scholarly journals Quantifying Global N<sub>2</sub>O Emissions from Natural Ecosystem Soils Using Trait-Based Biogeochemistry Models

2018 ◽  
Author(s):  
Tong Yu ◽  
Qianlai Zhuang
Keyword(s):  
Nitrogen Cycling ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
N2o Emission ◽  
Biogeochemical Model ◽  
N2o Emissions ◽  
Natural Ecosystem ◽  
Ammonia Oxidizing Bacteria ◽  
Carbon And Nitrogen ◽  
Terrestrial Ecosystem Model

Abstract. A group of soil microbes plays an important role in nitrogen cycling and N2O emissions from natural ecosystem soils. We developed a trait-based biogeochemical model based on an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), by incorporating the detailed microbial physiological processes of nitrification. The effect of ammonia-oxidizing archaea (AOA), ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) was considered in modeling nitrification. The microbial traits including microbial biomass and density were explicitly considered. In addition, nitrogen cycling was coupled with carbon dynamics based on stoichiometry theory between carbon and nitrogen. The model was parameterized using observational data and then applied to quantifying global N2O emissions from global terrestrial ecosystem soils from 1990 to 2000. Our estimates of 8.7 ± 1.6 Tg N yr−1 generally agreed with previous estimates during the study period. Tropical forests are a major emitter, accounting for 42 % of the global emissions. The model was more sensitive to temperature and precipitation, and less sensitive to soil organic carbon and nitrogen contents. Compared to the model without considering the detailed microbial activities, the new model shows more variations in response to seasonal changes in climate. Our study suggests that further information on microbial diversity and eco-physiology features is needed. The more specific guilds and their traits shall be considered in future soil N2O emission quantifications.

scholarly journals Quantifying global N<sub>2</sub>O emissions from natural ecosystem soils using trait-based biogeochemistry models

2019 ◽  
Vol 16 (2) ◽  
pp. 207-222 ◽  
Author(s):  
Tong Yu ◽  
Qianlai Zhuang
Keyword(s):  
Nitrogen Cycling ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
N2o Emission ◽  
Biogeochemical Model ◽  
N2o Emissions ◽  
Natural Ecosystem ◽  
Ammonia Oxidizing Bacteria ◽  
Carbon And Nitrogen ◽  
Terrestrial Ecosystem Model

Abstract. A group of soil microbes plays an important role in nitrogen cycling and N2O emissions from natural ecosystem soils. We developed a trait-based biogeochemical model based on an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), by incorporating the detailed microbial physiological processes of nitrification. The effect of ammonia-oxidizing Archaea (AOA), ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB) was considered in modeling nitrification. Microbial traits, including microbial biomass and density, were explicitly considered. In addition, nitrogen cycling was coupled with carbon dynamics based on stoichiometry theory between carbon and nitrogen. The model was parameterized using observational data and then applied to quantifying global N2O emissions from global terrestrial ecosystem soils from 1990 to 2000. Our estimates of 8.7±1.6 Tg N yr−1 generally agreed with previous estimates during the study period. Tropical forests are a major emitter, accounting for 42 % of the global emissions. The model was more sensitive to temperature and precipitation and less sensitive to soil organic carbon and nitrogen contents. Compared to the model without considering the detailed microbial activities, the new model shows more variations in response to seasonal changes in climate. Our study suggests that further information on microbial diversity and ecophysiology features is needed. The more specific guilds and their traits shall be considered in future soil N2O emission quantifications.

Spatially Explicit Parameterization of a Terrestrial Ecosystem Model and Its Application to the Quantification of Carbon Dynamics of Forest Ecosystems in the Conterminous United States

2012 ◽  
Vol 16 (5) ◽  
pp. 1-22 ◽  
Author(s):  
Min Chen ◽  
Qianlai Zhuang
Keyword(s):  
United States ◽  
Primary Production ◽  
Forest Ecosystems ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Carbon Dynamics ◽  
Spatially Explicit ◽  
Carbon And Nitrogen ◽  
Parameterization Method ◽  
Terrestrial Ecosystem Model

