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Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

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.

Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, 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-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst 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., European Union (EU), United States Department of Energy (DOE)

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Drylands account for approximately 40% of the global land surface and play a dominant role in the trend and variability of terrestrial carbon uptake and storage. Gross ecosystem photosynthesis – termed gross primary productivity (GPP) – is a critical driver of terrestrial carbon uptake and remains challenging to be observed directly. Currently, vegetation indices that largely capture changes in greenness are the most commonly used datasets in satellite-based GPP modeling. However, there remains significant uncertainty in the spatiotemporal relationship between greenness indices and GPP, especially for relatively heterogeneous dryland ecosystems. In this paper, we compared vegetation greenness indices from PhenoCam and satellite (Landsat and MODIS) observations against GPP estimates from the eddy covariance technique, across three representative ecosystem types of the southwestern United States. We systematically evaluated the changes in the relationship between vegetation greenness indices and GPP: i) across spatial scales of canopy-level, 30-meter, and 500-meter resolution; and ii) across temporal scale of daily, 8-day, 16-day, and monthly resolution. We found that greenness-GPP relationships were independent of spatial scales as long as land cover type and composition remained relatively constant. We also found that the greenness-GPP relationships became stronger as the time interval increased, with the strongest relationships observed at the monthly resolution. We posit that the greenness-GPP relationship breaks down at short timescales because greenness changes more slowly than plant physiological function, which responds rapidly to changes in key biophysical drivers. These findings provide insights into the potential for and limitations of modeling GPP using remotely sensed greenness indices across dryland ecosystem types.

Relatively small fluctuations in the surface energy balance and evapotranspiration in semiarid and arid regions can be indicative of significant changes to ecosystem health. Therefore, it is imperative to have approaches for monitoring surface fluxes in these regions. The remote sensing-based two-source energy balance (TSEB) model is a suitable method for flux estimation over sparsely vegetated semiarid and arid landscapes since it explicitly considers surface energy flux contributions from soil and vegetation. However, previous studies indicate that TSEB generally underestimates sensible heat flux (H) and hence overestimates latent heat flux (LE) or evapotranspiration for these regions unless soil resistance coefficients are modified based on additional ground information. In this study, TSEB is applied over semiarid and arid regions on three continents using the original soil resistance formulation with modified coefficients and a recently developed physically based soil resistance formulation. Model sensitivity analysis demonstrates the high sensitivity of TSEB with original soil resistance formulation to soil resistance coefficients, while TSEB with the new soil resistance formulation has relatively low sensitivity to uncertainties in all coefficients. The performance of TSEB using different soil resistance formulations is evaluated by comparing modeled H against eddy covariance measurements in six semiarid and arid study sites and ranking the error statistics. Our results indicate that incorporating the new soil resistance formulation into TSEB would enhance its utility in flux estimation over heterogeneous landscapes by obviating its reliance on semiempirical coefficients and thus provide more robust fluxes over sparsely vegetated regions without model calibration and/or parameter tuning., Spanish Ministry of Science and Innovation. Grant Number: CGL2016‐78075‐P DINCOS. Grant Number: CGL2016‐78075‐P Swiss National Science Foundation. Grant Number: P2EZP2‐165244 Strategic Priority Research Program of Chinese Academy of Sciences. Grant Number: XDA19040504

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (R S), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package., Here we describe the lightweight, open source COSORE (COntinuous SOil REspiration) database and software. COSORE focuses on automated, continuous and long‐term greenhouse gas flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation.

At the seasonal timescale, daily photochemical reflectance index (PRI) measurements track changes in photoprotective pigment pools as plants respond to seasonally variable environmental conditions. As such, remotely‐sensed PRI products present opportunities to study seasonal processes in evergreen conifer forests, where complex vegetation dynamics are difficult to capture due to small annual changes in chlorophyll content or leaf structure. Because PRI is tied explicitly to short and long term changes in photoprotective pigments that are responsible for regulating stress, we hypothesize that PRI by extension could serve as a proxy for stomatal response to seasonally changing hydroclimate, assuming plant functional responses to stress covary in space and time. To test this, we characterized PRI in a semi‐arid, montane mixed conifer forest in the Madrean sky islands of Arizona, USA during the monsoon growing season subject to precipitation pulse dynamics. To determine the sensitivity of PRI to ecohydrologic variability and associated changes in gross primary productivity (GPP), canopy spectral measurements were coupled with eddy covariance CO₂ flux and sap flow measurements. Seasonally, there was a significant relationship between PRI and sap flow velocity (R²=0.56), and multiple linear regression analysis demonstrated a PRI response to dynamic water and energy limitations in this system. We conclude that PRI has potential to serve as a proxy for forest functional response to seasonal ecohydrologic forcing. The coordination between photoprotective pigments and seasonal stomatal regulation demonstrated here could aid characterization of vegetation response to future changes in hydroclimate at increasing spatial scales.

