Browsing by Author "Stoy, Paul C."

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Air temperature and photosynthetically active photon flux density data from the Abisko Scientific Research center [dataset]
(2014-12) Stoy, Paul C.
Air temperature and photosynthetically active photon flux density data from the Abisko Scientific Research center courtesy of Annika Kristofferson. The Stoy Lab adheres to an open data policy. Data collected by the Stoy Lab are free to anyone to use with two caveats: 1. Coauthorship may be requested if intellectual input is provided. Intellectual input is defined in this case as an analysis that is critical to outcomes that could not otherwise be performed. 2. Graduate students operate the towers and analyze the data. They must be given the opportunity to be coauthors on your work. Please email paul dot stoy at gmail dot com with any questions. Further information is available from the Biosphere-Atmosphere Interactions Lab website https://sites.google.com/site/stoylab/home
Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration
(2010-02) Hollinger, David Y.; Ollinger, S. V.; Richardson, Andrew D.; Meyers, T. P.; Dail, D. B.; Martin, M. E.; Scott, N. A.; Arkebauer, T. J.; Baldocchi, Dennis D.; Clark, K. L.; Curtis, P. S.; Desai, Ankur R.; Dragoni, Danilo; Goulden, Michael L.; Gu, Lianhong; Katul, Gabriel G.; Pallardy, S. G.; Paw U, Kyaw Tha; Schmid, H. P.; Stoy, Paul C.; Suyker, Andrew E.; Verma, Shashi B.
Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site‐years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two‐stream albedo submodel provided accurate predictions of boreal needle‐leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two‐stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r2=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r2=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two‐stream albedo model and foliage nitrogen concentration. These nitrogen‐based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.
Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments
(Frontiers Media SA, 2022-10) Wood, David J. A.; Stoy, Paul C.; Powell, Scott L.; Beever, Erik A.
Ecological processes are complex, often exhibiting non-linear, interactive, or hierarchical relationships. Furthermore, models identifying drivers of phenology are constrained by uncertainty regarding predictors, interactions across scales, and legacy impacts of prior climate conditions. Nonetheless, measuring and modeling ecosystem processes such as phenology remains critical for management of ecological systems and the social systems they support. We used random forest models to assess which combination of climate, location, edaphic, vegetation composition, and disturbance variables best predict several phenological responses in three dominant land cover types in the U.S. Northwestern Great Plains (NWP). We derived phenological measures from the 25-year series of AVHRR satellite data and characterized climatic predictors (i.e., multiple moisture and/or temperature based variables) over seasonal and annual timeframes within the current year and up to 4 years prior. We found that antecedent conditions, from seasons to years before the current, were strongly associated with phenological measures, apparently mediating the responses of communities to current-year conditions. For example, at least one measure of antecedent-moisture availability [precipitation or vapor pressure deficit (VPD)] over multiple years was a key predictor of all productivity measures. Variables including longer-term lags or prior year sums, such as multi-year-cumulative moisture conditions of maximum VPD, were top predictors for start of season. Productivity measures were also associated with contextual variables such as soil characteristics and vegetation composition. Phenology is a key process that profoundly affects organism-environment relationships, spatio-temporal patterns in ecosystem structure and function, and other ecosystem dynamics. Phenology, however, is complex, and is mediated by lagged effects, interactions, and a diversity of potential drivers; nonetheless, the incorporation of antecedent conditions and contextual variables can improve models of phenology.
Applying information theory in the geosciences to quantify process uncertainty, feedback, scale
(2013-01-29) Ruddell, Benjamin L.; Brunsell, Nathaniel A.; Stoy, Paul C.
The geosciences are increasingly utilizing a systems approach to quantify spatial and temporal dynamics among multiple subsystems, their couplings, and their feedbacks. This systems approach demands novel strategies for experimentation and observation in the “natural laboratory” rather than in simple controlled experiments and thus relies heavily on Earth system observations and observation networks. Current and forthcoming examples of Earth system observatories include the Critical Zone Observatories (CZOs), the National Ecological Observatory Network (NEON), EarthScope, FLUXNET, National Water Information System/National Water‐Quality Assessment (NWIS/NAWQA), and others. These networks are designed to observe complex processes across a wide range of temporal and spatial scales to synthesize scientific understanding of the fundamental interactions across the interfaces of society, hydrology, ecology, atmospheric sciences, and geosciences.
