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Eddy covariance (EC) measurements can provide direct and non-invasive ecosystem measurements of the exchange of energy, water (H2O) and carbon dioxide (CO2). However, conventional eddy covariance (CON-EC) setups (ultrasonic anemometer and infrared gas analyser) can be expensive, which recently led to the development of lower-cost eddy covariance (LC-EC) setups. In the current study we test the performance of a LC-EC setup for CO2 and H2O flux measurements at an agroforestry and adjacent grassland site in a temperate ecosystem in northern Germany. The closed-path LC-EC setup was compared with a CON-EC setup using an enclosed-path gas analyser (LI-7200, LI-COR Inc., Lincoln, NE, USA). The LC-EC CO2 fluxes were lower compared to CON-EC by 7–13 % (R 2 = 0.91–0.95) and the latent heat fluxes were higher by 2–3 % in 2020 and 23 % in 2021 (R 2 = 0.84–0.90). The large difference between latent heat fluxes in 2021, seems to be a consequence of the lower LE fluxes measured by the CON-EC. Due to the slower response sensors of the LC-EC setup, the (co)spectra of the LC-EC were more attenuated in the high-frequency range compared to the CON-EC. This stronger attenuation of the LC-EC requires a larger spectral correction and as a consequence larger differences between spectral correction factors of different spectral correction methods. At the agroforestry site where the flux tower was taller compared to the grassland, the attenuation was lower, because the cospectrum peak and energy-containing eddies shift to lower frequencies which the LC-EC can measure. With the LC-EC and CON-EC systems was shown that the agroforestry site had a 2.3 times higher carbon uptake compared to the grassland site and both had an equal evapotranspiration when simultaneously measured for one month. Our results show that LC-EC has the potential to measure EC fluxes at various land-use systems for approximately 25 % of the costs of a CON-EC system. [ABSTRACT FROM AUTHOR]

Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at -5.75 ± 0.33 Pg C ⋅ yr -1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C ⋅ yr -1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7x10³ ± 0.9x10³ km 3 globally for the years 2001–2020, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57 % of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates. [ABSTRACT FROM AUTHOR]

Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GP P) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT ), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at -5.75 ± 0.33 P g C · yr−1 for the period 2001-2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 P gC · yr−1 for the same period, X-BASE GP P is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7x103 ± 0.9x103 km3 globally for the years 2001-2020, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57% of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates. [ABSTRACT FROM AUTHOR]

The O 2 : CO 2 exchange ratio (ER) between terrestrial ecosystems and the atmosphere is a key parameter for partitioning global ocean and land carbon fluxes. The long-term terrestrial ER is considered to be close to 1.10 mol of O 2 consumed per mole of CO 2 produced. Due to the technical challenge in measuring directly the ER of entire terrestrial ecosystems (ER eco), little is known about variations in ER at hourly and seasonal scales, as well as how different components contribute to ER eco. In this modeling study, we explored the variability in and drivers of ER eco and evaluated the hypothetical uncertainty in determining ecosystem O 2 fluxes based on current instrument precision. We adapted the one-dimensional, multilayer atmosphere–biosphere gas exchange model "CANVEG" to simulate hourly ER eco from modeled O 2 and CO 2 fluxes in a temperate beech forest in Germany. We found that the modeled annual mean ER eco ranged from 1.06 to 1.12 mol mol -1 within the 5-year study period. Hourly ER eco showed strong variations over diel and seasonal cycles and within the vertical canopy profile. The determination of ER from O 2 and CO 2 mole fractions in air above and within the canopy (ER conc) varied between 1.115 and 1.15 mol mol -1. CANVEG simulations also indicated that ecosystem O 2 fluxes could be derived with the flux-gradient method using measured vertical gradients in scalar properties, as well as fluxes of CO 2 , sensible heat and latent energy derived from eddy covariance measurements. Owing to measurement uncertainties, however, the uncertainty in estimated O 2 fluxes derived with the flux-gradient approach could be as high as 15 µ mol m -2 s -1 , which represented the 90 % quantile of the uncertainty in hourly data with a high-accuracy instrument. We also demonstrated that O 2 fluxes can be used to partition net CO 2 exchange fluxes into their component fluxes of photosynthesis and respiration if ER eco is known. The uncertainty of the partitioned gross assimilation ranged from 1.43 to 4.88 µ mol m -2 s -1 assuming a measurement uncertainty of 0.1 or 2.5 µ mol m -2 s -1 for net ecosystem CO 2 exchange and from 0.1 to 15 µ mol m -2 s -1 for net ecosystem O 2 exchange, respectively. Our analysis suggests that O 2 measurements at ecosystem scale have the potential to partition net CO 2 fluxes into their component fluxes, but further improvement in instrument precision is needed. [ABSTRACT FROM AUTHOR]