High-elevation montane forests are disproportionately important to carbon sequestration in semiarid climates where low elevations are dry and characterized by low carbon density ecosystems. However, these ecosystems are increasingly threatened by climate change with seasonal implications for photosynthesis and forest growth. As a result, we leveraged eddy covariance data from six evergreen conifer forest sites in the semiarid western United States to extrapolate the status of carbon sequestration within a framework of projected warming and drying. At colder locations, the seasonal evolution of gross primary productivity (GPP) was characterized by a single broad maximum during the summer that corresponded to snow melt-derived moisture and a transition from winter dormancy to spring activity. Conversely, winter dormancy was transient at warmer locations, and GPP was responsive to both winter and summer precipitation such that two distinct GPP maxima were separated by a period of foresummer drought. This resulted in a predictable sequence of primary limiting factors to GPP beginning with air temperature in winter and proceeding to moisture and leaf area during the summer. Due to counteracting winter (positive) and summer (negative) GPP responses to warming, leaf area index and moisture availability were the best predictors of annual GPP differences across sites. Overall, mean annual GPP was greatest at the warmest site due to persistent vegetation photosynthetic activity throughout the winter. These results indicate that the trajectory of this region's carbon sequestration will be sensitive to reduced or delayed summer precipitation, especially if coupled to snow drought and earlier soil moisture recession, but summer precipitation changes remain highly uncertain. Given the demonstrated potential for seasonally offsetting responses to warming, we project that decadal semiarid montane forest carbon sequestration will remain relatively stable in the absence of severe disturbance.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate. We acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL.

In nearly all large-scale terrestrial ecosystem models, soil respiration is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable across sites and there is often a pronounced hysteresis in the soil respiration-temperature relationship over the course of the growing season. This phenomenon indicates the importance of biophysical factors beyond just temperature in controlling soil respiration. To identify the potential mechanisms of the seasonal soil respiration-temperature hysteresis, we developed a set of numerical models to demonstrate how photosynthesis, soil moisture, and soil temperature, alone and in combination, affect the hysteresis relationship. Then, we used a variant of the model informed by observations of soil respiration, soil temperature, photosynthesis, and soil moisture from multiple mesic and semi-arid ecosystems to quantify the frequency of hysteresis and identify its potential controls. We show that the hysteresis can result from the seasonal cycle of photosynthesis (which supplies carbon to rhizosphere respiration), and soil moisture (which limits heterotrophic respiration when too low or too high). Using field observations of soil respiration, we found evidence of seasonal hysteresis in 9 out of 15 site-years across 8 diverse biomes. Specifically, clockwise hysteresis occurred when photosynthesis preceded seasonal soil temperature and counterclockwise hysteresis occurred when photosynthesis lagged soil temperature. We found that across all sites, much of the respiration-temperature lag was explained by the decoupling of photosynthesis and temperature, highlighting the importance of recently assimilated carbon to soil respiration. An analysis of observations from 129 FLUXNET sites revealed that time lags between gross primary productivity (a proxy for canopy photosynthesis) and soil temperature were common phenomena, which would tend to drive counterclockwise hysteresis at low-latitude sites and clockwise hysteresis at high-latitude sites. Collectively, our results show that incorporating photosynthesis and soil moisture in the standard exponential soil respiration-temperature model (i.e., Q10 model) improves the explanatory power of models at local scales.

A major challenge in critical zone science is to understand and predict the interaction between above-ground and below-ground ecohydrologic processes. One process that facilitates this connection is hydraulic redistribution, a phenomenon by which roots serve as preferential pathways for water movement from wet to dry soil layers. We use a multilayer canopy model in conjunction with experimental data to quantify the influence of hydraulic redistribution on ecohydrologic processes in order to characterize the competitive and facilitative interaction between mesquite trees and bunchgrasses in a semiarid savanna. Both measured and simulated results show that hydraulic descent dominates during the wet monsoon season, whereas hydraulic lift occurs between precipitation events. For 2015 year-long simulation, we find about 17% of precipitation is absorbed as soil moisture, with the rest of the precipitation returning to the atmosphere as evapotranspiration. In the wet season, 13% of precipitation is transferred to deep soil (>1.5 m) through roots, and in the dry season, 9% of this redistributed water is then transported back to shallow soil depths (

Widely distributed in arid and semiarid regions, phreatophytic roots extend into the saturated zone and extract water directly from groundwater. In this paper, we implemented a vegetation optimality model of root dynamics (VOM-ROOT) in the Noah land surface model with multi parameterization options (Noah-MP LSM) to model the extraction of groundwater through phreatophytic roots at a riparian site with a hyperarid climate (with precipitation of 35 mm/yr) in northwestern China. VOM-ROOT numerically describes the natural optimization of the root profile in response to changes in subsurface water conditions. The coupled Noah-MP/VOM-ROOT model substantially improves the simulation of surface energy and water fluxes, particularly during the growing season, compared to the prescribed static root profile in the default Noah-MP. In the coupled model, more roots are required to grow into the saturated zone to meet transpiration demand when the groundwater level declines over the growing season. The modeling results indicate that at the study site, the modeled annual transpiration is 472 mm, accounting for 92.3% of the total evapo- transpiration. Direct root water uptake from the capillary fringe and groundwater, which is supplied by lateral groundwater flow, accounts for approximately 84% of the total transpiration. This study demonstrates the importance of implementing a dynamic root scheme in a land surface model for adequately simulating phreatophytic root water uptake and the associated latent heat flux.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such model-based analyses are poorly constrained by measured CO2 exchange in open shrublands, which is the most common global land cover type, covering ∼14% of Earth’s surface. Here we evaluate how the amount and seasonal timing of water availability regulate CO2 exchange between shrublands and the atmosphere. We use eddy covariance data from six US sites across the three warm deserts of North America with observed ranges in annual precipitation of ∼100–400mm, annual temperatures of 13–18°C, and records of 2–8 years (33 site-years in total). The Chihuahuan, Sonoran and Mojave Deserts present gradients in both mean annual precipitation and its seasonal distribution between the wet-winter Mojave Desert and the wet-summer Chihuahuan Desert. We found that due to hydrologic losses during the wettest summers in the Sonoran and Chihuahuan Deserts, evapotranspiration (ET) was a better metric than precipitation of water available to drive dryland CO2 exchange. In contrast with recent synthesis studies across diverse dryland biomes, we found that NEP could not be directly predicted from ET due to wintertime decoupling of the relationship between ecosystem respiration (Reco) and gross ecosystem productivity (GEP). Ecosystem water use efficiency (WUE=GEP/ET) did not differ between winter and summer. Carbon use efficiency (CUE=NEP/GEP), however, was greater in winter because Reco returned a smaller fraction of carbon to the atmosphere (23% of GEP) than in summer (77%). Combining the water-carbon relations found here with historical precipitation since 1980, we estimate that lower average winter precipitation during the 21st century reduced the net carbon sink of the three deserts by an average of 6.8TgC yr1. Our results highlight that winter precipitation is critical to the annual carbon balance of these warm desert shrublands.