Are ecosystem carbon inputs and outputs coupled at short time scales? A case study from adjacent pine and hardwood forests using impulse-response analysis
(2007-06) Stoy, Paul C.; Palmroth, Sari; Oishi, A. Christopher; Siqueira, Mario B. S.; Juang, Jehn-Yih; Novick, Kimberly A.; Ward, Eric J.; Katul, Gabriel G.; Oren, Ram
A number of recent studies have attributed a large proportion of soil respiration (Rsoil) to recently photoassimilated carbon (C). Time lags (τPR) associated with these pulses of photosynthesis and responses of Rsoil have been found on time scales of hours to weeks for different ecosystems, but most studies find evidence for τPR on the order of 1–5 d. We showed that such time scales are commensurate with CO2 diffusion time scales from the roots to the soil surface, and may thus be independent from photosynthetic pulses. To further quantify the role of physical (i.e. edaphic) and biological (i.e. vegetative) controls on such lags, we investigated τPR at adjacent planted pine (PP) and hardwood (HW) forest ecosystems over six and four measurement years, respectively, using both autocorrelation analysis on automated soil surface flux measurements and their lagged cross‐correlations with drivers for and surrogates of photosynthesis. Evidence for τPR on the order of 1–3 d was identified in both ecosystems and using both analyses, but this lag could not be attributed to recently photoassimilated C because the same analysis yielded comparable lags at HW during leaf‐off periods. Future efforts to model ecosystem C inputs and outputs in a pulse–response framework must combine measurements of transport in the physical and biological components of terrestrial ecosystems.
Artificial drainage and associated carbon fluxes (CO2/CH4) in tundra ecosystems
(2009-11) Merbold, L.; Kutsch, Werner L.; Kolle, O.; Zimov, S. A.; Corradi, C.; Stoy, Paul C.; Schulze, E.-D.
Ecosystem flux measurements using the eddy covariance (EC) technique were undertaken in 4 subsequent years during summer for a total of 562 days in an arctic wet tundra ecosystem, located near Cherskii, Far‐Eastern Federal District, Russia. Methane (CH4) emissions were measured using permanent chambers. The experimental field is characterized by late thawing of permafrost soils in June and periodic spring floods. A stagnant water table below the grass canopy is fed by melting of the active layer of permafrost and by flood water. Following 3 years of EC measurements, the site was drained by building a 3 m wide drainage channel surrounding the EC tower to examine possible future effects of global change on the tundra tussock ecosystem. Cumulative summertime net carbon fluxes before experimental alteration were estimated to be about +15 g C m−2 (i.e. an ecosystem C loss) and +8 g C m−2 after draining the study site. When taking CH4 as another important greenhouse gas into account and considering the global warming potential (GWP) of CH4 vs. CO2, the ecosystem had a positive GWP during all summers. However CH4 emissions after drainage decreased significantly and therefore the carbon related greenhouse gas flux was much smaller than beforehand (475 ± 253 g C‐CO2‐e m−2 before drainage in 2003 vs. 23 ± 26 g C‐CO2‐e m−2 after drainage in 2005).
Assessing interactions among changing climate, management, and disturbance in forests: a macrosystems approach
(2015-03) Becknell, Justin M.; Desai, Ankur R.; Dietze, Michael C.; Schultz, Courtney A.; Starr, Gregory; Stoy, Paul C.; Duffy, Paul A.; Franklin, Jerry F.; Pourmokhtarian, Afshin; Hall, Jaclyn; Binford, Michael W.; Boring, Lindsay R.; Staudhammer, Christina L.
Forests are experiencing simultaneous changes in climate, disturbance regimes, and management, all of which affect ecosystem function. Climate change is shifting ranges and altering forest productivity. Disturbance regimes are changing with the potential for novel interactions among disturbance types. In some areas, forest management practices are intensifying, whereas in other areas, lower-impact ecological methods are being used. Interactions among these changing factors are likely to alter ecosystem structure and function at regional to continental scales. A macrosystems approach is essential to assessing the broadscale impacts of these changes and quantify cross-scale interactions, emergent patterns, and feedbacks. A promising line of analysis is the assimilation of data with ecosystem models to scale processes to the macrosystem and generate projections based on alternative scenarios. Analyses of these projections can characterize the range of future variability in forest function and provide information to guide policy, industry, and science in a changing world.
