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1. Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities

   https://doi.org/10.1002/EAP.2499  

   Euskirchen, Eugénie S. ; Serbin, Shawn P. ; Carman, Tobey B. ; Fraterrigo, Jennifer M. ; Genet, Hélène ; Iversen, Colleen M. ; Salmon, Verity ; McGuire, A. David ( November 2021 , Ecological Applications)

   As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive tomore »parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.« less
2. Dynamic global vegetation models underestimate net CO ₂ flux mean and inter-annual variability in dryland ecosystems

   https://doi.org/10.1088/1748-9326/ac1a38  

   MacBean, Natasha ; Scott, Russell L ; Biederman, Joel A ; Peylin, Philippe ; Kolb, Thomas ; Litvak, Marcy E ; Krishnan, Praveena ; Meyers, Tilden P ; Arora, Vivek K ; Bastrikov, Vladislav ; et al ( August 2021 , Environmental Research Letters)

   Abstract Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol . 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases inmore »gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.« less
3. Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle

   https://doi.org/10.1038/s41467-022-29391-5  

   Jian, Jinshi ; Bailey, Vanessa ; Dorheim, Kalyn ; Konings, Alexandra G. ; Hao, Dalei ; Shiklomanov, Alexey N. ; Snyder, Abigail ; Steele, Meredith ; Teramoto, Munemasa ; Vargas, Rodrigo ; et al ( December 2022 , Nature Communications)

   Abstract The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean $${149}_{-23}^{+29}$$ 149 − 23 + 29 Pg C yr −1 ) are significantly higher than most GPP estimates reported in the literature ( $${113}_{-18}^{+18}$$ 113 − 18 + 18 Pg C yr −1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of $${68}_{-8}^{+10}$$ 68 − 8 + 10 Pg C yr −1 ) statistically inconsistent with most published R S values ( $${87}_{-8}^{+9}$$ 87 − 8 + 9 Pg C yr −1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well asmore »CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.« less
4. FLUXNET-CH ₄ Synthesis Activity: Objectives, Observations, and Future Directions

   https://doi.org/10.1175/BAMS-D-18-0268.1  

   Knox, Sara H. ; Jackson, Robert B. ; Poulter, Benjamin ; McNicol, Gavin ; Fluet-Chouinard, Etienne ; Zhang, Zhen ; Hugelius, Gustaf ; Bousquet, Philippe ; Canadell, Josep G. ; Saunois, Marielle ; et al ( December 2019 , Bulletin of the American Meteorological Society)

   This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH 4 ) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH 4 flux measurements globally, initial results comparing CH 4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH 4 fluxes across sites ranged from −0.2 ± 0.02 g C m –2 yr –1 for an upland forest site to 114.9 ± 13.4 g C m –2 yr –1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m –2 yr –1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH 4 flux across wetland sites globally. Water table position was positively correlated with annual CH 4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH 4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH 4more »estimates due to gap-filling and random errors were on average ±1.6 g C m –2 yr –1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH 4 flux database, the controls on ecosystem CH 4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH 4 emissions.« less
5. Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach

   https://doi.org/10.5194/bg-18-2917-2021  

   Maignan, Fabienne ; Abadie, Camille ; Remaud, Marine ; Kooijmans, Linda M. ; Kohonen, Kukka-Maaria ; Commane, Róisín ; Wehr, Richard ; Campbell, J. Elliott ; Belviso, Sauveur ; Montzka, Stephen A. ; et al ( January 2021 , Biogeosciences)

   Abstract. Land surface modellers need measurable proxies toconstrain the quantity of carbon dioxide (CO2) assimilated bycontinental plants through photosynthesis, known as gross primary production(GPP). Carbonyl sulfide (COS), which is taken up by leaves through theirstomates and then hydrolysed by photosynthetic enzymes, is a candidate GPPproxy. A former study with the ORCHIDEE land surface model used a fixedratio of COS uptake to CO2 uptake normalised to respective ambientconcentrations for each vegetation type (leaf relative uptake, LRU) tocompute vegetation COS fluxes from GPP. The LRU approach is known to havelimited accuracy since the LRU ratio changes with variables such asphotosynthetically active radiation (PAR): while CO2 uptake slows underlow light, COS uptake is not light limited. However, the LRU approach hasbeen popular for COS–GPP proxy studies because of its ease of applicationand apparent low contribution to uncertainty for regional-scaleapplications. In this study we refined the COS–GPP relationship andimplemented in ORCHIDEE a mechanistic model that describes COS uptake bycontinental vegetation. We compared the simulated COS fluxes againstmeasured hourly COS fluxes at two sites and studied the model behaviour andlinks with environmental drivers. We performed simulations at a global scale,and we estimated the global COS uptake by vegetation to be −756 Gg S yr−1,in the middle range ofmore »former studies (−490 to −1335 Gg S yr−1). Basedon monthly mean fluxes simulated by the mechanistic approach in ORCHIDEE, wederived new LRU values for the different vegetation types, ranging between0.92 and 1.72, close to recently published averages for observed values of1.21 for C4 and 1.68 for C3 plants. We transported the COS using the monthlyvegetation COS fluxes derived from both the mechanistic and the LRUapproaches, and we evaluated the simulated COS concentrations at NOAA sites.Although the mechanistic approach was more appropriate when comparing tohigh-temporal-resolution COS flux measurements, both approaches gave similarresults when transporting with monthly COS fluxes and evaluating COSconcentrations at stations. In our study, uncertainties between these twoapproaches are of secondary importance compared to the uncertainties in theCOS global budget, which are currently a limiting factor to the potential ofCOS concentrations to constrain GPP simulated by land surface models on theglobal scale.« less