Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

López‐Blanco, Efrén; Exbrayat, Jean‐François; Lund, Magnus; Christensen, Torben R.; Tamstorf, Mikkel P.; Slevin, Darren; Hugelius, Gustaf; Bloom, A. Anthony; Williams, Mathew

doi:10.5194/esd-2018-19

Cited by 7 publications

(12 citation statements)

References 74 publications

(123 reference statements)

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“…The CARbon DAta-MOdel fraMework (CARDAMOM; e.g., Bloom et al, 2016;Yin et al, 2020;Exbrayat et al, 2018;Smallman et al, 2017;López-Blanco et al, 2019;Famiglietti et al, 2021;Bloom et al, 2020;Yang et al, 2021a) uses carbon cycle and meteorolog-ical observations to constrain carbon fluxes, states and process controls represented in the DALEC2 model of terrestrial C cycling (Williams et al, 2005;Bloom and Williams, 2015). Specifically, CARDAMOM uses a Bayesian model-data fusion approach to optimize DALEC2 time-invariant parameters (such as leaf traits, allocation and turnover times) and the "initial" C and H 2 O conditions (namely biomass, soil and water states at the start of the model simulation period).…”

Section: The Cardamom Model-data Fusion Systemmentioning

confidence: 99%

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework

et al. 2022

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Abstract. The flow of carbon through terrestrial ecosystems and the response to climate are critical but highly uncertain processes in the global carbon cycle. However, with a rapidly expanding array of in situ and satellite data, there is an opportunity to improve our mechanistic understanding of the carbon (C) cycle's response to land use and climate change. Uncertainty in temperature limitation on productivity poses a significant challenge to predicting the response of ecosystem carbon fluxes to a changing climate. Here we diagnose and quantitatively resolve environmental limitations on the growing-season onset of gross primary production (GPP) using nearly 2 decades of meteorological and C flux data (2000–2018) at a subalpine evergreen forest in Colorado, USA. We implement the CARbon DAta-MOdel fraMework (CARDAMOM) model–data fusion network to resolve the temperature sensitivity of spring GPP. To capture a GPP temperature limitation – a critical component of the integrated sensitivity of GPP to temperature – we introduced a cold-temperature scaling function in CARDAMOM to regulate photosynthetic productivity. We found that GPP was gradually inhibited at temperatures below 6.0 ∘C (±2.6 ∘C) and completely inhibited below −7.1 ∘C (±1.1 ∘C). The addition of this scaling factor improved the model's ability to replicate spring GPP at interannual and decadal timescales (r=0.88), relative to the nominal CARDAMOM configuration (r=0.47), and improved spring GPP model predictability outside of the data assimilation training period (r=0.88). While cold-temperature limitation has an important influence on spring GPP, it does not have a significant impact on integrated growing-season GPP, revealing that other environmental controls, such as precipitation, play a more important role in annual productivity. This study highlights growing-season onset temperature as a key limiting factor for spring growth in winter-dormant evergreen forests, which is critical in understanding future responses to climate change.

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Section: The Cardamom Model-data Fusion Systemmentioning

confidence: 99%

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework

et al. 2022

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“…The value of such efforts to reduce parameter uncertainty was underscored. On the other hand, the MDF models like DALEC with optimized parameters has comparable performance to state‐of‐art terrestrial biosphere model estimates in Trendy and CMIP5 (Quetin et al., 2020); recently, similar MDF‐based model simulations were adopted as novel benchmark in the International Land Model Benchmarking (ILAMB) project on C cycle to evaluate and improve ESM performance (López‐Blanco et al., 2019; Slevin et al., 2016).…”

Section: Discussionmentioning

confidence: 99%

Climate Sensitivities of Carbon Turnover Times in Soil and Vegetation: Understanding Their Effects on Forest Carbon Sequestration