The O2:CO2 exchange ratio (ER) between terrestrial ecosystems and the atmosphere is a key parameter for partitioning global ocean and land carbon fluxes. The long-term terrestrial ER is considered to be close to 1.10 moles of O2 consumed per mole of CO2 produced. Due to the technical challenge in measuring directly the ER of entire terrestrial ecosystems (EReco), little is known about the variations in ER at the hourly and seasonal scales as well as how different components contribute to EReco. In this modeling study, we explore the variability and drivers of EReco and evaluate the hypothetical uncertainty in determining ecosystem O2 fluxes based on current instrument precision. We adapted the onedimensional, multi-layer atmosphere-biosphere gas exchange model, CANVEG, to simulate hourly EReco from modeled O2 and CO2 fluxes in a temperate beech forest in Germany. We found that the annual mean EReco ranged from 1.06 to 1.12 mol mol -1 within the five years’ study period. Hourly EReco showed strong variations over diel and seasonal cycles and within the vertical canopy profile. Determination of ER from O2 and CO2 mole fractions in air above and within the canopy (ERconc) varied between 1.115 and 1.15 mol mol-1 . CANVEG simulations also indicated that ecosystem O2 fluxes could be derived using the flux-gradient method in combination with measurements of vertical scalar gradients and CO2, sensible heat or latent heat fluxes obtained with the eddy covariance technique. Owing to measurement uncertainties, however, the uncertainty in estimated O2 fluxes derived with the flux-gradient approach could be as high as 15 μmol m-2 s -1, which represented the 90% quantile of the uncertainty in hourly data with a highaccuracy instrument. We also demonstrated that O2 fluxes can be used to partition net CO2 exchange fluxes into their component fluxes of photosynthesis and respiration, if EReco is known. The uncertainty of the partitioned gross assimilation ranged from 1.43 to 4.88 μmol m-2 s -1 assuming a measurement uncertainty of 0.1 or 2.5 μmol m-2 s -1 for net ecosystem CO2 exchange and from 0.1 to 15 μmol m-2 s -1 for net ecosystem O2 exchange, respectively. Our analysis suggests that O2 measurements at ecosystem scale have the potential for partitioning net CO2 fluxes into their component fluxes, but further improvement in instrument precision is needed. [ABSTRACT FROM AUTHOR]

Droughts affect terrestrial ecosystems directly and concurrently and can additionally induce lagged effects in subsequent seasons and years. Such legacy effects of drought on vegetation growth and state have been widely studied in tree ring records and satellite-based vegetation greenness, while legacies on ecosystem carbon fluxes are still poorly quantified and understood. Here, we focus on two ecosystem monitoring sites in central Germany with a similar climate but characterised by different species and age structures. Using eddy covariance measurements, we detect legacies on gross primary productivity (GPP) by calculating the difference between random forest model estimates of potential GPP and observed GPP. Our results showed that, at both sites, droughts caused significant legacy effects on GPP at seasonal and annual timescales, which were partly explained by reduced leaf development. The GPP reduction due to drought legacy effects is of comparable magnitude to the concurrent drought effects but differed between two neighbouring forests with divergent species and age structures. The methodology proposed here allows the quantification of the temporal dynamics of legacy effects at the sub-seasonal scale and the separation of legacy effects from model uncertainties. The application of the methodology at a larger range of sites will help us to quantify whether the identified lag effects are general and on which factors they may depend. [ABSTRACT FROM AUTHOR]

