Plant water storage is fundamental to the functioning of terrestrial ecosystems by participating in plant metabolism, nutrient and sugar transport, and maintenance of the integrity of the hydraulic ...system of the plant. However, a global view of the size and dynamics of the water pools stored in plant tissues is still lacking. Here, we report global patterns of seasonal variations in ecosystem-scale plant water storage and their relationship with leaf phenology, based on space-borne measurements of L-band vegetation optical depth. We find that seasonal variations in plant water storage are highly synchronous with leaf phenology for the boreal and temperate forests, but asynchronous for the tropical woodlands, where the seasonal development of plant water storage lags behind leaf area by up to 180 days. Contrasting patterns of the time lag between plant water storage and terrestrial groundwater storage are also evident in these ecosystems. A comparison of the water cycle components in seasonally dry tropical woodlands highlights the buffering effect of plant water storage on the seasonal dynamics of water supply and demand. Our results offer insights into ecosystem-scale plant water relations globally and provide a basis for an improved parameterization of eco-hydrological and Earth system models.
Carbonyl sulphide (COS) is a potential tracer of gross primary productivity (GPP), assuming a unidirectional COS flux into the vegetation that scales with GPP. However, carbonic anhydrase (CA), the ...enzyme that hydrolyses COS, is expected to be light independent, and thus plants without stomata should continue to take up COS in the dark.
We measured net CO2 (A
C) and COS (A
S) uptake rates from two astomatous bryophytes at different relative water contents (RWCs), COS concentrations, temperatures and light intensities.
We found large A
S in the dark, indicating that CA activity continues without photosynthesis. More surprisingly, we found a nonzero COS compensation point in light and dark conditions, indicating a temperature-driven COS source with a Q
10 (fractional change for a 10°C temperature increase) of 3.7. This resulted in greater A
S in the dark than in the light at similar RWC. The processes underlying such COS emissions remain unknown.
Our results suggest that ecosystems dominated by bryophytes might be strong atmospheric sinks of COS at night and weaker sinks or even sources of COS during daytime. Biotic COS production in bryophytes could result from symbiotic fungal and bacterial partners that could also be found on vascular plants.
The oxygen isotope composition (δ18O) of atmospheric CO2 is among a very limited number of tools available to constrain estimates of the biospheric gross CO2 fluxes, photosynthesis and respiration at ...large scales. However, the accuracy of the partitioning strongly depends on the extent of isotopic disequilibrium between the signals carried by these two gross fluxes. Chamber‐based field measurements of total CO2 and CO18O fluxes from foliage and soil can help evaluate and refine our models of isotopic fractionation by plants and soils and validate the extent and pattern of isotopic disequilibrium within terrestrial ecosystems. Owing to sampling limitations in the past, such measurements have been very rare and covered only a few days. In this study, we coupled automated branch and soil chambers with tuneable diode laser absorption spectroscopy techniques to continuously capture the δ18O signals of foliage and soil CO2 exchange in a Pinus pinaster Aït forest in France. Over the growing season, we observed a seasonally persistent isotopic disequilibrium between the δ18O signatures of net CO2 fluxes from leaves and soils, except during rain events when the isotopic imbalance became temporarily weaker. Variations in the δ18O of CO2 exchanged between leaves, soil and the atmosphere were well explained by theory describing changes in the oxygen isotope composition of ecosystem water pools in response to changes in leaf transpiration and soil evaporation.
The contribution of photosynthesis and soil respiration to net land–atmosphere carbon dioxide (CO2) exchange can be estimated based on the differential influence of leaves and soils on budgets of the ...oxygen isotope composition (δ18O) of atmospheric CO2. To do so, the activity of carbonic anhydrases (CAs), a group of enzymes that catalyse the hydration of CO2 in soils and plants, needs to be understood. Measurements of soil CA activity typically involve the inversion of models describing the δ18O of CO2 fluxes to solve for the apparent, potentially catalysed, rate of CO2 hydration. This requires information about the δ18O of CO2 in isotopic equilibrium with soil water, typically obtained from destructive, depth-resolved sampling and extraction of soil water. In doing so, an assumption is made about the soil water pool that CO2 interacts with, which may bias estimates of CA activity if incorrect. Furthermore, this can represent a significant challenge in data collection given the potential for spatial and temporal variability in the δ18O of soil water and limited a priori information with respect to the appropriate sampling resolution and depth. We investigated whether we could circumvent this requirement by inferring the rate of CO2 hydration and the δ18O of soil water from the relationship between the δ18O of CO2 fluxes and the δ18O of CO2 at the soil surface measured at different ambient CO2 conditions. This approach was tested through laboratory incubations of air-dried soils that were re-wetted with three waters of different δ18O. Gas exchange measurements were made on these soils to estimate the rate of hydration and the δ18O of soil water, followed by soil water extraction to allow for comparison. Estimated rates of CO2 hydration were 6.8–14.6 times greater than the theoretical uncatalysed rate of hydration, indicating that CA were active in these soils. Importantly, these estimates were not significantly different among water treatments, suggesting that this represents a robust approach to assay the activity of CA in soil. As expected, estimates of the δ18O of the soil water that equilibrates with CO2 varied in response to alteration to the δ18O of soil water. However, these estimates were consistently more negative than the composition of the soil water extracted by cryogenic vacuum distillation at the end of the gas measurements with differences of up to −3.94 ‰ VSMOW–SLAP. These offsets suggest that, at least at lower water contents, CO2–H2O isotope equilibration primarily occurs with water pools that are bound to particle surfaces and are depleted in 18O compared to bulk soil water.
