ESS Unit 1.2 - Systems

Model

A simplified representation of a structure or process, used to improve understanding, make predictions, and communicate ideas

Uses of models

1. understanding the most important components and processes in a complex situation

2. make predictions about future

3. transfer understandings we have from one to another areas

4. understand things that are too small or too big (atoms, solar systems)

5. recognise patterns in the world

6. test processes and outcomes under different conditions

Limitaitons of models

based on assumptions and leave out certain information

→ to get around this we develop different scenarios, based on using different assumptions in the model

→ example: UN population projection model → UN can develop different possible population predictions by using different assumed birth rates, death rates and probabilities

Emergent properties (emergence)

Characteristics of a system that appear when the individual system parts interact; the system parts themselves do not have these characteristics
- e.g.: predator - pray oscillations (коливання) → where the number of predators and prey for certain ecosystems are found to change in a regular cycle

Gaia hypothesis

A theory that all living organisms, along with the Earth's physical components, form a complex system that maintains conditions suitable for life

System boundaries

A line that separates the system you want to study from the external environment that is not part of that system

Emergent properties

Characteristics of a system that appear when the individual system parts interact; the system parts themselves do not have these characteristics.

Open system

A system that exchanges both matter and energy with its external environment

examples of open systems

local ecosystem (e.g. a forest, pound or grassland)

human body

Closed system

A system that exchanges energy with the external environment, but not matter

Closed system examples

nitrogen, carbon, hydrological cycles

storages in a system

An accumulation of matter, energy, and information in a system; the location where matter, energy, and information are held.

→ examples: bathtub, country’s population, mineral deposits in an area, buildings in a city

→ represented by rectangular boxes

Flows in systems

A movement of matter, energy or information between storages in a system.

Inflow - causes the storage to increase

Outflow - causes the storage to decrease

→ represented by arrows

Difference between “input” & “output” and “inflow” & “outflow”

→ Inputs and outputs are things like water, oil, money, pollution, or some other thing that could be counted and accumulated

→ inflows and outflows are processes, either transfers or transformations, which are covered later in this section

→ inflows and outflows are more active

principles of storages and flows

1. inflows > outflows - storage level increases (upward trend)

2. outflows > inflows - storage level decreases (downward trend)

3. inflows = outflows - storage remains constant in dynamic equilibrium (horizontal line)

4. flows change faster than storages - storages take longer to change because flows need time to accumulate

Transfers

A system flow that involves a change in location of energy or matter, without any change in its state or form

examples: water flowing in a river, heat being moved by ocean currents, kinetic energy moving from a bat to a ball when the ball is hit

Tranformations

A system flow that moves energy and matter, but in the process there is also a change in the chemical nature, a change in state, or a change in energy.

examples: liquid water freezing to a solid state, plants turning solar energy into glucose, burning fossil fuels in combustion

Steady-state equilibrium

A situation where there are continuous inputs and outputs of energy or matter to the system that may result in short-term changes and imbalances

succession

The process of change over time in an ecosystem

Negative feedback loop

When the output of a storage or system returns as an input in a way that inhibits or reverses the operation of the same process; reduces change, stabilising

examples: homeostasis, predation,

Positive feedback loops

When the output of a storage or system returns as an input in a way that amplifies change, destabilises the system and drives it away from its equilibrium

example: population of species declines → more difficult for individuals to find mates → reproduction declines → less genetic biodiversity → decrease in the population’s resilience to disease and other disturbances → even lower population

Tipping point

A critical threshold at which even a small change can have dramatic effects and cause a disproportionately large response in the overall system

example: the sudden emergence of algal blooms in a small pond or lake by eutrophication (The natural or artificial enrichment of a body of water, particularly with respect to nitrates and phosphates, that results in depletion of the oxygen content of the water. Eutrophication is accelerated by human activities that add detergents, sewage, or agricultural fertilizers to bodies of water)

casual loop diagrams

A type of systems diagram that illustrates complex relationships between different variables in a system.

resilience

A system’s ability to recover when disturbed - the ability to avoid tipping points and maintain stability.

Efficiency in ecosystems

How well an organisation or system transforms physical, human, and financial inputs into outputs.

Productivity

The ratio of output per unit of input (materials, labour, or financial capital) over a period of time, for example, the rate of creation of new biomass in an ecosystem in a unit of time

Factors affecting resilience

casual loop diagram basic elements

• variables

• the casual connections between the variables

• the type of influence: direct relationship (+) or inverse relationship (-)

• the type of loop: negative (balancing, indicated by B) and positive (reinforcing, indicated with P)

Factors affecting resilience

• diversity

• size and number of storages