Environment Southland Using ‘systems thinking’ to explore ...

Environment Southland Using ‘systems thinking’ to explore potential drivers of solid waste – a pilot.

June 2020

Report by:

Justin Connolly Director Deliberate

Dr. Sam McLachlan Science Coordinator – Citizen Science Environment Southland

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Recommended citation: Connolly, J.D. & McLachlan, S. (2020). Using ‘systems thinking’ to explore potential drivers of solid waste – a pilot. (A report for Environment Southland). Hamilton, New Zealand: Deliberate. Version

Date Comments Authorised by

16 June 2020 Issued for review Justin Connolly Director, Deliberate

24 August 2020 Final report issued

(some delays in completion due to the COVID-19 pandemic)

Justin Connolly Director, Deliberate

Elaine Moriarty Science Manager, Environment Southland

Disclaimer: Every effort has been made to ensure that the information contained within this report is as accurate as possible. However, the authors do not guarantee that the publication is without flaw of any kind or is wholly appropriate for your particular purposes. They therefore disclaim all liability for any error, loss, omission or other consequence which may arise from any use of or reliance on the information in this publication. Sections two and three are often reproduced in Deliberate reports. They provide an overview description of what CLD are and how they are used.

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Contents Contents .................................................................................................................................. iii List of figures ........................................................................................................................... iv List of tables ............................................................................................................................ iv Executive summary ................................................................................................................. 1 1 Introduction ...................................................................................................................... 2 2 What is systems thinking? ............................................................................................... 3

1.1. CLD on the spectrum of complexity within System Dynamics ................................ 3 3 The fundamentals of Causal Loop Diagrams – articulating system structure ................. 4

1.2. Feedback loops – the basic building blocks of a CLD. ............................................ 4 1.3. Labelling variables .................................................................................................. 5 1.4. Annotating loops ..................................................................................................... 6 1.5. Goals and gaps – driving individual loop dominance. ............................................. 7

4 The process of building a CLD ........................................................................................ 7 5 Description of Waste CLD ............................................................................................. 10

1.6. Overview of the CLD ............................................................................................. 10 1.7. Progressive description of the CLD ....................................................................... 10

1.1.1 Infrastructure demand loops ............................................................................. 11 1.1.2 Asset burden loops ........................................................................................... 11 1.1.3 Asset burden and rates ..................................................................................... 12 1.1.4 Waste consciousness loops .............................................................................. 12 1.1.5 Waste & recycling ............................................................................................. 13 1.1.6 Fly or farm tipping ............................................................................................. 14 1.1.7 Tourism loops .................................................................................................... 15 1.1.8 Landfill erosion .................................................................................................. 16 1.1.9 Climate change and landfill erosion .................................................................. 17 1.1.10 Water quality ................................................................................................. 18 1.1.11 Prevalence of plastics ................................................................................... 19

6 Using the CLD to explore the anticipated dynamics of the system over time ................ 20 1.8. Different ways of gaining insight from a CLD ........................................................ 20 1.9. How analogue simulation was used ...................................................................... 20

1.1.12 Analogue simulation methodology ................................................................ 21 1.1.13 Analogue simulation scenarios ...................................................................... 21

1.10. Analogue simulation results .................................................................................. 22 1.1.14 Scenario 1: Waste education ........................................................................ 22 1.1.15 Scenario 2: Tourism levy ............................................................................... 23 1.1.16 Scenario 3: Privatised waste infrastructure ................................................... 24 1.1.17 Scenario 4: Plastic tax ................................................................................... 25

7 Summary and recommendations ................................................................................... 26 8 References .................................................................................................................... 28 Appendix 1 Glossary of factor names and complete image of Waste CLD ...................... 29 Appendix 2 Additional information for running analogue simulation interactively ............. 34

