Stoy Lab
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/14931
In the Stoy Lab, we study the role of vegetation in the climate system. To do so we measure and model the exchange of water, heat, and trace gases like carbon dioxide and methane between the terrestrial surface and the atmosphere. Recent efforts seek to understand feedbacks between land management and precipitation processes.
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Item Interannual variability of ecosystem carbon exchange: From observation to prediction(2017-09) Niu, Shuli; Zheng, Fu; Yiqi, Luo; Stoy, Paul C.; Keenan, Trevor F.; Poulter, Benjamin; Zhang, Leiming; Piao, Shilong; Zhou, Xuhui; Zheng, Han; Han, Jiayin; Wang, Qiufeng; Yu, GuiruiAim Terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location Global terrestrial ecosystems. Methods We conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. Results The phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi‐arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. Main conclusions To improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time‐series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.Item Land management and land-cover change have impacts of similar magnitude on surface temperature(2014-04) Luyssaert, Sebastiaan; Jammet, Mathilde; Stoy, Paul C.; Estel, Stephan; Pongratz, Julia; Ceschia, Eric; Churkina, Galina; Don, A.; Erb, K.; Ferlicoq, M.; Gielen, Bert; Grünwald, Thomas; Houghton, Richard A.; Klumpp, K.; Knohl, A.; Kolb, T.; Kuemmerle, T.; Laurila, T.; Lohila, A.; Loustau, Denis; Meyfroidt, P.; Moors, Eddy J.; Novick, Kimberly A.; Otto, Juliane; Pilegaard, Kim; Pio, C. A.; Rambal, Serge; Rebmann, C.; Ryder, J.; Suyker, Andrew E.; Varlagin, Andrej B.; Wattenbach, M.; Dolman, A. J.Anthropogenic changes to land cover (LCC) remain common, but continuing land scarcity promotes the widespread intensification of land management changes (LMC) to better satisfy societal demand for food, fibre, fuel and shelter1. The biophysical effects of LCC on surface climate are largely understood2,3,4,5, particularly for the boreal6 and tropical zones7, but fewer studies have investigated the biophysical consequences of LMC; that is, anthropogenic modification without a change in land cover type. Harmonized analysis of ground measurements and remote sensing observations of both LCC and LMC revealed that, in the temperate zone, potential surface cooling from increased albedo is typically offset by warming from decreased sensible heat fluxes, with the net effect being a warming of the surface. Temperature changes from LMC and LCC were of the same magnitude, and averaged 2 K at the vegetation surface and were estimated at 1.7 K in the planetary boundary layer. Given the spatial extent of land management (42–58% of the land surface) this calls for increasing the efforts to integrate land management in Earth System Science to better take into account the human impact on the climate8.Item 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.Item Separation of Net Ecosystem Exchange into Assimilation and Respiration Using a Light Response Curve Approach: Critical Issues and Global Evaluation(2010-01) Lasslop, Gitta; Reichstein, Markus; Papale, Dario; Richardson, Andrew D.; Arneth, Almut; Barr, Alan G.; Stoy, Paul C.; Wohlfahrt, GeorgThe measured net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere reflects the balance between gross CO2 assimilation [gross primary production (GPP)] and ecosystem respiration (Reco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light–response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of Reco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher Reco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m−2 yr−1), while errors arising from the random error (median absolute deviation: ∼2 g C m−2 yr−1) are negligible. Despite site‐specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and Reco is not spurious but holds true when quasi‐independent, i.e. daytime and nighttime based estimates are compared.Item Productivity, Respiration, and Light-Response Parameters of World Grassland and Agroecosystems