Russell K. Monson

University of Colorado Boulder

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Sean P. Burns

University of Colorado Boulder

Dennis Baldocchi

University of California, Berkeley

J. William Munger

Planetary Science Institute

A. H. Goldstein

University of California, Berkeley

Steven C. Wofsy

Harvard University

David Y. Hollinger

Northern Research Station

Andrew A. Turnipseed

University of Colorado System

Paul Szejner

Natural Resources Institute Finland

Soumaya Belmecheri

University of Arizona

B. E. Law

Oregon State University

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University of Colorado Boulder

106

NSF National Center for Atmospheric Research

University of Arizona

Cooperative Institute for Research in Environmental Sciences

University of California, Berkeley

National Oceanic and Atmospheric Administration

Colorado State University

Northern Arizona University

Chinese Academy of Sciences

University of Colorado System

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Volatile organic compound emissions from terrestrial ecosystems: A primary biological control over atmospheric chemistry

Israel Journal of Chemistry (2002)

Russell K. Monson

Abstract Plants produce a variety of non‐methane volatile organic compounds (NMVOCs) that react with photochemical components of the atmosphere and influence the production of atmospheric oxidants. In this review, the case is made that biogenic NMVOC emissions exert one of the primary controls over regional and global atmospheric chemistry. The diversity of biogenic, reactive organic compounds capable of fueling atmospheric chemistry is immense, including terpenes, alcohols, aldehydes, ketones, and organic acids. Considerable effort has been devoted to the design of models capable of predicting NMVOC emission rates, and thus driving atmospheric chemistry models. Over the past decade, however, what once seemed like promising conceptual connections of NMVOC emissions to fundamental biochemical processes such as photosynthesis, have not been realized; this has delayed the development of mechanistic NMVOC emissions models. Future progress in this area will require new subcellular experimental systems, and the biochemical insight that will accompany these investigations. The past use of existing coupled biogenic emission—photochemistry models at the global scale, even with their mechanistic limitations, has revealed the potential for NMVOC emissions from terrestrial ecosystems to cause reductions in tropospheric hydroxyl radical concentration and increases in the concentration and lifetime of radiatively important trace gases such as methane and ozone.

Atmospheric chemistry

Primary (astronomy)

Trace gas

Volatile organic compound

Terrestrial ecosystem

10.1560/0jjc-xqaa-jx0g-fxjg

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Citations (35)

Differential controls by climate and physiology over the emission rates of biogenic volatile organic compounds from mature trees in a semi-arid pine forest

Oecologia (2015)

Allyson S. D. Eller Lindsay L. Young Amy M. Trowbridge Russell K. Monson

Stomatal Conductance

Water Use Efficiency

Photosynthetic capacity

10.1007/s00442-015-3474-4

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Citations (16)

A model‐data intercomparison of CO₂ exchange across North America: Results from the North American Carbon Program site synthesis

Journal of Geophysical Research Atmospheres (2010)

Christopher R. Schwalm C. A. Williams Kevin Schaefer Robert S. Anderson M. Altaf Arain

Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO 2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO 2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.

Biome

Biosphere model

Temperate deciduous forest

Temperate forest

Temperate rainforest

Seasonality

Terrestrial ecosystem

Ecosystem model

10.1029/2009jg001229

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Citations (297)

Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables

Global Change Biology (2009)

Wenping Yuan Yiqi Luo Andrew D. Richardson Ram Oren Sebastiaan Luyssaert

Abstract Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO 2 based on 163 site‐years of eddy covariance data, from 39 northern‐hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.

Carbon sink

10.1111/j.1365-2486.2009.01870.x

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Citations (110)

Correction to: Atmospheric Stability Effects on Wind Fields and Scalar Mixing Within and Just Above a Subalpine Forest in Sloping Terrain

Boundary-Layer Meteorology (2019)

Sean P. Burns Jielun Sun Donald H. Lenschow Steven Oncley B. B. Stephens

Mistake

Subalpine forest

10.1007/s10546-019-00436-5

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Modeling the isoprene emission rate from leaves

New Phytologist (2012)

