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One of the major undetermined problems in evaporation (ET) retrieval using thermal infrared remote sensing is the lack of a physically based ground heat flux (G) model and its integration within the surface energy balance (SEB) equation. Here, we present a novel approach based on coupling a thermal inertia (TI)-based mechanistic G model with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC, version STIC1.2). The coupled model is named STIC-TI. The model is driven by noon–night (13:30 and 01:30 local time) land surface temperature, surface albedo, and a vegetation index from MODIS Aqua in conjunction with a clear-sky net radiation sub-model and ancillary meteorological information. SEB flux estimates from STIC-TI were evaluated with respect to the in situ fluxes from eddy covariance measurements in diverse ecosystems of contrasting aridity in both the Northern Hemisphere and Southern Hemisphere. Sensitivity analysis revealed substantial sensitivity of STIC-TI-derived fluxes due to the land surface temperature uncertainty. An evaluation of noontime G (Gi) estimates showed 12 %–21 % error across six flux tower sites, and a comparison between STIC-TI versus empirical G models also revealed the substantially better performance of the former. While the instantaneous noontime net radiation (RNi) and latent heat flux (LEi) were overestimated (15 % and 25 %), sensible heat flux (Hi) was underestimated (22 %). Overestimation (underestimation) of LEi (Hi) was associated with the overestimation of net available energy (RNi−Gi) and use of unclosed surface energy balance flux measurements in LEi (Hi) validation. The mean percent deviations in Gi and Hi estimates were found to be strongly correlated with satellite day–night view angle difference in parabolic and linear pattern, and a relatively weak correlation was found between day–night view angle difference versus LEi deviation. Findings from this parameter-sparse coupled G–ET model can make a valuable contribution to mapping and monitoring the spatiotemporal variability of ecosystem water stress and evaporation using noon–night thermal infrared observations from future Earth observation satellite missions such as TRISHNA, LSTM, and SBG.

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.

China has implemented some of the world's most ambitious ecological restoration (ER) programs over the past two decades. These large-scale multi-billion-dollar projects have achieved widespread greening across the country. However, the impacts of different ER-driven land cover modifications on total water resources remain largely unknown, particularly over areas characterized by complex environments of coupled human and natural systems. Here we quantified ecohydrological impacts of multiple ER programs applied over various parts of China's Yellow River Basin (YRB), with their lumped effects being partitioned into individual ones. ER-related drivers were disentangled, leading in individual attribution of inter-annual climatic variability and agricultural activity with cross-sensor satellite observations and statistical modelling. Our results showed an ecohydrological decoupling of water storage and vegetation greenness attributed to ER programs. Increases in natural land cover types (e.g. forest and grassland) were found at the expense of human intensive land use, such as farmland, with the combined changes resulting in a concurrent dramatic water storage loss of 3.70 billion tons/year from 2002 to 2021. ER was the dominant driver of water loss (>66 %) among all factors considered, commensurate with areal land-cover change and ER program cost. The entire basin was divided into two regions with opposite water trends by the ER activities with different restoration strategies. This study's framework is applicable to substantial part of the globe like YRB and is encouraged to be applied for more wholistic ER impact evaluations.

The vegetation's response to climate change is a significant source of uncertainty in future terrestrial biosphere model projections. Constraining climate–carbon cycle feedbacks requires improving our understanding of both the immediate and long-term plant physiological responses to climate. In particular, the timescales and strength of memory effects arising from both extreme events (i.e. droughts and heatwaves) and structural lags in the systems (such as delays between rainfall and peak plant water content or between a precipitation deficit and down-regulation of productivity) have largely been overlooked in the development of terrestrial biosphere models. This is despite the knowledge that plant responses to climatic drivers occur across multiple timescales (seconds to decades), with the impact of climate extremes resonating for many years. Using data from 12 eddy covariance sites, covering two rainfall gradients (256 to 1491 mm yr−1) in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales and magnitude of influence of antecedent drivers on daily net ecosystem exchange (NEE) and latent heat flux (λE). By focussing our analysis on a single continent (and predominately on a single genus), we reduced the degrees of variation between each site, providing a novel chance to explore the unique characteristics that might drive the importance of memory. Model fit varied considerably across sites when modelling NEE, with R2 values of between 0.30 and 0.83. λE was considerably more predictable across sites, with R2 values ranging from 0.56 to 0.93. When considered at a continental scale, both fluxes were more predictable when memory effects (expressed as lagged climate predictors) were included in the model. These memory effects accounted for an average of 17 % of the NEE predictability and 15 % for λE. Consistent with prior studies, the importance of environmental memory in predicting fluxes increased as site water availability declined (ρ=-0.73, p

International audience; Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State-of-the-art one-source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non-parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio-temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research.