DOE's Office of Science; NASA [NNH16ZDA001N]; USDA [58-0111-17-013]; DOE's Regional and Global Climate Modeling Program [DE-SC0016011]

Bidirectional Reflectance Distribution Function (BRDF) model parameters, Albedo quantities, and Nadir BRDF Adjusted Reflectance (NBAR) products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS), on the Suomi-NPP (National Polar-orbiting Partnership) satellite are evaluated with spatially representative in situ tower albedometer measurements and through comparison with the MODerate Resolution Imaging Spectroradiometer (MODIS) long term record. White Sky Albedo (WSA), Black Sky Albedo (BSA), NBAR, and Quality Assurance (QA) results show that the VIIRS algorithm is performing well at the global scale and is able to provide global data products comparable with the heritage MODIS (with an absolute bias of 0.0069 for shortwave broadband WSA) despite the spectral, angular, and effective spatial resolution differences between the two sensors. Both VIIRS and MODIS albedo are shown to agree well with in situ albedo measurements at a number of spatially representative sites. This evaluation provides confidence that the high quality, daily VIIRS BRDF model parameters, Albedo, and NBAR products will be able to provide the long term continuity required by the modeling and monitoring communities.

The National Aeronautics and Space Administration’s Soil Moisture Active Passive (SMAP) mission Level 4 Carbon (L4C) product provides model estimates of the Net Ecosystem CO2 exchange (NEE) incorporating SMAP soil moisture information. The L4C product includes NEE, computed as total ecosystem respiration less gross photosynthesis, at a daily time step posted to a 9-km global grid by plant functional type. Component carbon fluxes, surface soil organic carbon stocks, underlying environmental constraints, and detailed uncertainty metrics are also included. The L4C model is driven by the SMAP Level 4 Soil Moisture data assimilation product, with additional inputs from the Goddard Earth Observing System, Version 5 weather analysis, and Moderate Resolution Imaging Spectroradiometer satellite vegetation data. The L4C data record extends from March 31, 2015 to present with ongoing production and 8–12 day latency. Comparisons against concurrent global CO2 eddy flux tower measurements, satellite solar-induced canopy florescence, and other independent observation benchmarks show favorable L4C performance and accuracy, capturing the dynamic biosphere response to recent weather anomalies. Model experiments and L4C spatiotemporal variability were analyzed to understand the independent value of soil moisture and SMAP observations relative to other sources of input information. This analysis highlights the potential for microwave observations to inform models where soil moisture strongly controls land CO2 flux variability; however, skill improvement relative to flux towers is not yet discernable within the relatively short validation period. These results indicate that SMAP provides a unique and promising capability for monitoring the linked global terrestrial water and carbon cycles.

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

The separate components of evapotranspiration (ET) elucidate the pathways and time scales over which water is returned to the atmosphere, but ecosystem-scale measurements of transpiration (T) and evaporation (E) remain elusive. We propose a novel determination of E and T using multiyear eddy covariance estimates of ET and gross ecosystem photosynthesis (GEP). The method is applicable at water-limited sites over time periods during which a linear regression between GEP (abscissa) and ET (ordinate) yields a positive ET axis intercept, an estimate of E. At four summer-rainfall semiarid sites, T/ET increases to a peak coincident with maximum GEP and remains elevated as the growing season progresses, consistent with previous, direct measurements. The seasonal course of T/ET is related to increasing leaf area index and declining frequency of rainy days—an index of the wet surface conditions that promote E—suggesting both surface and climatic controls on ET partitioning.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such analyses are poorly constrained by measured CO2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm-2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (Reco ) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and Reco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO2 exchange may be up to 3-5 times larger than current estimates.

Recent research highlights the important role of (semi-)arid ecosystems in the global carbon (C) cycle. However, detailed process based investigations are still necessary in order to fully understand how drylands behave and to determine the main factors currently affecting their C balance with the aim of predicting how climate change will affect their structure and functions. Here, we explore the potential biological and non-biological processes that may compose net CO 2 exchange in a semiarid grassland in southeast Spain by means of eddy covariance measurements registered over six hydrological years (2009–2015). Results point out the great importance of subterranean ventilation, an advective transport process causing net CO 2 release, especially during drought periods and under high-turbulence conditions. Accordingly, extreme CO 2 release, far exceeding that found in the literature, was measured over the whole study period (2009–2015) averaging 230 g C m −2 year −1 ; this occurred mostly during the dry season and was very unlikely to correspond to concurrent biological activity and variations of in situ organic C pools. Underground CO 2 concentrations corroborate this finding. In this regard, the potential origins of the released CO 2 could be geological degassing and/or subterranean translocation of CO 2 in both gaseous and aqueous phases. However, future research is needed in order to understand how CO 2 transport and production processes interact and modulate drylands’ terrestrial C balance. Overall, the present study exposes how subterranean ventilation and hydrogeochemistry can complicate the interpretation of the terrestrial C cycle.