Droughts affect terrestrial ecosystems directly and concurrently, and can additionally induce lagged effects in subsequent seasons and years. Such legacy effects of drought on vegetation growth and state have been widely studied in tree-ring records and satellite-based vegetation greenness, while legacies on ecosystem carbon fluxes are still poorly quantified and understood. Here, we focus on two ecosystem monitoring sites in central Germany with similar climate but characterized by different species and age structures. Using eddy-covariance measurements, we detect legacies on gross primary productivity (GPP) by calculating the difference between random-forest model estimates of potential GPP and observed GPP. Our results showed that at both sites, droughts caused significant legacy effects on GPP at seasonal and annual time scales which were partly explained by reduced leaf development. The GPP reduction due to drought legacy effects is of comparable magnitude to the concurrent drought effects, but differed between two neighbouring forests with divergent species and age structures. The methodology proposed here allows quantifying the temporal dynamics of legacy effects at the sub-seasonal scale and separating legacy effects from model uncertainties. Application of the methodology at a larger range of sites will help quantify whether the identified lag effects are general and on which factors they may depend. [ABSTRACT FROM AUTHOR]

For the assessment of evapotranspiration, near-surface airborne thermography offers new opportunities for studies with high numbers of spatial replicates and in a fine spatial resolution. We tested drone-based thermography and the subsequent application of the DATTUTDUT energy balance model using the widely accepted eddy covariance technique as a reference method. The study site was a mature oil palm plantation in lowland Sumatra, Indonesia. For the 61 flight missions, latent heat flux estimates of the DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) model with measured net radiation agreed well with eddy covariance measurements (r2 = 0.85; MAE = 47; RMSE = 60) across variable weather conditions and times of day. Confidence intervals for slope and intercept of a model II Deming regression suggest no difference between drone-based and eddy covariance methods, thus indicating interchangeability. The DATTUTDUT model is sensitive to the configuration of the net radiation assessment. Overall, we conclude that drone-based thermography with energy balance modeling is a reliable method complementing available methods for evapotranspiration studies. It offers promising, additional opportunities for fine grain and spatially explicit studies. [ABSTRACT FROM AUTHOR]

Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing. [ABSTRACT FROM AUTHOR]

Measurements of the isotopic composition of water vapor, δv, as well as measurements of the isotopic composition of evaporation and transpiration provide valuable insights in the hydrological cycle. Here we present measurements of δv in the surface boundary layer (SBL) in combination with eddy covariance (EC) measurements of the isotopic composition of evapotranspiration δET for both δD as well as δ18O over a full growing season above a managed beech forest in central Germany. Based on direct measurements of isoforcing IF and the height h of the planetary boundary layer (PBL), we provide an estimate of isoforcing-related changes in δv, revealing the influence of local evapotranspiration (ET) on δv. At seasonal time scales we find no evidence for a dominant control of δv by local ET. Rayleigh distillation could at most explain 35 % of the observed variability and we did not find indications for the influence of entrainment at seasonal time scales. Instead, we obtain a strong significant correlation (R2 ≈ 0.52; p < 10-35) of δv to temperature. We conclude that the observed seasonal variability of δv is neither dominated by Rayleigh processes, entrainment nor local ET but likely linked to other temperature-related processes such as fractionation during evaporation. At a diurnal time scale we find that even during summer, when transpiration is high and at a height of only 10 m above the canopy, ET is overruled by entrainment effects throughout the day from approximately 10 am to 4 pm. ET only dominates the diurnal cycle of δv in the mornings and evenings. Thus, from diurnal to seasonal time scale, ET does not dominate the measured δv at our field site, even if the measurements were carried out close to the canopy. We further conclude, that accounting for PBL height h is essential to understand drivers of δv. [ABSTRACT FROM AUTHOR]

Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of normalized difference vegetation index (NDVI) of forest understory with multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 meter daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were hence tested across diverse forest conditions and phenological phases during the growing season, to examine its applicability on ecosystems other than boreal forests. Here we report the method can deliver good retrievals especially over different forest types with open canopies (low foliage cover). The performance of the method was found limited over forests with closed canopies (high foliage cover), where the signal from understory gets much attenuated. The spatial heterogeneity of individual field sites as well as the limitations and documented quality of the MODIS BRDF product are shown to be important for correct assessment and validation of the retrievals obtained with remote sensing. [ABSTRACT FROM AUTHOR]

In the past few years, the interest in growing crops and trees for bioenergy production has increased. One agricultural practice is the mixed cultivation of fast-growing trees and annual crops or perennial grasslands on the same piece of land, which is referred to as one type of agroforestry (AF). The inclusion of tree strips into the agricultural landscape has been shown – on the one hand – to lead to reduced wind speeds and higher carbon sequestration above ground and in the soil. On the other hand, concerns have been raised about increased water losses to the atmosphere via evapotranspiration (ET). Therefore, we hypothesise that short rotation coppice agroforestry systems have higher water losses to the atmosphere via ET compared to monoculture (MC) agriculture without trees. In order to test the hypothesis, the main objective was to measure the actual evapotranspiration of five AF systems in Germany and compare those to five monoculture systems in the close vicinity of the AF systems. We measured actual ET at five AF sites in direct comparison to five monoculture sites in northern Germany in 2016 and 2017. We used an eddy covariance energy balance (ECEB) set-up and a low-cost eddy covariance (EC-LC) set-up to measure actual ET over each AF and each MC system. We conducted direct eddy covariance (EC) measurement campaigns with approximately 4 weeks' duration for method validation. Results from the short-term measurement campaigns showed a high agreement between ETEC-LC and ETEC , indicated by slopes of a linear regression analysis between 0.86 and 1.3 (R2 between 0.7 and 0.94) across sites. Root mean square errors of LEEC-LC vs. LEEC (where LE is the latent heat flux) were half as small as LEECEB vs. LEEC , indicating a superior agreement of the EC-LC set-up with the EC set-up compared to the ECEB set-up. With respect to the annual sums of ET over AF and MC, we observed small differences between the two land uses. We interpret this as being an effect of compensating the small-scale differences in ET next to and in between the tree strips for ET measurements on the system scale. Most likely, the differences in ET rates next to and in between the tree strips are of the same order of magnitude, but of the opposite sign, and compensate each other throughout the year. Differences between annual sums of ET from the two methods were of the same order of magnitude as differences between the two land uses. Compared to the effect of land use and different methods on ET, we found larger mean evapotranspiration indices (∑ET/∑P) across sites for a drier than normal year (2016) compared to a wet year (2017). This indicates that we were able to detect differences in ET due to different ambient conditions with the applied methods, rather than the potentially small effect of AF on ET. We conclude that agroforestry has not resulted in an increased water loss to the atmosphere, indicating that agroforestry in Germany can be a land-use alternative to monoculture agriculture without trees. [ABSTRACT FROM AUTHOR]

For the assessment of evapotranspiration, near- surface airborne thermography offers new opportunities for studies with high numbers of spatial replicates and in a fine spatial resolution. We tested drone-based thermography and the subsequent application of three energy balance models (DATTUTDUT, TSEB-PT, DTD) using the widely accepted eddy covariance technique as a reference method. The study site was a mature oil palm plantation in lowland Sumatra, Indonesia. For the 61 flight missions, latent heat flux estimates of the DATTUTDUT model with measured net radiation agreed well with eddy covariance measurements (r2 = 0.85; MAE = 47; RMSE = 60) across variable weather conditions and daytimes. Confidence intervals for slope and intercept of a model II Deming regression suggest no difference between drone-based and eddy covariance method, thus indicating interchangeability. TSEB-PT and DTD yielded agreeable results, but all three models are sensitive to the configuration of the net radiation assessment. Overall, we conclude that drone-based thermography with energy-balance modeling is a reliable method complementing available methods for evapotranspiration studies. It offers promising, additional opportunities for fine grain and spatially explicit studies. [ABSTRACT FROM AUTHOR]