Derived From Flux-Tower Measurements(2010-01) Gilmanov, Tagir G.; Aires, Luis M. I.; Barcza, Zoltan; Baron, Vern S.; Belelli, Luca; Beringer, Jason; Billesbach, David; Bonal, Damien; Bradford, James A.; Ceschia, Eric; Cook, D.; Corradi, Chiara A. R.; Frank, Albert B.; Gianelle, Damiano; Gimeno, Cristina; Gruenwald, Thomas; Guo, Haiqiang; Hanan, Niall; Haszpra, Laszlo; Heilman, J.; Jacobs, Adrie F. G.; Jones, Mike B.; Johnson, Douglas A.; Kiely, Gerard K.; Li, Shenggong; Magliulo, Vincenzo; Moors, Eddy; Nagy, Zoltan; Nasyrov, M.; Owensby, Clenton E.; Pintér, Krisztina; Pio, Casimiro; Reichstein, Markus; Sanz-Sanchez, Maria José; Scott, Russell L.; Soussana, Jean-Francois; Stoy, Paul C.; Svejcar, T.; Tuba, Zoltán; Zhou, GuangshengGrasslands and agroecosystems occupy one-third of the terrestrial area, but their contribution to the global carbon cycle remains uncertain. We used a set of 316 site-years of CO2 exchange measurements to quantify gross primary productivity, respiration, and light-response parameters of grasslands, shrublands/savanna, wetlands, and cropland ecosystems worldwide. We analyzed data from 72 global flux-tower sites partitioned into gross photosynthesis and ecosystem respiration with the use of the light-response method (Gilmanov, T. G., D. A. Johnson, and N. Z. Saliendra. 2003. Growing season CO2 fluxes in a sagebrush-steppe ecosystem in Idaho: Bowen ratio/energy balance measurements and modeling. Basic and Applied Ecology 4:167–183) from the RANGEFLUX and WORLDGRASSAGRIFLUX data sets supplemented by 46 sites from the FLUXNET La Thuile data set partitioned with the use of the temperature-response method (Reichstein, M., E. Falge, D. Baldocchi, D. Papale, R. Valentini, M. Aubinet, P. Berbigier, C. Bernhofer, N. Buchmann, M. Falk, T. Gilmanov, A. Granier, T. Grünwald, K. Havránková, D. Janous, A. Knohl, T. Laurela, A. Lohila, D. Loustau, G. Matteucci, T. Meyers, F. Miglietta, J. M. Ourcival, D. Perrin, J. Pumpanen, S. Rambal, E. Rotenberg, M. Sanz, J. Tenhunen, G. Seufert, F. Vaccari, T. Vesala, and D. Yakir. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11:1424–1439). Maximum values of the quantum yield (α=75 mmol · mol−1), photosynthetic capacity (Amax=3.4 mg CO2 · m−2 · s−1), gross photosynthesis (Pg,max=116 g CO2 · m−2 · d−1), and ecological light-use efficiency (εecol=59 mmol · mol−1) of managed grasslands and high-production croplands exceeded those of most forest ecosystems, indicating the potential of nonforest ecosystems for uptake of atmospheric CO2. Maximum values of gross primary production (8 600 g CO2 · m−2 · yr−1), total ecosystem respiration (7 900 g CO2 · m−2 · yr−1), and net CO2 exchange (2 400 g CO2 · m−2 · yr−1) were observed for intensively managed grasslands and high-yield crops, and are comparable to or higher than those for forest ecosystems, excluding some tropical forests. On average, 80% of the nonforest sites were apparent sinks for atmospheric CO2, with mean net uptake of 700 g CO2 · m−2 · yr−1 for intensive grasslands and 933 g CO2 · m−2 · d−1 for croplands. However, part of these apparent sinks is accumulated in crops and forage, which are carbon pools that are harvested, transported, and decomposed off site. Therefore, although agricultural fields may be predominantly sinks for atmospheric CO2, this does not imply that they are necessarily increasing their carbon stock.Item Eddy covariance measurements of methane flux at a tropical peat forest in Sarawak, Malaysian Borneo(2018-05) Tang, Angela C. I.; Stoy, Paul C.; Hirata, Ryuichi; Musin, Kevin K.; Aeries, Edward B.; Wenceslaus, Joseph; Melling, LulieTropical biogenic sources are a likely cause of the recent increase in global atmospheric methane concentration. To improve our understanding of tropical methane sources, we used the eddy covariance technique to measure CH4 flux (FCH4) between a tropical peat forest ecosystem and the atmosphere in Malaysian Borneo over a 2‐month period during the wet season. Mean daily FCH4 during the measurement period, on the order of 0.024 g C‐CH4·m−2·day−1, was similar to eddy covariance FCH4 measurements from tropical rice agroecosystems and boreal