Classification of models depending upon modelling concepts Classification...

23
Classification of models depending upon modelling concepts Classification of models depending upon time-hierarchical level Classification map of forest models Categories of forest models Dedicated to everybody who loves forest models

Transcript of Classification of models depending upon modelling concepts Classification...

Page 1: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

• Classification of models depending upon modelling concepts • Classification of models depending upon time-hierarchical level • Classification map of forest models • Categories of forest models

Dedicated to everybody who loves forest models

Page 2: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

1

At genesis of forest modelling the three Wise men have operated :

The first has been called BIOLOGIST

and searched for the answer to: „Why tree organs growth?“

He gave to world: algorithm of photosynthesis

Gift has been accepted in disciplines: bioclimatology, ecopedology, plant physiology

Causal models have been established.

The second has been called MATHEMATICIAN

and searched for the answer to: „How the tree is formed in space ?“

He gave to world: fractal

Gift has been accepted in disciplines : formal grammar, fractal geometry, computer graphics

Morphological models have been established.

The third has been called FORESTER

and searched for the answer to: „What benefit is produced by forest?“

He gave to world: regression equation

Gift has been accepted in disciplines : biometry, forest mensuration, forest growth and yield science

Empirical models have been established.

Page 3: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

2

causal models process-based models eco-physiological models biochemical models bio-geochemical models mechanistic models "flux" models

Page 4: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

3

morphological models structural models fractal models recursive models

Page 5: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

4

empirical models biometric models statistical models correlation models

Page 6: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

5

empirical

models

structural

models

process-based

models

1994 – Kurth

Page 7: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

6

• Modelling of causal relations based on eco-physiological processes: absorption of radiation, pedotransfer functions, hydrological balance, stomatal conductance, transpiration, leaf energy balance, photosynthesis, respiration, phenology processes, allocation • Input: detailed climatic and soil variables, initial biomass, leaf area • Output: carbon and biomass production, variables of eco-physiological processes

Page 8: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

7

• Modelling of plant morphology based on plant architecture and organ topology with principles of recursive rules, fractal geometry, L-systems and turtle graphics • Input: initial axiom (structure), growth grammar and parameters of growth grammar • Output: plant morphology in years of prognosis

time

Page 9: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

8

• Modelling of forest production based on statistical equations derived from empirical data • Input: biometry variables from forest inventory, description of site conditions • Output: biometry variables

Page 10: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

9

second day year decade century millennium

cell

organ

organism

population

community

biome hierarchical level

time level

2001 – Pretzsch

Page 11: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

10

upscale

downscale

Page 12: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

11

Page 13: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

12

Position in map: I = organ + 3D Typical time scale: hour or day Concept: process-based Description: Eco-physiological tree models simulate processes in individual organs depending on their position in 3D space. Examples of products: BALANCE, TRAGIC, EFIMOD, SPRUCOM, model by Pfreundt

Page 14: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

13

Position in map: I = organ + 3D Typical time scale: year Concept: structural Description: Functional-structural plant models simulate development of plant morphology in 3D space based on L-systems and processes in organs. Examples of products : GROGRA, GroIMP, EMILION, LIGNUM

Page 15: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

14

Position in map: V = organ + region Typical time scale: hour or day Concept: process-based Description: Big leaf models simulate processes in abstract leaf representing total assimilation rate in modelled unit space. Assimilation rate is homogeneous in unit space. Examples of products : 3-PG, Biome-BGC, CASA, DEMETER, FBM, Forest-BGC, FORSANA, PnET, TEM, Tree-BGC, GOTILWA

Page 16: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

15

Position in map: II = individual+2D Typical time scale: year Concept: empirical Description: Distance dependent tree models simulate tree development based on statistical equations derived from empirical data. Competition of trees is dependent on tree positions in 2D space. Examples of products: pure empirical: FOREST, FORMOSAIC, MOSES; semi-empirical: SIBYLA, SILVA, SORTIE

Page 17: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

16

Position in map: IV = individual + stand Typical time scale: year Concept: empirical Description: Distance independent tree models simulate tree development based on statistical equations derived from empirical data. Competition of trees is independent on tree positions in 2D space. Examples of products : BWIN, PROGNAUS, STAND PROGNOSIS MODEL, TreeGrOSS

Page 18: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

17

Position in map: III = individual + bio-group Typical time scale: year, 5 years or decade Concept: empirical or process-based Description: Gap models simulate development of individual trees in bio-groups of trees on basis of change of generations. Natural succession is achieved by dynamics of bio-groups. Examples of products: FORECE, FORENA, FORET, FORMIND, FORSKA, JABOWA, LINKAGES, NEWCOP, PICUS, SIMA, ZELIG

Page 19: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

18

Position in map: III = class + bio-group Typical time scale: year, 5 years or decade Concept: empirical or process-based Description: Cohort models divide bio-groups to homogeneous parts. Parts called cohorts are represented by typical tree and frequencies of trees in cohorts. Examples of products: 4C, FLAM, ForClim, FORMIX

Page 20: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

19

Position in map: IV = class + stand Typical time scale: 5 years or decade Concept: empirical Description: Frequency models simulate development of diameter and height structure of stands along the time depending on changed frequency functions. Examples of products: LANDIS, LANDSIM, model by Cluter, Moser, von Gadow, Suzuki, Kouba, Sloboda

Page 21: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

20

Position in map: IV = population + stand Typical time scale: 5 years or decade Concept: empirical Description: Stand models (yield tables) describe development of entire stand on basis of site class and age. Conception of even-aged and pure stand is applied with limited management. Examples of products: STAOET, DFIT, model by Curtis, all yield tables (Assmann and Franz, Hamilton and Christie, Vuokila, Schmidt, Lembcke et al., Halaj et al., Petráš et al.)

Page 22: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

21

Position in map: V = ecosystem + region Typical time scale: century Concept: empirical or process-based Description: Biome models are static models simulating change of vegetation types (biomes) influenced by changing of environmental conditions (temperatures, precipitation, etc.) during long periods. Examples of products: empirical: model according to Holdridge; process-based: BIOME, DOLY, MAPSS, TVM

Page 23: Classification of models depending upon modelling concepts Classification …user.mendelu.cz/drapela/Sibyla/05_developer.pdf · 2014-01-20 · • Classification of models depending

22

Model according to Holdridge