Abstract The authors use a spatially explicit parameterization method and the Terrestrial Ecosystem Model (TEM) to quantify the carbon dynamics of forest ecosystems in the conterminous United States. Six key parameters that govern the rates of carbon and nitrogen dynamics in TEM are selected for calibration. Spatially explicit data for carbon and nitrogen pools and fluxes are used to calibrate the six key parameters to more adequately account for the spatial heterogeneity of ecosystems in estimating regional carbon dynamics. The authors find that a spatially explicit parameterization results in vastly different carbon exchange rates relative to a parameterization conducted for representative ecosystem sites. The new parameterization method estimates that the net ecosystem production (NEP), the annual gross primary production (GPP), and the net primary production (NPP) of the regional forest ecosystems are 61% (0.02 Pg C; 1 Pg = 1015 g) higher and 2% (0.11 Pg C) and 19% (0.45 Pg C) lower, respectively, than the values obtained using the traditional parameterization method for the period 1948–2000. The estimated vegetation carbon and soil organic carbon pool sizes are 51% (18.73 Pg C) lower and 29% (7.40 Pg C) higher. This study suggests that, to more adequately quantify regional carbon dynamics, spatial data for carbon and nitrogen pools and fluxes should be developed and used with the spatially explicit parameterization method.

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 Environmental change impacts on the C- and N-cycle of European forests: a model comparison study

2013 ◽  
Vol 10 (3) ◽  
pp. 1751-1773 ◽  
Author(s):  
D. R. Cameron ◽  
M. Van Oijen ◽  
C. Werner ◽  
K. Butterbach-Bahl ◽  
R. Grote ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Central Europe ◽  
Tree Species ◽  
Carbon Sink ◽  
N2o Emission ◽  
Forest Growth ◽  
N2o Emissions ◽  
European Forests ◽  
Considerable Uncertainty ◽  
Carbon And Nitrogen

Abstract. Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.

scholarly journals Changes of Soil Microbes Related with Carbon and Nitrogen Cycling after Long-Term CO2 Enrichment in a Typical Chinese Maize Field

2020 ◽  
Vol 12 (3) ◽  
pp. 1250 ◽  
Author(s):  
Tiantian Diao ◽  
Zhengping Peng ◽  
Xiaoguang Niu ◽  
Rongquan Yang ◽  
Fen Ma ◽  
...  
Keyword(s):  
16S Rrna ◽  
Nitrogen Cycling ◽  
Relative Abundance ◽  
Soil Microbes ◽  
Inorganic Nitrogen ◽  
Ammonia Oxidizing Bacteria ◽  
Rhizospheric Soil ◽  
Carbon And Nitrogen ◽  
Carbon And Nitrogen Cycling ◽  
Maize Field

Elevated atmospheric CO2 concentration (eCO2) has been the most important driving factor and characteristic of climate change. To clarify the effects of eCO2 on the soil microbes and on the concurrent status of soil carbon and nitrogen, an experiment was conducted in a typical summer maize field based on a 10-year mini FACE (Free Air Carbon Dioxide Enrichment) system in North China. Both rhizospheric and bulk soils were collected for measurement. The soil microbial carbon (MBC), nitrogen (MBN), and soil mineral N were measured at two stages. Characteristics of microbes were assayed for both rhizospheric soil and bulk soils at the key stage. We examined the plasmid copy numbers, diversities, and community structures of bacteria (in terms of 16s rRNA), fungi (in terms of ITS-internal transcribed spacer), ammonia oxidizing bacteria (AOB) and denitrifiers including nirK, nirS, and nosZ using the Miseq sequencing technique. Results showed that under eCO2 conditions, both MBC and MBN in rhizospheric soil were increased significantly. The quantity of ITS was increased in the eCO2 treatment compared with that in the ambient CO2 (aCO2) treatment, while the quantity of 16s rRNA in rhizospheric soil showed decrease in the rhizospheric soil in the eCO2 treatment. ECO2 changed the relative abundance of microbes in terms of compositional proportion of some orders or genera particularly in the rhizospheric soil-n particular, Chaetomium increased for ITS, Subgroups 4 and 6 increased for 16s rRNA, Nitrosospira decreased for AOB, and some genera showed increase for nirS, nirK, and nosZ. Nitrate N was the main inorganic nitrogen form at the tasseling stage and both quantities of AOB and denitrifiers, as well as the nosZ/(nirS+nirK) showed an increase under eCO2 conditions particularly in the rhizospheric soil. The Nitrosospira decreased in abundance under eCO2 conditions in the rhizospheric soil and some genera of denitrifiers also showed differences in abundance. ECO2 did not change the diversities of microbes significantly. In general, results suggested that 10 years of eCO2 did affect the active component of C and N pools (such as MBC and MBN) and both the quantities and relative abundance of microbes which are involved in carbon and nitrogen cycling, possibly due to the differences in both the quantities and component of substrate for relevant microbes in the rhizospheric soils.

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.

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