Assessing Self-Organization of Plant communities—A Thermodynamic Approach
(2009-03) Lin, Hua; Cao, Min; Stoy, Paul C.; Zhang, Yiping
Thermodynamics is a powerful tool for the study of system development and has the potential to be applied to studies of ecological complexity. Here, we develop a set of thermodynamic indicators including energy capture and energy dissipation to quantify plant community self-organization. The study ecosystems included a tropical seasonal rainforest, an artificial tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M. King & H. Robinson communities aged 13 years and 1 year. The communities represent a complexity transect from primary vegetation, to transitional community, economic plantation, and fallows and are typical for Xishuangbanna, southwestern China. The indicators of ecosystem self-organization are sensitive to plant community type and seasonality, and demonstrate that the tropical seasonal rainforest is highly self-organized and plays an important role in local environmental stability via the land surface thermal regulation. The rubber plantation is at a very low level of self-organization as quantified by the thermodynamic indicators, especially during the dry season. The expansion of the area of rubber plantation and shrinkage of tropical seasonal rainforest would likely induce local surface warming and a larger daily temperature range.
Bioenergy with Carbon Capture and Storage (BECCS) in the Upper Missouri River Basin
(Montana State University, 2017-04) Bauer, Brad; Poulter, Benjamin; Royem, Alisa; Stoy, Paul C.; Taylor, Suzi
A team of scientists from Montana State University (MSU), the University of Wyoming (UW) and the University of South Dakota (USD) has received funding from the National Science Foundation that is bringing $6 million to these states. The team will use computer models and field experiments to study what might happen over the next 100 years if we adopt a new energy system called BECCS. The project’s study region is the Upper River Missouri Basin, but the findings could help all regions better understand the impacts of BECCS on communities and citizens, agriculture and ecosystem services.
Biosphere-atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales
(2009-10) Stoy, Paul C.; Richardson, Andrew D.; Baldocchi, Dennis D.; Katul, Gabriel G.; Stanovick, J.; Mahecha, M. D.; Reichstein, M.; Detto, Matteo; Law, Beverly E.; Wohlfahrt, Georg; Arriga, N.; Campos, J.; McCaughey, J. H.; Montagnani, Leonardo; Paw U, Kyaw Tha; Sevanto, S.; Williams, Mathew
The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the relationship between flux and climate at multiple time scales is necessary for a comprehensive understanding of the role of climate in the terrestrial carbon cycle. Orthonormal wavelet transformation (OWT) can quantify the strength of the interactions between gappy eddy covariance flux and micrometeorological measurements at multiple frequencies while expressing time series variance in few energetic wavelet coefficients, offering a low-dimensional view of the response of terrestrial carbon flux to climatic variability. The variability of NEE, GEP and RE, and their co-variability with dominant climatic drivers, are explored with nearly one thousand site-years of data from the FLUXNET global dataset consisting of 253 eddy covariance research sites. The NEE and GEP wavelet spectra were similar among plant functional types (PFT) at weekly and shorter time scales, but significant divergence appeared among PFT at the biweekly and longer time scales, at which NEE and GEP were relatively less variable than climate. The RE spectra rarely differed among PFT across time scales as expected. On average, RE spectra had greater low frequency (monthly to interannual) variability than NEE, GEP and climate. CANOAK ecosystem model simulations demonstrate that "multi-annual" spectral peaks in flux may emerge at low (4+ years) time scales. Biological responses to climate and other internal system dynamics, rather than direct ecosystem response to climate, provide the likely explanation for observed multi-annual variability, but data records must be lengthened and measurements of ecosystem state must be made, and made available, to disentangle the mechanisms responsible for low frequency patterns in ecosystem CO2 exchange.
Biotic interactions and biogeochemical processes in the soil environment
(2012-05-24) Subke, J.-A.; Carbone, M.S.; Khomik, M.; Stoy, Paul C.; Bahn, Michael
"Soils play a key role in the terrestrial carbon (C) cycle bystoring and emitting large quantities of C. The impact of abiotic conditions (mainly soil temperature and moisture) on soil C turnover is well documented, but unravelling the influence of these drivers across temporal and spatial scales remains an important challenge. Biotic factors, such as microbial abundance and diversity, macro-faunal food webs and below-ground plant (i.e. root) biomass and diversity, play an important role in controlling soil C storage and emission, but remain under-investigated. To better understand the soil processes underlying terrestrial C cycling, the interactions between plants (autotrophs) and soil organisms (heterotrophs) need to be addressed more explicitly and integrated with short- and long-term effects of abiotic drivers. This special issue presents recent advances in field, laboratory, and modelling studies on soil C dynamics, with a particular emphasis on those aiming to resolve abiotic and biotic influences. The manuscripts highlight three areas of investigation that we suggest are central to current and future progress in ecosystem C dynamic research: (1) novel interpretations of abiotic controls on soil CO2 efflux, (2) legacy effects of abiotic drivers of soil C dynamics, and (3) the interaction between plant C dynamics and soil biological processes."
