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Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13°C 12°C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball-Berry stomatal conductance slope (mbb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised mbb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. This study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.

The seasonal pattern of the carbon isotope content (δ13C) of atmospheric CO2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δsource at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ13C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δsource at the forest sites (0.5‰ variation). We did not find a consistent seasonal relationship between VPD and δsource across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δsource (5‰) dominated by seasonal transitions in C3/C4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ13C of land-atmosphere CO2 exchange (δsource) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C3/C4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δsource when background atmospheric observations are remote and/or prone to anthropogenic influence.

Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. We distinguished between isotopic behavior in response to a decrease of δ13C within atmospheric CO2 (Suess effect) vs. photosynthetic discrimination (Δcanopy), by creating a site-customized atmospheric CO2 and δ13C of CO2 time series. We implemented a seasonally varying Vcmax model calibration that best matched site observations of net CO2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ13C of needle and stem tissue, but underestimated the δ13C of bulk soil carbon by 1-2%. The model overestimated the multiyear (2006-2012) average Δcanopy relative to prior data-based estimates by 2-4%. The amplitude of the average seasonal cycle of Δcanopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled An - gs (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled An - gs version used in the default model. The model attributed most of the seasonal variation in discrimination to An, whereas interannual variation in simulated Δcanopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10% increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.

Aims: We tested the hypothesis that vegetation composition and phenology drive both rhizospheric and heterotrophic soil processes, as an alternative to experimental approaches to partition these soil respiration sources. Methods: We compared surface CO2 efflux, depth profiles of CO2 production, extractable SOC and MBC, and soil temperature and moisture along transects between contrasting vegetation types (deciduous riparian trees and adjacent meadow) over the snow-free growing seasons of 2005 and 2006. Results: A dense flush of the nitrogen-fixing forb Melilotus officinalis dominated the meadow in 2005, corresponding with very high rates of CO2 efflux (56 % higher than under trees and 82 % higher than in the diverse meadow community present in 2006). In 2006, proximity to trees was associated with greater surface CO2 efflux and CO2 production to 50 cm depth. SOC was higher under trees than in the meadow (p < 0.0001). MBC was not consistently affected by position relative to trees, but seasonality of MBC was altered by trees as an interactive effect of transect position and sample date (p = 0.01). Conclusion: Community and phenology effects on soil carbon cycling demonstrate the interactions between plant traits and rhizospheric and heterotrophic soil respiration sources. This study highlights a unique case of a highly productive, nitrogen-fixing monoculture exhibiting vastly higher soil respiration rates than a diverse grass-forb community within a single, unmanaged site.

The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive "greenness" of these systems. We combine continuous needle-scale chlorophyll fluorescence measurements with tower-based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar-induced chlorophyll fluorescence (SIF) and solar intensity-normalized SIF (SIF relative ) under snow-covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near-infrared vegetation index [NIRv] under 50% snow cover). Needle-scale fluorescence and photochemistry strongly correlated (r 2  = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower-based estimates of LUE P and SIF relative which were well correlated across all sites (r 2  = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data-driven and process-based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems., (© 2024 The Author(s). Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO 2 ) and methane (CH 4 ) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation., (© 2022. The Author(s).)

