How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

Proximal remote sensing: an essential tool for bridging the gap between high-resolution ecosystem monitoring and global ecology

A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or 'proximal' remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site-level eddy-covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high-spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar-induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information-rich, enabling us to address key ecological questions unanswerable from space-based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

PhotoGEA: An R Package for Closer Fitting of Photosynthetic Gas Exchange Data With Non-Gaussian Confidence Interval Estimation

Fitting mechanistic models, such as the Farquhar-von-Caemmerer-Berry model, to experimentally measured photosynthetic CO2 response curves (A-Ci curves) is a widely used technique for estimating the values of key leaf biochemical parameters and determining limitations to photosynthesis in vivo. Here, we present PhotoGEA, an R package with tools for C3 A-Ci, C3 Variable J and C4 A-Ci curve fitting. In contrast to existing software, these automated tools use derivative-free optimizers to ensure close fits and they calculate non-Gaussian confidence intervals to indicate which parameter values are most reliable. Results from PhotoGEA's C3 A-Ci curve fitting tool are compared against other available tools, where it is found to achieve the closest fits and most reasonable parameter estimates across a range of curves with different characteristics. PhotoGEA's C3 Variable J and C4 A-Ci fitting tools are also presented, demonstrating how they can provide insights into mesophyll conductance and the processes limiting C4 photosynthesis at high CO2 concentrations. PhotoGEA enables users to develop data analysis pipelines for efficiently reading, processing, fitting and analysing photosynthetic gas exchange measurements. It includes extensive documentation and example scripts to help new users become proficient as quickly as possible.

Asymmetric environmental responses on evapotranspiration in Tibetan Plateau grassland

Evapotranspiration (ET) from the Tibetan Plateau (TP) grasslands plays a critical role in regulating water storage in the Asian Water Tower. However, the patterns, drivers, and responses of ET to climate change remain largely understudied due to limited observational data. This study integrated eddy covariance and long-term remote sensing data to examine the spatial patterns of ET and its drivers across the TP, comparing these patterns with those in other grassland ecosystems of the Northern Hemisphere. In the eastern TP, ET was primarily influenced by vapor pressure deficit and net radiation, whereas in the western TP, the impact of these two factors on the ET was significantly reduced. The regional differences were attributed to the unique energy-limited conditions in the eastern TP, which were driven by the East Asian monsoon and large-scale atmospheric circulation. In contrast, ET in other grassland ecosystems of the Northern Hemisphere, such as the North American Prairie and the Mongolian Plateau, was mainly controlled by water availability (e.g., precipitation and soil water content), similar to the western TP region. Under future climate warming, ET in the eastern TP is expected to increase significantly compared to other grasslands, particularly in the SSP5-8.5 scenario. This study revealed the distinct mechanisms regulating ET in TP grasslands and emphasized the need for further research on how grassland ET responds to global environmental changes.

Evapotranspiration Partitioning of the Populus euphratica Forest Ecosystem in the Drylands of Northwestern China

The comprehension of seasonal patterns of evapotranspiration (ET), as well as the interactive response to environmental factors, holds paramount importance for illuminating the intricate interaction within the carbon-water cycle of desert riparian forest ecosystems. Nonetheless, the driving mechanism behind ET changes is complex, and different components show significant differences in response to the same factor. Moreover, water resources are scarce in the region, and sustainable water resources management in arid regions usually aims to maximize transpiration (T) and minimize evaporation (E); therefore, reasonable calculation of ET components is urgent to effectively assess water resources consumption and improve water use efficiency. This discussion assessed the suitability and reliability of different methods for partitioning ET within the desert oasis in Northwestern China, calculated water use efficiency (WUE), and explored the differences in the response patterns of ET, transpiration (T), and WUE to environmental elements of constructive Populus euphratica forests in this region during the growing season. Continuous measurements of meteorological, soil, and vegetation factors were collected from 2014 to 2021 to facilitate this investigation. This study demonstrated that the underlying water use efficiency (uWUE) method effectively partitions ET into vegetation T and soil evaporation (E). Seasonal variations in ET and T were predominantly driven by temperature (Ta), radiation (Rn), soil moisture, and leaf area index (LAI). In addition, the exchange of water and carbon across different scales was governed by distinct regulatory mechanisms, where canopy-level WUE (WUEc) primarily depended on climatic conditions, while ecosystem-level WUE (WUEe) was more strongly influenced by vegetation structural characteristics. This study provided valuable insights into the ET characteristics, influencing factors, and water-carbon consumption mechanisms of desert vegetation in arid regions, and the conclusions of the discussion may provide theoretical insights for policymakers and ecosystem managers interested in preserving the ecological balance of arid regions.

DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts

With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models. Despite recent progress in deep learning to ecosystem monitoring, there is a need for datasets specifically designed to analyse compound heatwave and drought extreme impact. Here, we introduce the DeepExtremeCubes database, tailored to map around these extremes, focusing on persistent natural vegetation. It comprises over 40,000 globally sampled small data cubes (i.e. minicubes), with a spatial coverage of 2.5 by 2.5 km. Each minicube includes (i) Sentinel-2 L2A images, (ii) ERA5-Land variables and generated extreme event cube covering 2016 to 2022, and (iii) ancillary land cover and topography maps. The paper aims to (1) streamline data accessibility, structuring, pre-processing, and enhance scientific reproducibility, and (2) facilitate biosphere dynamics forecasting in response to compound extremes.

Vegetation Types Shift Physiological and Phenological Controls on Carbon Sink Strength in a Coastal Zone

The carbon sink function performed by the different vegetation types along the environmental gradient in coastal zones plays a vital role in mitigating climate change. However, inadequate understanding of its spatiotemporal variations across different vegetation types and associated regulatory mechanisms hampers determining its potential shifts in a changing climate. Here, we present long-term (2011-2022) eddy covariance measurements of the net ecosystem exchange (NEE) of CO2 at three sites with different vegetation types (tidal wetland, nontidal wetland, and cropland) in a coastal zone to examine the role of vegetation type on annual carbon sink strength. We found that the three study sites are stable carbon sinks and are influenced by their distinct physiological and phenological factors. The annual NEE of the tidal wetland, nontidal wetland, and cropland were determined predominantly by the seasonal peaks of net CO2 uptake, release, and duration of CO2 uptake period. Furthermore, the changes in annual NEE were sensitive to climatic variables, as spring mean air temperature reduced the carbon sink strength in the tidal wetland, maximum daily precipitation in summer reduced it in the nontidal wetland, and summer mean global radiation elicited the same effect in the cropland. Finally, a worldwide database of the three vegetation types was compiled, using which we further validated the global consistency of the biological controls. Overall, these results emphasize the importance of considering the underlying mechanisms by which vegetation types influence NEE for the accurate forecasting of carbon sink dynamics across different coastal vegetation types under climate change.

