequencies and polarizations led to different results. Combination of LAS and MWS measurements (i.e., two wavelength method) resulted in performance that fell in between those estimated using either LAS or MWS alone when compared with the EC system. The cause for discrepancies between surface heat fluxes derived from the EC system and those from the MWS systems and the two-wavelength method are possibly related to inaccurate assignment of the structure parameter of temperature and humidity. Additionally, measurements from MWSs can be associated with two values of the Bowen ratio, thereby leading to uncertainties in the estimation of the fluxes. While only one solution has been considered in this study, when L v E was approximately less than 200 W m −2 , the alternate solution may be more accurate. Therefore, for measurements of surface heat fluxes in a semi-arid or dry environment, the optical scintillometer is recommended, whereas further work will be required to improve the estimation of surface heat fluxes from microwave systems. [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP) characterizes episodes of greening and browning of the vegetated land surface from remote sensing imagery. LSP is of interest for quantification and monitoring of crop yield, wildfire fuel accumulation, vegetation condition, ecosystem response and resilience to climate variability and change. Deriving LSP represents an effort for end users and existing global products may not accommodate conditions in Australia, a country with a dry climate and high rainfall variability. To fill this information gap we developed the Australian LSP Product in contribution to AusCover/Terrestrial Ecosystem Research Network (TERN). We describe the product's algorithm and information content consisting of metrics that characterize LSP greening and browning episodes of the vegetated land surface. Our product allows tracking LSP metrics over time and thereby quantifying inter- and intraannual variability across Australia. We demonstrate the metrics' response to ENSO-driven climate variability. Lastly, we discuss known limitations of the current product and future development plans. [ABSTRACT FROM AUTHOR]

Accurate estimation of carbon fluxes across space and time is of great importance for quantifying global carbon balances. Current production efficiency models for calculation of gross primary production (GPP) depend on estimates of light-use-efficiency (LUE) obtained from look-up tables based on biome type and coarse-resolution meteorological inputs that can introduce uncertainties. Plant function is especially difficult to parameterize in the savanna biome due to the presence of varying mixtures of multiple plant functional types (PFTs) with distinct phenologies and responses to environmental factors. The objective of this study was to find a simple and robust method to accurately up-scale savanna GPP from local, eddy covariance (EC) flux tower GPP measures to regional scales utilizing entirely remote sensing oservations. Here we assessed seasonal patterns of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation products with seasonal EC tower GPP (GPP EC ) at four sites along an ecological rainfall gradient (the North Australian Tropical Transect, NATT) encompassing tropical wet to dry savannas. The enhanced vegetation index (EVI) tracked the seasonal variations of GPP EC well at both site- and cross-site levels ( R 2 = 0.84). The EVI relationship with GPP EC was further strengthened through coupling with ecosystem light-use-efficiency (eLUE), defined as the ratio of GPP to photosynthetically active radiation (PAR). Two savanna landscape eLUE models, driven by top-of-canopy incident PAR (PAR TOC ) or top-of-atmosphere incident PAR (PAR TOA ) were parameterized and investigated. GPP predicted using the eLUE models correlated well with GPP EC , with R 2 of 0.85 (RMSE = 0.76 g C m − 2 d − 1 ) and 0.88 (RMSE = 0.70 g C m − 2 d − 1 ) for PAR TOC and PAR TOA , respectively, and were significantly improved compared to the MOD17 GPP product ( R 2 = 0.58, RMSE = 1.43 g C m − 2 d − 1 ). The eLUE model also minimized the seasonal hysteresis observed between green-up and brown-down in GPP EC and MODIS satellite product relationships, resulting in a consistent estimation of GPP across phenophases. The eLUE model effectively integrated the effects of variations in canopy photosynthetic capacity and environmental stress on photosynthesis, thus simplifying the up-scaling of carbon fluxes from tower to regional scale. The results from this study demonstrated that region-wide savanna GPP can be accurately estimated entirely with remote sensing observations without dependency on coarse-resolution ground meteorology or estimation of light-use-efficiency parameters. [ABSTRACT FROM AUTHOR]