The 2015–2016 El Niño event ranks as one of the most severe on record in terms of the magnitude and extent of sea surface temperature (SST) anomalies generated in the tropical Pacific Ocean. Corresponding global impacts on the climate were expected to rival, or even surpass, those of the 1997–1998 severe El Niño event, which had SST anomalies that were similar in size. However, the 2015–2016 event failed to meet expectations for hydrologic change in many areas, including those expected to receive well above normal precipitation. To better understand how climate anomalies during an El Niño event impact soil moisture, we investigate changes in soil moisture in the humid tropics (between ±25 ∘) during the three most recent super El Niño events of 1982–1983, 1997–1998 and 2015–2016, using data from the Global Land Data Assimilation System (GLDAS). First, we use in situ soil moisture observations obtained from 16 sites across five continents to validate and bias-correct estimates from GLDAS (r2=0.54). Next, we apply a k -means cluster analysis to the soil moisture estimates during the El Niño mature phase, resulting in four groups of clustered data. The strongest and most consistent decreases in soil moisture occur in the Amazon basin and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. In addition, we compare changes in soil moisture to both precipitation and evapotranspiration, which showed a lack of agreement in the direction of change between these variables and soil moisture most prominently in the southern Amazon basin, the Sahel and mainland southeastern Asia. Our results can be used to improve estimates of spatiotemporal differences in El Niño impacts on soil moisture in tropical hydrology and ecosystem models at multiple scales. [ABSTRACT FROM AUTHOR]

The 2015-16 El Niño event ranks as one of the most severe on record in terms of the magnitude and extent of sea surface temperature (SST) anomalies generated in the tropical Pacific Ocean. Corresponding global impacts on the climate were expected to rival, or even surpass, those of the 1997-98 severe El Niño event, which had SST anomalies that were similar in size. However, the 2015-16 event failed to meet expectations for hydrologic change in many areas, including those expected to receive well above normal precipitation. To better understand how climate anomalies during an El Niño event impact soil moisture, we investigate changes in soil moisture in the humid tropics (between ±25°) during the three most recent super El Niño events of 1982-83, 1997-98, and 2015-16, using data from the Global Land Data Assimilation System (GLDAS). First, we validate the soil moisture estimates from GLDAS through comparison with in-situ observations obtained from 16 sites across five continents, showing an r² of 0.54. Next, we apply a k-means cluster analysis to the soil moisture estimates during the El Niño mature phase, resulting in four groups of clustered data. The strongest and most consistent decreases in soil moisture occur in the Amazon basin and maritime southeast Asia, while the most consistent increases occur over east Africa. In addition, we compare changes in soil moisture to both precipitation and evapotranspiration, which showed a lack of agreement in the direction of change between these variables and soil moisture most prominently in the southern Amazon basin, Sahel and mainland southeast Asia. Our results can be used to improve estimates of spatiotemporal differences in El Niño impacts on soil moisture in tropical hydrology and ecosystem models at multiple scales. [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) in 2015 was one of the strongest observed in almost 20 years and set the stage for a severe drought and the emergence of widespread fires and related smoke emission over large parts of Southeast Asia. In the tropical lowlands of Sumatra, which were heavily affected by the drought and haze, large areas of tropical rainforest have been converted into oil palm (Elaeis guineensis Jacq.) plantations during the past decades. In this study, we investigate the impact of drought and smoke haze on the net ecosystem CO2 exchange, evapotranspiration, yield and surface energy budget in a commercial oil palm plantation in Jambi province (Sumatra, Indonesia) by using micrometeorological measurements, the eddy covariance method, yield data and a multiple linear regression model (MLRM). With the MLRM we identify the contribution of meteorological and environmental parameters to the net ecosystem CO2 exchange. During the initial part of the drought, when incoming shortwave radiation was elevated, net CO2 uptake increased by 50 % despite a decrease in upper-layer soil moisture by 35 %, an increase in air temperature by 10 % and a tripling of atmospheric vapour pressure deficit. Emerging smoke haze decreased incoming solar radiation by 35 % compared to non-drought conditions and diffuse radiation almost became the sole shortwave radiation flux for 2 months, resulting in a strong decrease in net CO2 uptake by 86 %. Haze conditions resulted in a complete pause of oil palm net carbon accumulation for about 1.5 months and contributed to a decline in oil palm yield by 35 %. With respect to a projected pronounced drying trend over the western Pacific during a future El Niño, our model showed that an increase in drought may stimulate net CO2 uptake, while more severe smoke haze, in combination with drought, can lead to pronounced losses in productivity and net CO2 uptake, highlighting the importance of fire prevention. [ABSTRACT FROM AUTHOR]