Low temperature in winter depresses rates of photosynthesis, which, in evergreen plants, can exacerbate imbalances between light absorption and photochemical light use. Damage that could result from increased excess light absorption is minimized by the conversion of excitation energy to heat in a process known as energy dissipation, which involves the de-epoxidized carotenoids of the xanthophyll cycle. Overwintering evergreens employ sustained forms of energy dissipation observable even after lengthy periods of dark acclimation. Whereas most studies of photoprotective energy dissipation examine one or a small number of species; here, we measured the levels of sustained thermal energy dissipation of seventy conifer taxa growing outdoors under common-garden conditions at the Red Butte Garden in Salt Lake City, Utah, U.S.A. (forty nine taxa were also sampled for needle pigment content). We observed an extremely wide range of wintertime engagement of sustained energy dissipation; the percentage decrease in dark-acclimated photosystem II quantum efficiency from summer to winter ranged from 6 to 95%. Of the many pigment-based parameters measured, the magnitude of the seasonal decrease in quantum efficiency was most closely associated with the seasonal increase in zeaxanthin content expressed on a total chlorophyll basis, which explained only slightly more than one-third of the variation. We did not find evidence for a consistent wintertime decrease in needle chlorophyll content. Thus, the prevailing mechanism for winter decreases in solar-induced fluorescence emitted by evergreen forests may be decreases in fluorescence quantum yield, and wintertime deployment of sustained energy dissipation likely underlies this effect., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite-derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above-ground biomass. The adjusted simulation significantly reduced the above-ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation-constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon., (© 2021. The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO 2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices., (© 2020 The Authors New Phytologist © 2020 New Phytologist Foundation.)

The fluxes of energy, water, and carbon from terrestrial ecosystems influence the atmosphere. Land-atmosphere feedbacks can intensify extreme climate events like severe droughts and heatwaves because low soil moisture decreases both evaporation and plant transpiration and increases local temperature. Here, we combine data from a network of temperate and boreal eddy covariance towers, satellite data, plant trait datasets, and a mechanistic vegetation model to diagnose the controls of soil moisture feedbacks to drought. We find that climate and plant functional traits, particularly those related to maximum leaf gas exchange rate and water transport through the plant hydraulic continuum, jointly affect drought intensification. Our results reveal that plant physiological traits directly affect drought intensification and indicate that inclusion of plant hydraulic transport mechanisms in models may be critical for accurately simulating land-atmosphere feedbacks and climate extremes under climate change., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO 2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated ( R 2 = 0.62-0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution., Competing Interests: The authors declare no conflict of interest.

Plants influence the atmosphere through fluxes of carbon, water and energy 1 , and can intensify drought through land-atmosphere feedback effects 2-4 . The diversity of plant functional traits in forests, especially physiological traits related to water (hydraulic) transport, may have a critical role in land-atmosphere feedback, particularly during drought. Here we combine 352 site-years of eddy covariance measurements from 40 forest sites, remote-sensing observations of plant water content and plant functional-trait data to test whether the diversity in plant traits affects the response of the ecosystem to drought. We find evidence that higher hydraulic diversity buffers variation in ecosystem flux during dry periods across temperate and boreal forests. Hydraulic traits were the predominant significant predictors of cross-site patterns in drought response. By contrast, standard leaf and wood traits, such as specific leaf area and wood density, had little explanatory power. Our results demonstrate that diversity in the hydraulic traits of trees mediates ecosystem resilience to drought and is likely to have an important role in future ecosystem-atmosphere feedback effects in a changing climate.

Stable isotope ratios of H and O are widely used to identify the source of water, e.g., in aquifers, river runoff, soils, plant xylem, and plant-based beverages. In situations where the sampled water is partially evaporated, its isotope values will have evolved along an evaporation line (EL) in δ 2 H/δ 18 O space, and back-correction along the EL to its intersection with a meteoric water line (MWL) has been used to estimate the source water's isotope ratios. Here, we review the theory underlying isotopic estimation of source water for evaporated samples (iSW E ). We note potential for bias from a commonly used regression-based approach for EL slope estimation and suggest that a model-based approach may be preferable if assumptions of the regression approach are not valid. We then introduce a mathematical framework that eliminates the need to explicitly estimate the EL-MWL intersection, simplifying iSW E analysis and facilitating more rigorous uncertainty estimation. We apply this approach to data from the US EPA's 2007 National Lakes Assessment. We find that data for most lakes are consistent with a water source similar to annual runoff, estimated from monthly precipitation and evaporation within the lake basin. Strong evidence for both summer- and winter-biased sources exists, however, with winter bias pervasive in most snow-prone regions. The new analytical framework should improve the rigor of iSW E in ecohydrology and related sciences, and our initial results from US lakes suggest that previous interpretations of lakes as unbiased isotope integrators may only be valid in certain climate regimes.

