Introduction to ecosystem modelling

• Concept of a system

• From systems to ecosystems

• Models and their use in science and research

• System dynamics modelling

• Ecosystem modelling

NGEN02 Ecosystem Modelling 2015

Recommended reading:

Systems and simulation models, Compendium page 3

Smith & Smith Environmental Modelling, Chapter 1

The system concept

• ’Systems’ are fundamental to the organisation and processes of society

and daily life

political system

transport system

educational system

judicial system

booking system

heating system

Characteristics:

• impose structure, make things ’simple’, ’transparent’, ’efficient’

• ’make things work’

• consist of (clearly defined) elements ...

• ... and links between them

Political system

Transport system

Education system

The system concept

• In science, systems provide a way of organising knowledge and ideas

Characteristics:

• depict knowledge and ideas in a ’simple’, ’transparent’, ’efficient’ way

• consist of (clearly defined) elements and links

• have a clearly defined boundary

• omit extraneous detail, simplify / generalise

Related to the reductionist approach

• defined fragment of knowledge or theory ...

• ... reduced to its essential or most relevant (in a particular context)

elements

Knowledge

Study Alcohol

consumption

System governing outcome of university studies

+

Exam results

+

curiosity

+

+

existential

worry

+

+

parental

expectations

+

spare time

+ +

+

system boundary

external drivers

state variable

output

system- internal feedbacks

system elements

Exercise

• In discussion groups 3-4 students, 15 mins

• Think of and sketch a diagram describing a system from your daily lives,

e.g. travel to work, doing the dishes, meeting a boy/girl.

• Include and show

system boundaries

elements

sign and direction of links

state variable(s)

drivers and output(s)

at least one internal feedback

sign (+ or ) of each feedback loop

Knowledge

Study Alcohol

consumption

spare time parental

expectations

Exam results

curiosity existential

worry +

+

+

+

+

+

+ + +

+

System governing outcome of university studies

Tree biomass

photosynthesis respiration

temperature incoming

sunlight

Harvestable timber

leaf area index metabolic

biomass +

+

+

+

+

+

+ + +

+

System governing growth of a forest stand

external drivers

state variable

output

system- internal feedbacks

Summary: characteristics of a system A system:

• a group of distinct but interrelated elements comprising a unified whole

• may exhibit function arising from the interactions or links between elements

• may exhibit ’emergent’ properties or behaviour that can only be understood

through the interactions and relationships of the elements of the system

System element:

• can be specified by its properties (e.g. a tree: height, leaf area, biomass)

System function:

• a time-dependent process linking two elements (e.g. leaf shedding

transfers carbon between a tree and the soil) ...

• ... or the aggregate effect of multiple processes and interactions (e.g. net

primary production = photosynthesis plant respiration)

System state:

• the value of an element (state variable) at a point in time

From systems to ecosystems

Ecosystems (Tansley 1935):

• “Though the organisms may claim our prime interest ... we cannot separate them from their special environments, with which they form one physical system”

• “The whole system … including not only the organism-complex, but also the whole complex of physical factors forming what we call the environment”

Operational definition:

• The organisms living in a particular place and a particular time, and the

air, water and soil within which they live and with which they interact

boundary

elements links

compartment

process

flux

Ecosystem P cycle

in Lake Tanganyika

(Naithani et al. 2006)

From systems to ecosystems

Traditional conceptualisation:

• System elements = pools or compartments of carbon, nitrogen,

phosphorus, silica (major building blocks of life)

• System links = flows or fluxes of C, N, P, Si or energy between pools

• Processes (biological, chemical, physical) control system dynamics by

governing rates of fluxes.

Processes+fluxes = ecosystem function.

From systems to ecosystems

Special characteristics:

• Exhibit structure (spatial configuration of elements) at different scales

• Driven by incoming matter and energy

• Dynamic (evolve over time) governed by:

→ differential process rates

→ rate of incoming matter and energy

→ storage of matter or energy in ecosystem compartments

→ feedbacks between compartment sizes and process rates

tree biomass

C

litter+soil

organic matter

C

net primary

production

heterotrophic

respiration

litter

CO2 CO2

net ecosystem

exchange

time →

0

NPP

biomass C

respiration

soil C

NEE

C flux

C pool

Forest ecosystem C cycle

uptake

release

*Hyvönen et al. 2007

New Phytologist 173: 463-480

Forest ecosystem C cycle

Are ecosystems real or imaginary?