Improving global gross primary productivity estimation using two-leaf light use efficiency model by considering various environmental factors via machine learning

Distinguishing gross primary productivity (GPP) into sunlit (GPPsu) and shaded (GPPsh) components is critical for understanding the carbon exchange between the atmosphere and terrestrial ecosystems under climate change. Recently, the two-leaf light use efficiency (TL-LUE) model has proven effective for simulating global GPPsu and GPPsh. However, no known physical method has focused on integrating the overall constraint of intricate environmental factors on photosynthetic capability, and seasonal differences in the foliage clumping index (CI), which most likely influences GPP estimation in LUE models. Here, we propose the TL-CRF model, which uses the random forest technique to integrate various environmental variables, particularly for terrestrial water storage (TWS), into the TL-LUE model. Moreover, we consider seasonal differences in CI at a global scale. Based on 267 global eddy covariance flux sites, we explored the functional response of vegetation photosynthesis to key environmental factors, and trained and evaluated the TL-CRF model. The TL-CRF model was then used to simulate global eight-day GPP, GPPsu, and GPPsh from 2002 to 2020. The results show that the relative prediction error of environmental stress factors on the maximum LUE is reduced by approximately 52 % when these factors are integrated via the RF model. Thus the accuracy of global GPP estimation (R2 = 0.87, RMSE = 0.94 g C m-2 d-1, MAE = 0.61 g C m-2 d-1) in the TL-CRF model is greater than that (R2 = 0.76, RMSE = 2.18 g C m-2 d-1, MAE = 1.50 g C m-2 d-1) in the TL-LUE model, although this accuracy awaits further investigation among the released GPP products. TWS exerts the greatest control over ecosystem photosynthesis intensity, making it a suitable water indicator. Furthermore, the results confirm an optimal minimum air temperature for photosynthesis. Overall, these findings indicate a promising method for producing a new global GPP dataset, advancing our understanding of the dynamics and interactions between photosynthesis and environmental factors.

Long-term trend and interannual variation in evapotranspiration of a young temperate Douglas-fir stand over 2002-2022 reveals the impacts of climate change

The shortage of decades-long continuous measurements of ecosystem processes limits our understanding of how changing climate impacts forest ecosystems. We used continuous eddy-covariance and hydrometeorological data over 2002-2022 from a young Douglas-fir stand on Vancouver Island, Canada to assess the long-term trend and interannual variability in evapotranspiration (ET) and transpiration (T). Collectively, annual T displayed a decreasing trend over the 21 years with a rate of 1% yr-1, which is attributed to the stomatal downregulation induced by rising atmospheric CO2 concentration. Similarly, annual ET also showed a decreasing trend since evaporation stayed relatively constant. Variability in detrended annual ET was mostly controlled by the average soil water storage during the growing season (May-October). Though the duration and intensity of the drought did not increase, the drought-induced decreases in T and ET showed an increasing trend. This pattern may reflect the changes in forest structure, related to the decline in the deciduous understory cover during the stand development. These results suggest that the water-saving effect of stomatal regulation and water-related factors mostly determined the trend and variability in ET, respectively. This may also imply an increase in the limitation of water availability on ET in young forests, associated with the structural and compositional changes related to forest growth.

Intercomparison of sensible and latent heat flux measurements from combined eddy covariance, energy balance, and Bowen ratio methods above a grassland prairie

We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; HEC > HEBBR, HRES, and HMBR). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LEEC < LEEBBR and LERES), while a larger bias was found from MBR (m ~ 8% from unity; LEEC > LEMBR). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R2 = 0.81), with smaller scatter between RES and MBR, and EC (R2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

The Ecosystem as Super-Organ/ism, Revisited: Scaling Hydraulics to Forests under Climate Change

Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth's ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity.

Winter harvesting reduces methane emissions and enhances blue carbon potential in coastal phragmites wetlands

Enhancing the ability of coastal blue carbon to accumulate and store carbon and reduce net greenhouse gas emissions is an essential component of a comprehensive approach for tackling climate change. The annual winter harvesting of Phragmites is common worldwide. However, the effects of harvesting on methane (CH4) emissions and its potential as an effective blue carbon management strategy have rarely been reported. In this study, the effects of winter Phragmites harvesting on the CH4 and carbon dioxide (CO2) fluxes and the underlying mechanisms in coastal Phragmites wetlands were investigated by comparing the eddy covariance flux measurements for three coastal wetlands with different harvesting and tidal flow conditions. The results show that harvesting can greatly reduce the CH4 emissions and the radiative forcing of CH4 and CO2 fluxes in coastal Phragmites wetlands, suggesting that winter Phragmites harvesting has great potential as a nature-based strategy to mitigate global warming. The monthly mean CH4 fluxes were predominantly driven by air temperature, gross primary productivity, and latent heat fluxes, which are related to vegetation phenology. Additionally, variations in the salinity and water levels exerted strong regulation effects on CH4 emissions, highlighting the important role of proper tidal flow restoration and resalinization in enhancing blue carbon sequestration potential. Compared with the natural, tidally unrestricted wetlands, the CH4 fluxes in the impounded wetland were less strongly correlated with hydrometeorological variables, implying the increased difficulties of predicting CH4 variations in impounded ecosystem. This study facilitates the improved understanding of carbon exchange in coastal Phragmites wetlands with harvesting or impoundment, and provides new insights into effective blue carbon management strategies beyond tidal wetland restoration for mitigating the effects of climate change.

Study on the relationship between net primary productivity and site quality in Japanese larch plantations in mountainous areas of eastern Liaoning

Plantation forests enhance carbon storage in terrestrial ecosystems in China. Larix kaempferi (Lamb.) Carrière (Lamb.) (Larix olgensis Henry) is the main species for afforestation in the eastern Liaoning Province. Therefore, it is important to understand the correlation between the site class and carbon sink potential of Larix kaempferi plantations in Liaoning Province for afforestation and carbon sink in this area. The model was fitted using three classical theoretical growth equations: the Richards model, the Korf model, and the Hossfeld model. This study used the forest resource inventory data for management in Liaoning Province in 2011 to build six dynamic height-age models for a Larix kaempferi plantation in Dandong City regardless of base-age. The optimal model derived by the generalized algebraic difference approach (GADA) method was compared with the model derived by the algebraic difference approach (ADA) method. The superiority of GADA was demonstrated by comparison. The Levenberg-Marquardt algorithm was used to fit the model. The statistical and biological characteristics were considered synthetically when comparing the models. The best model was screened out by statistical analysis and graphic analysis. The results show that the differential height-age model derived from Richards equation can well explain the growth process of Larix kaempferi in Dandong City, Liaoning Province under different conditions. The site index model based on Richards equation and derived by GADA was used to calculate the site class of a Larix kaempferi plantation in Dandong City. The net primary productivity (NPP) value from the past ten years was extracted from the MOD17A3HGF data set. Spearman correlation analysis and Kendall correlation analysis were used to show that there is a significant positive correlation between NPP value and site class of Larix kaempferi plantation in Dandong City. Among them, the highest growth occurred in 2016; NPP increased by about 3.914 gC/m2/year for every two increases in height-age grade; the lowest increase in NPP was in 2014; NPP increased by about 2.113 gC/m2/year for every two increases in height-age grade; and for every two increases in height-age grade in the recent ten years, the average NPP value increased by about 2.731 gC/m2/year.