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List of figures Figure 1. System Dynamics tools exist on a spectrum - Causal Loop Diagrams (or System

maps), Stock and flow diagrams, and Simulation modelling. ...................................... 4 Figure 2. The two types of feedback loops .......................................................................... 5 Figure 3. Labelling variables ................................................................................................ 6 Figure 4. How arrows are labelled in CLDs .......................................................................... 6 Figure 5. How delays are annotated on arrows ................................................................... 6 Figure 6. Example of a ‘goal/gap’ structure in a CLD – pouring a glass of water ................ 7 Figure 7. Example factors generated to form part of the CLD ............................................. 8 Figure 8. The process of creating and using a CLD ............................................................. 9 Figure 9. Complete waste CLD .......................................................................................... 10 Figure 10. Infrastructure demand loops ............................................................................ 11 Figure 11. Asset burden loops .......................................................................................... 11 Figure 12. Asset burden and rates ................................................................................... 12 Figure 13. Waste consciousness loops ............................................................................ 13 Figure 14. Waste & recycling ............................................................................................ 14 Figure 15. Fly or farm tipping ............................................................................................ 15 Figure 16. Tourism loops .................................................................................................. 16 Figure 17. Landfill erosion ................................................................................................ 17 Figure 18. Climate change & landfill erosion .................................................................... 17 Figure 19. Water quality ................................................................................................... 18 Figure 20. Prevalence of plastics ..................................................................................... 19 Figure 21. Scenario 1: Waste education .......................................................................... 22 Figure 22. Scenario 2: Tourism levy ................................................................................. 23 Figure 23. Scenario 3: Privatised waste infrastructure ..................................................... 24 Figure 24. Scenario 4: Plastic tax ..................................................................................... 25 Figure 25. Complete Waste CLD ...................................................................................... 33 Figure 26. Example of analogue simulation set up with cups and marbles ...................... 35

List of tables Table 1. Analogue simulation methodology .................................................................... 21 Table 2. Glossary of factors portrayed in the CLD. ......................................................... 29 Table 3. In-person Analogue simulation methodology .................................................... 34 Table 4. Example table ................................................................................................... 36

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Executive summary As environmental challenges become increasingly more complex, nuanced techniques are required to understand and account for various political, social, economic and scientific phenomena. Systems thinking is an approach to understanding complex issues, helping map systems and explore the impact of multiple influences on a particular subject matter. Solid waste is one such environmental complexity that is useful to consider from a System Dynamics perspective. Global movements in the current era have showcased how topical this issue has become, through increased recycling efforts and movements to reduce harmful plastics and landfill degradation that cause environmental damage. Such is the case in Southland, where recent community engagement undertaken by Environment Southland has indicated a high level of concern towards the presence forms of solid waste in freshwater environments. This report builds on the issue of solid waste, employing System Dynamics mapping and the use of causal loop diagrams (CLD) to explore this complex issue in more detail. From a broader perspective, this report presents a CLD map that takes into account various topical issues that ultimately hold influence over the presence of solid waste in freshwater environments. This report:

1. Introduces the concept of systems thinking, explaining in detail the sub-discipline of System Dynamics and the use of CLDs in explaining the causes at play in creating an issue (known as ‘system structure’).

2. Explains the process of building a CLD. 3. Provides a detailed examination of the solid waste CLD established in this pilot

study. This is done by examining the CLD in stages, explaining the relevance of individual nodes and loops within the overall CLD map.

4. Examines how CLDs can then be applied to everyday problem solving. This introduces analogue simulation methodologies that map possible interventions to this CLD in a subjective manner, to explore their possible impacts across various factors in the map. It does this by exploring possible changes over time in these variables.

5. Provides recommendations for carrying forward the use of systems thinking and System Dynamics methodologies within future Council business.

Overall, this report brings to light the value that systems thinking has not only as a stand-alone social research tool, but as a tool that can work in conjunction alongside various reductionist discourses. It explains how complex issues can be better understood by mapping through straightforward causal logic, to challenge linear thinking and propose alternative problem solving and project management methods.