Cities are concentrated areas of CO 2 emissions and have become the foci of policies for mitigation actions. However, atmospheric measurement networks suitable for evaluating urban emissions over time are scarce. Here we present a unique long-term (decadal) record of CO 2 mole fractions from five sites across Utah's metropolitan Salt Lake Valley. We examine "excess" CO 2 above background conditions resulting from local emissions and meteorological conditions. We ascribe CO 2 trends to changes in emissions, since we did not find long-term trends in atmospheric mixing proxies. Three contrasting CO 2 trends emerged across urban types: negative trends at a residential-industrial site, positive trends at a site surrounded by rapid suburban growth, and relatively constant CO 2 over time at multiple sites in the established, residential, and commercial urban core. Analysis of population within the atmospheric footprints of the different sites reveals approximately equal increases in population influencing the observed CO 2 , implying a nonlinear relationship with CO 2 emissions: Population growth in rural areas that experienced suburban development was associated with increasing emissions while population growth in the developed urban core was associated with stable emissions. Four state-of-the-art global-scale emission inventories also have a nonlinear relationship with population density across the city; however, in contrast to our observations, they all have nearly constant emissions over time. Our results indicate that decadal scale changes in urban CO 2 emissions are detectable through monitoring networks and constitute a valuable approach to evaluate emission inventories and studies of urban carbon cycles., Competing Interests: The authors declare no conflict of interest.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO 2 sink. However, such analyses are poorly constrained by measured CO 2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm -2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (R eco ) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and R eco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO 2 exchange may be up to 3-5 times larger than current estimates., (Published 2017. This article is a U.S. Government work and is in the public domain in the USA.)

Productivity of conifers in seasonally snow-covered forests is high before and during snowmelt when environmental conditions are optimal for photosynthesis. Climate change is altering the timing of spring in many locations, and changes in the date of transition from winter dormancy can have large impacts on annual productivity. Sap flow methods provide a promising approach to monitor tree activity during the cold season and the winter-spring and fall-winter transitions. Although sap flow techniques have been widely used, cold season results are generally not reported. Here we examine the feasibility of using the Granier thermal dissipation (TD) sap flux density method to monitor transpiration and dormancy of evergreen conifers during the cold season. We conducted a laboratory experiment which demonstrated that the TD method reliably detects xylem water transport (when it occurs) both at near freezing temperature and at low flow rate, and that the sensors can withstand repeated freeze-thaw events. However, the dependence between sensor output and water transport rate in these experiments differed from the established TD relation. In field experiments, sensors installed in two Abies forests lasted through two winters and a summer with low failure. The baseline (no-flow) sensor output varied considerably with temperature during the cold season, and a new baseline algorithm was developed to accommodate this variation. The Abies forests differed in elevation (2070 and 2620 m), and there was a clear difference in timing of initiation and cessation of transpiration between them. We conclude that the TD method can be reliably used to examine water transport during cold periods with associated low flow conditions., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Natural abundance nitrate (NO3 (-)) isotopes represent a powerful tool for assessing denitrification, yet the scale and context dependence of relationships between isotopes and denitrification have received little attention, especially in surface soils. We measured the NO3 (-) isotope compositions in soil extractions and lysimeter water from a semi-arid meadow and lawn during snowmelt, along with the denitrification potential, bulk O2, and a proxy for anaerobic microsites. Denitrification potential varied by three orders of magnitude and the slope of δ(18)O/δ(15)N in soil-extracted NO3 (-) from all samples measured 1.04 ± 0.12 (R (2) = 0.64, p < 0.0001), consistent with fractionation from denitrification. However, δ(15)N of extracted NO3 (-) was often lower than bulk soil δ(15)N (by up to 24 ‰), indicative of fractionation during nitrification that was partially overprinted by denitrification. Mean NO3 (-) isotopes in lysimeter water differed from soil extractions by up to 19 ‰ in δ(18)O and 12 ‰ in δ(15)N, indicating distinct biogeochemical processing in relatively mobile water versus soil microsites. This implies that NO3 (-) isotopes in streams, which are predominantly fed by mobile water, do not fully reflect terrestrial soil N cycling. Relationships between potential denitrification and δ(15)N of extracted NO3 (-) showed a strong threshold effect culminating in a null relationship at high denitrification rates. Our observations of (1) competing fractionation from nitrification and denitrification in redox-heterogeneous surface soils, (2) large NO3 (-) isotopic differences between relatively immobile and mobile water pools, (3) and the spatial dependence of δ(18)O/δ(15)N relationships suggest caution in using NO3 (-) isotopes to infer site or watershed-scale patterns in denitrification.