Animals, such as termites, have largely been overlooked as global-scale drivers of biogeochemical cycles1,2, despite site-specific findings3,4. Deadwood turnover, an important component of the carbon cycle, is driven by multiple decay agents. Studies have focused on temperate systems5,6, where microbes dominate decay7. Microbial decay is sensitive to temperature, typically doubling per 10°C increase (decay effective Q10 = ~2)8–10. Termites are important decayers in tropical systems3,11–13 and differ from microbes in their population dynamics, dispersal, and substrate discovery14–16, meaning their climate sensitivities also differ. Using a network of 133 sites spanning 6 continents, we report the first global field-based quantification of temperature and precipitation sensitivities for termites and microbes, providing novel understandings of their response to changing climates. Temperature sensitivity of microbial decay was within previous estimates. Termite discovery and consumption were both much more sensitive to temperature (decay effective Q10 = 6.53), leading to striking differences in deadwood turnover in areas with and without termites. Termite impacts were greatest in tropical seasonal forests and savannas and subtropical deserts. With tropicalization17 (i.e., warming shifts to a tropical climate), the termite contribution to global wood decay will increase as more of the earth’s surface becomes accessible to termites. Acknowledgements. For materials, field, and lab assistance, we thank the Australian Landscape Trust Team, Juan Martínez de Aragón, Eric Roy, Hugh Wilson, Kylie Brice, Bethanie Coleman, Brendan Delroy, Coline Deveautour, Suzanne Donn, Generci Assis Neves, Ricardo Marques Barreiros, Ricardo Marques Barreiros, Generci Assis Neves from Resineves Agroflorestal company, Alfred Lochner, Pousada Vale do Céu, Humberto Robles, María M. Rivera, and Grant Kirker. Steve Allison and Tom Crowther provided comments on the manuscript and Abbey Yatsko helped with figure and manuscript formatting. Funding for this work was provided by US National Science Foundation (DEB-1655759, 2149151, 1713502, 1713435, 1647502, 1546686, 1831952), George Washington University, USDA Forest Service, Centre College Faculty Development Funds, Australia Terrestrial Ecosystem Research Network (TERN) National Collaborative Research Infrastructure Strategy (NCRIS), Royal Society-FCDO Africa Capacity Building Initiative, New Phytologist Foundation, Fondecyt grant:1160329, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Department of Ecology and Conservation of the Federal University of Lavras, CNPq, FAPEMIG, Australian Academy of Science 2017 Thomas Davies Research Grant, Australian Research Council (DP160103765), UK National Environment Research Council (NE/L000016/1), Fundação de Amparo à Pesquisa do Estado de São Paulo, Brazil (NERC - FAPESP)19/07773-1, Environment Research and Technology Development Fund (ERTDF; JPMEERF15S11420) of the Environmental Restoration and Conservation Agency (ERCA) of Japan, COLCIENCIAS (No. FP44842-046-2017), Spanish Government (grant PID2019-110521GB-I00), Catalan Government (grant SGR 2017-1005), Fundación Ramón Areces (grant ELEMENTAL-CLIMATE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) PICT 2019- 2472, National Agency for the Promotion of Research, Technological Development and Innovation, Scientific and Technological Research Project 2018-01561 (PICT 2018- 01561), iDiv German Research Foundation (DFG– FZT 118, 202548816), European Research Council (ERC), European Union's Horizon 2020 research and innovation program (grant agreement no. 677232).