fen ecosystems. A linear modeling analysis demonstrated that air temperature (Tair) was critical for modeling FCH4 before the water table breached the surface and that water table alone explained some 20% of observed FCH4 variability once standing water emerged. Future research should measure FCH4 on an annual basis from multiple tropical ecosystems to better constrain tropical biogenic methane sources.Item Toward a socioecological theory of forest macrosystems(2018-04) Kleindl, William J.; Stoy, Paul C.; Binford, Michael W.; Desai, Ankur R.; Dietze, Michael C.; Schultz, Courtney A.; Starr, Gregory; Staudhammer, Christina L.; Wood, David J. A.The implications of cumulative land-use decisions and shifting climate on forests, require us to integrate our understanding of ecosystems, markets, policy, and resource management into a social-ecological system. Humans play a central role in macrosystem dynamics, which complicates ecological theories that do not explicitly include human interactions. These dynamics also impact ecological services and related markets, which challenges economic theory. Here, we use two forest macroscale management initiatives to develop a theoretical understanding of how management interacts with ecological functions and services at these scales and how the multiple large-scale management goals work either in consort or conflict with other forest functions and services. We suggest that calling upon theories developed for organismal ecology, ecosystem ecology, and ecological economics adds to our understanding of social-ecological macrosystems. To initiate progress, we propose future research questions to add rigor to macrosystem-scale studies: (1) What are the ecosystem functions that operate at macroscales, their necessary structural components, and how do we observe them? (2) How do systems at one scale respond if altered at another scale? (3) How do we both effectively measure these components and interactions, and communicate that information in a meaningful manner for policy and management across different scales?Item An evaluation of semi-empirical models for partitioning photosynthetically active radiation into diffuse and direct beam components(2018-02) Oliphant, Andrew J.; Stoy, Paul C.Photosynthesis is more efficient under diffuse than direct beam photosynthetically activeradiation (PAR) per unit PAR, but diffuse PAR is infrequently measured at research sites. We examine fourcommonly used semiempirical models (Erbs et al., 1982, https://doi.org/10.1016/0038-092X(82)90302-4; Guet al., 1999, https://doi.org/10.1029/1999JD901068; Roderick, 1999, https://doi.org/10.1016/S0168-1923(99)00028-3; Weiss & Norman, 1985, https://doi.org/10.1016/0168-1923(85)90020-6) that partition PARinto diffuse and direct beam components based on the negative relationship between atmospherictransparency and scattering of PAR. Radiation observations at 58 sites (140 site years) from the La ThuilleFLUXNET data set were used for model validation and coefficient testing. All four models did a reasonable jobof predicting the diffuse fraction of PAR (ϕ) at the 30 min timescale, with site median r2values rangingbetween 0.85 and 0.87, model efficiency coefficients (MECs) between 0.62 and 0.69, and regression slopeswithin 10% of unity. Model residuals were not strongly correlated with astronomical or standardmeteorological variables. We conclude that the Roderick (1999, https://doi.org/10.1016/S0168-1923(99)00028-3) and Gu et al. (1999, https://doi.org/10.1029/1999JD901068) models performed betteroverall than the two older models. Using the basic form of these models, the data set was used to find bothindividual site and universal model coefficients that optimized predictive accuracy. A new universal form ofthe model is presented in section 5 that increased site median MEC to 0.73. Site-specific modelcoefficients increased median MEC further to 0.78, indicating usefulness of local/regional training ofcoefficients to capture the local distributions of aerosols and cloud types.Item 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.Item 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.