Bark beetle outbreaks are widespread in western North American forests, reducing primary productivity and transpiration, leading to forest mortality across large areas and altering ecosystem carbon cycling. Here the carbon isotope composition (δ(13) C) of soil respiration (δJ ) was monitored in the decade after disturbance for forests affected naturally by mountain pine beetle infestation and artificially by stem girdling. The seasonal mean δJ changed along both chronosequences. We found (a) enrichment of δJ relative to controls (<1 ‰) in near-surface soils in the first 2 years after disturbance; (b) depletion (1‰ or no change) during years 3-7; and (c) a second period of enrichment (1-2‰) in years 8-10. Results were consistent with isotopic patterns associated with the gradual death and decomposition of rhizosphere organisms, fine roots, conifer needles and woody roots and debris over the course of a decade after mortality. Finally, δJ was progressively more (13) C-depleted deeper in the soil than near the surface, while the bulk soil followed the well-established pattern of (13) C-enrichment at depth. Overall, differences in δJ between mortality classes (<1‰) and soil depths (<3‰) were smaller than variability within a class or depth over a season (up to 6‰)., (© 2016 The Authors. Plant, Cell and Environment published by John Wiley & Sons Ltd.)

Snowmelt dominates the hydrograph of many temperate montane streams, yet little work has characterized how streamwater sources and nitrogen (N) dynamics vary across wildland to urban land use gradients in these watersheds. Across a third-order catchment in Salt Lake City, Utah, we asked where and when groundwater vs shallow surface water inputs controlled stream discharge and N dynamics. Stream water isotopes (δ(2)H and δ(18)O) reflected a consistent snowmelt water source during baseflow. Near-chemostatic relationships between conservative ions and discharge implied that groundwater dominated discharge year-round across the montane and urban sites, challenging the conceptual emphasis on direct stormwater inputs to urban streams. Stream and groundwater NO3(-) concentrations remained consistently low during snowmelt and baseflow in most montane and urban stream reaches, indicating effective subsurface N retention or denitrification and minimal impact of fertilizer or deposition N sources. Rather, NO3(-) concentrations increased 50-fold following urban groundwater inputs, showing that subsurface flow paths potentially impact nutrient loading more than surficial land use. Isotopic composition of H2O and NO3(-) suggested that snowmelt-derived urban groundwater intercepted NO3(-) from leaking sewers. Sewer maintenance could potentially mitigate hotspots of stream N inputs at mountain/valley transitions, which have been largely overlooked in semiarid urban ecosystems.

Carbon isotope ratios (δ¹³C) of heterotrophic and rhizospheric sources of soil respiration under deciduous trees were evaluated over two growing seasons. Fluxes and δ¹³C of soil respiratory CO₂ on trenched and untrenched plots were calculated from closed chambers, profiles of soil CO₂ mole fraction and δ¹³C and continuous open chambers. δ¹³C of respired CO₂ and bulk carbon were measured from excised leaves and roots and sieved soil cores. Large diel variations (>5‰) in δ¹³C of soil respiration were observed when diel flux variability was large relative to average daily fluxes, independent of trenching. Soil gas transport modelling supported the conclusion that diel surface flux δ¹³C variation was driven by non-steady state gas transport effects. Active roots were associated with high summertime soil respiration rates and around 1‰ enrichment in the daily average δ¹³C of the soil surface CO₂ flux. Seasonal δ¹³C variability of about 4‰ (most enriched in summer) was observed on all plots and attributed to the heterotrophic CO₂ source., (© 2010 Blackwell Publishing Ltd.)

