Joe R. Melton


2023

DOI bib
A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)
Bo Qu, Alexandre Roy, Joe R. Melton, T. Andrew Black, B. D. Amiro, E. S. Euskirchen, Masahito Ueyama, Hideki Kobayashi, Christopher Schulze, Gabriel Hould Gosselin, Alex J. Cannon, Matteo Detto, Oliver Sonnentag
Environmental Research Letters, Volume 18, Issue 8

Abstract Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO 2 ) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce ( Picea mariana )-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parameterize, force, and evaluate TEMs. Specifically, it includes half-hourly, gap-filled meteorological forcing data, ancillary data essential for model parameterization, and half-hourly, gap-filled or partitioned component flux data on CO 2 (net ecosystem production, gross primary production [GPP], and ecosystem respiration [ER]) and energy (latent [LE] and sensible heat [H]) and their daily aggregates screened based on half-hourly gap-filling quality criteria. We present a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to: (1) demonstrate the utility of our dataset to benchmark TEMs and (2) provide guidance for model development and refinement. Model skill was evaluated using several statistical metrics and further examined through the flux responses to their environmental controls. Our results suggest that CLASSIC tended to overestimate GPP and ER among all stands. Model performance regarding the energy fluxes (i.e., LE and H) varied greatly among the stands and exhibited a moderate correlation with latitude. We identified strong relationships between simulated fluxes and their environmental controls except for H, thus highlighting current strengths and limitations of CLASSIC.

DOI bib
Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
Gavin McNicol, Etienne Fluet‐Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang‐Yu Chang, Min Chen, Kyle Delwiche, Sarah Féron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, W. J. Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David P. Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, E. S. Euskirchen, Jordan P. Goodrich, Timothy J. Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John S. King, Franziska Koebsch, Randall K. Kolka, Ken W. Krauss, Annalea Lohila, Ivan Mammarella, Mats E Nilson, Asko Noormets, Walter C. Oechel, Matthias Peichl, Torsten Sachs, Ayaka Sakabe, Christopher Schulze, Oliver Sonnentag, Ryan C. Sullivan, Eeva‐Stiina Tuittila, Masahito Ueyama, Timo Vesala, Eric J. Ward, Christian Wille, Guan Xhuan Wong, Donatella Zona, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
AGU Advances, Volume 4, Issue 5

Abstract Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account for a large source of uncertainty in the global CH 4 budget. Data‐driven upscaling of CH 4 fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH 4 emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH 4 flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH 4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH 4 emissions of 146 ± 43 TgCH 4 y −1 for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH 4 y −1 ) and overlaps with top‐down atmospheric inversion models (155–200 TgCH 4 y −1 ). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH 4 fluxes has the potential to produce realistic extra‐tropical wetland CH 4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC ( https://doi.org/10.3334/ORNLDAAC/2253 ).

2022

DOI bib
Characterizing performance of freshwater wetland methane models across time scales at FLUXNET-CH4 sites using wavelet analyses
Zhen Zhang, Sheel Bansal, Kuang‐Yu Chang, Etienne Fluet‐Chouinard, Kyle Delwiche, Mathias Goeckede, A. F. Gustafson, Sara Knox, Antti Leppänen, Licheng Liu, Jinxun Liu, Avni Malhotra, Tiina Markkanen, Gavin McNicol, Joe R. Melton, Paul Miller, Changhui Peng, Maarit Raivonen, W. J. Riley, Oliver Sonnentag, Tuula Aalto, Rodrigo Vargas, Wenxin Zhang, Qing Zhu, Qiuan Zhu, Qianlai Zhuang, L. Windham‐Myers, Robert B. Jackson, Benjamin Poulter

Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach has been developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that 1) significant model-observation disagreements are mainly at short- to intermediate time scales (< 15 days); 2) most of the models can capture the CH4 variability at long time scales (> 32 days) for the boreal and Arctic tundra wetland sites but have limited performance for temperate and tropical/subtropical sites; 3) model error approximates pink noise patterns, indicating that biases at short time scales (< 5 days) could contribute to persistent systematic biases on longer time scales; and 4) differences in error pattern are related to model structure (e.g. proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability in future wetland CH4 model developments.

2021

DOI bib
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Global Change Biology, Volume 27, Issue 15

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

DOI bib
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Global Change Biology, Volume 27, Issue 15

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

2020

DOI bib
Increasing contribution of peatlands to boreal evapotranspiration in a warming climate
Manuel Helbig, J. M. Waddington, Pavel Alekseychik, B. D. Amiro, Mika Aurela, Alan Barr, T. Andrew Black, Peter D. Blanken, Sean K. Carey, Jiquan Chen, Jinshu Chi, Ankur R. Desai, Allison L. Dunn, E. S. Euskirchen, Lawrence B. Flanagan, Inke Forbrich, Thomas Friborg, Achim Grelle, Silvie Harder, Michal Heliasz, Elyn Humphreys, Hiroki Ikawa, Pierre‐Erik Isabelle, Hiroki Iwata, Rachhpal S. Jassal, Mika Korkiakoski, J. Kurbatova, Lars Kutzbach, Anders Lindroth, Mikaell Ottosson Löfvenius, Annalea Lohila, Ivan Mammarella, Philip Marsh, Trofim C. Maximov, Joe R. Melton, Paul Moore, Daniel F. Nadeau, Erin M. Nicholls, Mats B. Nilsson, Takeshi Ohta, Matthias Peichl, Richard M. Petrone, Roman Petrov, Anatoly Prokushkin, W. L. Quinton, David E. Reed, Nigel T. Roulet, Benjamin R. K. Runkle, Oliver Sonnentag, Ian B. Strachan, Pierre Taillardat, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, Jessica Turner, Masahito Ueyama, Andrej Varlagin, Martin Wilmking, Steven C. Wofsy, Vyacheslav Zyrianov
Nature Climate Change, Volume 10, Issue 6

The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.
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