NSF [1417101, 1331408]; Marie Curie International Outgoing Fellowship within the Seventh European Community, DIESEL project [625988]

A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where numerical weather prediction (NWP) model background land surface temperature (LST) biases are greater than 2 K in magnitude. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations; a range of UM configurations were assessed with different model resolutions, land surface cover datasets and bare soil parameterisations. UM LST biases were evaluated at global resolution and in a limited area model (LAM) at a 2.2 km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in south-eastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (-13.6±2.8 K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1 with the cold LST biases reduced to -1.4±2.7 K and -3.6±3.0 K for Terra and Aqua overpasses, respectively. The higher-resolution LAM showed added value over the global configurations. The spatial distribution of the LST biases relative to MODIS and the modelled bare soil cover fraction were found to be moderately correlated (0.61±0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction, although with a less significant correlation (0.36±0.09), and indicated that the sparse vegetation canopies in south-eastern Arizona are not well represented in UM ancillary datasets. The x component of the orographic slope was positively correlated with the LST bias (0.41±0.05 for MODIS Aqua) and identified that regions of cold model LST bias are found on easterly slopes, and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. Our ability to partition evapotranspiration (ET) into E and T is limited at the ecosystem scale, which renders the validation of satellite data and land surface models incomplete. Here, we review current progress in partitioning E and T, and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques provide additional opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. Many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency (EWUE) exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but the conditions under which this assumption holds require further analysis. Another critical assumption for many ET partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T frequently exceeds 95 % of ET from some ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon-water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water flux and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

Knowing how evapotranspiration (ET) is mediated by abiotic and biotic pathways is essential to understanding how water affects ecosystem productivity. Recent studies have investigated the average transpiration fraction (T/ET) across sites and biomes, but the temporal variability of the partitioning and its controls are less understood. Here, we examine how water availability may regulate the seasonal to interannual variability of ET partitioning. To do this, we leveraged four partitioning techniques and long-term (14 years) eddy-flux records from a semiarid grassland and riparian woodland site in southeastern Arizona USA that share the same climate but differ in water table depth. T/ET was sensitive to changes in water availability over space and time as evidenced by consistently lower and more variable T/ET at the grassland, where the vegetation does not access groundwater. Seasonally, a pronounced dry foresummer T/ET depression at the rainfall-dependent grassland resulted in a bimodal T/ET distribution. In contrast, T/ET was unimodally distributed at the groundwater-dependent woodland, where high T/ET levels were maintained throughout both the dry and wet summer periods. Annual transpiration at both sites closely tracked water availability as quantified by ET, whereas abiotic evaporation was nearly constant. All ET partitioning methods yielded similar patterns of seasonal and interannual T/ET, although they differed by approximately 5 to 10% in magnitude. At both sites, transpiration was most closely correlated to plant metrics (photosynthesis, leaf area index) and ET, whereas evaporation was most correlated to surface moisture variables (soil moisture, precipitation). However, substantial differences between monthly and annual correlations demonstrate variable controls on monthly partitioning throughout the year. These results provide novel insights into the effects of water availability on the seasonal and interannual variability of ET partitioning and illuminate mechanisms regulating terrestrial ecosystem carbon and water exchange.

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF, both freely available online, could well capture the spatial extent and dynamics of the impacts of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R² = 0.44, p < 0.001) and GOSIF (R² = 0.76, p < 0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change.

US Department of Energy; National Science Foundation (NSF) [DEB 1552747]; NSF [DEB 1552976, EF 1241881, EAR 125501, EAR 155489]; NOAA/GFDL-Princeton University Cooperative Institute for Climate Science

The interacting effects of temperature and precipitation changes on grasslands remain hard to quantify. Research now indicates widespread and consistent increases in North American grassland productivity under climate change despite greater aridity.

Biological control of Tamarix spp. (tamarisk) with Diorhabda spp. (tamarisk beetle) was initiated in several states in the Western United States in 2001. We analysed 12 years of evapotranspiration (ET), net ecosystem production (NEP), and beetle abundance data from a tamarisk‐invaded site in Western Nevada along the Truckee River. Diorhabda carinulata (northern tamarisk beetle) appeared at the site in 2007. Large beetle outbreaks and associated defoliation of the tamarisk occurred in 2008 and 2009, then the beetle population was highly variable from year to year. Since 2016, the beetle population declined. Growing season ET noticeably declined from direct beetle herbivory in 2008, 2009, and 2010, but the decline in ET was seasonally transient as trees regrew leaves. In 2012 and 2013, total growing season ET was low, likely due to the combined effects of drought and beetle herbivory pressure. Total seasonal ET losses and NEP were primarily driven by annual precipitation with higher values in wetter years and reduced values when precipitation fell below 100 mm. In the last 2 years of the study, 2017–2018, there were few to no beetles observed at the site, and we measured increased tamarisk leaf area index, ET, and NEP. Since 2010 at the study site, no further releases of the beetles have occurred due to wildlife concerns, and subsequent declines in beetle populations where such that the “outbreak” conditions apparently required to impair tamarisk physiological function and significantly reduce ET have not occurred. ET and photosynthesis were highly correlated (r² ≥ .91) to the Landsat‐satellite normalized difference vegetation index (NDVI). Using a relationship between growing season ET and NDVI, we estimated ET for five additional tamarisk sites along several southwestern U.S. rivers. In the 2005 to 2018 analysis period, NDVI‐estimated ET declined at all sites after beetle arrival with three sites showing a recovery in pre‐beetle ET rates in subsequent years. At the other three sites, ET rates have not recovered to pre‐beetle levels.