We present a novel technique in which the carbon isotope ratio (delta(13)C) of soil CO(2) is measured from small gas samples (<5 mL) injected into a stream of CO(2)-free air flowing into a tunable diode laser absorption spectrometer (TDL). This new method extends the dynamic range of the TDL to measure CO(2) mole fractions ranging from ambient to pure CO(2), reduces the volume of sample required to a few mL, and does not require field deployment of the instrument. The measurement precision of samples stored for up to 60 days was 0.23 per thousand. The new TDL method was applied with a simple gas well sampling technique to obtain and measure gas samples from shallow soil depth increments for CO(2) mole fraction and delta(13)C analysis, and subsequent determination of the delta(13)C of soil-respired CO(2). The method was tested using an artificial soil system containing a controlled CO(2) source and compared with an independent method using the TDL and an open soil chamber. The profile and chamber estimates of delta(13)C of an artificially produced CO(2) flux were consistent and converged to the delta(13)C of the CO(2) source at steady state, indicating the accuracy of both methods under controlled conditions. The new TDL method, in which a small pulse of sample is measured on a carrier gas stream, is analogous for the TDL technique to the development of continuous-flow configurations for isotope ratio mass spectrometry. While the applications presented here are focused on soil CO(2), this new TDL method could be applied in a number of situations requiring measurement of delta(13)C of CO(2) in small gas samples with ambient to high CO(2) mole fractions., (2010 John Wiley & Sons, Ltd.)

Stable carbon isotopes are used extensively to examine physiological, ecological, and biogeochemical processes related to ecosystem, regional, and global carbon cycles and provide information at a variety of temporal and spatial scales. Much is known about the processes that regulate the carbon isotopic composition (delta(13)C) of leaf, plant, and ecosystem carbon pools and of photosynthetic and respiratory carbon dioxide (CO(2)) fluxes. In this review, systematic patterns and mechanisms underlying variation in delta(13)C of plant and ecosystem carbon pools and fluxes are described. We examine the hypothesis that the delta(13)C of leaf biomass can be used as a reference point for other carbon pools and fluxes, which differ from the leaf in delta(13)C in a systematic fashion. Plant organs are typically enriched in (13)C relative to leaves, and most ecosystem pools and respiratory fluxes are enriched relative to sun leaves of dominant plants, with the notable exception of root respiration. Analysis of the chemical and isotopic composition of leaves and leaf respiration suggests that growth respiration has the potential to contribute substantially to the observed offset between the delta(13)C values of ecosystem respiration and the bulk leaf. We discuss the implications of systematic variations in delta(13)C of ecosystem pools and CO(2) fluxes for studies of carbon cycling within ecosystems, as well as for studies that use the delta(13)C of atmospheric CO(2) to diagnose changes in the terrestrial biosphere over annual to millennial time scales.

Recent measurements of carbon isotopes in carbon dioxide using near-infrared, diode-laser-based cavity ring-down spectroscopy (CRDS) are presented. The CRDS system achieved good precision, often better than 0.2 per thousand, for 4% CO2 concentrations, and also achieved 0.15-0.25 per thousand precision in a 78 min measurement time with cryotrap-based pre-concentration of ambient CO2 concentrations (360 ppmv). These results were obtained with a CRDS system possessing a data rate of 40 ring-downs per second and a loss measurement of 4.0 x 10(-11) cm(-1) Hz(-1/2). Subsequently, the measurement time has been reduced to under 10 min. This standard of performance would enable a variety of high concentration (3-10%) isotopic measurements, such as medical human breath analysis or animal breath experiments. The extension of this ring-down to the 2 microm region would enable isotopic analysis at ambient concentrations, which, combined with the small size, robust design, and potential for frequent measurements at a remote site, make CRDS technology attractive for remote atmospheric measurement applications.