We described advection and diffusion of water isotopologues in leaves in the non-steady state, applied specifically to amphistomatous leaves. This explains the isotopic enrichment of leaf water from ...the xylem to the mesophyll, and we showed how it relates to earlier models of leaf water enrichment in non-steady state. The effective length or tortuosity factor of isotopologue movement in leaves is unknown and, therefore, is a fitted parameter in the model. We compared the advection-diffusion model to previously published data sets for Lupinus angustifolius and Eucalyptus globulus. Night-time stomatal conductance was not measured in either data set and is therefore another fitted parameter. The model compared very well with the observations of bulk mesophyll water during the whole diel cycle. It compared well with the enrichment at the evaporative sites during the day but showed some deviations at night for E. globulus. It became clear from our analysis that night-time stomatal conductance should be measured in the future and that the temperature dependence of the tracer diffusivities should be accounted for. However, varying mesophyll water volume did not seem critical for obtaining a good prediction of leaf water enrichment, at least in our data sets. In addition, observations of single diurnal cycles do not seem to constrain the effective length that relates to the tortuosity of the water path in the mesophyll. Finally, we showed when simpler models of leaf water enrichment were suitable for applications of leaf water isotopes once weighted with the appropriate gas exchange flux. We showed that taking an unsuitable leaf water enrichment model could lead to large biases when cumulated over only 1 day.
Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source-sink ...patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model-data comparison. Flux measurements made over four vegetation types were used to calibrate the land-surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land-surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite-measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982-1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of -1.2 Pg C yr⁻¹ for 1982-1995 is compatible with the PEM- and DGVM-predicted trends in NPP. There is, thus, a convergence in understanding derived from process-based models, remote-sensing-based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night-time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land-atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.
Forest canopies buffer macroclimatic temperature fluctuations. However, we do not know if and how the capacity of canopies to buffer understorey temperature will change with accelerating climate ...change. Here we map the difference (offset) between temperatures inside and outside forests in the recent past and project these into the future in boreal, temperate and tropical forests. Using linear mixed-effect models, we combined a global database of 714 paired time series of temperatures (mean, minimum and maximum) measured inside forests vs. in nearby open habitats with maps of macroclimate, topography and forest cover to hindcast past (1970–2000) and to project future (2060–2080) temperature differences between free-air temperatures and sub-canopy microclimates. For all tested future climate scenarios, we project that the difference between maximum temperatures inside and outside forests across the globe will increase (i.e. result in stronger cooling in forests), on average during 2060–2080, by 0.27 ± 0.16 °C (RCP2.6) and 0.60 ± 0.14 °C (RCP8.5) due to macroclimate changes. This suggests that extremely hot temperatures under forest canopies will, on average, warm less than outside forests as macroclimate warms. This knowledge is of utmost importance as it suggests that forest microclimates will warm at a slower rate than non-forested areas, assuming that forest cover is maintained. Species adapted to colder growing conditions may thus find shelter and survive longer than anticipated at a given forest site. This highlights the potential role of forests as a whole as microrefugia for biodiversity under future climate change.
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•Temperature differences inside vs. outside forests were mapped across the globe.•Forest canopies buffer minimum (Tmin), mean (Tmean) and maximum (Tmax) temperatures.•In the future, buffering for Tmean and Tmax may increase, but may decrease for Tmin.•Refugial capacity of forests might last longer than anticipated in a warming world.
Plant transpiration (T), biologically controlled movement of water from soil to atmosphere, currently lacks sufficient estimates in space and time to characterize global ecohydrology. Here we ...describe the Transpiration Estimation Algorithm (TEA), which uses both the signals of gross primary productivity and evapotranspiration (ET) to estimate temporal patterns of water use efficiency (WUE, i.e., the ratio between gross primary productivity and T) from which T is calculated. The method first isolates periods when T is most likely to dominate ET. Then, a Random Forest Regressor is trained on WUE within the filtered periods and can thus estimate WUE and T at every time step. Performance of the method is validated using terrestrial biosphere model output as synthetic flux data sets, that is, flux data where WUE dynamics are encoded in the model structure and T is known. TEA reproduced temporal patterns of T with modeling efficiencies above 0.8 for all three models: JSBACH, MuSICA, and CASTANEA. Algorithm output is robust to data set noise but shows some sensitivity to sites and model structures with relatively constant evaporation levels, overestimating values of T while still capturing temporal patterns. The ability to capture between‐site variability in the fraction of T to total ET varied by model, with root‐mean‐square error values between algorithm predicted and modeled T/ET ranging from 3% to 15% depending on the model. TEA provides a widely applicable method for estimating WUE while requiring minimal data and/or knowledge on physiology which can complement and inform the current understanding of underlying processes.
Plain Language Summary
While it is widely known that plants need water to survive, exactly how much water plants in an ecosystem use is hard to quantify. However, many places have been measuring how much total water leaves an ecosystem, both the water plants use directly and the water that simply evaporates from the soil or the surfaces of leaves, using eddy covariance towers. These eddy covariance towers also measure the coming and going of carbon, such as the total amount of carbon taken up by photosynthesis. Here we present the idea that by using the signals from both photosynthesis and total water losses together, we can capture the water signal related to plants, namely, transpiration, using an algorithm called Transpiration Estimation Algorithm (TEA). To verify that TEA is working the way we expect, we test it out using artificial ecosystem simulations where transpiration and photosynthesis come from mathematical models. By thoroughly testing TEA, we have a better idea of how it will work in a real world situation, hopefully opening the door for a better understanding on how much water ecosystems are using and how it might affect our changing planet.
Key Points
TEA is a method for extracting water use efficiency (WUE) dynamics from flux data with minimal assumptions
Validation shows that TEA is able to derive patterns of WUE and transpiration from three different models
Method is applicable to eddy covariance data sets, opening the door to wide‐scale transpiration estimates
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