Global warming and anthropogenic activities have imposed noticeable impacts on rainfall pattern changes at both spatial and temporal scales in recent decades. Systematic diagnosis of rainfall pattern changes is urgently needed at spatiotemporal scales for a deeper understanding of how climate change produces variations in rainfall patterns. The objective of this study was to identify rainfall pattern changes systematically under climate change at a subcontinental scale along a rainfall gradient ranging from 1800 to 200 mm yr−1 by analyzing centennial rainfall data covering 230 sites from 1910 to 2017 in the Northern Territory of Australia. Rainfall pattern changes were characterized by considering aspects of trends and periodicity of annual rainfall, abrupt changes, rainfall distribution, and extreme rainfall events. Our results illustrated that rainfall patterns in northern Australia have changed significantly compared with the early period of the twentieth century. Specifically, 1) a significant increasing trend in annual precipitation associated with greater variation in recent decades was observed over the entire study area, 2) temporal variations represented a mean rainfall periodicity of 27 years over wet to dry regions, 3) an abrupt change of annual rainfall amount occurred consistently in both humid and arid regions during the 1966–75 period, and 4) partitioned long-term time series of rainfall demonstrated a wetter rainfall distribution trend across coastal to inland areas that was associated with more frequent extreme rainfall events in recent decades. The findings of this study could facilitate further studies on the mechanisms of climate change that influence rainfall pattern changes. Significance Statement Characterizing long-term rainfall pattern changes under different rainfall conditions is important to understand the impacts of climate change. We conducted diagnosis of centennial rainfall pattern changes across wet to dry regions in northern Australia and found that rainfall patterns have noticeably changed in recent decades. The entire region has a consistent increasing trend of annual rainfall with higher variation. Meanwhile, the main shifting period of rainfall pattern was during 1966–75. Although annual rainfall seems to become wetter with an increasing trend, more frequent extreme rainfall events should also be noticed for assessing the impacts of climate changes. The findings support further study to understand long-term rainfall pattern changes under climate change.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8., Three key axes of variation of ecosystem functional changes and their underlying causes are identified from a dataset of surface gas exchange measurements across major terrestrial biomes and climate zones.

Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r2: 0.47~0.86, SIF r2: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.

Tamarix chinensis Lour., which is common throughout the southwestern USA, is a phreatophytic riparian tree capable of high water use. We investigated temporal congruence between daily total evapotranspiration (Esf) estimated from stem sap flux (Js) measurements (Esf) and eddy covariance (Ecv), both seasonally and immediately following rain events, and used measurements of leaf-level gas exchange, stem water content and diurnal changes in leaf water potential to track drivers of transpiration. In one study, conducted near the end of the growing season in a pure T. chinensis stand adjacent to the Rio Grande River in central New Mexico, nighttime Esf as a proportion of daily Esf increased with water availability to a peak of 36.6%. High nighttime Esf was associated with underestimates of nighttime Ecv. A second study, conducted in west Texas, beside the Pecos River, investigated the relationships between nighttime Js and stem tissue rehydration, on the one hand, and nighttime E, on the other hand. Leaf gas exchange measurements and stomatal impressions suggested that nighttime Js was primarily attributed to concurrent transpiration, although there were small overnight changes in stem water content. Both vapor pressure deficit and soil water availability were positively related to nighttime Js, especially following rainfall events. Thus, both studies indicate that T. chinensis can transpire large amounts at night, a fact that must be considered when attempting to quantify E either by eddy covariance or sap flux methods. © 2008 Heron Publishing.

Riparian plants have been classified as 'drought avoiders' due to their access to an abundant subsurface water supply. Recent water-relations research that tracks water sources of riparian plants using the stable isotopes of water suggests that many plants of the riparian zone use ground water rather than stream water, and not all riparian plants are obligate phreatophytes (dependent on ground water as a moisture source) but may occasionally be dependent on unsaturated soil moisture sources. A more thorough understanding of riparian plant-water relations must include water-source dynamics and how those dynamics vary over both space and time. Many rivers in the desert Southwest have been invaded by the exotic shrub Tamarix ramosissima (saltcedar). Our studies of Tamarix invasion into habitats formerly dominated by native riparian forests of primarily Populus and Salix have shown that Tamarix successfully invades these habitats because of its (1) greater tolerance to water stress and salinity, (2) status as a facultative, rather than obligate, phreatophyte and, therefore, its ability to recover from droughts and periods of ground-water drawdown, and (3) superior regrowth after fire. Analysis of water-loss rates indicate that Tamarix-dominated stands can have extremely high evapotranspiration rates when water tables are high but not necessarily when water tables are lower. Tamarix has leaf-level transpiration rates that are comparable to native species, whereas sap-flow rates per unit sapwood area are higher than in natives, suggesting that Tamarix maintains higher leaf area than can natives, probably due to its greater water stress tolerance. Tamarix desiccates and salinizes floodplains, due to its salt exudation and high transpiration rates, and may also accelerate fire cycles, thus predisposing these ecosystems to further loss of native taxa. Riparian species on regulated rivers can be exposed to seasonal water stress due to depression of floodplain water tables and elimination of annual floods. This can potentially result in a community shift toward more stress-tolerant taxa, such as Tamarix, due to the inability of other riparian species to germinate and establish in the desiccated floodplain environment. Management efforts aimed at maintaining native forests on regulated rivers and slowing the spread of Tamarix invasion must include at least partial reintroduction of historical flow regimes, which favor the recruitment of native riparian species and reverse long-term desiccation of desert floodplain environments.