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1 Introduction There is an increasing awareness in society that modern problems are ‘systemic’ or complex in nature, being made up of multiple inter-related causes that can be difficult to intuit or understand, let alone address. As a consequence, the request for ‘systems thinking’ to be applied to complex problems is increasing. Yet this term can be interpreted in many ways and it is unlikely that there is a single ‘correct’ way to approach systems thinking, so what approach can be taken to proceed? This report details Environment Southland’s piloting of one approach to systems to look at the issue of solid waste. This approach was based on the discipline of System Dynamics and resulted in the development of a Causal Loop Diagram (CLD). Under previous directorship, discussions around the use and exposure to complex problem-solving methodologies were beginning at Environment Southland. This was in response to strategic planning; how to advance the state of current and future business programmes through the application of alternative epistemologies. In particular, how to increase the exposure of social research methods across the organisation was integral to this thinking. The exploration of systems thinking as a method to explore complex or multifaceted issues was encouraged through piloting, following presentations to councillors that showcased its potential in environmental settings. To advance this interest in the method, it was put to the Science Strategy and Design team to link with Deliberate to pilot how System Dynamics can be utilised in a context-specific setting. Through the ‘Share your Wai’ engagement survey for the Values and Objectives workstream of the People, Water and Land (PWL) programme, a resounding response to questions around water use and values was made in association to visible pollution (rubbish, refuse, pollution and pollutants). This response was categorised and coded into an ‘issue’, for the purposes of this particular process. Overall, 253 out of the total 1,026 surveys identified rubbish, refuse, pollution, or particular pollutants as a significant problem related to various uses of freshwater environments. This represented approximately 25% of respondents, the most frequent issue raised across the entire survey (Wilson et al., 2019). The relative importance of this particular issue made it appropriate to therefore case study freshwater solid waste through a System Dynamics lens. The PWL programme was one of the high priority work programmes at Environment Southland at this time, as it leads the organisations response to set freshwater limits, as directed by the National Policy Statement for Freshwater Management from the national government. In acknowledging the value this data set holds for future council work, this pilot was able to bring it together with the demands from council to relevant examples of system dynamics in practice. As one of the more recent larger-scale community projects, the data suggests that this issue is therefore topical among the wider community, adding to the value of its investigation. This pilot has therefore been focused on understanding the multitude of influences on the behaviours of people disposing of, or being aware of, solid waste. A brief overview of what systems thinking is, from the perspective of System Dynamics, is provided in Section 2. Then, as a CLD was the main output of this pilot, the fundamentals of how these tools work is described in Section 3. This is an important section to understand before reading the rest of the report. Here, the fundamental concepts of feedback loops are explained, as is the simple but important-to-understand way that relationships are labelled (‘s’ or ‘o’). It also outlines the important and often used goal/gap structure. Section 4 describes the method used to build the CLD in this pilot and who was involved. Section 0 describes the CLD in detail, gradually building it up so that each part if explained and understood. Having developed a CLD is the first step, the next is to apply it to gain insight and help inform decision-making - Section 6 describes one method with which this can be approached. Finally, Section 7 provides a summary of the report and recommendations resulting from the pilot.

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2 What is systems thinking? The world that we live in is a highly interconnected place of causality and effect. The work of policy development often seeks to respond to undesirable behaviour or patterns being experienced in our natural environment and therefore seeks to influence these causes, to alter or improve the desired behaviour. ‘Systems Thinking’ is a name often applied to a range of approaches to thinking about issues holistically. One of these approaches is academic discipline of ‘System Dynamics’. System Dynamics originated from the Sloan School of Management at the Massachusetts Institute of Technology, Cambridge, Massachusetts in the late 1960’s. Systems thinking, as articulated by the discipline of System Dynamics, is a conceptual framework and set of tools that have been developed to help make these patterns of interconnectedness clearer (Senge, 2006)1. These tools help us understand the structure of a set of various interacting factors that create and how they interact to create some kind of behaviour-over-time that we are trying to understand, in order to then adjust in a more desirable direction. In this approach there is also a particular focus on thinking in loops of causality, rather than linear causality. Once these interconnections are articulated, we can better understand which parts of a system are having the most influence on the behaviour, allowing us to identify areas of leverage in order to influence this. When the term systems thinking has been used in this report, it refers to the qualitative concepts articulated by the discipline of System Dynamics (Senge, 2006; Sterman, 2000). The main qualitative tool that this discipline uses to understanding systems is called a causal loop diagram (CLD) (it is sometimes called a ‘system map’. Both terms can be interchangeable but CLD is used throughout this report). This is a conceptual diagram made up of variables (nodes described as words) and relationships between these variables (arrows connecting these nodes). A CLD was the main output from this report, and so the mechanics of how these work are explained in more detail in section 3. Firstly, where CLD sit in the range of tools available in System Dynamics is explained in below.