Variation in the carbon isotopic composition of ecosystem respiration (δ 13 C R ) was studied for 3  years along a precipitation gradient in western Oregon, USA, using the Keeling plot approach. Study sites included six coniferous forests, dominated by Picea sitchensis, Tsuga heterophylla, Pseudotsuga menziesii, Pinus ponderosa, and Juniperus occidentalis, and ranged in location from the Pacific coast to the eastern side of the Cascade Mountains (a 250-km transect). Mean annual precipitation across these sites ranged from 227 to 2,760 mm. Overall δ 13 C R varied from -23.1 to -33.1‰, and within a single forest, it varied in magnitude by 3.5-8.5‰. Mean annual δ 13 C R differed significantly in the forests and was strongly correlated with mean annual precipitation. The carbon isotope ratio of carbon stocks (leaves, fine roots, litter, and soil organic matter) varied similarly with mean precipitation (more positive at the drier sites). There was a strong link between δ 13 C R and the vapor saturation deficit of air (vpd) 5-10 days earlier, both across and within sites. This relationship is consistent with stomatal regulation of gas exchange and associated changes in photosynthetic carbon isotope discrimination. Recent freeze events caused significant deviation from the δ 13 C R versus vpd relationship, resulting in higher than expected δ 13 C R values.

Because the rate of isoprene (2-methyl-1,3-butadiene) emission from plants is highly temperature-dependent, we investigated natural fluctuations in leaf temperature and effects of rapid temperature change on isoprene emission of red oak (Quercus rubra L.) leaves at the top of the canopy at Harvard Forest. Throughout the day, leaves often reached temperatures as much as 15 degrees C above air temperature. The highest temperatures were reached for only a few seconds at a time. We compared isoprene emission rates measured when leaf temperature was changed rapidly with those measured when temperature was changed slowly. In all cases, isoprene emission rate increased with increasing leaf temperature up to about 32 degrees C and then decreased with higher temperatures. The temperature at which isoprene emission rates began to decrease depended on how quickly measurements were made. Isoprene emission rates peaked at 32.5 degrees C when measured hourly, whereas rates peaked at 39 degrees C when measurements were made every four minutes. This behavior reflected the rapid increase in isoprene emission rate that occurred immediately after an increase in leaf temperature, and the subsequent decrease in isoprene emission rate when leaf temperature was held steady for longer than 20 minutes. We concluded that the observed temperature response of isoprene emission rate is a function of measurement protocol. Omitting this parameter from isoprene emission models will not affect simulated isoprene emission rates at mild temperatures, but can increase isoprene emission rates at high temperatures.

The micrometeorological flux measurement technique known as relaxed eddy accumulation (REA) holds promise as a powerful new tool for ecologists. The more popular eddy covariance (eddy correlation) technique requires the use of sensors that can respond at fast rates (10 Hz), and these are unavailable for many ecologically relevant compounds. In contrast, the use of REA allows flux measurement with sensors that have much slower response time, such as gas chromatography and mass spectrometry. In this review, relevant micrometeorological details underlying REA are presented, and critical analytical and system design details are discussed, with the goal of introducing the technique and its potential applications to ecologists. The validity of REA for measuring fluxes of isoprene, a photochemically reactive hydrocarbon emitted by several plant species, was tested with measurements over an oak-hickory forest in the Walker Branch Watershed in eastern Tennessee. Concurrent eddy covariance measurements of isoprene flux were made using a newly available chemiluminesence instrument. Excellent agreement was obtained between the two techniques (r 2  = 0.974, n = 62), providing the first direct comparison between REA and eddy covariance for measuring the flux rate of a reactive compound. The influence of a bias in vertical wind velocity on the accuracy of REA was examined. This bias has been thought to be a source of significant error in the past. Measurements of normalized bias ([Formula: see text]) alone would lead us to think that a large potential error exists at this site. However, with our isoprene data and through simulations of REA with fast-response H 2 O and CO 2 data, we conclude that accurate REA flux measurements can be made even in the presence of a bias in w.