Adaptation of stomatal conductance, photosynthesis and water-use efficiency at shoot and canopy scales in adjacent stands of Dacrycarpus dacrydioides and Podocarpus totara

We tested an approach to estimate daily canopy net photosynthesis, A, based on estimates of transpiration, E, using measurements of sap flow and water-use efficiency, ω, by measuring δ13C in CO2 respired from shoots in the canopies of two conifers (Podocarpaceae) native to New Zealand. The trees were planted in adjacent 20-year-old stands with the same soil and environmental conditions. Leaf area index was lower for Dacrycarpus dacrydioides D.Don in Lamb (1.34 m2 m-2) than for Podocarpus totara G.Benn. ex D.Don var. totara (2.01 m2 m-2), but mean (± standard error) stem diameters were the same at 152 ± 21 mm for D. dacrydioides and 154 ± 25 mm for P. totara. Over a 28-day period, daily A (per unit ground area) ranged almost five-fold but there were no significant differences between species (mean 2.73 ± 1.02 gC m-2 day-1). This was attributable to higher daily values of E (2.63 ± 0.83 mm day-1) and lower ω (1.35 ± 0.53 gC kg H2O-1) for D. dacrydioides compared with lower E (1.82 ± 0.72 mm day-1) and higher ω (1.90 ± 0.77 gC kg H2O-1) for P. totara. We attributed this to higher nitrogen availability and nitrogen concentration per unit foliage area, Na, and greater exposure to irradiance in the D. dacrydioides canopy compared with P. totara. Our findings support earlier observations that D. dacrydioides is more adapted to sites with poor drainage. In contrast, the high retention of leaf area and maintaining low rates of transpiration by P. totara, resulting in higher water-use efficiency, is an adaptive response to survival in dry conditions. Our findings show that physiological adjustments for two species adapted to different environments led to similar canopy photosynthesis rates when the trees were grown in the same conditions. We demonstrated consistency between whole-tree and more intensive shoot-scale measurements, confirming that integrated approaches are appropriate for comparative estimates of carbon uptake in stands with different species.

Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015

Large datasets of carbon dioxide, energy, and water fluxes were measured with the eddy-covariance (EC) technique, such as FLUXNET2015. These datasets are widely used to validate remote-sensing products and benchmark models. One of the major challenges in utilizing EC-flux data is determining the spatial extent to which measurements taken at individual EC towers reflect model-grid or remote sensing pixels. To minimize the potential biases caused by the footprint-to-target area mismatch, it is important to use flux datasets with awareness of the footprint. This study analyze the spatial representativeness of global EC measurements based on the open-source FLUXNET2015 data, using the published flux footprint model (SAFE-f). The calculated annual cumulative footprint climatology (ACFC) was overlaid on land cover and vegetation index maps to create a spatial representativeness dataset of global flux towers. The dataset includes the following components: (1) the ACFC contour (ACFCC) data and areas representing 50%, 60%, 70%, and 80% ACFCC of each site, (2) the proportion of each land cover type weighted by the 80% ACFC (ACFCW), (3) the semivariogram calculated using Normalized Difference Vegetation Index (NDVI) considering the 80% ACFCW, and (4) the sensor location bias (SLB) between the 80% ACFCW and designated areas (e.g. 80% ACFCC and window sizes) proxied by NDVI. Finally, we conducted a comprehensive evaluation of the representativeness of each site from three aspects: (1) the underlying surface cover, (2) the semivariogram, and (3) the SLB between 80% ACFCW and 80% ACFCC, and categorized them into 3 levels. The goal of creating this dataset is to provide data quality guidance for international researchers to effectively utilize the FLUXNET2015 dataset in the future.

The seasonal variability of future evapotranspiration over China during the 21st century

The evapotranspiration (ET) plays a crucial role in shaping regional climate patterns and serves as a vital indicator of ecosystem function. However, there remains a limited understanding of the seasonal variability of future ET over China and its correlation with environmental drivers. This study evaluated the skills of 27 models from the Six Phase of Coupled Model Intercomparison Project in modeling ET and the Bayesian Model Averaging (BMA) method was employed to merge monthly simulated ET based on the top five best-performing models. The seasonal changes in ET under three climate scenarios from 2030 to 2099 were analyzed based on the BMA-merged ET, which was well validated with observed ET collected from fourteen flux sites across China. Significant increasing ET over China are projected under all seasons during 2030-2099, with 0.05-0.13 mm yr-1, 0.11-0.23 mm yr-1, and 0.20-0.41 mm yr-1 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, respectively. Relative to the historical period (1980-2014), the relative increase in ET over China is highest in winter and lowest in summer. Seasonal ET increases significantly in all seven climate sub-regions under high forcing scenario. Higher ET increase is generally found in southeastern humid regions, while lowest ET increase occurs in northwest China. At the country level, the primary factor driving ET increase during spring, summer, and autumn seasons is the increasing net radiation and warming. In contrast, ET increase during winter is influenced not only by energy factors but also by vegetation-related factors. Future seasonal ET increase is predominantly driven by increasing energy factors in the southeastern humid region and Tibetan Plateau, while seasonal ET changes in the northwest region prevailingly depend on soil moisture. Results indicate that China will experience a "wet season will get wetter, and dry season will become drier" in the 21st century with high radiation forcing scenario.