1.1. CLD on the spectrum of complexity within System Dynamics The tools of System Dynamics themselves exist on a spectrum of complexity. These are shown in Figure 1 which highlights how these varying tools can demonstrate the same system, and to make the point that CLDs are not the ONLY possible output from the use of System Dynamics tools.

1 For a detailed introduction to the concepts of systems thinking, the reader is referred to The Fifth Discipline – the art and practice of the learning organisation by Peter Senge (2006) as an accessible introduction.

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Figure 1. System Dynamics tools exist on a spectrum - Causal Loop Diagrams (or System maps), Stock and flow diagrams, and Simulation modelling.

CLD, as developed here, exist at the conceptual (low complexity) end of this spectrum. These can range from using the simple dynamics of a single feedback loop to demonstrate a type of behaviour, to multiple loop systems – themselves reasonably complex. The next steps up in complexity are Stock and Flow Diagrams (SFD). SFD usually contain multiple stocks of interest (although not all factors need to be stocks) and their architecture tends to represent a greater level of mathematical functionality. This is because SFD tend to be qualitative representations of the actual functions and equations that would be represented in a stock and flow model. Yet these are still only conceptual models. Computer simulation modelling (based on the stock and flow formulation) is the next step in complexity – that is, actually turning stock and flow diagrams into simulation models. There is huge variability in the types of simulation models that can be developed, with some people advocating that large system insights can be gained from using small scale models (Meadows, 2008), to other demonstrating the utility of large scale and highly complex simulation models (Sterman, 2000). The actual application is likely to be determined by the relative need for such complexity, the available time and the cost.

3 The fundamentals of Causal Loop Diagrams – articulating system structure

At the core of a CLD is the desire to visually articulate the relationships between variables that best explain the behaviour of the system that you are trying to understand. This visual articulation of relationship is known as ‘system structure’. This section outlines important fundamental elements of system structure. These are: feedback loops; how they are correctly annotated; the use of the ‘goal/gap’ structure (as this can explain how different loops dominant in a system at different times).

1.2. Feedback loops – the basic building blocks of a CLD. Systems thinking is especially interested in systems where loops of causality are identified – these are called feedback loops. There are two types of feedback loops, reinforcing and balancing (Senge, 2006). The two types of feedback loop are described in Figure 2.

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Figure 2. The two types of feedback loops

In a reinforcing feedback loop, the direction of influence provided by one factor to another will transfer around the loop and influence back on the originating factor in the same direction. This has the effect of reinforcing the direction of the original influence, and any change will build on itself and amplify. Reinforcing loops are what drive growth or decline within a system. In a balancing feedback loop, the direction of influence provided by one factor to another will transfer around the loop through that one factor (or series of factors) and influence back on the originating factor in the opposite direction. This has the effect of balancing out the direction of the original influence. Balancing loops are what create control, restraint or resistance within a system. Feedback loops can be made up of more than two variables and can be mapped together to form a CLD). How these interact provide insight into how a wider system operates.

1.3. Labelling variables An important concept within CLD is the concept of accumulation (or decumulation) –where do things build-up (or decrease) in your system? The simple analogy of a bathtub is often used to describe this. In CLD, this concept of accumulation is captured by describing variables in such a way that their name implies that they can increase or decrease. This means that they should be described as nouns; have a clear sense of direction; and have a normal sense of direction that is positive. Examples to demonstrate this are shown in Figure 3.

