Fernando Esteban Moyano

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 mol of O2 consumed per mole of CO2 produced. Due to the technical challenges in measuring directly the ER of entire terrestrial ecosystems (EReco), little is known about variations in ER at hourly and seasonal scales, as well as how different ecosystem and flux components (e.g., vegetation and soil, assimilation and respiration) contribute to EReco. In this modeling study, we explored the variability in and drivers of EReco and evaluated the hypothetical uncertainty in determining ecosystem O2 fluxes based on current instrument precision used in micrometeorological methods such as the flux-gradient approach. We updated the one-dimensional, multilayer atmosphere–biosphere gas exchange model “CANVEG” by 1) implementing ER for various ecosystem components in the model; 2) implementing the control of triose phosphate utilization (TPU) and Medlyn’s stomatal conductance equation to CO2 assimilation; and 3) linking photosynthetic O2 emission to nitrogen (N) assimilation sources. The model study was conducted at the Leinefelde FLUXNET site, a temperate beech forest in Germany, where eddy covariance, profile, and gas exchange chamber measurements were available.We found that when assuming fixed ER for CO2 assimilation and respiration, the hourly EReco showed strong variations over diel and seasonal cycles and within the vertical canopy profile, indicating the potential to partition eddy-covariance derived CO2 fluxes with corresponding O2 flux measurements. The O2 and CO2 mole fraction ratio of canopy air (ERconc) showed different values and mechanisms from EReco. The model showed more robust performances in future CO2, temperature and air humidity conditions when taking into account TPU limitation and Medlyn’s stomatal conductance algorithm in CO2 assimilation processes. The predicted net carbon sink under elevated atmospheric CO2 mole fraction increased less with TPU limitation than without. The most significant impacts on photosynthetic O2 emission and hence the ER of CO2 assimilation resulted from variation in nitrogen assimilation sources. The ER of net assimilation measured with branch-level gas exchange chambers showed little variation from 1.0 mol mol-1, indicating ammonia as the main N assimilation source. The model indicated that the O2 emission would increase by up to 23% if nitrate was used as N assimilation source.Our study successfully coupled oxygen with carbon fluxes within a multilayer atmosphere–biosphere gas exchange model. The modeling study yielded that the application of the flux-gradient measurement approach is feasible to derive ecosystem O2 fluxes. To achieve better model behavior, it is necessary to incorporate TPU limitation in the assimilation model and to properly consider N assimilation during photosynthesis.

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 mol of O₂ consumed per mole of CO₂ 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 O₂ 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 O₂ and CO₂ 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 O₂ and CO₂ 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 O₂ fluxes could be derived with the flux-gradient method using measured vertical gradients in scalar properties, as well as fluxes of CO₂, sensible heat and latent energy derived from eddy covariance measurements. 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 high-accuracy 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 ER_eco 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 to partition net CO₂ fluxes into their component fluxes, but further improvement in instrument precision is needed.

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 (ER_eco), little is known about the variations in ER at the hourly and seasonal scales as well as how different components contribute to ER_eco. In this modeling study, we explore the variability and drivers of ER_eco and evaluate the hypothetical uncertainty in determining ecosystem O₂ fluxes based on current instrument precision. We adapted the one-dimensional, multi-layer atmosphere-biosphere gas exchange model, CANVEG, to simulate hourly ER_eco from modeled O₂ and CO₂ fluxes in a temperate beech forest in Germany. We found that the annual mean ER_eco ranged from 1.06 to 1.12 mol mol^-1 within the five years’ study period. Hourly ER_eco 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 (ER_conc) 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 high-accuracy 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 ER_eco 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.

Wind erosion is seen as one of the main risks for modern agriculture in dry and sandy regions. Shelterbelts and agroforestry systems are known for their ability to reduce wind speed and, consequently, wind erosion. The current study considers temperate alley cropping agroforestry systems, where multiple tree strips (shelterbelts) are interleaved with either annual rotating crops or perennial grassland. The aim was to quantify the potential wind erosion reduction by alley cropping agroforestry systems and the effect of design decisions for a case study in Germany. By combining wind measurements and Large Eddy Simulations, the wind speed and potential wind erosion inside an agroforestry system were estimated. Our model simulations result in an average reduction in wind speed between 17% and 67%, and a reduction of average potential wind erosion between 24% and 97%. The most optimal reduction of the average potential wind erosion was larger than 92% for tree strips orientated perpendicular to the main wind direction, whereas for a diagonal orientation of the tree strips to the main wind direction we found an average reduction of 86%. Parallel orientated tree strips reduce wind erosion on average by less than 35%. Tree strips planted with ≤48 m distance provide a strong and constant reduction of wind erosion, even for tree strips of 2 m height the average reduction was 86%, when the tree strips were orientated optimal to the dominant wind direction. Our model simulations showed that alley cropping agroforestry systems in a temperate climate have a large potential to reduce wind erosion by more than 80% when the system is well-designed and managed.

