SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS
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Transcript of SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS
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SIMULATION OF GROUND VEGETATION DIVERSITY IN
BOREAL FORESTS
Larisa Khanina1, Maxim Bobrovsky2, Alexander Komarov2, Alex Mikhajlov2
1 Institute of Mathematical Problems in Biology of RAS,
Pushchino
2 Institute of Physicochemical and
Biological Problems in Soil Science of RAS, Pushchino
IBFRA conf. ‘New challenges in Management of Boreal Forests’ August 28–30 2006 Umeå Sweden
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Dynamics of ecosystem and plant species diversity
• abiotic parameters (climatic, soil, water, etc.)• temporal parameters of plant populations in different forest zones• spatial parameters of the area and plant populations• availability of seed sources
Forest Ecosystem Modelling
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EFIMOD forest-soil model (Chertov et al., 1999, Komarov, et al., 2003)
Different levels of forest modelling
Forest ecosystem modelling
FORRUSIndividual-based models
forest model (Chumachenko et al., 2003)
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T R E E S
Climate
PAR
Initialisation
Available PAR for trees, ground vegetation and natural regeneration
Redistribution of soil available nitrogen
1 2 3 . n Ground vegetation
Natural regeneration
Model of soil organic matter ROMUL
Forest manager
Data viewer Graph interface 3D visualisation Ecosystem production
Soil features Trees renewal
Ground Vegetation
EFIMOD
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The first step
to calculate dynamics of ground vegetation diversity at a level of forest stand on a base of
· State Forest Inventory Data· Forest simulated results
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Our approachplant species functional groups in ground vegetation modelling
ecological-coenotic species groups
introduced in Nitsenko (1969)
derived from multivariate analysis species traits matrix community matrix matrix of
environmental factors
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Ecological-coenotic groupsNemoral
Nm
species of broad-leaved
and oak forests
BorealBr
species of boreal spruce
and spruce-fir forests
PinyPn
species of pure pine
forests
Nitrophilous Nt
species of flooded
black alder forests
Meadow Md
species of meadows,
steppes and forest edges
Water-marsh Wt
species of coastal and
intrawater habitats, lowland bogs
Oligotrophic
Olgplants of oligotrophic bogs
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To use the groups for modelling dynamics of ground vegetation· to define the dominant group
at the initial step of simulation
· to define rules of the group switching according to dynamics of the simulated parameters
tree species composition, light supply, deadwood, litter, soil C and N pools etc.
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At the initial step of simulation
Regional vegetation databases
Ecological-coenotic forest type
Dominant groups in ground
vegetation
Ecological-coenotic groups of plants
Average species
richness for the forest
unit
Indices of vegetation diversity for
regional forest types
Forest Inventory DataDominant treein overstorey
Dominant species in understorey
Phytosociological releves
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Database on 11000 vegetation sample plots in mapped points of European Russian forests
Regional vegetation databases
Phytosociological releves
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Average species richness for the forest
unit
Average species richness for the forest
unit
Dynamics of ground vegetation diversity
Step 1 Step n
Dominant tree species
Dominant ecological-
coenotic group
Forest inventory data EFIMOD runs Tree species composition
Deadwood, litter, soil C and N pools
Ecological-coenotic
forest type Dominant ecological-
coenotic group
Dominant tree species Ecological-
coenotic forest type
Regional vegetation databases
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BioCalc - a software for dynamic analysis
of forest ground vegetation diversity
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BioCalc input data
· tables of probabilistic distribution of the groups in ground vegetation according to the tree dominant and the forest site class· a correspondence tables between the forest types and ranks of plant species richness· a time series table of forest stand ecosystem parameters (results of the EFIMOD runs)
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Creation of rules for the switching the ecological-coenotic groups
BioCalc user selects in an interactive mode from the time series tables the thresholds for a number of ecosystem parameters.
These thresholds cause a change of the dominant ecological-coenotic group.
The user can observe all values of any ecosystem parameter displayed graphically
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Creation of rules for the switching the ecological-coenotic groups
If the values are digital, the graphic is built with the values in ascending order, which allows for an`easy detection of the thresholds
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BioCalck outputsDynamics of
· ground vegetation functional groups,
· forest types, and · ranks of species diversity
Transfer of the output results to the Common-GIS (Andrienko, Andrienko, 1999) for visual exploration of ground vegetation dynamics at the landscape level
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A case study experimental forestry“Russkii Les” (Moscow region)
273 ha 104 units
Strategies of silvicultural regimes for 200 years time span
·natural development ·legal clear cutting
·selective cutting ·illegal clear
cutting
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(i) meadow group switched to boreal group when spruce began to dominate in overstorey
(ii) any group switched to nemoral when oak and lime began to dominate in overstorey
(iii) piny group switched to boreal group when deadwood overpassed the 1st threshold value
(iv) any group switched to nitrophilous group when deadwood overpassed the second threshold value, and
(v) nitrophilous group switched to nemoral group when deadwood fell below the 2nd threshold value
Case study rules of functional group switching
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In the scenarios with clear cuttings: after the clear cutting, a dominant
group was taken from a specially designed probabilistic table of the group distribution in ground vegetation designed for the after-clear-cutting conditions
Case study rules of functional group switching
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Tree dominant dynamicsSelective cuttingsNatural development
Illegal clear cuttingsLegal clear cuttings
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Tree dominant dynamics
The beginning
Legal clear cutting
Natural development
Legal selective cutting
Illegal clear cutting
200-year dynamics
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Deadwood dynamics
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Functional group dynamics
The beginning
Legal clear cutting
Natural development
Legal selective cutting
Illegal clear cutting
200-year dynamics
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Functional group dynamicsNatural development
Legal clear cutting Illegal clear cutting
Legal selective cuttings
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Species diversity dynamics
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Species diversity dynamics
The beginning
Legal clear cutting
Natural development
Legal selective cutting
Illegal clear cutting
200-year dynamics
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I initial state, II legal clear-cutting, III natural development
50-year dynamics
Regional level: Manturovsky forestry (Kostroma region), 120 000 ha, 3430 units
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ConclusionThe functional group approach was
elaborated and tested for modelling the dynamics of forest ground vegetation diversity.
The modelling results showed that cuttings support a higher ecosystem diversity of the area in comparison to the free forest development.
However, the protective strategy leads to the higher species diversity in ground vegetation, if a free forest development has taken place for rather long time, e.g. more than 100 years in our study area.
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used tree compositiondeadwood
in progress C and N soil pools
in plan light soil moisture
EFIMOD parameters for ground vegetation dynamics
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Thank you for your attention!