Highlights: [•] Seven light use efficiency models were compared at global eddy covariance towers. [•] Performance of seven models differed substantially among ecosystem types. [•] It is needed to improve LUE models by integrating impacts of diffuse radiation and reliable water stress equations. [Copyright &y& Elsevier]

Abstract: The use of Penman–Monteith (PM) equation in thermal remote sensing based surface energy balance modeling is not prevalent due to the unavailability of any direct method to integrate thermal data into the PM equation and due to the lack of physical models expressing the surface (or stomatal) and boundary layer conductances (gS and gB ) as a function of surface temperature. Here we demonstrate a new method that physically integrates the radiometric surface temperature (TS ) into the PM equation for estimating the terrestrial surface energy balance fluxes (sensible heat, H and latent heat, λE). The method combines satellite TS data with standard energy balance closure models in order to derive a hybrid closure that does not require the specification of surface to atmosphere conductance terms. We call this the Surface Temperature Initiated Closure (STIC), which is formed by the simultaneous solution of four state equations. Taking advantage of the psychrometric relationship between temperature and vapor pressure, the present method also estimates the near surface moisture availability (M) from TS , air temperature (TA ) and relative humidity (RH ), thereby being capable of decomposing λE into evaporation (λEE ) and transpiration (λET ). STIC is driven with TS , TA , RH , net radiation (RN ), and ground heat flux (G). TS measurements from both MODIS Terra (MOD11A2) and Aqua (MYD11A2) were used in conjunction with FLUXNET RN , G, TA , RH , λE and H measurements corresponding to the MODIS equatorial crossing time. The performance of STIC has been evaluated in comparison to the eddy covariance measurements of λE and H at 30 sites that cover a broad range of biomes and climates. We found a RMSE of 37.79 (11%) (with MODIS Terra TS ) and 44.27Wm−2 (15%) (with MODIS Aqua TS ) in λE estimates, while the RMSE was 37.74 (9%) (with Terra) and 44.72Wm−2 (8%) (with Aqua) in H. STIC could efficiently capture the λE dynamics during the dry down period in the semi-arid landscapes where λE is strongly governed by the subsurface soil moisture and where the majority of other λE models generally show poor results. Sensitivity analysis revealed a high sensitivity of both the fluxes to the uncertainties in TS . A realistic response and modest relationship was also found when partitioned λE components (λEE and λET ) were compared to the observed soil moisture and rainfall. This is the first study to report the physical integration of TS into the PM equation and finding analytical solution of the physical (gB ) and physiological conductances (gS ). The performance of STIC over diverse biomes and climates points to its potential to benefit future NASA and NOAA missions having thermal sensors, such as HyspIRI, GeoSTAR and GOES-R for mapping multi-scale λE and drought. [Copyright &y& Elsevier]