Rubber plantations are an economically viable land-use type that occupies large swathes of land in Southeast Asia that have undergone conversion from native forest to intensive plantation forestry. Such land-use change has a strong impact on carbon, energy, and water fluxes in ecosystems, and uncertainties exist in the modeling of future land-use change impacts on these fluxes due to the scarcity of measured data and poor representation of key biogeochemical processes. In this current modeling effort, we utilized the Community Land Model Version 5 (CLM5) to simulate a rubber plant functional type (PFT) by comparing the baseline parameter values of tropical evergreen PFT and tropical deciduous PFT with a newly developed rubber PFT (focused on the parameterization and modification of phenology and allocation processes) based on site-level observations of a rubber clone in Indonesia. We found that the baseline tropical evergreen and baseline tropical deciduous functions and parameterizations in CLM5 poorly simulate the leaf area index, carbon dynamics, and water fluxes of rubber plantations. The newly developed rubber PFT and parametrizations (CLM-rubber) showed that daylength could be used as a universal trigger for defoliation and refoliation of rubber plantations. CLM-rubber was able to predict seasonal patterns of latex yield reasonably well, despite highly variable tapping periods across Southeast Asia. Further, model comparisons indicated that CLM-rubber can simulate carbon and energy fluxes similar to the existing rubber model simulations available in the literature. Our modeling results indicate that CLM-rubber can be applied in Southeast Asia to examine variations in carbon and water fluxes for rubber plantations and assess how rubber-related land-use changes in the tropics feedback to climate through carbon and water cycling.

Rainforest conversion to woody croplands impacts the carbon cycle via ecophysiological processes such as photosynthesis and autotrophic respiration. Changes in the carbon cycle associated with land-use change can be estimated through Land Surface Models (LSMs). The accuracy of carbon flux estimation in carbon fluxes associated with land-use change has been attributed to uncertainties in the model parameters affecting photosynthetic activity, which is a function of both carboxylation capacity (V_cmax) and electron transport capacity (J_max). In order to reduce such uncertainties for common tropical woody crops and trees, in this study we measured V_cmax25 (V_cmax standardized to 25 °C), J_max25 (J_max standardized to 25 °C) and light-saturated photosynthetic capacity (A_max) of Elaeis guineensis Jacq. (oil palm), Hevea brasiliensis (rubber tree), and two native tree species, Eusideroxylon zwageri and Alstonia scholaris, in a converted landscape in Jambi province (Sumatra, Indonesia) at smallholder plantations. We considered three plantations; a monoculture rubber, a monoculture oil palm, and an agroforestry system (jungle rubber plantation), where rubber trees coexist with some native trees. We performed measurements on leaves at the lower part of the canopy, and used a scaling method based on exponential function to scale up photosynthetic capacity related traits to the top of the canopy. At the lower part of the canopy, we found (i) high V_cmax25 values for H. brasiliensis from monoculture rubber plantation and jungle rubber plantation that was linked to a high area-based leaf nitrogen content, and (ii) low value of A_max for E. guineensis from oil palm plantation that was due to a low value of V_cmax25 and a high value of dark respiration. At the top of the canopy, A_max varied much more than V_cmax25 among different land-use types. We found that photosynthetic capacity declined fastest from the top to the lower part of the canopy in oil palm plantations. We demonstrate that photosynthetic capacity related traits measured at the lower part of the canopy can be successfully scaled up to the top of the canopy. We thus provide helpful new data that can be used to constrain LSMs that simulate land-use change related to rubber and oil palm expansion.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature–ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature–ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.

Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate‐change studies. It is imperative to increase confidence in long‐term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process‐based C models by comparing simulations to experimental data from seven long‐term bare‐fallow (vegetation‐free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi‐year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge‐based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin‐up initialization of SOC. Changes in the multi‐model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (±15.5) Mg C/ha compared to the observed mean of 36.0 (±19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 ± 16.7 Mg C/ha) and Spe (36.8 ± 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long‐term average thermal conditions at coarse spatial resolutions only. Hence, many climate‐forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold‐air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free‐air temperatures, microclimatic ground and near‐surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near‐surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

The conventional soil organic matter (SOM) decay paradigm considers SOM quality as the dominant decay limitation, and it is modelled with simple first-order decay kinetics. This view and modelling approach is criticized for being too simplistic and unreliable for predictive purposes. It is still under debate if first-order models can correctly capture the variability in temporal SOM decay observed between different environments. The hypothesis needs to be tested statistically, but this implies the use of a dynamic model with multiple degrees of freedom to describe the observations. Since we want to test the general validity of the SOC decay theory the test must also include multiple sites, and rises the problem of how to describe the unavoidable local variability. This defines a multivariate space where the hypothesis must be tested which, considering also the known problem of an equifinality “by design” in biogeochemical models, generate difficulties.To address this issue, we calibrated a first-order model (Q) on six long-term bare fallow field experiments across Europe within a Bayesian framework assuming some general and some local parameters. Following conventional SOM decay theory, we assumed that parameters directly describing SOC decay (rate of SOM quality change and decomposer metabolism) are thermodynamically constrained, therefore valid for all sites. Initial litter input quality and edaphic interactions (both local by definition) and microbial efficiency (possibly affected by nutrient stoichiometry) were instead assumed to be site-specific. Initial litter input quality explained most observed kinetics variability, and the model predicted a convergence toward a common kinetics over time, while site-specific variables played no detectable role. All these characteristics could be represented with posterior probability distributions and their comparison provided the hypothesis testing.According to our analysis the decay of decades-old SOM seemed mostly influenced by OM chemistry and was well described by first order kinetics and a single set of general kinetics parameters.