Mesoscale structure of the atmospheric boundary layer across a natural roughness transition

The structure and intensity of turbulence in the atmospheric boundary layer (ABL) drive fluxes of sediment, contaminants, heat, moisture, and CO[Formula: see text] at the Earth's surface. Where ABL flows encounter changes in roughness-such as cities, wind farms, forest canopies, and landforms-a new mesoscopic flow scale is introduced: the internal boundary layer (IBL), which represents a near-bed region of transient flow adjustment that develops over kilometers. Measurement of this new mesoscopic scale lies outside present observational capabilities of ABL flows, and simplified models fail to capture the sensitive dependence of turbulence on roughness geometry. Here, we use large-eddy simulations, run over high-resolution topographic data and validated against field observations, to examine the structure of the ABL across a natural roughness transition: the emergent sand dunes at White Sands National Park. We observe that development of the IBL is triggered by the abrupt transition from smooth playa surface to dunes; however, continuous changes in the size and spacing of dunes over several kilometers influence the downwind patterns of boundary stress and near-bed turbulence. Coherent flow structures grow and merge over the entire [Formula: see text]10 km distance of the dune field and modulate the influence of large-scale atmospheric turbulence on the bed. Simulated boundary stresses in the developing IBL counter existing expectations and explain the observed downwind decrease in dune migration, demonstrating a mesoscale coupling between flow and form that governs landscape dynamics. More broadly, our findings demonstrate the importance of resolving both turbulence and realistic roughness for understanding fluid-boundary interactions in environmental flows.

A Beginner's Guide to Eddy Covariance: Methodology and Its Applications to Photosynthesis

The eddy covariance technique, commonly applied using flux towers, enables the investigation of greenhouse gas (e.g., carbon dioxide, methane, nitrous oxide) and energy (latent and sensible heat) fluxes between the biosphere and the atmosphere. Through measuring carbon fluxes in particular, eddy covariance flux towers can give insight into how ecosystem scale photosynthesis (i.e., gross primary productivity) changes over time in response to climate and management. This chapter is designed to be a beginner's guide to understanding the eddy covariance method and how it can be applied in photosynthesis research. It introduces key concepts and assumptions that apply to the method, what materials are required to set up a flux tower, as well as practical advice for site installation, maintenance, data management, and postprocessing considerations. This chapter also includes examples of what can go wrong, with advice on how to correct these errors if they arise. This chapter has been crafted to help new users design, install, and manage the best towers to suit their research needs and includes additional resources throughout to further guide successful eddy covariance research activities.

Global observation gaps of peatland greenhouse gas balances: needs and obstacles

Greenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.

Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.

Eighteen years of upland grassland carbon flux data: reference datasets, processing, and gap-filling procedure

Plant-atmosphere exchange fluxes of CO₂ measured with the Eddy covariance method are used extensively for the assessment of ecosystem carbon budgets worldwide. The present paper describes eddy flux measurements for a managed upland grassland in Central France studied over two decades (2003-2021). We present the site meteorological data for this measurement period, and we describe the pre-processing and post-processing approaches used to overcome issues of data gaps, commonly associated with long-term EC datasets. Recent progress in eddy flux technology and machine learning now paves the way to produce robust long-term datasets, based on normalised data processing techniques, but such reference datasets remain rare for grasslands. Here, we combined two gap-filling techniques, Marginal Distribution Sampling (short gaps) and Random Forest (long gaps), to complete two reference flux datasets at the half-hour and daily-scales respectively. The resulting datasets are valuable for assessing the response of grassland ecosystems to (past) climate change, but also for model evaluation and validation with respect to future global change research with the carbon-cycle community.

Comparison of environmental controls on daily actual evapotranspiration dynamics among different terrestrial ecosystems in China

Terrestrial actual evapotranspiration (ET_a) is a key state variable modulating land surface processes; however, it remains challenging to recognize how daily ET_a responses to environmental variables vary with ecosystems, which is relevant for understanding various ecosystem processes. To this end, comprehensive datasets were synthesized for 22 field sites equipped with eddy covariance towers from the ChinaFLUX network and the National Tibetan Plateau Data Center, which included four different ecosystems across China (e.g., barren or sparsely vegetated-BAR, grassland, forest, and cropland ecosystems). The impacts of environmental variables on daily ET_a variations at each field site were assessed by the boosted regression tree (BRT) method. Overall, the BRT results showed that invariant of ecosystem types, net radiation (Rn) was the primary control on daily ET_a dynamics with an average contribution of 62.9 % for all the sites, followed by leaf area index-LAI (18.4 %), vapor pressure deficit (8.2 %), soil water content-SWC (7.4 %), and wind speed (3.1 %). More importantly, it was revealed that the interactions of daily ET_a with energy (Rn) and water (SWC) supplies could be significantly modified by vegetation through various regulation mechanisms. Specifically, for the BAR and grassland ecosystems, the influences of vegetation on daily ET_a highly depended on local land cover and hydrological conditions (e.g., groundwater). For the forest ecosystem, the contrasting impacts of LAI between evergreen and temperate forests were largely attributed to the differences in LAI dynamics over growing seasons, while physiological differences in crops affected the daily ET_a responses to LAI variations at cropland sites. This study underscored the varying interactions of daily ET_a with Rn and SWC, which could be further shaped by vegetation through a variety of regulation mechanisms across different ecosystems.

The ecosystem wilting point defines drought response and recovery of a Quercus-Carya forest

Soil and atmospheric droughts increasingly threaten plant survival and productivity around the world. Yet, conceptual gaps constrain our ability to predict ecosystem-scale drought impacts under climate change. Here, we introduce the ecosystem wilting point (Ψ_EWP ), a property that integrates the drought response of an ecosystem's plant community across the soil-plant-atmosphere continuum. Specifically, Ψ_EWP defines a threshold below which the capacity of the root system to extract soil water and the ability of the leaves to maintain stomatal function are strongly diminished. We combined ecosystem flux and leaf water potential measurements to derive the Ψ_EWP of a Quercus-Carya forest from an "ecosystem pressure-volume (PV) curve," which is analogous to the tissue-level technique. When community predawn leaf water potential (Ψ_pd ) was above Ψ_EWP (=-2.0 MPa), the forest was highly responsive to environmental dynamics. When Ψ_pd fell below Ψ_EWP , the forest became insensitive to environmental variation and was a net source of carbon dioxide for nearly 2 months. Thus, Ψ_EWP is a threshold defining marked shifts in ecosystem functional state. Though there was rainfall-induced recovery of ecosystem gas exchange following soaking rains, a legacy of structural and physiological damage inhibited canopy photosynthetic capacity. Although over 16 growing seasons, only 10% of Ψ_pd observations fell below Ψ_EWP , the forest is commonly only 2-4 weeks of intense drought away from reaching Ψ_EWP , and thus highly reliant on frequent rainfall to replenish the soil water supply. We propose, based on a bottom-up analysis of root density profiles and soil moisture characteristic curves, that soil water acquisition capacity is the major determinant of Ψ_EWP , and species in an ecosystem require compatible leaf-level traits such as turgor loss point so that leaf wilting is coordinated with the inability to extract further water from the soil.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (R_eco ), net ecosystem CO₂ exchange (NEE; R_eco  - GPP), and terrestrial methane (CH₄ ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km² flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO₂ -C year^-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH₄ emissions from tundra and boreal wetlands (not accounting for aquatic CH₄ ) were estimated at 35 Tg CH₄ -C year^-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Warming and drought weaken the carbon sink capacity of an endangered paleoendemic temperate rainforest in South America