The phenology of a landscape is a key parameter in climate and biogeochemical cycle models and its correct representation is central to the accurate simulation of carbon, water and energy exchange between the land surface and the atmosphere. Whereas biogeographic phenological patterns and shifts have received much attention in temperate ecosystems, much less is known about the phenology of savannas, despite their sensitivity to climate change and their coverage of approximately one eighth of the global land surface. Savannas are complex assemblages of multiple tree, shrub, and grass vegetation strata, each with variable phenological responses to seasonal climate and environmental variables. The objectives of this study were to investigate biogeographical and inter-annual patterns in savanna phenology along a 1100km ecological rainfall gradient, known as North Australian Tropical Transect (NATT), encompassing humid coastal Eucalyptus forests and woodlands to xeric inland Acacia woodlands and shrublands. Key phenology transition dates (start, peak, end, and length of seasonal greening periods) were extracted from 13years (2000–2012) of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data using Singular Spectrum Analysis (SSA). Two distinct biogeographical patterns in phenology were observed, controlled by different climate systems. The northern (mesic) portion of the transect, from 12°S, to around 17.7°S, was influenced by the Inter-Tropical Convergence Zone (ITCZ) seasonal monsoon climate system, resulting in strong latitudinal shifts in phenology patterns, primarily associated with the functional response of the C4 grass layer. Both the start and end of the greening (enhanced vegetation activity) season occurred earlier in the northern tropical savannas and were progressively delayed towards the southern limit of the Eucalyptus-dominated savannas resulting in relatively stable length of greening periods. In contrast, the southern xeric portion of the study area was largely decoupled from monsoonal influences and exhibited highly variable phenology that was largely rainfall pulse driven. The seasonal greening periods were generally shorter but fluctuated widely from no detectable greening during extended drought periods to length of greening seasons that exceeded those in the more mesic northern savannas in some wet years. This was in part due to more extreme rainfall variability, as well as a C3/C4 grass-forb understory that provided the potential for extended greening periods. Phenology of Acacia dominated savannas displayed a much greater overall responsiveness to hydroclimatic variability. The variance in annual precipitation alone could explain 80% of the variances in the length of greening season across the major vegetation groups. We also found that increased variation in the timing of phenology was coupled with a decreasing tree-grass ratio. We further compared the satellite-based phenology results with tower-derived measures of Gross Ecosystem Production (GEP) fluxes at three sites over two contrasting savanna classes. We found good convergence between MODIS EVI and tower GEP, thereby confirming the potential to link these two independent data sources to better understand savanna ecosystem functioning. [ABSTRACT FROM AUTHOR]

Abstract: Tropical savanna ecosystems are a major contributor to global CO2, CH4 and N2O greenhouse gas exchange. Savanna fire events represent large, discrete C emissions but the importance of ongoing soil-atmosphere gas exchange is less well understood. Seasonal rainfall and fire events are likely to impact upon savanna soil microbial processes involved in N2O and CH4 exchange. We measured soil CO2, CH4 and N2O fluxes in savanna woodland (Eucalyptus tetrodonta/Eucalyptus miniata trees above sorghum grass) at Howard Springs, Australia over a 16 month period from October 2007 to January 2009 using manual chambers and a field-based gas chromatograph connected to automated chambers. The effect of fire on soil gas exchange was investigated through two controlled burns and protected unburnt areas. Fire is a frequent natural and management action in these savanna (every 1–2 years). There was no seasonal change and no fire effect upon soil N2O exchange. Soil N2O fluxes were very low, generally between −1.0 and 1.0μg Nm−2 h−1, and often below the minimum detection limit. There was an increase in soil NH4 + in the months after the 2008 fire event, but no change in soil NO3 −. There was considerable nitrification in the early wet season but minimal nitrification at all other times. Savanna soil was generally a net CH4 sink that equated to between −2.0 and −1.6kg CH4 ha−1 y−1 with no clear seasonal pattern in response to changing soil moisture conditions. Irrigation in the dry season significantly reduced soil gas diffusion and as a consequence soil CH4 uptake. There were short periods of soil CH4 emission, up to 20μg Cm−2 h−1, likely to have been caused by termite activity in, or beneath, automated chambers. Soil CO2 fluxes showed a strong bimodal seasonal pattern, increasing fivefold from the dry into the wet season. Soil moisture showed a weak relationship with soil CH4 fluxes, but a much stronger relationship with soil CO2 fluxes, explaining up to 70% of the variation in unburnt treatments. Australian savanna soils are a small N2O source, and possibly even a sink. Annual soil CH4 flux measurements suggest that the 1.9million km2 of Australian savanna soils may provide a C sink of between −7.7 and −9.4 Tg CO2-e per year. This sink estimate would offset potentially 10% of Australian transport related CO2-e emissions. This CH4 sink estimate does not include concurrent CH4 emissions from termite mounds or ephemeral wetlands in Australian savannas. [Copyright &y& Elsevier]