“Sky islands” are characteristic of sequential mountain-valley terrain where mountains form an island archipelago rising from surrounding valleys of desert “sea”. At high elevations in the Madrean sky islands of the southwestern United States (USA) and Mexico, mixed evergreen conifer forests occur near the latitudinal extent of their distribution. This setting provides a unique opportunity to explore the ecosystem response to warmer and drier conditions that are forecasted to become more common throughout the species range. Accordingly, this work used the eddy covariance method to quantify carbon and water cycling dynamics from a Madrean sky island forest ecosystem for nine years between 2009 and 2018. The forest functioned as net sink of carbon dioxide throughout the year, which resulted in more carbon sequestration than other monitored montane forests in the continental western USA. Sustained forest activity was made possible by the combination of mild winter temperatures and a bimodal precipitation regime that delivered moisture during both summer and winter. Seasonally, gross primary production (GPP) was temperature limited in winter and could become moisture limited during the dry early summer period depending on antecedent snowmelt moisture. Ecosystem respiration was more sensitive than GPP to moisture availability throughout the rest of the non-winter period. Forecasted warming could thus stimulate forest carbon gains during the winter and either increase or decrease respiratory carbon loss during summer as a function of moisture. Overall, a metric of snow aridity that included snow depth and potential evapotranspiration was the best predictor of the warm season carbon balance (R2 = 0.86). The seasonally dissimilar impacts of warming and drying identified by this work inform current understanding of how climate change and/or variability may affect forest water and carbon cycling dynamics throughout the montane forest biome.

The precipitation legacy effect, defined as the impact of historical precipitation (PPT) on extant ecosystem dynamics, has been recognized as an important driver in shaping the temporal variability of dryland aboveground primary production (ANPP) and soil respiration. How the PPT legacy influences whole ecosystem-level carbon (C) fluxes has rarely been quantitatively assessed, particularly at longer temporal scales. We parameterized a process-based ecosystem model to a semiarid savanna ecosystem in southwestern US, calibrated and evaluated the model performance based on 7 years of eddy covariance measurements, and conducted two sets of simulation experiments to assess interdecadal and interannual scale PPT legacy effects over a 30 year simulation period. The results showed that decreasing the previous period/year PPT (dry legacy) always imposed positive impacts on net ecosystem production (NEP) whereas increasing the previous period/year PPT (wet legacy) had negative impacts on NEP. The simulated dry legacy impacts were mostly positive on gross ecosystem production (GEP) and negative on ecosystem respiration (Re) but the wet legacy impacts were mostly negative on GEP and positive on Re. Although the direction and magnitude of GEP and Re responses to the simulated dry and wet legacies were influenced by both the previous and current PPT conditions, the NEP responses were predominantly determined by the previous PPT characteristics including rainfall amount, seasonality and event size distribution. Larger PPT difference between periods/years resulted in larger legacy impacts, with dry legacies fostering more C sequestration and wet legacies more C release. By analyzing the resource pool (C, N, and H2O) responses to the simulated dry and wet legacies, we found that the carryover of soil N between periods/years was mainly responsible for the GEP responses while the carryovers of plant biomass, litter and soil organic matter were mainly responsible for the Re responses. These simulation results suggest that previous PPT conditions can exert substantial legacy impacts on current ecosystem C balance, which should be taken into account while assessing the response of dryland ecosystem C dynamics to future PPT regime changes.

Drylands make up roughly 40% of the Earth's land surface, and billions of people depend on services provided by these critically important ecosystems. Despite their relatively sparse vegetation, dryland ecosystems are structurally and functionally diverse, and emerging evidence suggests that these ecosystems play a dominant role in the trend and variability of the terrestrial carbon sink. More, drylands are highly sensitive to climate and are likely to have large, non-linear responses to hydroclimatic change. Monitoring the spatiotemporal dynamics of dryland ecosystem structure (e.g., leaf area index) and function (e.g., primary production and evapotranspiration) is therefore a high research priority. Yet, dryland remote sensing is defined by unique challenges not typically encountered in mesic or humid regions. Major challenges include low vegetation signal-to-noise ratios, high soil background reflectance, presence of photosynthetic soils (i.e., biological soil crusts), high spatial heterogeneity from plot to regional scales, and irregular growing seasons due to unpredictable seasonal rainfall and frequent periods of drought. Additionally, there is a relative paucity of continuous, long-term measurements in drylands, which impedes robust calibration and evaluation of remotely-sensed dryland data products. Due to these issues, remote sensing techniques developed in other ecosystems or for global application often result in inaccurate, poorly constrained estimates of dryland ecosystem structural and functional dynamics. Here, we review past achievements and current progress in remote sensing of dryland ecosystems, including a detailed discussion of the major challenges associated with remote sensing of key dryland structural and functional dynamics. We then identify strategies aimed at leveraging new and emerging opportunities in remote sensing to overcome previous challenges and more accurately contextualize drylands within the broader Earth system. Specifically, we recommend: 1) Exploring novel combinations of sensors and techniques (e.g., solar-induced fluorescence, thermal, microwave, hyperspectral, and LiDAR) across a range of spatiotemporal scales to gain new insights into dryland structural and functional dynamics; 2) utilizing near-continuous observations from new-and-improved geostationary satellites to capture the rapid responses of dryland ecosystems to diurnal variation in water stress; 3) expanding ground observational networks to better represent the heterogeneity of dryland systems and enable robust calibration and evaluation; 4) developing algorithms that are specifically tuned to dryland ecosystems by utilizing expanded ground observational network data; and 5) coupling remote sensing observations with process-based models using data assimilation to improve mechanistic understanding of dryland ecosystem dynamics and to better constrain ecological forecasts and long-term projections.

