1

1

II. CONCEPTUAL AND

MODELING THEORY

ECOLOGICAL MODELLING

2

1. Models

- Mankind has always used models as tools to solve problems as they give a simplified picture of reality

- The model never contain all the features of the real system

- The model contains the elements essential in the context of the problem to be described or solved

2

3

1. Models

Geographical maps:

- different types / different purposes (roads, land use, …)

- different scales

- don't contain all details

Ecological models:

- focus on the objects of interest for the problem under consideration

- too many irrelevant details would cloud the main objectives of the model

- very many different models of the same ecosystem.

Comparisons : geographical maps vs. ecological models

4

1. Physical and Mathematical models

- Physical models: model plants, pot experiements = micro cosmos models

3

5

1. Physical and Mathematical models

- Mathematical models: describing the main characteristics of the system in mathematical terms

Micro-cosmos models help to build mathematical models

6

1. Condition for modelling

Conditions that enabled rapid development of ecological modelling in last 30 years:1: Development of computer technology: - enabled to handle very complex mathematical models2: General understanding of pollution problems:- complete elimination of pollution is not feasible (“zero discharge”) - pollution control requires serious consideration of pollution impacts on ecosystems 3: New knowledge about environment and ecological problems:- quantitative relationships between the elements in the ecosystems and between ecosystem and its’ environment

4

7

1. Models vs. Statistics

Model: a synthesis of what we know about the ecosystem with the reference to the considered problem

Statistical analysis: reveal of relationships between the data

Model encompasses our knowledge about the system:- which components interact with each other i.e.

zooplankton grazes on phytoplankton - mathematical formulation of the processes between the

elements of the model - link between the problem and the process needed for the

solution of the problem

8

1. Models vs. Statistics

Model can offer deeper understanding of the system then statistical analysis.

It may yield better management plan for solving the focal environmental problem.

The results of statistical methods should not be ignored in the process of model making.

Models are build on:- statistical analysis of data - physical-chemical-ecological knowledge - the laws of nature- soft knowledge (common sense)

5

9

2. Models as a Scientific tool

- to understand the function of such a complex system

- to survey the many components of and their reactions in an ecosystem

The application of models in ecology is almost compulsory:

==>> investigation of complex systems

==>> solving complex problems

==>> the only approach to deal with irreducible systems-

10

2. Models as a Scientific tool

- Nuclear physic: properties of sub atomic particles are studied by models

- Astronomy: life of the stars and galaxies are studied by models

- Ecology: properties of ecosystems is examined with models

6

11

2. Models as a Scientific tool

Modelling as an instrument to understand the properties of ecosystem.

Advantages of models as useful tool in ecology: - instruments in the survey of complex systems - used to reveal system properties- reveal the weakness in our knowledge => used to set up research priorities - test of scientific hypothesis as the model can simulate ecosystem reactions which can be compared with observations

12

2. Models as a Scientific tool

Use of models to test hypothesis => very often purpose of modelling

“PRO”:

=> model about interaction between two or more variable is tested on additional several cases to increase certainty

=> if the relationship holds several examinations a wider scientific use of this model in possible

7

13

2. Models as a Scientific tool

“CONTRA”:Using model (ecological model) to test hypothesis:

1.=> model is correct and the hypothesis is correct

2.=> model is not correct but the hypothesis is correct

3.=> model is correct but hypothesis is not correct

4.=> model is not correct and the hypothesis is not correct

14

2. Models as a Scientific tool

The idea behind the use of models as scientific tools may be descried as an iterative development of pattern:1. Both the model and the hypothesis are correct => new piece of the pattern is made2. Does the piece fit into the general pattern? => NO --- go back: - change the model or hypothesis

- forced to change the pattern

=> YES --- new piece can be used at last temporarily in the pattern which is used to: - explain other observations - improve our models and make other predictions, which are then tested

8

15

2. Models as a Scientific tool

A developed model with acceptable results in several

case studies

Improved model Hypothesis

Confirmation

Further confirmation

Elements in the theoretical pattern (ecosystem theory)

The model is tested in more case studies

More tests of the hypothesis by the

model

The model is used to test the hypothesis in a

few cases

Test against the general theoretical

pattern.

16

3. Models as a Management tool

The idea behind the use of ecological management models:

Industrialisation and urbanisation

Emission ECOSYSTEM

Ecological modeling

Environmental technologies

Reasoning for introduction of ecological modelling as a management tool in around 1970.

9

17

3. Models as a Management tool

Modelling approach used today is more complex and more comprehensive (system approach) and respects:

- Application of environmental technologies - Cleaner technologies - Point or no point (diffuse) source of pollution (agronomy) - Global warming, depletion of the ozone layer

18

4. The development of ecological and environmental models1920 (1st generation of models):

-the model of the oxygen balance in a stream (the Streeter-Phelps model):

- the pray-predator realtionship (the Lotka-Volterra model)

Alfred Lotka

Vito Volterra

10

19

4. The development of ecological and environmental models1950-60 (2nd generation of models): population dynamic models, more complex river models

20

4. The development of ecological and environmental models1970 (3rd generation of models): use of ecological models in environmental management (first eutrophication models, very complex river models ):

revolution in computer technology

limitation of data and knowledge about ecosystems and ecological processes (structures and processes)

11

21

4. The development of ecological and environmental modelsTo develop sound ecological models we need

knowledge about ecosystem

well defined problem

knowledge about ecological components

quality data

Modelers became critical in their acceptance of the models

22

4. The development of ecological and environmental modelsThey confirmed general recommendations for development of the models

follow strictly all steps of the procedure (i.e. conceptualization, selection of parameters, verification, calibration, sensitivity, validation, etc.)

complexity of the model must be in balance between data, problem, ecosystem and knowledge

sensitivity analysis should be used in the selection of model components and model complexity

parameters estimation by using all the methods: literature, measurements in lab or on site, calibration sub-model and entire model, estimation based on allometric principles, …

12

23

4. The development of ecological and environmental models1970-80 (4th generation of models):

- relatively sound ecological bases

- emphases on realism and simplicity

- based on many case studies

- development of ecotoxicological models

24

4. The development of ecological and environmental models1990-2000 (5th generation of models)

- development of structural dynamic models - development of modelling software tools (ECOPATH, STELLA, MATLAB)

13

25

4. The development of ecological and environmental models2000-2010 (6th generation of models)

- induction of models from data (AI, machine

learninig, data mining)

- qualitative models

26

4. The development of ecological and environmental modelsConclusions:

- Following recommendation it is possible to develop models that could be used as prognostic tools

- Models based on lower quality data could give insight into the handled – they are more simple and such are often of particular value

- Models based upon ecological knowledge are powerful tools in understanding ecosystem behavior and as a tools setting up research priorities =>contribution to ecosystem theory and better environmental management