Aerodynamic resistance (hereafter r a) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of r a plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r a with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates. The present study investigates the influence of r a and its relation to LST uncertainties on the performance of three structurally different SEB models. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE , the energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST , LAI, and in-situ meteorological datasets were evaluated against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019. Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in r a retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low r a (high wind speeds) and caused a slight underestimation of LE at the water-limited sites. The impact of r a on the LE residual error was found to be of the same magnitude as the influence of LST uncertainties in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for the mesic forest ecosystems indicated minor dependency on r a for modelling LE (VIP < 0.4), which was due to a higher roughness length and lower LST resulting in the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of r a. • Modelled latent heat flux is uncertain under drought due to aerodynamic resistance. • Overestimation of aerodynamic resistance at water-limited sites for low wind speed. • Stability links aerodynamic resistance with surface temperature and sensible heat. • Novel formulations for aerodynamic resistance are needed to model latent heat flux. [ABSTRACT FROM AUTHOR]

Savannas, occupying a fifth of the global land surface, are characterized by the coexistence of trees and grasses. Accurate estimation of savanna evapotranspiration (ET) is vital for understanding the regional and global water balance and its feedback to climate. However, the overlapping phenology and different water-use patterns of trees and grasses constitute a major challenge for modeling efforts. To estimate savanna ET, we used a three-source ET model, partitioning ET among soil, trees, and grasses. To represent legacy effects of precipitation on ecosystem water use, the Normalized Ecosystem Drought Index (NEDI, i.e. a function of precipitation and potential evapotranspiration) was included to limit canopy conductances in the model and also in two other classic two-layer models (Shuttleworth-Wallace model and Penman-Monteith-Leuning model). The results of our model and the other models were tested and compared using tower-based eddy covariance flux data collected at six sites (including four savanna sites, one pasture site, and one grassland site) along a precipitation gradient in northern Australia, together with satellite-derived leaf area index, which was partitioned to represent the canopy dynamics of trees and grasses. Inclusion of NEDI significantly reduced seasonal biases in ET estimation results for all models compared with observations at savanna sites (fitted slopes were closer to unity by 0.08–0.10, R2 increased by 0.03–0.04, and RMSE decreased by 0.07–0.09 mm d−1). The three-source model provides insights into simulation of water fluxes over vegetated areas of complex composition. Our work makes a contribution to savanna research by determining a flexible indicator defining the seasonal water availability limitation on savanna ET. The inclusion of NEDI in ET models could guide future research on modeling ecosystem water and carbon fluxes in response to seasonal droughts. [ABSTRACT FROM AUTHOR]

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 GPP tree and GPP grass 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, GPP tree showed a steeper decrease with precipitation along the NATT compared to GPP grass , 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. • Functional partition of savanna GPP into tree and grass using MODIS was achieved. • Validation of the partitioned results against flux tower data showed good agreement. • Savanna tree and grass ratio varies according to rainfall, soil, and other factors. • Seasonal & inter-annual savanna GPP and tree-grass ratio was driven by C 4 grasses. • Savanna is particularly sensitive to climate change and hydroclimatic variability. [ABSTRACT FROM AUTHOR]