Carbon dioxide and water vapor exchange in a warm temperate grassland
(2004-01) Novick, Kimberly A.; Stoy, Paul C.; Katul, Gabriel G.; Ellsworth, D. S.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Oren, Ram
Grasslands cover about 40% of the ice-free global terrestrial surface, but their contribution to local and regional water and carbon fluxes and sensitivity to climatic perturbations such as drought remains uncertain. Here, we assess the direction and magnitude of net ecosystem carbon exchange (NEE) and its components, ecosystem carbon assimilation (A c) and ecosystem respiration (R E), in a southeastern United States grassland ecosystem subject to periodic drought and harvest using a combination of eddy-covariance measurements and model calculations. We modeled A c and evapotranspiration (ET) using a big-leaf canopy scheme in conjunction with ecophysiological and radiative transfer principles, and applied the model to assess the sensitivity of NEE and ET to soil moisture dynamics and rapid excursions in leaf area index (LAI) following grass harvesting. Model results closely match eddy-covariance flux estimations on daily, and longer, time steps. Both model calculations and eddy-covariance estimates suggest that the grassland became a net source of carbon to the atmosphere immediately following the harvest, but a rapid recovery in LAI maintained a marginal carbon sink during summer. However, when integrated over the year, this grassland ecosystem was a net C source (97 g C m−2 a−1) due to a minor imbalance between large A c (−1,202 g C m−2 a−1) and R E (1,299 g C m−2 a−1) fluxes. Mild drought conditions during the measurement period resulted in many instances of low soil moisture (θ<0.2 m3m−3), which influenced A c and thereby NEE by decreasing stomatal conductance. For this experiment, low θ had minor impact on R E. Thus, stomatal limitations to A c were the primary reason that this grassland was a net C source. In the absence of soil moisture limitations, model calculations suggest a net C sink of −65 g C m−2 a−1 assuming the LAI dynamics and physiological properties are unaltered. These results, and the results of other studies, suggest that perturbations to the hydrologic cycle are key determinants of C cycling in grassland ecosystems.
Causality and Persistence in Ecological Systems: A Nonparametric Spectral Granger Causality Approach
(2012-02-20) Detto, Matteo; Molini, Annalisa; Katul, Gabriel; Stoy, Paul C.; Palmroth, Sari; Baldocchi, Dennis
Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.
Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land‐surface models: An NACP analysis
(2014-07) Mathany, Ashley M.; Bohrer, Gil; Stoy, Paul C.; Baker, Ian T.; Black, Andy T.; Desai, Ankur R.; Gough, Christopher M.; Ivanov, Valeriy Y.; Jassal, Rachhpal S.; Novick, Kimberly A.; Schäfer, Karina V.R.; Verbeeck, Hans
Land-surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface-atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model-simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture-limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns.
Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site‐level synthesis
(2011-12-20) Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; M. Altaf Arain, M. Altaf; Baker, Ian T.; Blac, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Suyker, Andrew E.; Tain, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.; Weifeng, Wang; Weng, Ensheng
Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the identification of the dominant time scales contributing to model performance in the frequency domain. In this study we used wavelet analyses to synthesize the performance of 21 ecosystem models at 9 eddy covariance towers as part of the North American Carbon Program's site-level intercomparison. This study expands upon previous single-site and single-model analyses to determine what patterns of model error are consistent across a diverse range of models and sites. To assess the significance of model error at different time scales, a novel Monte Carlo approach was developed to incorporate flux observation error. Failing to account for observation error leads to a misidentification of the time scales that dominate model error. These analyses show that model error (1) is largest at the annual and 20–120 day scales, (2) has a clear peak at the diurnal scale, and (3) shows large variability among models in the 2–20 day scales. Errors at the annual scale were consistent across time, diurnal errors were predominantly during the growing season, and intermediate-scale errors were largely event driven. Breaking spectra into discrete temporal bands revealed a significant model-by-band effect but also a nonsignificant model-by-site effect, which together suggest that individual models show consistency in their error patterns. Differences among models were related to model time step, soil hydrology, and the representation of photosynthesis and phenology but not the soil carbon or nitrogen cycles. These factors had the greatest impact on diurnal errors, were less important at annual scales, and had the least impact at intermediate time scales.
