scholarly journals Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

2020 ◽  
Vol 13 (12) ◽  
pp. 5973-6009
Author(s):  
Virginie Moreaux ◽  
Simon Martel ◽  
Alexandre Bosc ◽  
Delphine Picart ◽  
David Achat ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Soil Carbon ◽  
Biogeochemical Processes ◽  
Forest Operations ◽  
Time Step ◽  
Vegetation Control ◽  
Clear Cutting ◽  
Go Model ◽  
The Impact

Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

scholarly journals Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

2020 ◽  
Author(s):  
Virginie Moreaux ◽  
Simon Martel ◽  
Alexandre Bosc ◽  
Delphine Picart ◽  
David Achat ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Mechanistic Model ◽  
Biogeochemical Processes ◽  
Forest Operations ◽  
Time Step ◽  
Vegetation Control ◽  
Clear Cutting ◽  
Go Model ◽  
The Impact

Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon sub-model is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time-step. It represents a forest stand covering typically 1 ha and can be straightforwardly up-scaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil-vegetation-atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close-to-nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables. We show how the model performs when compared with observations such as time series of forest-atmosphere exchanges of energy, water and CO2 monitored over Douglas fir, European beech and pine forests of different ages as well as long-term series of tree growth, soil water and soil carbon data recorded at continuously monitored forests plots. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

The impact of porosity on organic matter cycling in a two-dimensional porous medium 

2021 ◽  
Author(s):  
Hanbang Zou ◽  
Pelle Ohlsson ◽  
Edith Hammer
Keyword(s):  
Porous Medium ◽  
Organic Matter ◽  
Carbon Sequestration ◽  
Soil Carbon ◽  
Pore Network ◽  
Pore Scale ◽  
Decomposition Of Organic Matter ◽  
Organic Matter Cycling ◽  
The Impact

<p>Carbon sequestration has been a popular research topic in recent years as the rapid elevation of carbon emission has significantly impacted our climate. Apart from carbon capture and storage in e.g. oil reservoirs, soil carbon sequestration offers a long term and safe solution for the environment and human beings. The net soil carbon budget is determined by the balance between terrestrial ecosystem sink and sources of respiration to atmospheric carbon dioxide. Carbon can be long term stored as organic matters in the soil whereas it can be released from the decomposition of organic matter. The complex pore networks in the soil are believed to be able to "protect" microbial-derived organic matter from decomposition. Therefore, it is important to understand how soil structure impacts organic matter cycling at the pore scale. However, there are limited experimental studies on understanding the mechanism of physical stabilization of organic matter. Hence, my project plan is to create a heterogeneous microfluidic porous microenvironment to mimic the complex soil pore network which allows us to investigate the ability of organisms to access spaces starting from an initial ecophysiological precondition to changes of spatial accessibility mediated by interactions with the microbial community.</p><p>Microfluidics is a powerful tool that enables studies of fundamental physics, rapid measurements and real-time visualisation in a complex spatial microstructure that can be designed and controlled. Many complex processes can now be visualized enabled by the development of microfluidics and photolithography, such as microbial dynamics in pore-scale soil systems and pore network modification mimicking different soil environments – earlier considered impossible to achieve experimentally. The microfluidic channel used in this project contains a random distribution of cylindrical pillars of different sizes so as to mimic the variations found in real soil. The randomness in the design creates various spatial availability for microbes (preferential flow paths with dead-end or continuous flow) as an invasion of liquids proceeds into the pore with the lowest capillary entry pressure. In order to study the impact of different porosity in isolation of varying heterogeneity of the porous medium, different pore size chips that use the same randomly generated pore network is created. Those chips have the same location of the pillars, but the relative size of each pillar is scaled. The experiments will be carried out using sterile cultures of fluorescent bacteria, fungi and protists, synthetic communities of combinations of these, or a whole soil community inoculum. We will quantify the consumption of organic matter from the different areas via fluorescent substrates, and the bio-/necromass produced. We hypothesise that lower porosity will reduce the net decomposition of organic matter as the narrower pore throat limits the access, and that net decomposition rate at the main preferential path will be higher than inside branches</p>

scholarly journals Long-term effects of silviculture on soil carbon storage: does vegetation control make a difference?