The net ecosystem exchange (NEE) is the difference between ecosystem CO 2 assimilation and CO 2 losses to the atmosphere. Ecosystem respiration (R eco ), the efflux of CO 2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; R soil ) and aboveground plant respiration. Therefore, R soil is a fraction of R eco and theoretically has to be smaller than R eco at daily, seasonal, and annual scales. However, several studies estimating R eco with the eddy covariance technique and measuring R soil within the footprint of the tower have reported higher R soil than R eco at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to test if measurements of R eco are consistently higher than R soil . In general, both fluxes showed similar temporal patterns, but R eco was not consistently higher than R soil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling R soil that could result in an underestimation of R eco and/or an overestimation of R soil . These issues are discussed based on (a) nighttime measurements of NEE, (b) R soil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q 10 ). We highlight that there is still a need for better integration of R soil with eddy covariance measurements to address challenges related to the spatial and temporal variability of R eco and R soil .

© 2017 Elsevier B.V. AmeriFlux scientists were early adopters of a network-enabled approach to ecosystem science that continues to transform the study of land-atmosphere interactions. In the 20 years since its formation, AmeriFlux has grown to include more than 260 flux tower sites in the Americas that support continuous observation of ecosystem carbon, water, and energy fluxes. Many of these sites are co-located within a similar climate regime, and more than 50 have data records that exceed 10 years in length. In this prospective assessment of AmeriFlux's strengths in a new era of network-enabled ecosystem science, we discuss how the longevity and spatial distribution of AmeriFlux data make them exceptionally well suited for disentangling ecosystem response to slowly evolving changes in climate and land-cover, and to rare events like droughts and biological disturbances. More recently, flux towers have also been integrated into environmental observation networks that have broader scientific goals; in North America these include the National Ecological Observatory Network (NEON), Critical Zone Observatory network (CZO), and Long-Term Ecological Research network (LTER). AmeriFlux stands apart from these other networks in its reliance on voluntary participation of individual sites, which receive funding from diverse sources to pursue a wide, transdisciplinary array of research topics. This diffuse, grassroots approach fosters methodological and theoretical innovation, but also challenges network-level data synthesis and data sharing to the network. While AmeriFlux has had strong ties to other regional flux networks and FLUXNET, better integration with networks like NEON, CZO and LTER provides opportunities for new types of cooperation and synergies that could strengthen the scientific output of all these networks.

A long-standing ambition in ecosystem science has been to understand the relationship between ecosystem community composition, structure and function. Differential water use and hydraulic redistribution have been proposed as one mechanism that might allow for the coexistence of overstory woody plants and understory grasses. Here, we investigated how patterns of hydraulic redistribution influence overstory and understory ecophysiological function and how patterns vary across timescales of an individual precipitation event to an entire growing season. To this end, we linked measures of sap flux within lateral and tap roots, leaf-level photosynthesis, ecosystem-level carbon exchange and soil carbon dioxide efflux with local meteorology data. The hydraulic redistribution regime was characterized predominantly by hydraulic descent relative to hydraulic lift. We found only a competitive interaction between the overstory and understory, regardless of temporal time scale. Overstory trees used nearly all water lifted by the taproot to meet their own transpirational needs. Our work suggests that alleviating water stress is not the reason we find grasses growing in the understory of woody plants; rather, other stresses, such as excessive light and temperature, are being ameliorated. As such, both the two-layer model and stress gradient hypothesis need to be refined to account for this coexistence in drylands.

Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m2. MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available.

The exchange of carbon dioxide is a key measure of ecosystem metabolism and a critical intersection between the terrestrial biosphere and the Earth's climate. Despite the general agreement that the terrestrial ecosystems in North America provide a sizeable carbon sink, the size and distribution of the sink remain uncertain. We use a data-driven approach to upscale eddy covariance flux observations from towers to the continental scale by integrating flux observations, meteorology, stand age, aboveground biomass, and a proxy for canopy nitrogen concentrations from AmeriFlux and Fluxnet-Canada Research Network as well as a variety of satellite data streams from the MODIS sensors. We then use the resulting gridded flux estimates from March 2000 to December 2012 to assess the magnitude, distribution, and interannual variability of carbon fluxes for the U.S. and Canada. The mean annual gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of the U.S. over the period 2001–2012 were 6.84, 5.31, and 1.10 Pg C yr−1, respectively; the mean annual GPP, ER, and NEP of Canada over the same 12-year period were 3.91, 3.26, and 0.60 Pg C yr−1, respectively. The mean nationwide annual NEP of natural ecosystems over the period 2001–2012 was 0.53 Pg C yr−1 for the U.S. and 0.49 Pg C yr−1 for the conterminous U.S. Our estimate of the carbon sink for the conterminous U.S. was almost identical with the estimate of the First State of the Carbon Cycle Report (SOCCR). The carbon fluxes exhibited relatively large interannual variability over the study period. The main sources of the interannual variability in carbon fluxes included drought and disturbance. The annual GPP and NEP were strongly related to annual evapotranspiration (ET) for both the U.S. and Canada, showing that the carbon and water cycles were closely coupled. Our gridded flux estimates provided an independent, alternative perspective on ecosystem carbon exchange over North America.

