Report of St. Petersburg Team O.G. Chertov, M.A. Nadporozhskaya E.V. Abakumov Biological Research Institute St. Petersburg State University 2005 INTAS.

Slides:



Advertisements
Similar presentations
1 Stocks of biomass / C soil organic matter Expert meeting on land use and Ecosystem accounting 18./
Advertisements

Screening of recent scientific research results on soil related C pools – support for KP reporting V. Blujdea, G. Grassi JRC technical workshop on LULUCF.
EU INTAS SILVICS Project Pushchino Research Centre of the Russian Academy of Sciences Institute of Mathematical Problems in Biology (Pushchino.
Overview of Research Activities of ARICFR, Team CR M. Palenova – team leader V. Korotkov S. Ripa E. Zubkova, All-Russian Research Institute.
Hans Verkerk, Vladimir Korotkov, Jeannette Meyer, Sergey Zudin, Sergey Lebedev, Marcus Lindner Impact of wood demand and forest management on forest development.
New flagship initiative Adaptive Forest Management and Biomass Production EUSBSR Priority Area Agri Forestry Workshop Helsinki 29 August 2013 Lars Andersson.
Report of Pushchino 1 Team A.Komarov, A.Mikhailov, S.Bykhovets Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy.
National Report of the Russian Federation for the 6 th Meeting of the UNECE/FAO Team of Specialists to Monitor and Develop Assistance to Countries of Central.
INTRODUCTION TO SOILS FIELD STUDY
1 Climate change impacts and adaptation: An international perspective Chris Field Carnegie Institution: Department of Global Ecology
Effects of Forest Thinning on CO 2 Efflux Peter Erb, Trisha Thoms, Jamie Shinn Biogeochemistry 2003: Block 1.
Figure 3. Outlines of the study with links between different components used. The figure presents the main inputs and outputs from the model used (Glob3PG)
Chapter 3 Forest Resources and Carbon Sink First draft O. Chertov St. Petersburg State University, University of Applied Sciences Bingen e-LUP Simulating.
Peter S. Curtis Department of Evolution, Ecology, and Organismal Biology The Ohio State University Managing Great Lakes Forests for Climate Change Mitigation.
CENTURY ECOSYSTEM MODEL Introduction to CENTURY. WHY CENTURY Evaluate Effects of Environmental Change Evaluate Changes in Management.
SOM control: Controls on soil organic matter in Swiss forest soils: The impact of forest productivity, land-use history, climate and physico-chemical stabilization.
1 Abstract 1. 2 Hydrologic Processes within Landscapes 2 snobear.colorado.edu/IntroHydro/hydro.gif.
Improving soils data for better vegetation modeling Wendy Peterman, Dominique Bachelet Conservation Biology Institute  Abstract Over.
Carbon Sequestration Akilah Martin Fall Outline Pre-Assessment  Student learning goals  Carbon Sequestration Background  Century Model Overview.
“Carbon Isotope Systematics in Soil” -or- “Plant Poo and Microbe Farts” Justin Yeakel, UCSC.
Forest simulation models in Netherlands: main developments and challenges WG1 Gert-Jan Nabuurs, Koen Kramer, MartJan Schelhaas, Isabel vd Wyngaert, Geerten.
DIFFERENCES IN SOIL RESPIRATION RATES BASED ON VEGETATION TYPE Maggie Vest Winter Ecology 2013 Mountain Research Station.
Modelling forest ground vegetation on landscape scale Larisa Khanina 1, Maxim Bobrovsky 2, Alexander Komarov 2, Alex Mikhajlov 2 1 Institute of Mathematical.
Chapter 5 The Biosphere: The Carbon Cycle of Terrestrial Ecosystems
Modeling climate change impacts on forest productivity with PnET-CN Emily Peters, Kirk Wythers, Peter Reich NE Landscape Plan Update May 17, 2012.
Plant Ecology - Chapter 14 Ecosystem Processes. Ecosystem Ecology Focus on what regulates pools (quantities stored) and fluxes (flows) of materials and.
Paul R. Moorcroft David Medvigy, Stephen Wofsy, J. William Munger, M. Dietze Harvard University Developing a predictive science of the biosphere.
EFIMOD – a system of models for Forest Management A.S. Komarov, A.V. Mikhailov, S.S. Bykhovets, M.V.Bobrovsky, E.V.Zubkova Institute of Physicochemical.
SOME ASPECTS OF ACCUMULATED CARBON IN FEW BRYOPHYTE- DOMINATED ECOSYSTEMS: A BRIEF MECHANISTIC OVERVIEW Mahesh Kumar SINGH Department of Botany and Plant.
1. Ecological legacies are: Anything handed down from a pre-disturbance ecosystem (Perry 1994). The carry-over or memory of the system with regard to.
Chapter 17 Frontiers in Ecosystem Science © 2013 Elsevier, Inc. All rights reserved. From Fundamentals of Ecosystem Science, Weathers, Strayer, and Likens.