Climate controls over the net carbon uptake period and amplitude of net ecosystem production in temperate and boreal ecosystems
(2017-09) Fu, Zheng; Stoy, Paul C.; Luo, Yiqi; Chen, Jiquan; Sun, Jian; Montagnani, Leonardo; Wohlfahrt, Georg; Rahman, Abdullah F.; Rambal, Serge; Bernhofer, Christian; Wang, Jinsong; Shirkey, Gabriela; Niu, Shuli
The seasonal and interannual variability of the terrestrial carbon cycle is regulated by the interactions of climate and ecosystem function. However, the key factors and processes determining the interannual variability of net ecosystem productivity (NEP) in different biomes are far from clear. Here, we quantified yearly anomalies of seasonal and annual NEP, net carbon uptake period (CUP), and the maximum daily NEP (NEPmax) in response to climatic variables in 24 deciduous broadleaf forest (DBF), evergreen forest (EF), and grassland (GRA) ecosystems that include at least eight years of eddy covariance observations. Over the 228 site-years studied, interannual variations in NEP were mostly explained by anomalies of CUP and NEPmax. CUP was determined by spring and autumn net carbon uptake phenology, which were sensitive to annual meteorological variability. Warmer spring temperatures led to an earlier start of net carbon uptake activity and higher spring and annual NEP values in DBF and EF, while warmer autumn temperatures in DBF, higher autumn radiation in EF, and more summer and autumn precipitation in GRA resulted in a later ending date of net carbon uptake and associated higher autumn and annual NEP. Anomalies in NEPmax s were determined by summer precipitation in DBF and GRA, and explained more than 50% of variation in summer NEP anomalies for all the three biomes. Results demonstrate the role of meteorological variability in controlling CUP and NEPmax, which in turn help describe the seasonal and interannual variability of NEP.
Climate mitigation potential and soil microbial response of cyanobacteria‐fertilized bioenergy crops in a cool semi‐arid cropland
(Wiley, 2022-10) Gay, Justin D.; Goemann, Hannah M.; Currey, Bryce; Stoy, Paul C.; Christiansen, Jesper Riis; Miller, Perry R.; Poulter, Benjamin; Peyton, Brent M.; Brookshire, E. N. Jack
Bioenergy carbon capture and storage (BECCS) systems can serve as decarbonization pathways for climate mitigation. Perennial grasses are a promising second-generation lignocellulosic bioenergy feedstock for BECCS expansion, but optimizing their sustainability, productivity, and climate mitigation potential requires an evaluation of how nitrogen (N) fertilizer strategies interact with greenhouse gas (GHG) and soil organic carbon (SOC) dynamics. Furthermore, crop and fertilizer choice can affect the soil microbiome which is critical to soil organic matter turnover, nutrient cycling, and sustaining crop productivity but these feedbacks are poorly understood due to the paucity of data from certain agroecosystems. Here, we examine the climate mitigation potential and soil microbiome response to establishing two functionally different perennial grasses, switchgrass (Panicum virgatum, C4) and tall wheatgrass (Thinopyrum ponticum, C3), in a cool semi-arid agroecosystem under two fertilizer applications, a novel cyanobacterial biofertilizer (CBF) and urea. We find that in contrast to the C4 grass, the C3 grass achieved 98% greater productivity and had a higher N use efficiency when fertilized. For both crops, the CBF produced the same biomass enhancement as urea. Non-CO2 GHG fluxes across all treatments were low and we observed a 3-year net loss of SOC under the C4 crop and a net gain under the C3 crop at a 0–30 cm soil depth regardless of fertilization. Finally, we detected crop-specific changes in the soil microbiome, including an increased relative abundance of arbuscular mycorrhizal fungi under the C3, and potentially pathogenic fungi in the C4 grass. Taken together, these findings highlight the potential of CBF-fertilized C3 crops as a second-generation bioenergy feedstock in semi-arid regions as a part of a climate mitigation strategy.
A Comparison of Methods Reveals that Enhanced Diffusion Helps Explain Cold-Season Soil CO 2 Efflux in a Lodgepole Pine Ecosystem
(2016-01) Rains, F. Aaron; Stoy, Paul C.; Welch, Christopher M.; Montagne, Cliff; McGlynn, Brian L.