The El Niño-Southern Oscillation (ENSO) in 2015 was one of the strongest observed in almost 20 years and set the stage for a severe drought and the emergence of widespread fires and related smoke emission over large parts of Southeast Asia. In the tropical lowlands of Sumatra, which were heavily affected by the drought and haze, large areas of tropical rainforest have been converted into oil palm (Elaeis guineensis Jacq.) plantations during the past decades. In this study, we investigate the impact of drought and smoke haze on the CO2 exchange, evapotranspiration and surface energy budget in a commercial oil palm plantation in Jambi province (Sumatra, Indonesia) by using micrometeorological measurements, the eddy covariance method and a multi linear regression model (MLRM). With the MLRM we identify the contribution of meteorological and environmental parameters to net ecosystem CO2 exchange. During the initial part of the drought, when incoming shortwave radiation was elevated, CO2 uptake increased by 50 % despite a decrease in upper-layer soil moisture by 35 %, an increase in air temperature by 10% and a tripling of atmospheric vapor pressure deficit. Emerging smoke haze decreased incoming solar radiation by 35% compared to non-drought conditions and diffuse radiation became almost the sole shortwave radiation flux for two months resulting in a strong decrease in CO2 uptake by 86 %. Haze conditions resulted in a complete pause of oil palm carbon uptake for about 1.5 months and contributed to a decline in oil palm yield by 35 %. With respect to climate change and a pronounced drying trend over the western Pacific during El Niño, our model showed that an increase in drought may stimulate CO2 uptake while more severe smoke haze, in combination with drought, can lead to pronounced losses in productivity and CO2 uptake highlighting the importance of fire prevention. [ABSTRACT FROM AUTHOR]

Land-use change has a strong impact on carbon, energy and water fluxes and its effect is particularly pronounced in tropical regions. Uncertainties exist in the prediction of future land-use change impacts on these fluxes by land surface models due to scarcity of suitable measured data for parametrization and poor representation of key biogeochemical processes associated with tropical vegetation types. Rubber plantations (Havea brasilliensis) are a crucial land-use type across tropical landscapes that has greatly expanded in recent decades. Here, we first synthesize the relevant data for describing the biogeochemical processes of rubber from our past measurement campaigns in Jambi province, Indonesia. We then use these data-sets to develop a rubber plant functional type (PFT) for the Community Land Model (CLM4.5). Field measured data from small-holder plantations on leaf litterfall, soil respiration, latex harvest, leaf area index, transpiration, net primary productivity, and above-ground and fine root biomass were used to develop and calibrate a new PFT-based model (CLM4.5-rubber). CLM-rubber predictions adequately captured the annual net primary productivity and above-ground biomass as well as the seasonal dynamics of leaf litterfall, soil respiration, soil moisture and leaf area index. All of the predicted water fluxes of CLM-rubber were very similar to a site-specific calibrated soil water model. Including temporal variations in leaf life span enabled CLM-rubber to better capture the seasonality of leaf litterfall. Increased sensitivity of stomata to soil water stress and the enhancement of growth and maintenance respiration of fine roots in response to soil nutrient limitation enabled CLM-rubber to capture the magnitude of transpiration and leaf area index. Since CLM-rubber predicted reasonably well the carbon and water use, we think that the current model can be used for larger-scale simulations within Jambi province because more than 99% of the rubber plantations are smallholder owned in Jambi province and have low soil fertility. [ABSTRACT FROM AUTHOR]