Improving the Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Satellite Data E.Kantzas, S.Quegan & M.Lomas School of Maths.
Summary of Research on Climate Change Feedbacks in the Arctic Erica Betts April 01, 2008.
Limits and Possibilities for Sustainable Development in Northern Birch Forests: AO Gautestad, FE Wielgolaski*, B Solberg**, I Mysterud* * Department of.
A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v. 3.0) A. D. Friend, A.K. Stevens, R.G. Knox, M.G.R. Cannell. Ecological Modelling.
BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms.
«An adaptation of Larix in Global climate changes in Arkhangelsk region». Elena Surina FGU «Northern Research Institute of Forestry»(Arkhangelsk) FGU «Northern.
June 2011 The UNEP Java Climate Model Cindy Shellito University of Northern Colorado.
Effects of Forest Management Practices on Carbon Storage Coeli M. Hoover USDA Forest Service, Northern Research Station Forest PLUS, Washington DC December.
SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS Larisa Khanina 1, Maxim Bobrovsky 2, Alexander Komarov 2, Alex Mikhajlov 2 1 Institute of Mathematical.
Modeling Modes of Variability in Carbon Exchange Between High Latitude Ecosystems and the Atmosphere Dave McGuire (UAF), Joy Clein (UAF), and Qianlai.
International and National Abatement Strategies for Transboundary air Pollution New concepts and methods for effect-based strategies on transboundary air.
Investigating the Carbon Cycle in Terrestrial Ecosystems (ICCTE) Scott Ollinger * -PI, Jana Albrecktova †, Bobby Braswell *, Rita Freuder *, Mary Martin.
The patterns and consequences of post-fire successional trajectories in Alaska’s boreal forest The “Generators” - Fire severity - Abiotic and biotic site.
Inhofe, who held an impromptu press conference in the Bella Center, said the chances of passage of pending climate and energy legislation were "zero" and.
Scaling Up Above Ground Live Biomass From Plot Data to Amazon Landscape Sassan S. Saatchi NASA/Jet Propulsion Laboratory California Institute of Technology.
1 UIUC ATMOS 397G Biogeochemical Cycles and Global Change Lecture 1: An Introduction Don Wuebbles Department of Atmospheric Sciences University of Illinois,
Modeling CO 2 emissions in Prairie Pothole Region using DNDC model and remotely sensed data Zhengpeng Li 1, Shuguang Liu 2, Robert Gleason 3, Zhengxi Tan.
Goal: to understand carbon dynamics in montane forest regions by developing new methods for estimating carbon exchange at local to regional scales. Activities:
George Peacock, Team Leader Grazing Lands Technology Development Team Central National Technology Support Center 2010 Southern Regional Cooperative Soil.
Soil Basics AP Environmental Science. SOIL ≠ DIRT.
DIAS INFORMATION DAY GLOBAL WATER RESOURCES AND ENVIRONMENTAL CHANGE Date: 09/07/2004 Research ideas by The Danish Institute of Agricultural Sciences (DIAS)
Soil organic carbon response to harvested crops: a comparison between biogeochemistry model versions Beth Drewniak.
Above and Below ground decomposition of leaf litter Sukhpreet Sandhu.
Ecological insurance and risk assessment Authors: Prof. A.N.Kosarikov, Dr.Sc (Econ) Assoc.Prof. A.V.Ivanov Assoc.Prof. Zh.A.Shevchenko, Cand.Sc. (Econ)
European NWFPs network |Action FP1203 | 1 COST Action FP1203: European non-wood forest products (NWFPs) network Task Force 3:Optimising co-production.
Chapter 4 Part 2. Soil Formation and Generalized Soil Profile.
SOIL AS AN ECOSYSTEM INTRODUCTION TO SOILS FIELD STUDY What do we know about soil now? What makes up soil? What lives there? Where does soil come from?
Nitrogen in the Terrestrial Environment November 15 th, 2006 General Ecology lecture.
Alternative Silvicultural Techniques for European Sub-alpine and Montane Protection Forests: Managing for community protection, disturbance resistance.
Carbon Sequestration Akilah Martin Fall 2005.
Community Land Model (CLM)
ICP Integrated Monitoring of Air Pollution Effects on Ecosystems -
Global Terrestrial Observing System
Raisa Mäkipää Natural Resources Institute Finland
Biogeochemistry of Wetlands
Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.
Plateforme ECOBAG Inter-regional Platform «Water and sustainable development» of Adour-Garonne River Basin ECOBAG Connecting science and stakeholders in.
Rangeland Soil Carbon: State of Knowledge
Anna-Stiina Heiskanen Luc Feyen
Presentation transcript:

