Constraining carbon allocation in a terrestrial ecosystem model using long-term forest biomass time series

2020 ◽  
Author(s):  
Simon Besnard ◽  
Sujan Koirala ◽  
Maurizio Santoro ◽  
Shanning Bao ◽  
Oliver Cartus ◽  
...  
Keyword(s):  
Time Series ◽  
Forest Biomass ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Dynamic Allocation ◽  
Terrestrial Ecosystem Model ◽  
C Dynamics ◽  
C Cycling ◽  
C Stocks

<p>Forests cover about 30% of the terrestrial surface of our planet and store a large part of the terrestrial carbon (C), indicating their fundamental role in terrestrial C dynamics. In recent years, significant advances have been made in understanding terrestrial C cycling across scales, albeit uncertainties remain about fundamental processes, such as photosynthesis, allocation, and mortality, which exert dominant controls on vegetation C dynamics. Allocation plays a critical role in forest ecosystem C cycling by partitioning the products of net photosynthesis into leaves, wood, and below-ground components but is still poorly represented mostly given limitations in process understanding as well as in both suitable and commensurate observations.</p><p>Here, we explore different approaches in constraining C allocation alongside processes driving assimilation and out fluxes in a terrestrial ecosystem model based on novel forest biomass datasets. More specifically, we use a series of temporally changing above-ground biomass (AGB) data from local (i.e. in-situ forest inventory data) to global (i.e. long-term C-band satellite retrievals from 1992 to 2018) scales, in a multi-constraint approach. We explore the information contained in a novel AGB time series to diagnose the potential of using changes in vegetation C stocks, jointly with C and water fluxes, to constrain and parameterize different C allocation modeling approaches. Both at FLUXNET site level and global scale, we will: i) present these novel AGB datasets, their strengths and limitations, ii) demonstrate the relevance of constraining C allocation with such temporally changing AGB estimates, and iii) provide a comparison of different C allocation approaches (i.e. fixed versus dynamic allocation, and an hybrid modeling approach) and their implications in representing ecosystem dynamics.</p>

scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (ca. 2.8° × 2.8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms (OPTICS (Ankerst et al., 1999; Daszykowski et al., 2002) and Sander et al. (2003)) to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures, however differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global scale simulations using a simple grid-mean value.

scholarly journals Simulating high-latitude permafrost regions by the JSBACH terrestrial ecosystem model

2014 ◽  
Vol 7 (2) ◽  
pp. 631-647 ◽  
Author(s):  
A. Ekici ◽  
C. Beer ◽  
S. Hagemann ◽  
J. Boike ◽  
M. Langer ◽  
...  
Keyword(s):  
High Latitude ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Layered Soil ◽  
Data Sets ◽  
High Latitudes ◽  
Current Version ◽  
Freeze Thaw ◽  
Terrestrial Ecosystem Model ◽  
Permafrost Regions

Abstract. The current version of JSBACH incorporates phenomena specific to high latitudes: freeze/thaw processes, coupling thermal and hydrological processes in a layered soil scheme, defining a multilayer snow representation and an insulating moss cover. Evaluations using comprehensive Arctic data sets show comparable results at the site, basin, continental and circumarctic scales. Such comparisons highlight the need to include processes relevant to high-latitude systems in order to capture the dynamics, and therefore realistically predict the evolution of this climatically critical biome.

scholarly journals Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

2016 ◽  
Vol 9 (1) ◽  
pp. 323-361 ◽  
Author(s):  
J. R. Melton ◽  
V. K. Arora
Keyword(s):  
Spatial Distribution ◽  
Large Scale ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Plant Functional Types ◽  
Atmospheric Composition ◽  
Climate Modelling ◽  
Fractional Coverage ◽  
Terrestrial Ecosystem Model ◽  
Functional Types

Abstract. The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land–atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka–Volterra (L–V) predator–prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L–V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L–V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

scholarly journals Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1

2019 ◽  
Vol 12 (6) ◽  
pp. 2227-2253 ◽  
Author(s):  
Thomas Luke Smallman ◽  
Mathew Williams
Keyword(s):  
Stomatal Conductance ◽  
Data Fusion ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Sensitivity Analyses ◽  
Model Data ◽  
Time Step ◽  
Terrestrial Ecosystem Model ◽  
Intermediate Complexity ◽  
Large Ensembles