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Figure 3. Labelling variables

1.4. Annotating loops Variables within CLD are connected (and made into feedback loops) by arrows, which indicate that one factor has a causal relationship with the next. These arrows are annotated with either an ‘s’ or an ‘o’ which stands for ‘same’ or ‘opposite’. These terms correspond to the direction of change that any change in the first variable will have on the second variable.

Figure 4. How arrows are labelled in CLDs

If a directional change in one variable leads to a directional change in the next variable in the same direction, it is a same relationship. Likewise, if the second variable changes in the opposite direction, it is an opposite relationship. See Figure 4 for a visual description. If there is a notable delay in this influence presenting in the second variable, when compared to the other influences described in the CLD, this is annotated as a double line crossing the arrow. An example of this is shown in Figure 5.

Figure 5. How delays are annotated on arrows

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1.5. Goals and gaps – driving individual loop dominance. Realising that multiple loops are operating within a system is the first useful insight of systems thinking. A further useful insight is understanding that not all loops operate at the same strength all of the time. Different loops can dominate the dynamics of a system at different times. For example, a system might be dominated by a period of growth (a reinforcing loop), but when some kind of physical limit is approached (e.g. the available space in a pond for algae to grow) a balancing loop will start to dominate, therefore slowing the rate of growth. One useful mechanism for gaining insight into the strength of a balancing loop is the ‘goal/gap’ structure. This is a structure that combines both a desired level of something (a ‘goal’), with an actual level of something. This difference between these variables is the ‘gap’ between the desired and actual levels. The higher the desired level and the lower the actual level, the greater the ‘gap’ or difference and the stronger the operation of the loops that this gap influences. The lower the desired level and the higher the actual level, the lower the ‘gap’ or difference, and therefore the weaker the operation of the loops that this gap influences.

Figure 6. Example of a ‘goal/gap’ structure in a CLD – pouring a glass of water

The ‘goal/gap’ mechanism can be seen within the CLD. A conceptual example is shown in Figure 6 which shows the act of filling a glass of water. Initially, while the gap/difference between the desired and actual water level is high, the tap will be opened more and the strength of the water flow is higher. As the desired level of water is approached the gap/difference reduces, so the tap is closed further, weakening the flow of water (you don’t want the water to overflow the glass), until it is fully closed when the water level reaches the desired amount (Senge, 2006).

4 The process of building a CLD Having explained how the mechanics of a CLD work, this section outlines the process that was used to develop the CLD described in this report. As described in Section 2, the use of systems thinking is based around viewing the problem at hand as a behaviour-over-time or trend; then articulating system structure to understand and explain that trend so that interventions can be made to change that trend into the future. The process used here is based on this logic. It is described below in the broad following steps.

1. How has the waste problem been trending to this point in time? The issue of solid waste in the environment was the focus of this pilot as it had been raised as an increasing issue through the ‘Share your Wai’ values survey. This was not a longitudinal survey, nor was there available data on the prevalence of solid

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waste in the environment. Therefore, no clear behaviour over time could be articulated (e.g. was it a sharp rise? Or a gradual one?). However, for the purposes of guiding the CLD development, there was assumed to have been a noticeable (likely gradual) increase of solid waste in the environment.

2. Generate a list of other factors that may be contributing to trend, considering each as their own behaviour-over-time graph. This is an opportunity to brainstorm potentially related factors. The act of articulating these as their own trends encourages people to think about them in a dynamic way and to ‘tell the story’ of how these factors have also changed over time. This allows an opportunity to discuss factors in relation to each other and articulate possible connections, which may be structured into the CLD. Some examples of factors that were generated during this exercise are presented in Figure 7 (the hand-drawn vertical line ¾ of the way along each graph marks the current point in time, beyond here is assumed)

