scholarly journals Seasonal leaf dynamics for tropical evergreen forests in a process based global ecosystem model

2012 ◽  
Vol 5 (1) ◽  
pp. 639-681 ◽  
Author(s):  
M. De Weirdt ◽  
H. Verbeeck ◽  
F. Maignan ◽  
P. Peylin ◽  
B. Poulter ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Net Primary Production ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Dry Season ◽  
Water Fluxes ◽  
Flux Tower ◽  
Terrestrial Ecosystem Model ◽  
Leaf Litterfall ◽  
Global Vegetation

Abstract. The influence of seasonal phenology in tropical humid forests on canopy photosynthesis remains poorly understood and its representation in global vegetation models highly simplified, typically with no seasonal variability of canopy leaf area properties taken into account. However, recent flux tower and remote sensing studies suggest that seasonal phenology in tropical rainforests exerts a large influence over carbon and water fluxes, with feedbacks that can significantly influence climate dynamics. A more realistic description of the underlying mechanisms that drive seasonal tropical forest photosynthesis and phenology could improve the correspondence of global vegetation model outputs with the wet-dry season biogeochemical patterns measured at flux tower sites. Here, we introduce a leaf Net Primary Production (NPP) based canopy dynamics scheme for evergreen tropical forests in the global terrestrial ecosystem model ORCHIDEE and validated the new scheme against in-situ carbon flux measurements. Modelled Gross Primary Productivity (GPP) patterns are analyzed in details for a flux tower site in French Guiana, in a forest where the dry season is short and where the vegetation is considered to have developed adaptive mechanisms against drought stress. By including leaf litterfall seasonality and a coincident light driven leaf flush and seasonal change in photosynthetic capacity in ORCHIDEE, modelled carbon and water fluxes more accurately represent the observations. The fit to GPP flux data was substantially improved and the results confirmed that by modifying canopy dynamics to benefit from increased light conditions, a better representation of the seasonal carbon flux patterns was made.

The Effects of Different Climate Input Datasets on Simulated Carbon Dynamics in the Western Arctic

2007 ◽  
Vol 11 (12) ◽  
pp. 1-24 ◽  
Author(s):  
Joy Clein ◽  
A. David McGuire ◽  
Eugenie S. Euskirchen ◽  
Monika Calef
Keyword(s):  
Climate Model ◽  
Net Primary Production ◽  
Temporal Trends ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Carbon Dynamics ◽  
Total Carbon ◽  
Terrestrial Ecosystem Model ◽  
Western Arctic ◽  
Climate Model Simulations

Abstract As part of the Western Arctic Linkage Experiment (WALE), simulations of carbon dynamics in the western Arctic (WALE region) were conducted during two recent decades by driving the Terrestrial Ecosystem Model (TEM) with three alternative climate datasets. Among the three TEM simulations, we compared the mean monthly and interannual variability of three carbon fluxes: 1) net primary production (NPP), 2) heterotrophic respiration (Rh), and 3) net ecosystem production (NEP). Cumulative changes in vegetation, soil, and total carbon storage among the simulations were also compared. This study supports the conclusion that the terrestrial carbon cycle is accelerating in the WALE region, with more rapid turnover of carbon for simulations driven by two of the three climates. The temperature differences among the climate datasets resulted in annual estimates of NPP and Rh that varied by a factor of 2.5 among the simulations. There is much spatial variability in the temporal trends of NPP and Rh across the region in the simulations driven by different climates, and the spatial pattern of trends is quite different among simulations. Thus, this study indicates that the overall response of NEP in simulations with TEM across the WALE region depends substantially on the temporal trends in the climate dataset used to drive the model. Similar to the recommendations of other studies in the WALE project, this study indicates that coupling methodologies should use anomalies of future climate model simulations to alter the climate of more trusted datasets for purposes of driving ecosystem models of carbon dynamics.

Simulating Competition and Coexistence between Plant Functional Types in a Dynamic Vegetation Model

2006 ◽  
Vol 10 (10) ◽  
pp. 1-30 ◽  
Author(s):  
Vivek K. Arora ◽  
George J. Boer
Keyword(s):  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Plant Functional Types ◽  
Quasi Equilibrium ◽  
Terrestrial Ecosystem Model ◽  
Functional Types ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Competition Equations ◽  
Global Vegetation

Abstract The global distribution of vegetation is broadly determined by climate, and where bioclimatic parameters are favorable for several plant functional types (PFTs), by the competition between them. Most current dynamic global vegetation models (DGVMs) do not, however, explicitly simulate inter-PFT competition and instead determine the existence and fractional coverage of PFTs based on quasi-equilibrium climate–vegetation relationships. When competition is explicitly simulated, versions of Lotka–Volterra (LV) equations developed in the context of interaction between animal species are almost always used. These equations may, however, exhibit unrealistic behavior in some cases and do not, for example, allow the coexistence of different PFTs in equilibrium situations. Coexistence may, however, be obtained by introducing features and mechanisms such as temporal environmental variation and disturbance, among others. A generalized version of the competition equations is proposed that includes the LV equations as a special case, which successfully models competition for a range of climate and vegetation regimes and for which coexistence is a permissible equilibrium solution in the absence of additional mechanisms. The approach is tested for boreal forest, tropical forest, savanna, and temperate forest locations within the framework of the Canadian Terrestrial Ecosystem Model (CTEM) and successfully simulates the observed successional behavior and the observed near-equilibrium distribution of coexisting PFTs.

scholarly journals Reduction of Global Plant Production due to Droughts from 2001 to 2010: An Analysis with a Process-Based Global Terrestrial Ecosystem Model

2015 ◽  
Vol 19 (16) ◽  
pp. 1-21 ◽  
Author(s):  
Chang Liao ◽  
Qianlai Zhuang
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Plant Production ◽  
Model Parameters ◽  
Drought Impact ◽  
Terrestrial Ecosystem Model

Abstract Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.

The role of carbon flux and biometric observations in constraining a terrestrial ecosystem model: a case study in disturbed forests in East Asia

2013 ◽  
Vol 28 (5) ◽  
pp. 893-905 ◽  
Author(s):  
Masayuki Kondo ◽  
Kazuhito Ichii ◽  
Masahito Ueyama ◽  
Yasuko Mizoguchi ◽  
Ryuichi Hirata ◽  
...  
Keyword(s):  
East Asia ◽  
Carbon Flux ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Terrestrial Ecosystem Model

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.

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