• Like any system, an ecosystem is an abstraction (simplified representation)

of the real-world thing it represents!

• The degree and type of abstraction is defined by the choice of:

→ boundaries (physical/geographic/conceptual)

→ included elements (e.g. ”soil C” encompasses many compounds,

organism groups and species)

→ included processes / fluxes / links / feedbacks

→ included drivers

→ representation of structure

The Scientific Method

knowledge observation

hypothesis

true false conclusion

all

knowledge

new

knowledge

systematic

observations

test

hypothesis

?

statistical test

What is a model?

In general:

• An idealised, simplified or down-sized representation of something ...

• ... the purpose is to describe, explain or depict the thing the model

represents

What is a model?

In science:

• An idealised or simplified conceptual or formal representation of a

phenomenon or item of interest, usually from the real world

• ... the purpose is to describe, explain or study the real-world phenomenon

the model represents ...

• ... enabling conclusions to be drawn about its properties or behaviour

Part of the scientific method:

• A model may be thought of as a formalised or explicit hypothesis about the

real-world phenomenon under investigation

• May be falsified by comparing its predictions to observational data.

False model = rejected hypothesis

What is a model?

May be very simple or general:

• ”Helium is composed of two electrons bound by the

electromagnetic force to a nucleus containing two protons along

with one or two neutrons, held together by the strong force”

... or complex and mathematically explicit:

Choosing the right model for the right task

Smith & Smith

Section 1.4

A model should be as simple as possible (for the task in hand) ...

... but no simpler

e.g. Light interception

by a forest canopy

Uses of models

Models have the potential to:

• Make predictions about the response of a system to change in its drivers

• Compare the results of two alternative theories

• Describe the effect of complex factors, such as random variation in inputs

• Explain how the underlying processes contribute to the result

• Extrapolate results to other situations

• Predict future events

• Translate knowledge and results into a form that can be easily used by

non-experts

In short, models are tools for

prediction — interpretation — communication

System dynamics modelling

’Model’ and ’system’ are closely-related concepts. Both:

• strive to depict knowledge and ideas in a simple, transparent or efficient

way

• strive to describe or explain how something ’works’

• can help predict how something may change in response to a perturbation

in external driving forces, i.e. to relate ’cause’ to ’effect’ or ’input’ to ’output’

• many though not all models can be broken down into a number of

elements with links between them, i.e. they represent a system

System dynamics modelling

• Developed in 1960’s by Jay Forrester initially to describe how interactions

between actors and inputs in economic systems govern oscillations like

the ’business cycle’

• Describe a system in terms of ’stocks’ (elements), ’flows’ (links) and inputs

or drivers

• Time-dependent equations govern the dependency of flows on stocks and

inputs

e.g. Population

model for a city

population

N

births food

offspring

per adult

deaths

+

+

+

Ecosystem modelling

Numerical ecosystem models are generally system dynamics models:

• Ecosystem compartments as stocks (state variables) e.g.

• C, N, P in biomass and detritus pools

• population density of organism groups

• water storage in soil, snow pack, canopy

• Ecosystem fluxes as flows

• into system (e.g. photosynthesis)

• out of system (e.g. respiration, evapotranspiration)

• between compartments (e.g. litter transfer from vegetation to soil)

• External drivers e.g. temperature, solar insolation, rainfall, N deposition

• Time-dependent equations describe processes controlling (rates of) fluxes

depending on state variables and external drivers

A typical Ecosystem model

Drivers - Temperature - Radiation - Precipitation

Fluxes - Exchange of energy and matter between the

system and its surrounding - Exchange of energy and matter between the

stocks of the system

State variables - Carbon stocks - Leaf area - Soil water - Soil moisture

Processes - Light interception - Photosynthesis - Respiration - Hydrology

• system

• element, link, feedback

• boundary, driver, state variable

• emergent property

• structure, function

• ecosystem

• compartment, flux, process

• dynamics

• scientific method, hypothesis

falsification

• abstraction, conceptual model

• scope

• functional, mechanistic

• deterministic, stochastic

• prediction

• cause-effect relationship

• time-dependent equation

• ecosystem model

Keywords from this lecture