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2. Contributors

Author

Angevine, Wayne M., primary, Arthur, Robert S., additional, Aubinet, Marc, additional, Berry, Kodi L., additional, Bohrer, Gil, additional, Butterworth, Brian, additional, Desai, Ankur R., additional, Hall, Peter K., additional, Hiscox, April L., additional, Kutter, Eric, additional, McCombs, Alexandria G., additional, Monson, Russell K., additional, Nappo, Carmen J., additional, Paleri, Sreenath, additional, Viner, Brian, additional, Yazbeck, Theresia, additional, and Yi, Chuixiang, additional

Published
2023
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8. Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Author

Albert, Loren P, Keenan, Trevor F, Burns, Sean P, Huxman, Travis E, and Monson, Russell K

Subjects
Zoology, Ecology, Evolutionary Biology, Biological Sciences, Climate Action, Carbon Dioxide, Climate, Ecosystem, Forests, Seasons, Trees, Coniferous, Model-data assimilation, Photosynthesis, Fluxnet, Eddy covariance, Evolutionary biology
Abstract

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone.

Published
2017

9. Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy‐scale photosynthesis

Author

Toomey, Michael, Friedl, Mark A, Frolking, Steve, Hufkens, Koen, Klosterman, Stephen, Sonnentag, Oliver, Baldocchi, Dennis D, Bernacchi, Carl J, Biraud, Sebastien C, Bohrer, Gil, Brzostek, Edward, Burns, Sean P, Coursolle, Carole, Hollinger, David Y, Margolis, Hank A, Mccaughey, Harry, Monson, Russell K, Munger, J William, Pallardy, Stephen, Phillips, Richard P, Torn, Margaret S, Wharton, Sonia, Zeri, Marcelo, And, Andrew D, and Richardson, Andrew D

Subjects
Plant Biology, Biological Sciences, Forests, Photography, Photosynthesis, Pigments, Biological, Plants, Seasons, Time Factors, deciduous broadleaf forest, digital repeat photography, evergreen needleleaf forest, grassland, gross primary productivity, PhenoCam, phenology, photosynthesis, seasonality, Environmental Sciences, Agricultural and Veterinary Sciences, Ecology, Agricultural, veterinary and food sciences, Biological sciences, Environmental sciences
Abstract

The proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. We used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.

Published
2015

10. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M. Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K., Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D., Bohrer, Gil, Boike, Julia, Bolstad, Paul V., Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R., Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P., Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R., Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D., Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S., D’Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J., De Cinti, Bruno, de Grandcourt, Agnes, De Ligne, Anne, De Oliveira, Raimundo C., Delpierre, Nicolas, Desai, Ankur R., Di Bella, Carlos Marcelo, di Tommasi, Paul, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M., Eugster, Werner, Ewenz, Cacilia M., Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janouš, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jørgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Rebmann, Corinna, Reed, David, de Dios, Victor Resco, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlák, Pavel, Serrano-Ortíz, Penélope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

Published
2021
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11. Observations and models of emissions of volatile terpenoid compounds from needles of ponderosa pine trees growing in situ: control by light, temperature and stomatal conductance

Author

Harley, Peter, Eller, Allyson, Guenther, Alex, and Monson, Russell K

Subjects
Abscisic Acid, Acyclic Monoterpenes, Bicyclic Monoterpenes, Carbon Isotopes, Colorado, Gas Chromatography-Mass Spectrometry, Light, Models, Biological, Monoterpenes, Pentanols, Pinus ponderosa, Plant Leaves, Plant Stomata, Seasons, Temperature, Terpenes, Volatile Organic Compounds, BVOC emissions, 2-Methyl-3-buten-2-ol, C-13 labeling, Linalool, Ecology
Abstract

Terpenoid emissions from ponderosa pine (Pinus ponderosa subsp. scopulorum) were measured in Colorado, USA over two growing seasons to evaluate the role of incident light, needle temperature, and stomatal conductance in controlling emissions of 2-methyl-3-buten-2-ol (MBO) and several monoterpenes. MBO was the dominant daylight terpenoid emission, comprising on average 87% of the total flux, and diurnal variations were largely determined by light and temperature. During daytime, oxygenated monoterpenes (especially linalool) comprised up to 75% of the total monoterpenoid flux from needles. A significant fraction of monoterpenoid emissions was dependent on light and 13CO2 labeling studies confirmed de novo production. Thus, modeling of monoterpenoid emissions required a hybrid model in which a significant fraction of emissions was dependent on both light and temperature, while the remainder was dependent on temperature alone. Experiments in which stomata were forced to close using abscisic acid demonstrated that MBO and a large fraction of the monoterpene flux, presumably linalool, could be limited at the scale of seconds to minutes by stomatal conductance. Using a previously published model of terpenoid emissions, which explicitly accounts for the physicochemical properties of emitted compounds, we were able to simulate these observed stomatal effects, whether induced experimentally or arising under naturally fluctuation conditions of temperature and light. This study shows unequivocally that, under naturally occurring field conditions, de novo light-dependent monoterpenes comprise a significant fraction of emissions in ponderosa pine. Differences between the monoterpene composition of ambient air and needle emissions imply a significant non-needle emission source enriched in Δ-3-carene.