• Forests and wetlands buffer thermal fluctuation better than non-forests • Forest degradation reduces thermal buffer ability, especially at high latitudes • Canopy height is the primary impact factor influencing TBA of forests • Energy partitioning, water and CO 2 exchange are the main drivers of non-forests TBA • Protecting mature forests mitigates thermal fluctuation under extreme events With the increase in intensity and frequency of extreme climate events, interactions between vegetation and local climate are gaining more and more attention. Both the mean temperature and the temperature fluctuations of vegetation will exert thermal influence on local climate and the life of plants and animals. Many studies have focused on the pattern in the mean canopy surface temperature of vegetation, whereas there is still no systematic study of thermal buffer ability (TBA) of different vegetation types across global biomes. We developed a new method to measure TBA based on the rate of temperature increase, requiring only one radiometer. With this method, we compared TBA of ten vegetation types with contrasting structures, e.g. from grasslands to forests, using data from 133 sites globally. TBA ranged from 5.2 to 21.2 across these sites and biomes. Forests and wetlands buffer thermal fluctuation better than non-forests (grasslands, savannas, and croplands), and the TBA boundary between forests and non-forests was typically around 10. Notably, seriously disturbed and young planted forests displayed a greatly reduced TBA as low as that of non-forests at high latitudes. Canopy height was a primary controller of TBA of forests, while the TBA of grasslands and savannas were mainly determined by energy partition, water availability, and carbon sequestration rates. Our research suggests that both mean values and fluctuations in canopy surface temperature should be considered to predict the risk for plants under extreme events. Protecting mature forests, both at high and low latitudes, is critical to mitigate thermal fluctuation under extreme events. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• Predictability of fluxes was evaluated across nineteen agricultural sites. • High-intensity management promoted coupling of carbon, water and energy fluxes. • Some environmental factors were affected by management, and others were fixed. • Temporal complementarity of water and energy limitations degraded predictability. A comprehensive understanding of the effects of agricultural management on climate–crop interactions has yet to emerge. Using a novel wavelet–statistics conjunction approach, we analysed the synchronisation amongst fluxes (net ecosystem exchange NEE, evapotranspiration and sensible heat flux) and seven environmental factors (e.g., air temperature, soil water content) on 19 farm sites across Australia and New Zealand. Irrigation and fertilisation practices improved positive coupling between net ecosystem productivity (NEP = −NEE) and evapotranspiration, as hypothesised. Highly intense management tended to protect against heat stress, especially for irrigated crops in dry climates. By contrast, stress avoidance in the vegetation of tropical and hot desert climates was identified by reverse coupling between NEP and sensible heat flux (i.e., increases in NEP were synchronised with decreases in sensible heat flux). Some environmental factors were found to be under management control, whereas others were fixed as constraints at a given location. Irrigated crops in dry climates (e.g., maize, almonds) showed high predictability of fluxes given only knowledge of fluctuations in climate (R2 > 0.78), and fluxes were nearly as predictable across strongly energy- or water-limited environments (0.60 < R2 < 0.89). However, wavelet regression of environmental conditions on fluxes showed much smaller predictability in response to precipitation pulses (0.15 < R2 < 0.55), where mowing or grazing affected crop phenology (0.28 < R2 < 0.59), and where water and energy limitations were balanced (0.7 < net radiation ∕ precipitation < 1.3; 0.27 < R2 < 0.36). By incorporating a temporal component to regression, wavelet–statistics conjunction provides an important step forward for understanding direct ecosystem responses to environmental change, for modelling that understanding, and for quantifying nonstationary, nonlinear processes such as precipitation pulses, which have previously defied quantitative analysis. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Wildfires are increasing in frequency, intensity, and extent globally due to climate change and they can alter forest composition, structure, and function. The destruction and subsequent regrowth of young vegetation can modify the ecosystem evapotranspiration and downstream water availability. However, the response of forest recovery on hydrology is not well known with even the sign of evapotranspiration and water yield changes following forest fires being uncertain across the globe. Here, we quantify the effects of forest regrowth after catastrophic wildfires on evapotranspiration and runoff in the world's tallest angiosperm forest (Eucalyptus regnans) in Australia. We combine eddy covariance measurements including pre- and post-fire periods, mechanistic ecohydrological modeling and then extend the analysis spatially to multiple fires in eucalypt-dominated forests in south-eastern Australia by utilizing remote sensing. We find a fast recovery of evapotranspiration which reaches and exceeds pre-fire values within 2 years after the bushfire, a result confirmed by eddy covariance data, remote sensing, and modeling. Such a fast evapotranspiration recovery is likely generalizable to tall eucalypt forests in south-eastern Australia as shown by remote sensing. Once climate variability is discounted, ecohydrological modeling shows evapotranspiration rates from the recovering forest which reach peak values of +20% evapotranspiration 3 years post-fire. As a result, modeled runoff decreases substantially. Contrary to previous research, we find that the increase in modeled evapotranspiration is largely caused by the aerodynamic effects of a much shorter forest height leading to higher surface temperature, higher humidity gradients and therefore increased transpiration. However, increases in evapotranspiration as well as decreases in runoff caused by the young forest are constrained by energy and water limitations. Our result of an increase in evapotranspiration due to aerodynamic warming in a shorter forest after wildfires could occur in many parts of the world experiencing forest disturbances., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm -2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types., (© 2022. The Author(s).)

Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th 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 CO 2 sink to a net CO 2 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., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Despite their size and contribution to the global carbon cycle, we have limited understanding of tropical savannas and their current trajectory with climate change and anthropogenic pressures. Here we examined interannual variability and externally forced long-term changes in carbon and water exchange from a high rainfall savanna site in the seasonal tropics of north Australia. We used an 18-year flux data time series (2001-2019) to detect trends and drivers of fluxes of carbon and water. Significant positive trends in gross primary productivity (GPP, 15.4 g C m 2  year -2 ), ecosystem respiration (R eco , 8.0 g C m 2  year -2 ), net ecosystem productivity (NEE, 7.4 g C m 2  year -2 ) and ecosystem water use efficiency (WUE, 0.0077 g C kg H 2 O -1  year -1 ) were computed. There was a weaker, non-significant trend in latent energy exchange (LE, 0.34 W m -2  year -1 ). Rainfall from a nearby site increased statistically over a 45-year period during the observation period. To examine the dominant drivers of changes in GPP and WUE, we used a random forest approach and a terrestrial biosphere model to conduct an attribution experiment. Radiant energy was the dominant driver of wet season fluxes, whereas soil water content dominated dry season fluxes. The model attribution suggested that [CO 2 ], precipitation and T air accounting for 90% of the modelled trend in GPP and WUE. Positive trends in fluxes were largest in the dry season implying tree components were a larger contributor than the grassy understorey. Fluxes and environmental drivers were not significant during the wet season, the period when grasses are active. The site is potentially still recovering from a cyclone 45 years ago and regrowth from this event may also be contributing to the observed trends in sequestration, highlighting the need to understand fluxes and their drivers from sub-diurnal to decadal scales., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Quantifying the responses of the coupled carbon and water cycles to current global warming and rising atmospheric CO 2 concentration is crucial for predicting and adapting to climate changes. Here we show that terrestrial carbon uptake (i.e. gross primary production) increased significantly from 1982 to 2011 using a combination of ground-based and remotely sensed land and atmospheric observations. Importantly, we find that the terrestrial carbon uptake increase is not accompanied by a proportional increase in water use (i.e. evapotranspiration) but is largely (about 90%) driven by increased carbon uptake per unit of water use, i.e. water use efficiency. The increased water use efficiency is positively related to rising CO 2 concentration and increased canopy leaf area index, and negatively influenced by increased vapour pressure deficits. Our findings suggest that rising atmospheric CO 2 concentration has caused a shift in terrestrial water economics of carbon uptake.The response of the coupled carbon and water cycles to anthropogenic climate change is unclear. Here, the authors show that terrestrial carbon uptake increased significantly from 1982 to 2011 and that this increase is largely driven by increased water-use efficiency, rather than an increase in water use.

Photosynthesis provides plants with their main building material, carbohydrates, and with the energy necessary to thrive and prosper in their environment. We expect, therefore, that natural vegetation would evolve optimally to maximize its net carbon profit (NCP), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled N(CP) for an optimal vegetation for a site in the wet-dry tropics of north Australia based on this hypothesis and on an ecophysiological gas exchange and photosynthesis model, and compared the modelled CO2 fluxes and canopy properties with observations from the site. The comparison gives insights into theoretical and real controls on gas exchange and canopy structure, and supports the optimality approach for the modelling of gas exchange of natural vegetation. The main advantage of the optimality approach we adopt is that no assumptions about the particular vegetation of a site are required, making it a very powerful tool for predicting vegetation response to long-term climate or land use change.