Extreme climatic events, such as droughts and heat stress, induce anomalies in ecosystem--atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and Reco within and between ecosystems remain poorly predicted. Here we aim to identify the major factors controlling the amplitude of extreme-event impacts on GPP, Reco, and the resulting net ecosystem production (NEP). We focus on the impacts of heat and drought and their combination. We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30-year time period. We then used FLUXNET eddy covariance flux measurements to estimate the CO2 flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they downregulated GPP, resulting in a moderate reduction in the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on both GPP and Reco and, hence, often resulted in neutral NEP responses. The combination of drought and heat typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of Reco over time turned from an initial increase to a downregulation after about 2 weeks. This confirms earlier theories that not only the magnitude but also the duration of an extreme event determines its impact. Our study corroborates the results of several local sitelevel case studies but as a novelty generalizes these findings on the global scale. Specifically, we find that the different response functions of the two antipodal land--atmosphere fluxes GPP and Reco can also result in increasing NEP during certain extreme conditions. Apparently counterintuitive findings of this kind bear great potential for scrutinizing the mechanisms implemented in state-of-the-art terrestrial biosphere models and provide a benchmark for future model development and testing. [ABSTRACT FROM AUTHOR]

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a highresolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1±2.6 °C (mean±SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change. [ABSTRACT FROM AUTHOR]

Extreme climatic events, such as droughts and heat stress induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and Reco within and between ecosystems remain poorly predicted. Here we aim to identify the major factors controlling the amplitude of extreme event impacts on GPP, Reco, and the resulting net ecosystem production (NEP). We focus on the impacts of heat and drought and their combination. We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30 year time period. We then used FLUXNET eddy-covariance flux measurements to estimate the CO2 flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they down-regulated GPP, resulting in a moderate reduction of the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on both GPP and Reco, and, hence, often resulted in neutral NEP responses. The combination of drought and heat typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of Reco over time turned from an initial increase to a down-regulation after about two weeks. This confirms earlier theories that not only the magnitude but also the duration of an extreme event determines its impact. Our study corroborates the results of several local site-level case studies, but as a novelty generalizes these findings at the global scale. Specifically, we find that the different response functions of the two antipodal land-atmosphere fluxes GPP and Reco can also result in increasing NEP during certain extreme conditions. Apparently counterintuitive findings of this kind bear great potential for scrutinizing the mechanisms implemented in state-of-the-art terrestrial biosphere models and provide a benchmark for future model development and testing. [ABSTRACT FROM AUTHOR]

Indonesia is currently one of the regions with the highest transformation rate of the land surface worldwide due to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impact of land transformation in Indonesia on LST. We analyse LST from the thermal band of a Landsat image and produce a high resolution surface temperature map (30 m) for the lowlands of the Jambi province on Sumatra (Indonesia), a region of large land transformation towards oil palm and other cash crops over the past decades. We compare LST, albedo, Normalized Differenced Vegetation Index (NDVI), and evapotranspiration (ET) of seven different land cover types (forest, urban areas, clear cut land, young and mature oil palm plantations, acacia and rubber plantations) and show that forests have lower surface temperatures than these land cover types indicating a local warming effect after forest conversion with LST differences up to 10.09 ± 2.6 °C (mean ± SD) between forest and clear cut land. The differences in surface temperatures are explained by an evaporative cooling effect offsetting an albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature of the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceed the effects of climate warming. Our study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase in air temperature due to climate change. [ABSTRACT FROM AUTHOR]