Figure 7. Example factors generated to form part of the CLD

3. Discuss the different ways that these factors are related and build into a CLD

This step is both analytical and creative, where causal relationships between factors, which were discussed in the stories articulated through the graph development, are articulated as relationships in a CLD. The success of this step is to label variables in such a way that they either increase or decrease (as described in section 1.3). This is critical for any causal relationships between variables, represented as arrows, to also be labelled correctly with an ‘s’ or ‘o’ (as described in section 1.4). This is a simple step to articulate, but in practice is likely to be iterated several times in an organic and reflective way. This may be iterated in conjunction with step 2, or new variables may be articulated in this step. There is no firm rule as to how to follow this, but the focus should be on the identification of feedback loops of causality. A demonstration of success is the development of a causal structure that can be accepted as explaining the original trend being discussed.

4. Use the CLD to generate insight about the possible future trends of factors The process of developing the CLD generates insight into the system and the nature of connections within it. Further, the CLD can then be used to generate insight into potential future behaviours of factors within the CLD. This was done here through a process of analogue simulation. Here, based on the CLD and the knowledge generated from its development, potential future trends of factors are discussed and sketched on graphs. A do-nothing or business-as-usual approach is done first, to

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demonstrate some form of probable baseline, then other trends are sketched based on proposed interventions. While these insights are subjective and qualitative, they are a useful way of exploring the complexity within the system without needing to undertake more expensive research or modelling. While this may still be required, this analogue simulation step provides a useful opportunity to build a solid understanding of where any further research or modelling should be focused.

Figure 8. The process of creating and using a CLD

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5 Description of Waste CLD The following is an overview and then a progressive description of the Waste Causal Loop Diagram (CLD), developed as part of a trial of systems thinking with Environment Southland. Different colours have been used throughout the CLD to indicate where loops and influences tend to go together or operate as part of the same loop, or sector. While these provide support to interpret the diagram, note that some arrows may form part of several loops, which may themselves be different colours. Therefore, colours should not exclusively be used as a guide or indication of what factors are associated with loops or sectors.

1.6. Overview of the CLD This sub-section provides an overview of the CLD. It is described in stages in the following sub-section. The CLD is shown below in Figure 9. A total of 15 feedback loops have been identified and directly labelled, although more are likely to be operating to a lesser extent through cascading effects. 12 of these were balancing loops, while only three were reinforcing feedback loops. A significant number of delays were also identified (indicated by the double lines on the arrows). These were all impossible to quantify and of varying lengths, yet they are an indication that there are likely to be significant delays or lags in this system.

Figure 9. Complete waste CLD

1.7. Progressive description of the CLD This sub-section describes the CLD in stages, gradually building up the complete CLD. A glossary of factors can be found in Appendix 1.

Env. Sthlnd: Solid waste in the environment CLD21.05.2020

wastedisposed

appropriately

top

bot

LHS

RHS

totalinfrastructure

Newinfrastructure

demand forinfrastructure

attractivenessof site

siteattractiveness

gap

desiredattractiveness

reputation

visitor #'s

touristwaste

S

O

O

S

S

O

O

S S

SS

quality ofinfrastructure

maintenance

ability tofund

assetburdenS

SO

S

S

SS

S

O

awareness andconcern relating

to rubbish

socialconsciousnessaround rubbish

habits

S

S

waste inenvironment

(visibility)

S

S

fly or farmtipping

likelihood ofcapture/

prosecution

stigma ofbeing apolluter

landfill orrecycling

use

accessibilityof landfill or

recycling

frustrationof paying

personal costof landfill or

recycling

ratesburden

need to covercosts outside

rates

level of comfortwith rates

S

S

S

OO

O O

S

S

S

S

O

S

active use ofrivers &

outdoor areas

educationabout rubbish

disposal

O

O

S

S

S

amount ofplasticwaste

plasticproducts

population

S

S

S

landfillrubbish inwaterways

S

likelihoodof landfillerosion

# historiclandfills

(all sizes)

maintenanceof historiclandfills

streambankand coastal

erosion

S S

SOS

freq. & int. ofweather events

climatechange

S

S

S

positive perception biasof historical waste habits('we were never this bad')