Measurements of ecosystem carbon (C) fluxes in temperate forests are concentrated in the Northern Hemisphere, leaving the functionally diverse temperate forests in the Southern Hemisphere underrepresented. Here, we report three years (February 2018-January 2021) of C fluxes, studied with eddy-covariance and closed chamber techniques, in an endangered temperate evergreen rainforest of the long-lived paleoendemic South American conifer Fitzroya cupressoides. Using classification and regression trees we analyzed the most relevant drivers and thresholds of daily net ecosystem exchange (NEE) and soil respiration. The annual NEE showed that the forest was a moderate C sink during the period analyzed (-287±38 g C m^-2 year ^-1). We found that the capacity to capture C of the Fitzroya rainforests in the Coastal Range of southern Chile is optimal under cool and rainy conditions in the early austral spring (October-November) and decreases rapidly towards the summer dry season (January-February) and autumn. Although the studied forest type has a narrow geographical coverage, the gross primary productivity measured at the tower was highly representative of Fitzroya and other rainforests in the region. Our results suggest that C fluxes in paleoendemic cool F. cupressoides forests may be negatively affected by the warming and drying predicted by climate change models, reinforcing the importance of maintaining this and other long-term ecological research sites in the Southern Hemisphere.

Carbon balance and controlling factors in a summer maize agroecosystem in the Guanzhong Plain, China

BACKGROUND

Quantifying the carbon balance of agroecosystems and clarifying the factors controlling it are essential for estimating the regional carbon cycle and global carbon balance.

RESULTS

Based on the eddy covariance (EC) technique and soil respiration observations during the 2017 and 2019 summer maize growing seasons, this study analyzed the carbon balance and revealed the factors controlling carbon fluxes in the summer maize agroecosystem. Green leaf area index was the most important factor affecting net ecosystem exchange (NEE), total primary productivity, and total ecosystem respiration (TER) in the rapid development stage during the growing season, followed by soil water content. However, precipitation, air temperature, relative humidity, saturated vapor pressure difference, and photosynthetically active radiation were the main factors that influenced carbon balance at the middle stage. The cumulative TER in 2019 was 40% (320.9 g C m^-2 ) higher than that in 2017. The NEE estimates of summer maize agroecosystems in 2017 and 2019 were -71.7 and 160.4 g C m^-2 , respectively. Accounting for the carbon input at sowing (10 g C m^-2 ) and the similar carbon output at harvest owing to grain removal, the net biome productivity in 2019 was 1.75 times that in 2017, at -636 and -363 g C m^-2 , respectively.

CONCLUSION

The carbon balance of the summer maize agroecosystem in the Guanzhong Plain was determined to be a net carbon source that could export carbon at an average rate of 499.5 g C m^-2  yr^-1 . © 2022 Society of Chemical Industry.

Environmental controls on the light use efficiency of terrestrial gross primary production

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C₃ species; however, additional assumptions are required to "scale up" from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple "goodness of fit" comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

A widely-used eddy covariance gap-filling method creates systematic bias in carbon balance estimates

Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude [Formula: see text]) sites. MDS systematically overestimates the carbon dioxide (CO[Formula: see text]) emissions of carbon sources and underestimates the CO[Formula: see text] sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias.

The effect of conventional and sustainable agricultural management practices on carbon and water fluxes in a Mexican semi-arid region

Background

Agriculture is essential for food security. However, conventional agriculture alters the water and carbon cycle and soil properties. We investigated the effect of conventional management (CM) and sustainable management (SM) on the carbon and water cycle in crops of nopal (Np) and wheat (Wh).

Methods

A micrometeorological eddy covariance tower was installed to measure water use through evapotranspiration (ET) and the net exchange of CO₂ during the crop's development. Gross primary productivity (GPP), water use efficiency (WUE), and soil properties were obtained.

Results

The results showed that both agricultural managements influenced the carbon flux of the ecosystem, with a lower GPP and Reco in the nopal field (1.85 and 0.99 mmol C m^-2 s^-1, respectively), compared to the wheat field (6.34 and 1.8 mmol C m^-2 s^-1, respectively). It was mainly attributed to the metabolic plant differences, phenological stages, and wheat biomass developed during the winter. On the other hand, the accumulated ET in the SM-Wh plots was lower than SM-Np. Therefore, the crops subjected to sustainable practices use water more efficiently with 1.42 and 1.03 g C m^-3 H₂O for nopal and wheat, respectively. In regard to soil properties, it was observed that tillage alters microbial activity affecting organic matter and carbon. It can be concluded that the differences in agricultural management for both crops altered the carbon and water cycle and soil quality. In addition, implementing good agricultural practices allows more efficient use of water by the plant, higher retention of water in the soil, and less ET.

Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems

Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO₂) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO₂ increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.

Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere

Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPP_max), and the ratio of mean daily GPP to GPP_max (α_GPP)), and then decomposed AGPP into mean leaf area index (LAI_m) and annual photosynthetic capacity per leaf area (AGPP_lm). Furthermore, GPP_max was decomposed into leaf area index of DOY_max (the day when GPP_max appeared) (LAI_max) and photosynthesis per leaf area of DOY_max (GPP_lmax). Relative contributions of parameters to AGPP and GPP_max were then calculated. Finally, environmental variables of DOY_max were extracted to analyze factors influencing interannual variation of GPP_lmax. Trends of AGPP in 39 ecosystems varied from -65.23 to 53.05 g C m^-2 yr^-2, with the mean value of 6.32 g C m^-2 yr^-2. Photosynthetic capacity (GPP_max and AGPP_lm), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPP_lmax determined the interannual variation of GPP_max, and temperature, water, and radiation conditions of DOY_max affected the interannual variation of GPP_lmax. This study used the cascade relationship of "environmental variables-GPP_lmax-GPP_max-AGPP" to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.