Report of St. Petersburg Team O.G. Chertov, M.A. Nadporozhskaya E.V. Abakumov Biological Research Institute St. Petersburg State University 2005 INTAS SILVICS

Introduction n A close cooperation with the Pushchino and Fraunhofer teams n Development of a theoretical background for the SOM model n Incorporation of a new experimental data into the models n Formulation a new version of ROMUL model n Test the models for different spatial scales

The laboratory experiments § Impact of biochemical parameters of plant debris on the rate of their decomposition § Impact of the disposition of decomposing matter (pure or in mixture with different soil material) to specify difference of above-ground and below-ground litter decomposition and patterns of decomposition in organic layers § Specification of nitrogen mineralisation in dependence on SOM and soil properties

The field works include: Experiments on decomposition of forest litter fall of different quality in the forest A study of SOM accumulation in a process of primary soil formation

Theoretical analysis of the decomposition process

Model of SOM and N dynamics ROMUL n The model is based on a classical concept of humus type (Humusform) n Experimental base for the model compilation is published and authors data on organic debris decomposition in controlled conditions n The rate of litter and SOM humification and mineralisation is dependent on quality of litter, soil temperature and moisture, and some soil physical and chemical parameters n There is a specification of rate variables for above and below ground litter cohorts n The model calculates the dynamics of organic matter and nitrogen during the decomposition with gross CO 2 and available N evaluation n The model was evaluated against the long-term experimental data n The model is in use as a soil compartment in three forest ecosystem models

Flow chart of ROMUL model

Elaboration of a new ROMUL version n A large set of experimental data for SOM decomposition allows for a revision of ROMUL model n The kinetic coefficients of litter and SOM mineralisation were re-calculated using Bleasdale function and a special program (A.S. Komarov and M.A. Nadporozhskaya) n This allowed to specify the mineralisation rate in two sub horizons of forest floor (F and H) and a peat n A structure and test program of a new version of ROMUL model was compiled and preliminary tested

Calculation of kinetic coefficients of organic debris mineralisation and humification Stage of fast decomposition reflects a mineralisation of fresh organic debris Stage of slow decomposition represents a mineralisation of humified organic debris - not the material with increased concentration of lignin only The function of Bleasdale was used for approximation of experimental curves: y = (a + bt) - 1/c or y = (a + bt) 1/c

Flow chart of a new version of ROMUL model

The use of forest ecosystem model EFIMOD for research and practical implementation at forest stand, local and regional levels n Recently, the idea on the necessity to have a cascade of forest ecosystem models with a different spatial resolution was dominated in the terrestrial ecosystem modelling n Now there are technical opportunities allowing for a use of one basic model type at any spatial levels without the loss of information obtained at the lower levels n Some results of and prospects for the implementation of one basic model type to cover different spatial scales in forest ecosystem modelling were investigated

Methods and Material n Standard EFIMOD simulations of a single stand growth and soil changes were performed for the model use at different scales: n Individual tree growth n Stand level: effects of environmental changes; thinning regimes n Local (landscape) level: silvicultural regimes in forest enterprise (case studies) n Regional level: soil carbon dynamics for a large forest area

Individual tree growth Trajectories of individual tree growth on 25-m transect in a modelled Norway spruce stand Map of individual trees disposition on the modelled plot

Hierarchy of spatial scales for the application of a stand level model Stand level: Parameters of individual trees growth Stand/soil parameters in detail No generalised parameters for forest area Local/landscape level: Optionally parameters of individual tree growth Stand/soil parameters in details Generalised parameters of any format for forest area Regional level: No parameters of individual tree growth Optionally stand/soil parameters in full details Generalised parameters of any format for forest area

The results of EFIMOD runs at different scales shows that n The application of one basic stand-level forest model for different spatial scales has positive prospects for its further development At local and regional levels, this approach was used by Chumachenko et al. (2003: ForRus), Ho et al. (1999: LANDIS), Garman (2004), Kurz & Apps (1999: CBM-CFS2) and Nabuurs et al. (2003: EFISCEN) n The approach can be an additional methodological option that will be more effective for the practical implementation of the forest modelling for the realisation of the concept of Sustainable Forest Management

Case study I and II: Application of the EFIMOD-Pro for the analysis of carbon balance at different silvicultural regimes in forests of Central European Russia

Collaboration with Projects Teams n Close co-operation with Pushchino and Fraunhofer teams n Participation in the Case Study Participation in the interpretation and presentation of the results of geovisualisation and Exploratory Spatial Data Analysis (ESDA) for Case Study

Links to other projects n EU INTAS Project Podzol n St. Petersburg State University Project Changes of Soils and Soil Cover under Anthropogenic Factors n Russian Federal Science and Technology Program Global Climate Changes and Carbon Cycle, part 14 Soil as a source of greenhouse gases

Publications for the period International journals Published4 Submitted 3 Proceedings and national journals Published7 Submitted3 Abstracts to conferences 19

21 presentations at international and national scientific meetings for the period May February 2005 Pushkin, SPB (3) Gent(1) DSS Vienna (3), Uni Hohenheim (1) Trippstadt Forest Station (1) Pushchino (3), Kazan (2), Quebec (1) ForMod Vienna (3) ECEM 04 (2)

Acknowledgements The participants of SPBU team acknowledge colleagues from other teams of the Project, the Administration of the Biological Institute, the Department of Soil Science and Soil Ecology of St. Petersburg State University and the Dokuchaev Soil Museum for their active collaboration and valuable help