2012 ◽  
Vol 86 (1) ◽  
pp. 47-58 ◽  
Author(s):  
R. F. Powers ◽  
M. D. Busse ◽  
K. J. McFarlane ◽  
J. Zhang ◽  
D. H. Young
Keyword(s):  
Soil Carbon ◽  
Carbon Storage ◽  
Soil Carbon Storage ◽  
Long Term Effects ◽  
Vegetation Control

Dynamic modelling framework to track sediment provenance and solve lakes in long-term landscape evolution models

2021 ◽  
Author(s):  
Boris Gailleton ◽  
Luca Malatesta ◽  
Jean Braun ◽  
Guillaume Cordonnier
Keyword(s):  
Landscape Evolution ◽  
Dynamic Modelling ◽  
Signal Propagation ◽  
Sediment Provenance ◽  
Topological Order ◽  
Time Step ◽  
Spatial And Temporal Scales ◽  
Modelling Framework ◽  
The Impact

<p>Many laws have been developed to describe the different aspects of landscape evolution at large spatial and temporal scales. Natural landscapes have heterogeneous properties (lithologies, climates, tectonics, etc.) that are associated with multiple coexisting processes. In turn, this can demand different mathematical expressions to model landscape evolution as a function of time and or space. Landscape Evolution Models are mostly designed to facilitate the combination of different landscape-wide laws in a plug-and-play way and many frameworks are being developed in this aim. However, most current frameworks cannot capture important landscape processes such as lake dynamics and full sediment tracing because they are optimized for speed and handle fluxes separately. Several processes require information from more than the immediate neighboring cells within a time step and demand an integrated knowledge from the entire upstream trajectory. Lakes for example require knowledge of all upstream water and sediment fluxes to be filled. These can only be known if all the laws controlling those have been processed. Tackling these situation with a grid logic requires substantial amount of numerical refactoring from existing models.</p><p>We present an alternative method to tackle landscape evolution modelling in heterogeneous landscapes with a framework inspired from Lagrangian and cellular automaton methods. Our framework only relies on the assumption that upstream nodes needs to be processed before the downstream ones, including lakes with outlets, in order to process all selected governing equations on a pixel-to-pixel basis. This way, we ensure that the true content of sediment and water fluxes can be known and tracked at any points. We first utilise graph theory to (i) find the most comprehensive path to reroute water through depressions and (ii) determine a generic multiple flow topological order (any node is processed after all potential upstream ones). Particles that register and track all fluxes simultaneously can then "roll" on the landscape and merge between each other while interacting with the grid.</p><p>This formulation makes possible a number of generic features. (i) The laws can be dynamically adapted to the environment (e.g. switching from single to multiple flow function of water content, adapting erodibility function of the sediment composition and quantity), (ii) Depressions can be explicitly managed, filled (or not) and separated from the rest of the landscape (e.g. sedimentation or evaporation in lakes) as a function function of inputted fluxes and parameters, (iii) full provenance, transport time, and deposition tracking as the particle can always keep in memory where the fluxes are from and in what proportions. In this contribution, we demonstrate the impact the importance of considering these additional elements in landscape evolution. In particular, lake dynamic can significantly impact the long-term signal propagation from source to sink.</p>

scholarly journals THE RESPONSE OF SUGARCANE TO TRASH RETENTION AND NITROGEN IN THE BRAZILIAN COASTAL TABLELANDS: A SIMULATION STUDY

2015 ◽  
Vol 52 (1) ◽  
pp. 69-86 ◽  
Author(s):  
ANA PAULA PESSIM DE OLIVEIRA ◽  
PETER J. THORBURN ◽  
JODY S. BIGGS ◽  
EDUARDO LIMA ◽  
LÚCIA HELENA CUNHA DOS ANJOS ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Soil Carbon ◽  
Cropping Systems ◽  
Cane Yield ◽  
Mean Square ◽  
Systems Model ◽  
Sugarcane Yield ◽  
N Rates ◽  
The Impact

SUMMARYTo evaluate the impact of trash management on sugarcane production and N fertiliser requirements in environmental conditions of Brazilian coastal tablelands, a simulation was conducted with APSIM-Sugar cropping systems model. The model was parameterised for, and validated against results from a long term (over 23 years) experiment comparing the system-burnt trash and green cane trash blanketing (GCTB), in Linhares-ES. Simulations were conducted over two crop cycles (14 years) with different management (100%, 75%, 50%, 25% GCTB and burnt trash), and N fertiliser rates from 0 to 240 kg ha−1 (in 40 kg ha−1 increments) on the ratoon crops, and 75% of these rates on the plant crops. Measured cane yields and soil carbon were simulated well by the model. The RMSE (root mean square error) of predictions in burnt and GCTB treatments were 14.02 Mg ha−1 and 13.45 Mg ha−1 for yield, and 0.09 and 0.13% for soil carbon. In the simulation, the cane yield responded positively to the GCTB systems. Optimum N rates were higher in the 100%, 75% and 50% GCTB than with burnt trash and 25% GCTB reflecting the greater yields under GCTB systems. The response to trash retention was dependent on N fertiliser, and it was smaller or even negative at lower N rates. With adequate N, the positive responses were predicted to occur in all crops after the imposition of GCTB system. The removal of any proportion of the trash reduced the potential sugarcane yield. The simulations showed that average environmental losses of N are likely to be greater from trash-retained systems at all N fertiliser rates.