Russell K. Monson Rüdiger Grote Ülo Niinemets Jörg‐Peter Schnitzler

The leaves of many plants emit isoprene (2-methyl-1,3-butadiene) to the atmosphere, a process which has important ramifications for global and regional atmospheric chemistry. Quantitation of leaf isoprene emission and its response to environmental variation are described by empirically derived equations that replicate observed patterns, but have been linked only in some cases to known biochemical and physiological processes. Furthermore, models have been proposed from several independent laboratories, providing multiple approaches for prediction of emissions, but with little detail provided as to how contrasting models are related. In this review we provide an analysis as to how the most commonly used models have been validated, or not, on the basis of known biochemical and physiological processes. We also discuss the multiple approaches that have been used for modeling isoprene emission rate with an emphasis on identifying commonalities and contrasts among models, we correct some mathematical errors that have been propagated through the models, and we note previously unrecognized covariances within processes of the models. We come to the conclusion that the state of isoprene emission modeling remains highly empirical. Where possible, we identify gaps in our knowledge that have prevented us from achieving a greater mechanistic foundation for the models, and we discuss the insight and data that must be gained to fill those gaps.

Isoprene

10.1111/j.1469-8137.2012.04204.x

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Citations (118)

Assessing FPAR source and parameter optimization scheme in application of a diagnostic carbon flux model

Remote Sensing of Environment (2009)

David P. Turner William D. Ritts Sonia Wharton Christoph Thomas Russell K. Monson

Biome

Photosynthetically active radiation

SeaWiFS

Ecosystem respiration

10.1016/j.rse.2009.03.003

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Citations (25)

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

Scientific Data (2021)

Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

10.1038/s41597-021-00851-9

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Citations (76)

Beyond greenness: Detecting temporal changes in photosynthetic capacity with hyperspectral reflectance data

PLoS ONE (2017)

Mallory L. Barnes David D. Breshears Darin J. Law Willem van Leeuwen Russell K. Monson

Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season. We quantify photosynthetic capacity as the maximum rate of RuBP carboxylation (Vcmax) and regeneration (Jmax). Vcmax and Jmax vary within-season due to interactions between ontogenetic processes and meteorological variables. Remote sensing-based estimation of Vcmax and Jmax using leaf reflectance spectra is promising, but temporal variation in relationships between these key determinants of photosynthetic capacity, leaf reflectance spectra, and the models that link these variables has not been evaluated. To address this issue, we studied hybrid poplar (Populus spp.) during a 7-week mid-summer period to quantify seasonally-dynamic relationships between Vcmax, Jmax, and leaf spectra. We compared in situ estimates of Vcmax and Jmax from gas exchange measurements to estimates of Vcmax and Jmax derived from partial least squares regression (PLSR) and fresh-leaf reflectance spectroscopy. PLSR models were robust despite dynamic temporal variation in Vcmax and Jmax throughout the study period. Within-population variation in plant stress modestly reduced PLSR model predictive capacity. Hyperspectral vegetation indices were well-correlated to Vcmax and Jmax, including the widely-used Normalized Difference Vegetation Index. Our results show that hyperspectral estimation of plant physiological traits using PLSR may be robust to temporal variation. Additionally, hyperspectral vegetation indices may be sufficient to detect temporal changes in photosynthetic capacity in contexts similar to those studied here. Overall, our results highlight the potential for hyperspectral remote sensing to estimate determinants of photosynthetic capacity during periods with dynamic temporal variations related to seasonality and plant stress, thereby improving estimates of plant productivity and characterization of the associated carbon budget.

Photosynthetic capacity

Enhanced vegetation index

Seasonality

10.1371/journal.pone.0189539

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Citations (67)

A nonparametric method for separating photosynthesis and respiration components in CO₂ flux measurements

Geophysical Research Letters (2004)

Chuixiang Yi Runze Li Peter S. Bakwin Ankur R. Desai D. M. Ricciuto

Future climate change is expected to affect ecosystem‐atmosphere CO 2 exchange, particularly through the influence of temperature. To date, however, few studies have shown that differences in the response of net ecosystem CO 2 exchange (NEE) to temperature among ecosystems can be explained by differences in the photosynthetic and respiratory processes that compose NEE. Using a new nonparametric statistical model, we analyzed data from four forest ecosystems. We observed that differences among forests in their ability to assimilate CO 2 as a function of temperature were attributable to consistent differences in the temperature dependence of photosynthesis and respiration. This observation provides empirical validation of efforts to develop models of NEE from the first‐principle relationships between photosynthetic and respiratory processes and climate. Our results also showed that models of seasonal dynamics in NEE that lack specific consideration of the temperature dependence of respiration and photosynthesis are likely to carry significant uncertainties.

Terrestrial ecosystem

10.1029/2004gl020490

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Citations (28)