Published
2014

17. Perspectives on next-generation technology for environmental sensor networks

Author

Benson, Barbara J, Bond, Barbara J, Hamilton, Michael P, Monson, Russell K, and Han, Richard

Subjects
sensor networks, ecological informatics
Abstract

Sensor networks promise to transform and expand environmental science. However, many technological dif- ficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization schemes, integrating appropriate communication protocols, streamlining data management and access, using innovative graphic and statistical analyses, and enabling both scientists and the public to access the results. Multidisciplinary partnerships are making major contribu- tions to technological advances, and we showcase examples of this exciting new technology, as well as new approaches for training researchers to make effective use of emerging tools.

Published
2010

18. Controls over ozone deposition to a high elevation subalpine forest

Author

Turnipseed, Andrew A, Burns, Sean P, Moore, David JP, Hu, Jia, Guenther, Alex B, and Monson, Russell K

Subjects
Biological Sciences, Ecology, Earth Sciences, Plant Biology, Atmospheric Sciences, Ozone deposition, Eddy covariance, Coniferous forest, Stomatal conductance, Agricultural and Veterinary Sciences, Meteorology & Atmospheric Sciences, Agricultural, veterinary and food sciences, Biological sciences, Earth sciences
Abstract

Ecosystem level ozone (O₃) fluxes during four different years were examined at a subalpine forest site in the Colorado Rocky Mountains. The local mountain-valley wind system and the proximity of the Denver Metropolitan area leads to high summertime ozone episodes on many afternoons. The timing between these episodes and the ecosystem processes controlling photosynthesis during the growing season plays a critical role in determining the amount of ozone deposition. Light and vapor pressure deficit (VPD) were the most dominant environmental drivers controlling the deposition of O₃ at this site through their influence on stomatal conductance. 81% of the daytime O₃ uptake was predicted to occur through the stomata. Stomatal uptake decreased at high VPD and temperatures leading to an overall decrease in O₃ flux; however, we did observe a non-stomatal conductance for O₃ that increased slightly with temperature before leveling off at higher values. During the growing season, O₃ deposition fluxes were enhanced after midday precipitation events and continued at elevated levels throughout the following night, implying a role for surface wetness. From nighttime data, evidence for both the presence of water films on the needles and non-closure of the plant stomata were observed. During the winter (non-growing) season, the ozone deposition velocity showed a consistent dependency on the latent heat flux. Although the mechanism is unclear, it is apparent that precipitation events play a role here through their influence on latent heat flux.

Published
2009

19. Response of isoprene emission to ambient CO2 changes and implications for global budgets

Author

HEALD, COLETTE L, WILKINSON, MICHAEL J, MONSON, RUSSELL K, ALO, CLEMENT A, WANG, GUILING, and GUENTHER, ALEX

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, 2100, CAM, carbon dioxide, climate change, CLM, emission, isoprene, MEGAN, Vostok, Environmental Sciences, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

We explore the potential role of atmospheric carbon dioxide (CO₂) on isoprene emissions using a global coupled land-atmosphere model [Community Atmospheric Model-Community Land Model (CAM-CLM)] for recent (year 2000, 365 ppm CO₂) and future (year 2100, 717 ppm CO₂) conditions. We incorporate an empirical model of observed isoprene emissions response to both ambient CO₂ concentrations in the long-term growth environment and short-term changes in intercellular CO₂ concentrations into the MEGAN biogenic emission model embedded within the CLM. Accounting for CO₂ inhibition has little impact on predictions of present-day global isoprene emission (increase from 508 to 523 Tg C yr⁻¹). However, the large increases in future isoprene emissions typically predicted in models, which are due to a projected warmer climate, are entirely offset by including the CO₂ effects. Projected global isoprene emissions in 2100 drop from 696 to 479 Tg C yr⁻¹ when this effect is included, maintaining future isoprene sources at levels similar to present day. The isoprene emission response to CO₂ is dominated by the long-term growth environment effect, with modulations of 10% or less due to the variability in intercellular CO₂ concentration. As a result, perturbations to isoprene emissions associated with changes in ambient CO₂ are largely aseasonal, with little diurnal variability. Future isoprene emissions increase by more than a factor of two in 2100 (to 1242 Tg C yr⁻¹) when projected changes in vegetation distribution and leaf area density are included. Changing land cover and the role of nutrient limitation on CO₂ fertilization therefore remain the largest source of uncertainty in isoprene emission prediction. Although future projections suggest a compensatory balance between the effects of temperature and CO₂ on isoprene emission, the enhancement of isoprene emission due to lower ambient CO₂ concentrations did not compensate for the effect of cooler temperatures over the last 400 thousand years of the geologic record (including the Last Glacial Maximum).