Greenhouse gas fluxes (CO2, N2O and CH4) of pea and maize during two cropping seasons: Drivers, budgets, and emission factors for nitrous oxide

Agriculture contributes considerably to the increase of global greenhouse gas (GHG) emissions. Hence, magnitude and drivers of temporal variations in carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) fluxes in croplands are urgently needed to develop sustainable, climate-smart agricultural practices. However, our knowledge of GHG fluxes from croplands is still very limited. The eddy covariance technique was used to quantify GHG budgets and N2O emission factors (EF) for pea and maize in Switzerland. The random forest technique was applied for gap-filling N2O and CH4 fluxes as well as to determine the relevance of environmental, vegetation vs. management drivers of the GHG fluxes during two cropping seasons. Environmental (i.e., net radiation, soil water content, soil temperature) and vegetation drivers (i.e., vegetation height) were more important drivers for GHG fluxes at field scale than time since management for the two crop species. Both crops acted as GHG sinks between sowing and harvest, clearly dominated by net CO2 fluxes, while CH4 emissions were negligible. However, considerable N2O emissions occurred in both crop fields early in the season when crops were still establishing. N2O fluxes in both crops were small later in the season when vegetation was tall, despite high soil water contents and temperatures. Results clearly show a strong and highly dynamic microbial-plant competition for N driving N2O fluxes at the field scale. The total loss was 1.4 kg N2O-N ha-1 over 55 days for pea and 4.8 kg N2O-N ha-1 over 127 days for maize. EFs of N2O were 1.5 % (pea) and 4.4 % (maize) during the cropping seasons, clearly exceeding the IPCC Tier 1 EF for N2O. Thus, sustainable, climate-smart agriculture needs to consider crop phenology and better adapt N supply to crop N demand for growth, particularly during the early cropping season when competition for N between establishing crops and soil microorganisms modulates N2O losses.

Environmental factors contributing to variations in CO2 flux over a barley-rice double-cropping paddy field in the Korean Peninsula

Understanding the CO₂ flux over agricultural crop fields is critical because the temporal cycle is driven by both ecological environment and anthropogenic change. We analyzed the net ecosystem exchange of CO₂ measured over a barley-rice double-cropping field using the eddy covariance method for 5 years. We conducted gap-filling based on u_*-threshold criteria and partitioned the net ecosystem exchange into gross primary production and respiration. The relative importance analysis of solar radiation, temperature, soil heat flux, soil water content, and vapor deficit revealed that solar radiation and temperature were the dominant contributors to net ecosystem exchange. The annual variation in the net ecosystem exchange followed a bimodal pattern driven by CO₂ uptake by both barley and rice, displaying two negative peaks in late April and mid-August. The elongation stages of the crops exhibited the highest flux. Gross primary production and respiration were closely related to solar radiation and nighttime temperature, respectively. The relative importance of the other environmental variables was affected by the cultivation season and irrigation water. In the period of rice cultivation, respiration was approximately 3 µmol m^-2 s^-1 higher during rice drainage than during the flooded period. The accumulated net ecosystem production was estimated to be 315 gC m^-2 and 349 gC m^-2 for the barley and rice growing periods, respectively, and 649 gC m^-2 for the annual total. These values are comparable with the results of other studies on barley-rice double-cropping fields.

CO2 flux in a wheat-soybean succession in subtropical Brazil: A carbon sink

The subtropical region of Brazil is home to 33% of the soybean [Glycine max (L.) Merr.] growing area and 90% of the wheat (Tritucum aestivum L.) growing area of this country. A soybean-wheat succession with fallow between crops is used in about 11% of the cultivated area. No study has quantified CO2 fluxes in annual soybean-wheat succession in this region. Hence, this study analyzed the seasonality of CO2 exchange (net ecosystem exchange [NEE]) in a 2015/2016 wheat-soybean succession in a commercial farm located in Carazinho, Rio Grande do Sul State, Brazil. The eddy covariance method was used to estimate the annual C balance of this system. The NEE was partitioned between gross primary productivity and ecosystem respiration to understand the dynamics of these fluxes during a year of wheat-soybean succession. Considering the net ecosystem balance between photosynthesis and respiration during the growing season, both soybean and wheat absorbed CO2 from the atmosphere (NEE wheat: -347 ± 4 g C m-2 ; NEE soybean: -242 ± 3 g C m-2 ). The fallow periods between growing seasons, however, acted as a source of 156 ± 2 g C m-2 , reducing the C absorbed by the crops by 27%. For 1 yr, the net biome productivity was -50 g C m-2  yr-1 . The results obtained here demonstrate that the wheat-soybean succession was a net C sink under these specific climatic conditions and field management practices and that the long fallow period between crops limited the agroecosystem from becoming a more efficient CO2 sink.

Re-assessment of the climatic controls on the carbon and water fluxes of a boreal aspen forest over 1996-2016: Changing sensitivity to long-term climatic conditions

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (R_e ) over 1996-2016, but R_e was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R²  > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and R_e ) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

Combining NDVI, PRI and the quantum yield of solar-induced fluorescence improves estimations of carbon fluxes in deciduous and evergreen forests

We used automated spectroradiometers to continuously monitor changes in the optical parameters of phenological and photosynthetic traits in beech and spruce forests. We examined seasonal variations in the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and solar-induced fluorescence in the oxygen A band (SIFA) that was estimated using a 3-FLD discrimination method from radiance data. The optical parameters tracked the activation and cessation of photosynthesis in spring and autumn. Data at photon fluxes >1200 μmol m^-2 s^-1 during extended noon hours were used to link the seasonal PRI and SIFA variations to the dynamics of photosynthesis. Seasonal PRI was significantly correlated with photosynthetic light-use efficiency (LUE) with R² values of 0.66 and 0.48 for the measurements in beech and spruce forests, respectively. SIFA emissions were significantly correlated with the gross primary production (GPP) of the evergreen spruce forest (R² = 0.47), but R² was only 0.13 when measured in the beech forest. The correlations between the optical parameters and GPP or LUE, however, tended to be lower when using a dataset with constant NDVI. Introducing an equation combining NDVI, PRI, and the quantum yield of SIFA emission increased R² for LUE estimation to 0.77 in the spruce forest and 0.63 in the beech forest. GPP was estimated from the parametric equation with improved accuracy reaching R² = 0.53 and RMSE = 5.95 μmol CO₂ m^-2 s^-1 in spruce forest and R² = 0.58 and RMSE = 5.23 μmol CO₂ m^-2 s^-1 in beech forest. Parametric equations were more efficient in estimating photosynthesis in datasets that consisted of an entire season's data. By combining NDVI, PRI and the quantum yield of SIFA, we could thus substantially improve estimations of carbon fluxes in diverse deciduous and evergreen canopies.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

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.

