Danilo Dragoni

Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise

Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata—small pores on the leaf surface that regulate gas exchange—to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation–climate models.

Redefinition and global estimation of basal ecosystem respiration rate

Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from similar to 3 degrees S to similar to 70 degrees N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr (-1), with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.

Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when. global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and environmental constraints on E. It uses remotely sensed leaf area index (L-ai) and surface meteorological data to estimate E by: 1) introducing a simple biophysical model for canopy conductance (G(c)), defined as a constant maximum stomatal conductance g(smax) of 12.2 mm s(-1) multiplied by air relative humidity (R-h) and L-ai (G(c) = g(srnax) x R-h X L-ai); 2) calculating canopy transpiration with the G(c)-based Penman-Monteith (PM) E model; 3) calculating soil evaporation from an air-relative-humidity-based model of evapotranspiration (Yan & Shugart, 2010); 4) calculating total E (E-0) as the sum of the canopy transpiration and soil evaporation, assuming the absence of soil water stress; and 5) correcting E-0 for soil water stress using a soil water balance model. This physiological ARTS E model requires no calibration. Evaluation against eddy covariance measurements at 19 flux sites, representing a wide variety of climate and vegetation types, indicates that daily estimated E had a root mean square error = 0.77 mm d(-1). bias = -0.14 mm d(-1), and coefficient of determination, R-2 = 0.69. Global, monthly, 0.5 degrees-gridded ARTS E simulations from 1984 to 1998, which were forced using Advanced Very High Resolution Radiometer Lai data, Climate Research Unit climate data, and surface radiation budget data, predicted a mean annual land E of 58.4 x 10(3) km(3). This falls within the range (58 x 10(3)-85 x 10(3) km(3)) estimated by the Second Global Soil Wetness Project (GSWP-2: Dirmeyer et al., 2006). The ARTS E spatial pattern agrees well with that of the global E estimated by GSWP-2. The global annual ARTS E increased by 15.5 mm per decade from 1984 to 1998, comparable to an increase of 9.9 mm per decade from the model tree ensemble approach (Jung et al., 2010). These comparisons confirm the effectivity of the ARTS E model to simulate the spatial. pattern and climate response of global E. This model is the first of its kind among remote-sensing-based PM E models to provide global land E estimation with consideration of the soil water balance

On the calibration of continuous, high‐precision δ18O and δ2H measurements using an off‐axis integrated cavity output spectrometer

The (18)O and (2)H of water vapor serve as powerful tracers of hydrological processes. The typical method for determining water vapor delta(18)O and delta(2)H involves cryogenic trapping and isotope ratio mass spectrometry. Even with recent technical advances, these methods cannot resolve vapor composition at high temporal resolutions. In recent years, a few groups have developed continuous laser absorption spectroscopy (LAS) approaches for measuring delta(18)O and delta(2)H which achieve accuracy levels similar to those of lab-based mass spectrometry methods. Unfortunately, most LAS systems need cryogenic cooling and constant calibration to a reference gas, and have substantial power requirements, making them unsuitable for long-term field deployment at remote field sites. A new method called Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) has been developed which requires extremely low-energy consumption and neither reference gas nor cryogenic cooling. In this report, we develop a relatively simple pumping system coupled to a dew point generator to calibrate an ICOS-based instrument (Los Gatos Research Water Vapor Isotope Analyzer (WVIA) DLT-100) under various pressures using liquid water with known isotopic signatures. Results show that the WVIA can be successfully calibrated using this customized system for different pressure settings, which ensure that this instrument can be combined with other gas-sampling systems. The precisions of this instrument and the associated calibration method can reach approximately 0.08 per thousand for delta(18)O and approximately 0.4 per thousand for delta(2)H. Compared with conventional mass spectrometry and other LAS-based methods, the OA-ICOS technique provides a promising alternative tool for continuous water vapor isotopic measurements in field deployments.