avg. age oflong-termpopulation

S

S

awareness ofpolution effects

on human health

availability ofinformation

likelihood ofreading

information

SS

Swaterquality

regulations forpoint-source

pollution

point-sourcepollution

correct SW& WW

connections

newconnections

emergingorganic

contaminants

O

O

O

O

S

O

S

O

education aboutconnections and

regulationsS

S

S

diffusepollution

O

tourismloop

infrastructureloops

wasteconsciousness

loops

fly andfarm

tippingloops


loops

asset burdenand rates

landfillerosion

climatechange.

prevalenceof plastic

B9

B1

B8 B2

OR1

R2

B3

B5

B4

B10

B12

B6

B7

R3

B11

waste andrecycling loops

S

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1.1.1 Infrastructure demand loops At the core of this waste CLD is the visibility or existence of solid waste in the environment. This has been represented with the factor waste in the environment (visibility). As the CLD is built up, many factors or loops will pass through this factor (and a couple of others near it). This factor is influenced by the factor waste disposed appropriately. This is an opposite relationship, as the more that waste is disposed of appropriately, the less waste there will be in the environment. Waste in the environment (visibility) also has a same relationship with demand for infrastructure. This refers to waste disposal infrastructure such as rubbish bins, waste drop off points, etc. If there was an increase in waste, then there would be an increase in the demand for such infrastructure. Over time, this would likely result in new infrastructure, so this is represented with a same relationship with a delay mark (double lines). This will also be constrained by the ability to fund new infrastructure (this is added later). Any new infrastructure will increase the total infrastructure (same relationship), which in turn will increase the likelihood that waste is disposed appropriately (also a same relationship). This creates a balancing loop where if there is sufficient total infrastructure, then waste is disposed appropriately; however, if it is not this creates more demand for infrastructure, eventually resulting in additional infrastructure to cope. Whether waste is disposed appropriately is also influenced by the quality of the infrastructure available. That is, if is it not maintained or in good condition, then it is less likely to be used.

Figure 10. Infrastructure demand loops

1.1.2 Asset burden loops There is a same relationship between total infrastructure and the amount of maintenance required – that is, the more infrastructure the more maintenance is required (over time – hence the delay). Maintenance also has a same relationship with quality of infrastructure – the more maintenance is carried out, the better quality the assets. This also has an opposite relationship the other way, the better quality the asset, the less maintenance it requires. These two factors operate in a balancing loop with each other. Finally, both quality of infrastructure and the total infrastructure have same relationships with asset burden. The higher quality an asset and the more of it there is, then the greater the ‘book value’ (the accounting value in Council’s accounts) of them, thus the greater the asset burden on council’s accounts.

Figure 11. Asset burden loops

wastedisposed

appropriately

top

bot

LHS

RHS

totalinfrastructure

Newinfrastructure


S S

S


S

O

waste inenvironment

(visibility)

S infrastructureloops

B1

Env Sthlnd: Solid waste in the environment CLD13.03.2020

Infrastructure demand loop


wastedisposed

appropriately

top

bot

LHS

RHS

totalinfrastructure

Newinfrastructure


S S

S


maintenanceasset

burdenS

SO

S

S

S

O

waste inenvironment

(visibility)

S infrastructureloops

B1

B2

Asset burden

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1.1.3 Asset burden and rates The asset burden has a same relationship with the rates burden, as they will both increase due to rates being required to fund new and existing infrastructure for Council. In turn, the rates burden has an opposite relationship with the ability to ability to fund infrastructure – the greater the rates burden, the lower the capacity to raise new rates to fund infrastructure. To demonstrate this, the ability to fund infrastructure has delayed same relationships with both new infrastructure and maintenance. These two connections complete a balancing loop (with two pathways – via maintenance and new infrastructure), with some of the asset burden factors. In effect, the greater the investment in assets and maintenance, the greater the asset and then rates burden, resulting in a diminished ability to fund any further infrastructure. This means that this loop tends be meet some kind of eventual constraint. Another factor that influences the rates burden is the level of comfort with rates, which is a factor that describes an overall level of comfort within Councils’ constituencies, with the level of rates that they collect. This is a same relationship and acts as a social constraint on the rates burden – the higher the comfort level with rates, the greater the eventual rates burden. The rates burden also has a same relationship with the need to cover costs outside rates. This is a factor that describes the need to fund activities via other methods (e.g. user fees). The greater the rates burden, the more likely that costs will need to be covered outside of rates.