Dormant Season Vegetation Phenology and Eddy Fluxes in Native Tallgrass Prairies of the U.S. Southern Plains

Carbon dioxide (CO2) fluxes and evapotranspiration (ET) during the non-growing season can contribute significantly to the annual carbon and water budgets of agroecosystems. Comparative studies of vegetation phenology and the dynamics of CO2 fluxes and ET during the dormant season of native tallgrass prairies from different landscape positions under the same climatic regime are scarce. Thus, this study compared the dynamics of satellite-derived vegetation phenology (as captured by the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI)) and eddy covariance (EC)-measured CO2 fluxes and ET in six differently managed native tallgrass prairie pastures during dormant seasons (November through March). During December–February, vegetation phenology (EVI and NDVI) and the dynamics of eddy fluxes were comparable across all pastures in most years. Large discrepancies in fluxes were observed during March (the time of the initiation of growth of dominant warm-season grasses) across years and pastures due to the influence of weather conditions and management practices. The results illustrated the interactive effects between prescribed spring burns and rainfall on vegetation phenology (i.e., positive and negative impacts of prescribed spring burns under non-drought and drought conditions, respectively). The EVI better tracked the phenology of tallgrass prairie during the dormant season than did NDVI. Similar EVI and NDVI values for the periods when flux magnitudes were different among pastures and years, most likely due to the satellite sensors’ inability to fully observe the presence of some cool-season C3 species under residues, necessitated a multi-level validation approach of using ground-truth observations of species composition, EC measurements, PhenoCam (digital) images, and finer-resolution satellite data to further validate the vegetation phenology derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) during dormant seasons. This study provides novel insights into the dynamics of vegetation phenology, CO2 fluxes, and ET of tallgrass prairie during the dormant season in the U.S. Southern Great Plains.

A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020

Distinguishing gross primary production of sunlit and shaded leaves (GPPsun and GPPshade) is crucial for improving our understanding of the underlying mechanisms regulating long-term GPP variations. Here we produce a global 0.05°, 8-day dataset for GPP, GPPshade and GPPsun over 1992-2020 using an updated two-leaf light use efficiency model (TL-LUE), which is driven by the GLOBMAP leaf area index, CRUJRA meteorology, and ESA-CCI land cover. Our products estimate the mean annual totals of global GPP, GPPsun, and GPPshade over 1992-2020 at 125.0 ± 3.8 (mean ± std) Pg C a-1, 50.5 ± 1.2 Pg C a-1, and 74.5 ± 2.6 Pg C a-1, respectively, in which EBF (evergreen broadleaf forest) and CRO (crops) contribute more than half of the totals. They show clear increasing trends over time, in which the trend of GPP (also GPPsun and GPPshade) for CRO is distinctively greatest, and that for DBF (deciduous broadleaf forest) is relatively large and GPPshade overwhelmingly outweighs GPPsun. This new dataset advances our in-depth understanding of large-scale carbon cycle processes and dynamics.

Does growing atmospheric CO2 explain increasing carbon sink in a boreal coniferous forest?

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001-2017) of eddy-covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter-annual variability (IAV). The forest was a mean annual carbon sink (252 [ ± 42] gC m-2a-1 ), and NEP increased at rate +6.4-7.0 gC m-2a-1 (or ca. +2.5% a-1 ) during the period. This was attributed to the increasing gross-primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a-1 , and increase in GPP and NEP outside the main growing season contributed ca. one-third and one-fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long-term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi-layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30-40% of the observed ecosystem GPP increase could be attributed to CO2 . The increasing trend in leaf-area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid-rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna

Despite their size and contribution to the global carbon cycle, we have limited understanding of tropical savannas and their current trajectory with climate change and anthropogenic pressures. Here we examined interannual variability and externally forced long-term changes in carbon and water exchange from a high rainfall savanna site in the seasonal tropics of north Australia. We used an 18-year flux data time series (2001-2019) to detect trends and drivers of fluxes of carbon and water. Significant positive trends in gross primary productivity (GPP, 15.4 g C m²  year^-2 ), ecosystem respiration (R_eco , 8.0 g C m²  year^-2 ), net ecosystem productivity (NEE, 7.4 g C m²  year^-2 ) and ecosystem water use efficiency (WUE, 0.0077 g C kg H₂ O^-1  year^-1 ) were computed. There was a weaker, non-significant trend in latent energy exchange (LE, 0.34 W m^-2  year^-1 ). Rainfall from a nearby site increased statistically over a 45-year period during the observation period. To examine the dominant drivers of changes in GPP and WUE, we used a random forest approach and a terrestrial biosphere model to conduct an attribution experiment. Radiant energy was the dominant driver of wet season fluxes, whereas soil water content dominated dry season fluxes. The model attribution suggested that [CO₂ ], precipitation and T_air accounting for 90% of the modelled trend in GPP and WUE. Positive trends in fluxes were largest in the dry season implying tree components were a larger contributor than the grassy understorey. Fluxes and environmental drivers were not significant during the wet season, the period when grasses are active. The site is potentially still recovering from a cyclone 45 years ago and regrowth from this event may also be contributing to the observed trends in sequestration, highlighting the need to understand fluxes and their drivers from sub-diurnal to decadal scales.

Carbon dioxide uptake overrides methane emission at the air-water interface of algae-shellfish mariculture ponds: Evidence from eddy covariance observations

Mariculture ponds are widely distributed along the coastal regions and have been increasingly recognized as biogeochemical hotspots of air-water greenhouse gas (GHG) fluxes, but their source/sink dynamics and climate benefits have not been well understood. Due to strong temporal variations of GHG fluxes over mariculture ponds, previous studies based on short-term or discrete flux measurements have large uncertainty in assessing GHG budgets and their radiative effects. In this study, we examined the temporal variations of air-water GHG fluxes, net CO₂ exchange (NEE) and net CH₄ exchange (NME), and their environmental controls, based on one-year (2020) continuous eddy covariance (EC) measurements over algae-shellfish mariculture ponds (razor clam) in a subtropical estuary of Southeast China. The results showed that (a) annually the ponds acted as a strong CO₂ sink of -227.7 g CO₂-C m^-2 and a weak CH₄ source of 1.44 g CH₄-C m^-2, and thus the NME-induced warming effect offset 25.9% (12.1%) of the NEE-induced cooling effect at a 20-year (100-year) time horizon using the metric of sustained-flux global warming potential; (b) two GHG fluxes showed different diurnal and seasonal variations but both had stronger source/sink capacity in summer and more fluctuating fluxes in winter; (c) temporal variations of NEE and NME tended to be more regulated by photosynthetically active radiation and tidal salinity, respectively, but both of them were affected by water temperature and area proportion of algae ponds within the EC footprint. This is the first study to disentangle temporal variations of air-water GHG fluxes over mariculture ponds based on simultaneous EC measurements of CO₂ and CH₄ fluxes. This study highlights the climate benefits of algae-shellfish mariculture ponds as biogeochemical hotspots by exerting a net radiative cooling effect dominated by the CO₂ sink.