Mycorrhizal type determines the magnitude and direction of root‐induced changes in decomposition in a temperate forest

Although it is increasingly being recognized that roots play a key role in soil carbon (C) dynamics, the magnitude and direction of these effects are unknown. Roots can accelerate soil C losses by provisioning microbes with energy to decompose organic matter or impede soil C losses by enhancing microbial competition for nutrients. We experimentally reduced belowground C supply to soils via tree girdling, and contrasted responses in control and girdled plots for three consecutive growing seasons. We hypothesized that decreases in belowground C supply would have stronger effects in plots dominated by ectomycorrhizal (ECM) trees rather than arbuscular mycorrhizal (AM) trees. In ECM-dominated plots, girdling decreased the activity of enzymes that break down soil organic matter (SOM) by c. 40%, indicating that, in control plots, C supply from ECM roots primes microbial decomposition. In AM-dominated plots, girdling had little effect on SOM-degrading enzymes, but increased the decomposition of AM leaf litter by c. 43%, suggesting that, in control plots, AM roots may intensify microbial competition for nutrients. Our findings indicate that root-induced changes in soil processes depend on forest composition, and that shifts in the distribution of AM and ECM trees owing to climate change may determine soil C gains and losses.

Toward a consistency cross-check of eddy covariance flux-based and biometric estimates of ecosystem carbon balance,.

Quantification of an ecosystems carbon balance and its components is pivotal for understanding both ecosystem functioning and global cycling. Several methods are being applied in parallel to estimate the different components of the CO2 balance. However, different methods are subject to different sources of error. Therefore, it is necessary that site level component estimates are cross-checked against each other before being reported. Here we present a two-step approach for testing the accuracy and consistency of eddy covariance–based gross primary production (GPP) and ecosystem respiration (Re) estimates with biometric measurements of net primary production (NPP), autotrophic (Ra) and heterotrophic (Rh) respiration. The test starts with closing the CO2 balance to account for reasonable errors in each of the component fluxes. Failure to do so within the constraints will classify the flux estimates on the site level as inconsistent. If the CO2 balance can be closed, the test continues by comparing the closed site level Ra/GPP with the Rh/GPP ratio. The consistency of these ratios is then judged against expert knowledge. Flux estimates of sites that pass both steps are considered consistent. An inconsistent ratio is not necessarily incorrect but provides a signal for careful data screening that may require further analysis to identify the possible biological reasons of the unexpected ratios. We reviewed the literature and found 16 sites, out of a total of 529 research forest sites, that met the data requirements for the consistency test. Thirteen of these sites passed both steps of the consistency cross-check. Subsequently, flux ratios (NPP/GPP, Rh/NPP, Rh/Re, and Re/GPP) were calculated for the consistent sites. Similar ratios were observed at sites which lacked information to check consistency, indicating that the flux data that are currently used for validating models and testing ecological hypotheses are largely consistent across a wide range of site productivities. Confidence in the output of flux networks could be further enhanced if the required fluxes are independently estimated at all sites for multiple years and harmonized methods are used.

Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (V(cm)), and quantum yield (alpha) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAI(F) for a large range of sites, comparable to the LAI(M) derived from MODIS. There are discrepancies when LAI(F) reach zero levels and LAI(M) still provides a small positive value. We find that temperature is the most common constraint for LAI(F) in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAI(F) or LAIM (r(2) = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAI(F). V(cm) has the largest seasonal variation. This holds for all vegetation types and climates. The parameter alpha is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen.

Keenan et al . reply

replying to C. D. Holmes 507, http://dx.doi.org/10.1038/nature13113 (2014)Forests have become more efficient at using water over the past two decades. A series of hypotheses exist to explain this trend, but the only credible explanation to date is a response to rising atmospheric CO2. Keenan et al. show that the observed trend is physiologically plausible, but is much larger than expected from conventional theory and experimental evidence. This has led to suggestions that processes other than increased atmospheric CO2 may have contributed to the observed trend. One such process that has yet to be examined is the effect of tropospheric ozone on forest water-use efficiency (WUE). In the accompanying Comment, Holmes reports that ozone concentrations have declined in the northeastern and midwestern USA by about 50% from 1995 to 2010. Using empirical relationships, he estimates that this decline could explain roughly 15% of the reported increase in WUE over North America, and a significantly lower proportion of the trend in Europe.