scholarly journals Long-term trends in fertility of soils under continuous cultivation and cereal cropping in southern Queensland. IX. Simulation of soil carbon and nitrogen pools using CENTURY model

Soil Research ◽  
2007 ◽  
Vol 45 (3) ◽  
pp. 206 ◽  
Author(s):  
C. R. Chilcott ◽  
R. C. Dalal ◽  
W. J. Parton ◽  
J. O. Carter ◽  
A. J. King
Keyword(s):  
Organic Matter ◽  
Soil Carbon ◽  
Continuous Cultivation ◽  
Carbon Pools ◽  
Century Model ◽  
Nitrogen Mineralisation ◽  
Carbon And Nitrogen ◽  
Soil Carbon And Nitrogen ◽  
The Impact

Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

scholarly journals What is the impact of human wastewater biosolids (sewage sludge) application on long-term soil carbon sequestration rates? A systematic review protocol

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mike J. Badzmierowski ◽  
Gregory K. Evanylo ◽  
W. Lee Daniels ◽  
Kathryn C. Haering
Keyword(s):  
Carbon Sequestration ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Full Text ◽  
Land Application ◽  
Carbon Stocks ◽  
Soil Organic Carbon Stocks ◽  
The Impact

Abstract Background Human wastewater biosolids, hereafter referred to as biosolids, are produced in significant quantities around the world and often applied to an extensive land mass including agricultural fields, forests, mine lands, and urban areas. Land-application of biosolids has been reported in peer-reviewed and non-peer-reviewed work to change soil organic carbon stocks in varying amounts. Determining the potential of soil organic carbon (SOC) stock change and sequestration from biosolids land application is critical for biosolids producers and users to gain access to carbon credit markets. Our review question is, "what is the impact of biosolids application on long-term soil carbon sequestration rates?” We look to explore this main question with the follow-up, "does biosolids processing methods and characteristics, application method, soil properties, land management and other modifiers affect rates of carbon accumulation from land-applied biosolids?" Methods Searches will be conducted using online databases (i.e., Web of Science Core Collection, CAB Abstracts, Scopus, ProQuest Dissertations & Theses Global), search engines (Google Scholar and Microsoft Academic), and specialist websites to find primary field studies and grey literature of biosolids land-application effects on soil organic carbon stocks. We will use English search terms and predefined inclusion criteria of: (1) a field study of at least 24 months that reports soil organic carbon/matter (SOC/SOM) concentrations/stocks; (2) has two types of treatments: (i) a control (non-intervention AND/OR synthetic fertilizer) AND (ii) a biosolids-based amendment; and (3) information of amendment properties and application dates and rates to estimate the relative contribution of the applied materials to SOC changes. We will screen results in two stages: (1) title and abstract and (2) full text. A 10% subset will be screened by two reviewers for inclusion at the title and abstract level and use a kappa analysis to ensure agreement of at least 0.61. All results in the full text stage will be dual screened. Data will be extracted by one person and reviewed by a second person. Critical appraisal will be used to assess studies’ potential bias and done by two reviewers. A meta-analysis using random effects models will be conducted if sufficient data of high enough quality are extracted.

scholarly journals Dynamics of the COVID-19 pandemic in India

2020 ◽  
Author(s):  
Subhas Khajanchi ◽  
Kankan Sarkar ◽  
Jayanta Mondal ◽  
Matjaz Perc
Keyword(s):  
Sensitivity Analysis ◽  
West Bengal ◽  
Seasonal Occurrence ◽  
Contact Tracing ◽  
Short Term ◽  
Social Distancing ◽  
Oscillatory Dynamics ◽  
The Impact ◽  
Worrying Trend

Abstract Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and hospitalization data from Indian provinces Kerala, Delhi, Maharashtra, and West Bengal, as well as from overall India. We have performed a sensitivity analysis to identify the most crucial input parameters, and we have calibrated the model to describe the data as best as possible. Short-term predictions reveal an increasing and worrying trend of COVID-19 cases for all four provinces and India as a whole, while long-term predictions also reveal the possibility of oscillatory dynamics. Our research thus leaves the option open that COVID-19 might become a seasonal occurrence. We also simulate and discuss the impact of media on the dynamics of the COVID-19 pandemic.

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