Soil CO2 efflux (Fsoil) is a major component of the ecosystem carbon balance. Globally expansive semiarid ecosystems have been shown to influence the trend and interannual variability of the terrestrial carbon sink. Modeling Fsoil in water-limited ecosystems remains relatively difficult due to high spatial and temporal variability associated with dynamics in moisture availability and biological activity. Measurements of the processes underlying variability in Fsoil can help evaluate Fsoil models for water-limited ecosystems. Here we combine automated soil chamber and flux tower data with models to investigate how soil temperature (Ts), soil moisture (&theta, ), and gross ecosystem photosynthesis (GEP) control Fsoil in semiarid ecosystems with similar climates and different vegetation types. Across grassland, shrubland, and savanna sites, &theta, regulated the relationship between Fsoil and Ts, and GEP influenced Fsoil magnitude. Thus, the combination of Ts, &theta, and GEP controlled rates and patterns of Fsoil. In a root exclusion experiment at the grassland, we found that growing season autotrophic respiration accounted for 45% of Fsoil. Our modeling results indicate that a combination of Ts, &theta, and GEP terms is required to model spatial and temporal dynamics in Fsoil, particularly in deeper-rooted shrublands and savannas where coupling between GEP and shallow &theta, is weaker than in grasslands. Together, these results highlight that including &theta, and GEP in Fsoil models can help reduce uncertainty in semiarid ecosystem carbon dynamics.

The global terrestrial carbon sink offsets one-third of the world's fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting in substantial economic damage. It is crucial to understand the dynamics of such events because warmer temperatures and a higher prevalence of drought are projected in a changing climate. Here, we combine an extensive network of direct ecosystem flux measurements with satellite remote sensing and atmospheric inverse modeling to quantify the impact of the warmer spring and summer drought on biosphere-atmosphere carbon and water exchange in 2012. We consistently find that earlier vegetation activity increased spring carbon uptake and compensated for the reduced uptake during the summer drought, which mitigated the impact on net annual carbon uptake. The early phenological development in the Eastern Temperate Forests played a major role for the continental-scale carbon balance in 2012. The warm spring also depleted soilwater resources earlier, and thus exacerbated water limitations during summer. Our results show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake. However, the results also suggest that the positive carbon cycle effect of warm spring enhances water limitations and can increase summer heating through biosphere-atmosphere feedbacks.

In the southwest United States, the current prolonged warm drought is similar to the predicted future climate change scenarios for the region. This study aimed to determine patterns in vegetation response to the early 21st century drought across multiple biomes. We hypothesized that different biomes (forests, shrublands, and grasslands) would have different relative sensitivities to both climate drivers (precipitation and temperature) and legacy effects (previous‐year's productivity). We tested this hypothesis at eight Ameriflux sites in various Southwest biomes using NASA Moderate‐resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI) from 2001 to 2013. All sites experienced prolonged dry conditions during the study period. The impact of combined precipitation and temperature on Southwest ecosystems at both annual and sub‐annual timescales was tested using Standardized Precipitation Evapotranspiration Index (SPEI). All biomes studied had critical sub‐annual climate periods during which precipitation and temperature influenced production. In forests, annual peak greenness (EVImax) was best predicted by 9‐month SPEI calculated in July (i.e., January–July). In shrublands and grasslands, EVImax was best predicted by SPEI in July through September, with little effect of the previous year's EVImax. Daily gross ecosystem production (GEP) derived from flux tower data yielded further insights into the complex interplay between precipitation and temperature. In forests, GEP was driven by cool‐season precipitation and constrained by warm‐season maximum temperature. GEP in both shrublands and grasslands was driven by summer precipitation and constrained by high daily summer maximum temperatures. In grasslands, there was a negative relationship between temperature and GEP in July, but no relationship in August and September. Consideration of sub‐annual climate conditions and the inclusion of the effect of temperature on the water balance allowed us to generalize the functional responses of vegetation to predicted future climate conditions. We conclude that across biomes, drought conditions during critical sub‐annual climate periods could have a strong negative impact on vegetation production in the southwestern United States.

The severity and incidence of climatic extremes, including drought, have increased as a result of climate warming. Analyses of observational and reanalysis data suggest that the strength of the western North American carbon sink declined by 30–298 Tg carbon per year during the drought at the turn of the century. Fossil fuel emissions aside, temperate North America is a net sink of carbon dioxide at present1,2,3. Year-to-year variations in this carbon sink are linked to variations in hydroclimate that affect net ecosystem productivity3,4. The severity and incidence of climatic extremes, including drought, have increased as a result of climate warming5,6,7,8. Here, we examine the effect of the turn of the century drought in western North America on carbon uptake in the region, using reanalysis data, remote sensing observations and data from global monitoring networks. We show that the area-integrated strength of the western North American carbon sink declined by 30–298 Tg C yr−1 during the 2000–2004 drought. We further document a pronounced drying of the terrestrial biosphere during this period, together with a reduction in river discharge and a loss of cropland productivity. We compare our findings with previous palaeoclimate reconstructions7 and show that the last drought of this magnitude occurred more than 800 years ago. Based on projected changes in precipitation and drought severity, we estimate that the present mid-latitude carbon sink of 177–623 Tg C yr−1 in western North America could disappear by the end of the century.

Theory relating changes in area-average evaporation with changes in the evaporation from pans or open water is developed. Such changes can arise by Type (a) processes related to large-scale changes in atmospheric concentrations and circulation that modify surface evaporation rates in the same direction, and Type (b) processes related to coupling between the surface and atmospheric boundary layer (ABL) at the landscape scale that usually modify area-average evaporation and pan evaporation in different directions. The interrelationship between evaporation rates in response to Type (a) changes is derived. They have the same sign and broadly similar magnitude but the change in area-average evaporation is modified by surface resistance. As an alternative to assuming the complementary evaporation hypothesis, the results of previous modelling studies that investigated surface-atmosphere coupling are parametrized and used to develop a theoretical description of Type (b) coupling via vapour pressure deficit (VPD) in the ABL. The interrelationship between appropriately normalized pan and area-average evaporation rates is shown to vary with temperature and wind speed but, on average, the Type (b) changes are approximately equal and opposite. Long-term Australian pan evaporation data are analyzed to demonstrate the simultaneous presence of Type (a) and (b) processes, and observations from three field sites in southwestern USA show support for the theory describing Type (b) coupling via VPD. Copyright c � 2009 Royal Meteorological Society

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ~29°N to ~64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.