Remote Sensing Products Validated by Flux Tower Data in Amazon Rain Forest

This work compares methods of climate measurements, such as those used to measure evapotranspiration, precipitation, net radiation, and temperature. The satellite products used were compared and evaluated against flux tower data. Evapotranspiration was validated against the SSEBop monthly and GLEAM daily and monthly products, respectively, and the results were RMSE = 24.144 mm/month, NRMSE = 0.223, r2 = 0.163, slope = 0.411; RMSE = 1.781 mm/day, NRMSE = 0.599, r2 = 0.000, slope = 0.006; RMSE = 36.17 mm/month, NRMSE = 0.401, r2 = 0.002, and slope = 0.026. Precipitation was compared with the CHIRPS data, K67 was not part of the CHIRPS station correction. The results for both the daily and monthly comparisons were RMSE = 18.777 mm/day, NRMSE = 1.027, r2 = 0.086, slope = 0.238 and RMSE = 130.713 mm/month, NRMSE = 0.706, r2 = 0.402, and slope = 0.818. The net radiation validated monthly with CERES was RMSE = 75.357 W/m2, NRMSE = 0.383, r2 = 0.422, and slope = 0.867. The temperature results, as compared to MOD11C3, were RMSE = 2.829 °C, NRMSE = 0.116, r2 = 0.153, and slope = 0.580. Comparisons between the remote sensing products and validation against the ground data were performed on a monthly basis. GLEAM and CHIRPS daily were the data sets with considerable discrepancy.

Light and flow regimes regulate the metabolism of rivers

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.

A new open-path eddy covariance method for nitrous oxide and other trace gases that minimizes temperature corrections

Low-power, open-path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open-path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser-based, open-path sensors with the needed sensitivity for trace gases like methane (CH₄ ) and nitrous oxide (N₂ O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N₂ O fluxes. Consequently, measuring background fluxes with laser-based, open-path sensors is extremely challenging, particularly for N₂ O and gases with similar high-precision requirements. We demonstrate a new laser-based, open-path N₂ O sensor and a general approach applicable to other gases that minimizes temperature-related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open-path N₂ O sensor was tested at a corn (Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature-related corrections were 6% of density corrections, reducing EC random errors by 20-fold compared to previously examined lines. Measured open-path N₂ O EC fluxes showed excellent agreement with those made with static chambers (m = 1.0 ± 0.3; r²  = .96). More generally, we identified absorption lines for CO₂ and CH₄  flux measurements that can reduce the temperature-related corrections by 10-100 times compared to existing open-path sensors. The proposed method provides a new direction for future open-path sensors, facilitating the expansion of accurate EC flux measurements.

Methane emission dynamics from a Danish landfill: The effect of changes in barometric pressure

This study investigates temporal variability on landfill methane (CH₄) emissions from an old abandoned Danish landfill, caused by the rate of changes in barometric pressure. Two different emission quantification techniques, namely the dynamic tracer dispersion method (TDM) and the eddy covariance method (EC), were applied simultaneously and their results compared. The results showed a large spatial and temporal CH₄ emission variation ranging from 0 to 100 kg h^-1 and 0 to 12 μmol m^-2 s^-1, respectively. Landfill CH₄ emissions dynamics were influenced by two environmental factors: the rate of change in barometric pressure (a strong negative correlation) and wind speed (a weak positive correlation). The relationship between CH₄ emissions and the rate of change in barometric pressure was more complicated than a linear one, thereby making it difficult to estimate accurately annual CH₄ emissions from a landfill based on discrete measurements. Furthermore, the results did not show any clear relationship between CH₄ emissions and ambient temperature. Large seasonal variations were identified by the two methods, whereas no diurnal variability was observed throughout the investigated period. CH₄ fluxes measured with the EC method were strongly correlated with emissions from the TDM method, even though no direct relationship could be established, due to the different sampling ranges of the two methods and the spatial heterogeneity of CH₄ emissions.

A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems

It is well documented that energy balance and other remote sensing-based evapotranspiration (ET) models face greater uncertainty over water-limited tree-grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass-dominated understory and tree-dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy-limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal-based three-source energy balance (3SEB) model, accommodating an additional vegetation source within the well-known two-source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy-covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m² ; MSG: LE RMSD ~90 W/m² ), improving over both TSEB and seasonally changing TSEB (TSEB-2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.

Heat and drought impact on carbon exchange in an age-sequence of temperate pine forests

BACKGROUND

Most North American temperate forests are plantation or regrowth forests, which are actively managed. These forests are in different stages of their growth cycles and their ability to sequester atmospheric carbon is affected by extreme weather events. In this study, the impact of heat and drought events on carbon sequestration in an age-sequence (80, 45, and 17 years as of 2019) of eastern white pine (Pinus strobus L.) forests in southern Ontario, Canada was examined using eddy covariance flux measurements from 2003 to 2019.

RESULTS

Over the 17-year study period, the mean annual values of net ecosystem productivity (NEP) were 180 ± 96, 538 ± 177 and 64 ± 165 g C m^-2 yr^-1 in the 80-, 45- and 17-year-old stands, respectively, with the highest annual carbon sequestration rate observed in the 45-year-old stand. We found that air temperature (Ta) was the dominant control on NEP in all three different-aged stands and drought, which was a limiting factor for both gross ecosystem productivity (GEP) and ecosystems respiration (RE), had a smaller impact on NEP. However, the simultaneous occurrence of heat and drought events during the early growing seasons or over the consecutive years had a significant negative impact on annual NEP in all three forests. We observed a similar trend of NEP decline in all three stands over three consecutive years that experienced extreme weather events, with 2016 being a hot and dry, 2017 being a dry, and 2018 being a hot year. The youngest stand became a net source of carbon for all three of these years and the oldest stand became a small source of carbon for the first time in 2018 since observations started in 2003. However, in 2019, all three stands reverted to annual net carbon sinks.

CONCLUSIONS

Our study results indicate that the timing, frequency and concurrent or consecutive occurrence of extreme weather events may have significant implications for carbon sequestration in temperate conifer forests in Eastern North America. This study is one of few globally available to provide long-term observational data on carbon exchanges in different-aged temperate plantation forests. It highlights interannual variability in carbon fluxes and enhances our understanding of the responses of these forest ecosystems to extreme weather events. Study results will help in developing climate resilient and sustainable forestry practices to offset atmospheric greenhouse gas emissions and improving simulation of carbon exchange processes in terrestrial ecosystem models.