Wintertime respiration contributes significantly to the annual loss of carbon from terrestrial ecosystems to the atmosphere, but the magnitude and physical transport mechanisms of this flux through snow remain unclear. Here, we quantify wintertime soil CO2 efflux in a Lodgepole pine (Pinus contorta Dougl.) forest by comparing chamber, flux gradient, and subcanopy eddy covariance measurements. CO2 efflux estimates from the flux gradient system deviated from the eddy covariance measurements during early and late winter but were only ca. 25% lower than eddy covariance measurements during the main snow accumulation period in mid-winter. During the snow-covered period, the flux gradient carbon efflux estimate (15 g C m− 2) was ca. three-fold less than eddy covariance measurements (49 g C m− 2). An analysis of the relationship between friction velocity and eddy covariance-measured CO2 efflux lends support to the notion that advection through snow is an important transport mechanism for trace gasses. A spectral Granger causality analysis indicates that the wind speed time series contributes information to the subnivean CO2 concentration time series during the melt period at time scales greater than 10 hours. All three methodologies indicate that wintertime respiration is a major contributor to the annual carbon budget: the sum of eddy covariance-measured CO2 efflux during the snow-covered period was 1/3 of that during the snow-free period of 2011 (ca. 140 g C m− 2). Future studies should incorporate adjustments for advection when using snow flux gradient systems to avoid underestimating the often-underappreciated contribution of the cold season to ecosystem CO2 efflux.
Controls on seasonal patterns of maximum ecosystem carbon uptake and canopy-scale photosynthetic light response: contributions from both temperature and photoperiod
(2014-02-14) Stoy, Paul C.; Trowbridge, Amy M.; Bauerle, William L.
Most models of photosynthetic activity assume that temperature is the dominant control over physiological processes. Recent studies have found, however, that photoperiod is a better descriptor than temperature of the seasonal variability of photosynthetic physiology at the leaf scale. Incorporating photoperiodic control into global models consequently improves their representation of the seasonality and magnitude of atmospheric CO2 concentration. The role of photoperiod versus that of temperature in controlling the seasonal variability of photosynthetic function at the canopy scale remains unexplored. We quantified the seasonal variability of ecosystem-level light response curves using nearly 400 site years of eddy covariance data from over eighty Free Fair-Use sites in the FLUXNET database. Model parameters describing maximum canopy CO2uptake and the initial slope of the light response curve peaked after peak temperature in about 2/3 of site years examined, emphasizing the important role of temperature in controlling seasonal photosynthetic function. Akaike’s Information Criterion analyses indicated that photoperiod should be included in models of seasonal parameter variability in over 90 % of the site years investigated here, demonstrating that photoperiod also plays an important role in controlling seasonal photosynthetic function. We also performed a Granger causality analysis on both gross ecosystem productivity (GEP) and GEP normalized by photosynthetic photon flux density (GEP n ). While photoperiod Granger-caused GEP and GEP n in 99 and 92 % of all site years, respectively, air temperature Granger-caused GEP in a mere 32 % of site years but Granger-caused GEP n in 81 % of all site years. Results demonstrate that incorporating photoperiod may be a logical step toward improving models of ecosystem carbon uptake, but not at the expense of including enzyme kinetic-based temperature constraints on canopy-scale photosynthesis.
Convective suppression before and during the United States Northern Great Plains flash drought of 2017
(2018-08) Gerken, Tobias; Bromley, Gabriel T.; Ruddell, Benjamin L.; Williams, Skylar; Stoy, Paul C.
Flash droughts tend to be disproportionately destructive because they intensify rapidly and are difficult to prepare for. We demonstrate that the 2017 US Northern Great Plains (NGP) flash drought was preceded by a breakdown of landâ€“atmosphere coupling. Severe drought conditions in the NGP were first identified by drought monitors in late May 2017 and rapidly progressed to exceptional drought in July. The likelihood of convective precipitation in May 2017 in northeastern Montana, however, resembled that of a typical August when rain is unlikely. Based on the lower tropospheric humidity index (HIlow), convective rain was suppressed by the atmosphere on nearly 50% of days during March in NE Montana and central North Dakota, compared to 30% during a normal year. Micrometeorological variables, including potential evapotranspiration (ETp), were neither anomalously high nor low before the onset of drought. Incorporating convective likelihood to drought forecasts would have noted that convective precipitation in the NGP was anomalously unlikely during the early growing season of 2017. It may therefore be useful to do so in regions that rely on convective precipitation.