Published
2009

24. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M. Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K., Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D., Bohrer, Gil, Boike, Julia, Bolstad, Paul V., Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R., Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P., Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R., Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D., Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S., D’Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J., Cinti, Bruno De, Grandcourt, Agnes de, Ligne, Anne De, De Oliveira, Raimundo C., Delpierre, Nicolas, Desai, Ankur R., Di Bella, Carlos Marcelo, Tommasi, Paul di, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M., Eugster, Werner, Ewenz, Cacilia M., Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janouš, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jørgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Rebmann, Corinna, Reed, David, Dios, Victor Resco de, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlák, Pavel, Serrano-Ortíz, Penélope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

Published
2020
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46. Modelling changes in VOC emission in response to climate change in the continental United States

Author

Constable, JohN VH, Guenther, AleX B, Schimel, David S, and Monson, Russell K

Subjects
Climate Action, climate change, isoprene, modelling, monoterpenes, VOC emission, Environmental Sciences, Biological Sciences, Ecology
Abstract

The alteration of climate is driven not only by anthropogenic activities, but also by biosphere processes that change in conjunction with climate. Emission of volatile organic compounds (VOCs) from vegetation may be particularly sensitive to changes in climate and may play an important role in climate forcing through their influence on the atmospheric oxidative balance, greenhouse gas concentration, and the formation of aerosols. Using the VEMAP vegetation database and associated vegetation responses to climate change, this study examined the independent and combined effects of simulated changes in temperature, CO2 concentration, and vegetation distribution on annual emissions of isoprene, monoterpenes, and other reactive VOCs (ORVOCs) from potential vegetation of the continental United States. Temperature effects were modelled according to the direct influence of temperature on enzymatic isoprene production and the vapour pressure of monoterpenes and ORVOCs. The effect of elevated CO2 concentration was modelled according to increases in foliar biomass per unit of emitting surface area. The effects of vegetation distribution reflects simulated changes in species spatial distribution and areal coverage by 21 different vegetation classes. Simulated climate warming associated with a doubled atmospheric CO2 concentration enhanced total modelled VOC emission by 81.8% (isoprene +82.1%, monoterpenes +81.6%, ORVOC +81.1%), whereas a simulated doubled CO2 alone enhanced total modelled VOC emission by only +11.8% (isoprene +13.7%, monoterpenes +4.1%, ORVOC +11.7%). A simulated redistribution of vegetation in response to altered temperatures and precipitation patterns caused total modelled VOC emission to decline by 10.4% (isoprene -11.7%, monoterpenes -18.6%, ORVOC 0.0%) driven by a decline in area covered by vegetation classes emitting VOCs at high rates. Thus, the positive effect of leaf-level adjustments to elevated CO2 (i.e. increases in foliar biomass) is balanced by the negative effect of ecosystem-level adjustments to climate (i.e. decreases in areal coverage of species emitting VOC at high rates).

Published
1999

47. Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

Author

Volkmann, Till H. M., primary, Sengupta, Aditi, additional, Pangle, Luke A., additional, Dontsova, Katerina, additional, Barron-Gafford, Greg A., additional, Harman, Ciaran J., additional, Niu, Guo-Yue, additional, Meredith, Laura K., additional, Abramson, Nate, additional, Neto, Antonio A. Meira, additional, Wang, Yadi, additional, Adams, John R., additional, Breshears, David D., additional, Bugaj, Aaron, additional, Chorover, Jon, additional, Cueva, Alejandro, additional, DeLong, Stephen B., additional, Durcik, Matej, additional, Ferre, Ty P. A., additional, Hunt, Edward A., additional, Huxman, Travis E., additional, Kim, Minseok, additional, Maier, Raina M., additional, Monson, Russell K., additional, Pelletier, Jon D., additional, Pohlmann, Michael, additional, Rasmussen, Craig, additional, Ruiz, Joaquin, additional, Saleska, Scott R., additional, Schaap, Marcel G., additional, Sibayan, Michael, additional, Tuller, Markus, additional, Haren, Joost L. M. van, additional, Zeng, Xubin, additional, and Troch, Peter A., additional

Published
2018
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