We used the recently developed Delta Ray Isotope Ratio Infrared Spectrometer (IRIS) to continuously measure the CO2 concentration c and its isotopic composition δ13C and δ18O in a managed beech forest in Central Germany. Our objectives are (a) to characterize the Delta Ray IRIS and its performance under field conditions and (b) to quantify the seasonal variability of c, δ13C, δ18O and the isotopic composition of CO2 exchange (Reco13C and Reco18O) derived from nighttime Keeling-Plot intercepts. The minimal Allan deviation (as a measure of precision) was below 0.01ppm for the CO2 concentration and below 0.03‰ for both delta values. For repeated measurements of a target gas, the long-term standard deviation from the mean value was 0.2ppm for c and below 0.3‰ for both delta values. The accuracy based on our calibration setup was approximately 0.45ppm for c, 0.1‰ for δ13C and 0.6‰ for delta 18O. We used measurements of nine different inlet heights in the beech forest, to evaluate the isotopic compositions of respiration Reco13C and Reco18O in a three months measurement campaign in autumn 2015. During this period, an early snow and frost event occurred, coinciding with a change in the observed characteristics of both Reco13C and Reco18O. Before the first snow, R_eco 13C correlated significantly (Pearson correlation coefficient rpear=0.55 and corresponding critical value rcrit≈0.38 for α=0.005) with time-lagged net radiation Rn, a driver of photosynthesis and photosynthetic discrimination against 13C. This correlation became insignificant after the first snow. For 18O, we measured a decrease of 30‰ within 10 days in Reco18O after the snow event potentially reflecting the influence of 18O depleted snow on soil moisture. This decrease was ten times larger than the corresponding decrease in delta 18O in ambient CO2 (below 3‰) and took three times longer to recover (three weeks vs. one week). In summary, we conclude that 1) the new Delta Ray IRIS with its internal calibration procedure provides an opportunity to precisely and accurately measure c, delta 13C and delta 18O at field sites and 2) even short snow or frost events could have strong effects on the isotopic composition of CO2 exchange at ecosystem scale. [ABSTRACT FROM AUTHOR]

Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multilayer energy budget in the ORCHIDEE-CAN v1.0 land surface model (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad-leaved and evergreen needle-leaved forest with a maximum leaf area index (LAI; all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes - namely the diffusion, advection, and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence, and resistance modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature, and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although the multi-layer model simulation results showed few or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem. [ABSTRACT FROM AUTHOR]

Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multi-layer energy budget in the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad leaved and evergreen needle leaved forest with a maximum LAI (all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes - namely the diffusion, advection and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence and resistances modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although, the multi-layer model simulation results showed little or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compounds (BVOC) emissions from the terrestrial ecosystem. [ABSTRACT FROM AUTHOR]

Changes in land-use and climate can contribute to important CO2 emissions from soil to the atmosphere. In such scenarios, models are necessary to predict future changes, to extrapolate results to larger areas as well as to explore and understand underlying mechanisms. Many drivers of ecosystem dynamics play a role in tropical regions, including deforestation, land use intensification, increasing concentrations of atmospheric CO2 and possible changes in temperature and precipitation. Our study aims to simulate changes in soil C associated with transitions from the natural forest vegetation to oil palm plantations as observed in the Jambi region of Sumatra, Indonesia. For this we modeled the vegetation and soil C using the Community Land Model (CLM 4.5) and changed the model parameter values to better fit the model to the observations.Two aspects were necessary to obtain realistic model outcomes: properly simulating the state of the natural forest vegetation and capturing the dynamics after land use change. Parameter adjustments were made in order to approximate simulations to observed forest productivity, biomass, soil respiration and soil C stocks. Forest disturbance through selective logging also was a factor that needed to be accounted for. Oil palm growth was simulated using a PFT recently developed and calibrated for the same site. Finally, the simulation of soil carbon stocks and soil respiration was improved by adjusting model parameters controlling the turnover time of soil C pools. When using the default parameter values, the model underestimated total soil organic carbon and overestimated soil respiration of both forest and oil palm. The simulated forest carbon stocks increased after model calibration, showing a better agreement with observations (from an average of 6.3 kg C m-2 to 23 kg C m-2; compared to the observed value of 24 kg C m-2). Simulated soil respiration decreased, also approaching observed values and lowering the model RMSE from 20.2 to 16.3 mg C m-2 hour-1. For oil palm, model calibration improved the simulation of soil C stocks (from 5.5 kg C m-2 to 13 kg C m-2, observed value18 kg C m-2) as well as soil respiration (RMSE lowered from 12.5 to 11 mg C m-2 hour-1).Once the model is fully calibrated, we will be able to estimate the long term effects of land use change and compare them to those of CO2 fertilization. We will also be able to estimate the regional short and long term impact of land use on soil C stocks and fluxes. [ABSTRACT FROM AUTHOR]