Abstract. Photosynthesis (gross primary production, GPP) and evapotranspiration (ET) are ecosystem processes with global significance for climate, the global carbon and hydrological cycles and a range of ecosystem services. The mechanisms governing these processes are complex but well understood. There is strong coupling between these processes, mediated directly by stomatal conductance and indirectly by root zone soil moisture content and its accessibility. This coupling must be effectively modelled for robust predictions of earth system responses to global change. Yet, it is highly demanding to model leaf and cellular processes, like stomatal conductance or electron transport, with response times of minutes, over decadal and global domains. Computational demand means models resolving this level of complexity cannot be easily evaluated for their parameter sensitivity nor calibrated using earth observation information through data assimilation approaches requiring large ensembles. To overcome these challenges, here we describe a coupled photosynthesis evapotranspiration model of intermediate complexity. The model reduces computational load and parameter numbers by operating at canopy scale and daily time step. Through the inclusion of simplified representation of key process interactions, it retains sensitivity to variation in climate, leaf traits, soil states and atmospheric CO2. The new model is calibrated to match the biophysical responses of a complex terrestrial ecosystem model (TEM) of GPP and ET through a Bayesian model–data fusion framework. The calibrated ACM-GPP-ET generates unbiased estimates of TEM GPP and ET and captures 80 %–95 % of the sensitivity of carbon and water fluxes by the complex TEM. The ACM-GPP-ET model operates 3 orders faster than the complex TEM. Independent evaluation of ACM-GPP-ET at FLUXNET sites, using a single global parameterisation, shows good agreement, with typical R2∼0.60 for both GPP and ET. This intermediate complexity modelling approach allows full Monte Carlo-based quantification of model parameter and structural uncertainties and global-scale sensitivity analyses for these processes and is fast enough for use within terrestrial ecosystem model–data fusion frameworks requiring large ensembles.

scholarly journals McGill wetland model: evaluation of a peatland carbon simulator developed for global assessments

2010 ◽  
Vol 7 (11) ◽  
pp. 3517-3530 ◽  
Author(s):  
F. St-Hilaire ◽  
J. Wu ◽  
N. T. Roulet ◽  
S. Frolking ◽  
P. M. Lafleur ◽  
...  
Keyword(s):  
Water Table ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
General Structure ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Terrestrial Ecosystem Model ◽  
Use Efficiency ◽  
One Year ◽  
Anoxic Zones

Abstract. We developed the McGill Wetland Model (MWM) based on the general structure of the Peatland Carbon Simulator (PCARS) and the Canadian Terrestrial Ecosystem Model. Three major changes were made to PCARS: (1) the light use efficiency model of photosynthesis was replaced with a biogeochemical description of photosynthesis; (2) the description of autotrophic respiration was changed to be consistent with the formulation of photosynthesis; and (3) the cohort, multilayer soil respiration model was changed to a simple one box peat decomposition model divided into an oxic and anoxic zones by an effective water table, and a one-year residence time litter pool. MWM was then evaluated by comparing its output to the estimates of net ecosystem production (NEP), gross primary production (GPP) and ecosystem respiration (ER) from 8 years of continuous measurements at the Mer Bleue peatland, a raised ombrotrophic bog located in southern Ontario, Canada (index of agreement [dimensionless]: NEP = 0.80, GPP = 0.97, ER = 0.97; systematic RMSE [g C m−2 d−1]: NEP = 0.12, GPP = 0.07, ER = 0.14; unsystematic RMSE: NEP = 0.15, GPP = 0.27, ER = 0.23). Simulated moss NPP approximates what would be expected for a bog peatland, but shrub NPP appears to be underestimated. Sensitivity analysis revealed that the model output did not change greatly due to variations in water table because of offsetting responses in production and respiration, but that even a modest temperature increase could lead to converting the bog from a sink to a source of CO2. General weaknesses and further developments of MWM are discussed.

scholarly journals Climate and atmospheric drivers of historical terrestrial carbon uptake in the province of British Columbia, Canada

2014 ◽  
Vol 11 (3) ◽  
pp. 635-649 ◽  
Author(s):  
Y. Peng ◽  
V. K. Arora ◽  
W. A. Kurz ◽  
R. A. Hember ◽  
B. J. Hawkins ◽  
...  
Keyword(s):  
British Columbia ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Ecosystem Model ◽  
Carbon Uptake ◽  
Stem Wood ◽  
Terrestrial Ecosystem Model ◽  
Changing Climate ◽  
Model Response ◽  
Two Factors

Abstract. The impacts of climate change and increasing atmospheric CO2 concentration on the terrestrial uptake of carbon dioxide since 1860 in the Canadian province of British Columbia are estimated using the process-based Canadian Terrestrial Ecosystem Model (CTEM). Model simulations show that these two factors yield an enhanced carbon uptake of around 44 gC m−2 yr−1 (or equivalently 63 gC m−2 yr−1 over the province's forested area), during the 1980s and 1990s, and continuing into the 2000s. About three-quarters of the simulated sink enhancement in our study compared to pre-industrial conditions is attributed to changing climate, and the rest is attributed to increase in CO2 concentration. The model response to changing climate and increasing CO2 is corroborated by comparing simulated stem wood growth rates with ground-based measurements from inventory plots in coastal British Columbia. The simulated sink is not an estimate of the net carbon balance because the effects of harvesting, insect disturbances and land-use change are not considered.

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