This current study explores satellite-based soil moisture downscaling approaches and applies them to common passive microwave retrievals. Three variations of a second-order polynomial regression were tested based on the surface temperature/greenness index concept and merged information from higher spatial resolution moderate-resolution imaging spectroradiometer with soil moisture active passive (SMAP) and soil moisture and ocean salinity (SMOS) products to obtain soil moisture estimates at higher resolutions (1 km). Downscaled products were evaluated at the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Results show slight differences in performance among the three downscaling methods and little improvement between original low-resolution products and downscaled (1 km) products. Spatial analysis over WGEW demonstrates downscaled products were able to decipher small-scale heterogeneities in surface soil moisture, though spatial variability remains low compared to observations with a difference of only 0.06 m3/m3 in spatial standard deviation between observations and the mean between downscaling techniques. Results demonstrate the ability of both SMOS and SMAP to represent soil moisture accurately on the point scale without applying downscaling techniques in the region under study.

Large areas of the Brazilian savanna (cerrado) have been converted into farmland in recent years; however, little attention has been paid to the consequences of this land use and land cover change on groundwater recharge. Here, we assessed groundwater recharge in different physiognomies of the cerrado located in an outcrop area of the Guarani Aquifer System. Water table fluctuations were measured from October 2011 through August 2013, by 58 monitoring wells distributed on four physiognomies of the undisturbed cerrado. We used multiple monitoring wells located in “campo limpo” (cerrado grassland), “campo sujo” (shrub cerrado), “campo cerrado” (open wooded cerrado), and “cerrado sensu stricto” (wooded cerrado), cover types. Recharge rates were computed for each well using the water table fluctuation method. The measured precipitation for hydrological years 2011–2012 and 2012–2013 were 1247 and 1194 mm, respectively. We found values of average annual recharge of 363 ± 87 mm, 354 ± 85 mm, 324 ± 78 mm, and 315 ± 76 mm for “campo limpo,” “campo sujo,” “campo cerrado,” and “cerrado sensu stricto,” respectively. Our results suggest that recharge tends to decrease with the increase in the density of vegetation (grassland to woodland). These results indicate that water table depth may have an influence on the cerrado physiognomies or vice versa. Furthermore, replacement of undisturbed dense cerrado with croplands will likely alter recharge dynamics. Therefore, sound management of land use and land cover is needed to ensure future groundwater quantity and quality.

Comparing biosphere–atmosphere carbon exchange across monsoon (warm-season rainfall) and Mediterranean (cool-season rainfall) regimes can yield information about the interaction between energy and water limitation. Using data collected from eddy covariance towers over grass and shrub ecosystems in Arizona, USA and Almeria, Spain, we used net ecosystem carbon dioxide exchange (NEE), gross ecosystem production (GEP), and other meteorological variables to examine the effects of the different precipitation seasonality. Considerable crossover behavior occurred between the two rainfall regimes. As expected in these usually water-limited ecosystems, precipitation magnitude and timing were the dominant drivers of carbon exchange, but temperature and/or light also played an important role in regulating GEP and NEE at all sites. If significant rainfall occurred in the winter at the Arizona sites, their behavior was characteristically Mediterranean whereby the carbon flux responses were delayed till springtime. Likewise, the Spanish Mediterranean sites showed immediate pulse-like responses to rainfall events in non-winter periods. The observed site differences were likely due to differences in vegetation, soils, and climatology. Together, these results support a more unified conceptual model for which processes governing carbon cycling in semiarid ecosystems need not differ between warm-season and cool-season rainfall regimes., This paper is the result of a fellowship funded by the OECD Co-operative Research Programme: Biological Resource Management for Sustainable Agricultural Systems to R.L. Scott. This paper has been supported in part by the Andalusian regional government project GEOCARBO and GLOCHARID (P08-RNM-3721), European Union Funds (ERDF and ESF), the Spanish flux-tower network CARBORED-ES (Science Ministry project CGL2010-22193-C04-02), and the European Commission collaborative project GHG Europe (FP7/2007-2013; grant agreement 244122).

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenology and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000–2005 at a 0.05° × 0.05° spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 Pg C yr−1 and net primary production (NPP) ranges from 3.81 to 4.38 Pg C yr−1 and net ecosystem production (NEP) varies within 0.08–0.73 Pg C yr−1 over the period 2000–2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 Pg C yr−1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.

As a result of climate change, rainfall regimes became more extreme over the course of the 20th century, characterised by fewer and larger rainfall events. Such changes are expected to continue throughout the current century. The effect of changes in the 5 temporal distribution of rainfall on ecosystem carbon fluxes is poorly understood, with most available information coming from experimental studies of grassland ecosystems. Here, continuous measurements of ecosystem carbon fluxes and precipitation from the worldwide FLUXNET network of eddy-covariance sites are exploited to investigate the effects of differences in rainfall distribution on the carbon balance of seasonally water10 limited shrubland and forest sites. Once the strong dependence of ecosystem fluxes on total annual rainfall amount is accounted for, results show that sites with more extreme rainfall distributions have significantly lower gross productivity, slightly lower ecosystem respiration and consequently a smaller net ecosystem productivity., JRC.H.7-Climate Risk Management