Zhang

et al. 2022

JGR Biogeosciences

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The high uncertainty associated with the response of terrestrial carbon (C) cycle to climate is dominated by ecosystem C turnover time (τ eco ). Although the relationship between τ eco and climate has been extensively studied, significant knowledge gaps remain regarding the differential climate sensitivities of turnover time in major biomass (τ veg ) and soil (τ soil ) pools, and their effects on vegetation and soil C sequestration under climate change are poorly understood. Here, we collected multiple time series observations on soil and vegetation C from permanent plots in 10 Chinese forests and used model-data fusion to retrieve key C cycle process parameters that regulate τ soil and τ veg . Our analysis showed that τ veg and τ soil both decreased with increasing temperature and precipitation, and τ soil was more than twice as sensitive (1.27 years/°C, 1.70 years/100 mm) than τ veg (0.53 years/°C, 0.40 years/100 mm). The higher climate sensitivity of τ soil caused a more rapid decrease in τ soil than in τ veg with increasing temperature and precipitation, thereby significantly reducing the difference between τ soil and τ veg (τ diff ) under warm and humid conditions. τ diff , an indicator of the balance between the soil C input and exit rate, was strongly responsible for the variation (more than 50%) in soil C sequestration. Therefore, a smaller τ diff under warm and humid conditions suggests a relatively lower contribution from soil C sequestration. This information has strong implications for understanding forest C-climate feedback, predicting forest C sink distributions in soil and vegetation under climate change, and implementing C mitigation policies in forest plantations or soil conservation. Plain Language SummaryCarbon turnover time is the average time that a carbon atom stays in an ecosystem from entrance to exit. Together, ecosystem carbon input via photosynthesis (i.e., productivity) and carbon turnover time determine ecosystem carbon sequestration. However, in contrast to the well-studied ecosystem productivity, carbon turnover time was found to dominate the uncertainty in terrestrial carbon sequestration and its response to climate. However, the climate sensitivities of carbon turnover times in various plant and soil pools and their effects on carbon storage have not been well-studied. Here, we quantified that carbon turnover time in soil (τ soil ) was more sensitive to climate than that of vegetation (τ veg ). This finding indicated the difference between τ veg and τ soil (τ diff ) being shortened in warm and humid regions. We further found that τ diff , as an indicator of the balance between soil carbon input and the carbon exit rate, is closely associated with the capacity for soil carbon sequestration. Therefore, a decreasing τ diff with increasing temperature/precipitation indicates a smaller proportion of carbon sequestered by soil than vegetation. Our findings facilitate understanding of carbon-climate feedback and the prediction of carbon sink distributions GE ET AL.

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“…Current estimates of annual net CO 2 sink-source strength across the evergreen boreal forest, utilizing terrestrial biosphere models or assimilation of various data sources, are subject to high uncertainties suggesting that the boreal forest zone is likely a net carbon sink, but possibly a net carbon source 1,4,18,19 .…”

Section: Limitations Of Current Carbon Exchange Assessmentsmentioning

confidence: 99%

Four decades increase in gross photosynthesis of boreal forests balanced out by increase in ecosystem respiration

Pulliainen

Aurela

Vesala

et al. 2022

Preprint

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Changes in the net carbon sink of boreal forests constitute a major source of uncertainty in the future global carbon budget and hence climate change projections1. The annual net ecosystem exchange of carbon dioxide (CO2) controlling the terrestrial carbon stock is the result of the small difference between respiratory CO2 release and the photosynthetic CO2 uptake by vegetation2. The boreal forest, and the boreal biome in general, is regarded as a persistent and even an increasing net carbon sink3,4. However, decreases in photosynthetic CO2 uptake and/or concurrent increases in respiratory CO2 release under a changing climate may turn boreal forests from a net sink to a net source of CO21. Here, we assessed the dynamics of boreal forest net CO2 sink-source strength and its components from 1981 to 2018. Our remote sensing approach - trained by net CO2 flux observations at eddy covariance sites across the circumpolar boreal forests - employs satellite-derived retrievals of snow melt timing, landscape freeze-thaw status, and yearly maximum estimates of the normalized difference vegetation index as a proxy for peak vegetation productivity. Our results for the period 1981-2018 suggest that the mean annual evergreen boreal forest CO2 sink was 0.4 Pg C y-1 (0.3 Pg C y-1 for Eurasia and 0.2 Pg C y-1 for North America). In contrast to earlier investigations3,4 our results do not indicate an increasing trend in the circumpolar evergreen boreal forest CO2 sink, as the increase in CO2 uptake is compensated by increasing respiratory releases with both components of CO2 sink-source strength showing considerable interannual variabilities.

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Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

Cited by 7 publications

References 74 publications

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework

Climate Sensitivities of Carbon Turnover Times in Soil and Vegetation: Understanding Their Effects on Forest Carbon Sequestration

Four decades increase in gross photosynthesis of boreal forests balanced out by increase in ecosystem respiration

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