Figure 12. Asset burden and rates

1.1.4 Waste consciousness loops The waste consciousness loops described in this section form an important role in many dynamics of this CLD. At the core of this CLD, as described earlier, is the opposite relationship between waste disposed appropriately and waste in the environment (visibility) – the more often it is disposed of appropriately, the less there is visible in the environment. The more waste there is visible in the environment, the less active use of rivers & outdoor areas there will be (an opposite relationship). At the same time, higher levels of waste will eventually (delay) prompt greater education about rubbish disposal activities (a same relationship) by Council, through communication and information programmes. These two factors also influence the level of awareness and concern relating to rubbish, as does the waste in the environment (visibility) directly. Over time (delay), the level of awareness and concern relating to rubbish has a same influence on people’s social consciousness around rubbish habits. That is, being more aware of a problem will eventually have an impact on how people view their own waste disposal habits. The level of social consciousness around rubbish habits that people have will have a same influence on the amount of waste disposed appropriately. These connections create a series of balancing loops that are at the core of this CLD: B3 – the level of rubbish in the environment will directly influence people’s awareness and concerns relating to rubbish, leading to reflection on their personal habits, leading to more

wastedisposed

appropriately

top

bot

LHS

RHS

totalinfrastructure

Newinfrastructure


S S

S


maintenance

ability tofund

assetburdenS

SO

S

S

SS

S

O

waste inenvironment

(visibility)

S

ratesburden


rates


S

S

S

infrastructureloops


B1

B2

B6

O


Asset burden and rates loop

13

appropriate waste disposal; B4 – the same influences but via a pathway of the levels of waste impacting active use of outdoor areas as a catalyst first, and; B5 – the same influences but via a pathway of waste levels influencing the amount of education undertaken by Council about waste disposal. All of these loops are operating at the same time. The extent to which any one is, or all are, operating at the same time will impact how much waste is disposed appropriately. Other factors influence these loops from the side. It is expected that there is a delayed influence from a positive perception bias of historical waste habits. In short, some people are likely to view the average person’s current habits relating to waste as worse than theirs in the past – whether this was actually the case or not. This has anecdotally been experienced within older cohorts of the population, therefore the average age of the long-term population will have a same influence on this factor. Concurrently, the level of awareness of pollution effects on human health that any one person has will also have a same influence (over time – delay) on their social consciousness around rubbish habits. This factors captures the level to which people are more aware of the potential impact of rubbish on human health, whereas in the past rubbish may have been viewed as more benign than it is now. This awareness is influenced (same influences with delays) by the availability of information on that subject and their likelihood of reading information.

Figure 13. Waste consciousness loops

1.1.5 Waste & recycling Two more loops that pass through parts of the infrastructure and rates loops relate to waste disposal (landfill) and recycling. These retain the same series of influences from waste disposed appropriately through to rates burden, then add two new arcs of influence between these two factors. The amount of landfill or recycling use has a same influence on the amount of waste disposed appropriately – if their use increases, so does the amount of waste that is disposed appropriately. However, the two main factors that influence this factor influence it in different directions. The accessibility of landfill or recycling has a same influence on landfill or recycling use; while the personal costs of landfill or recycling use has an opposite influence. In other words, the more accessible facilities or services are the more they are used, but the more they cost the less they are used. Any cost for using such facilities also increases people’s frustration


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of paying (people tend not to like paying for services), and this in turn also has an opposite influence on the use of facilities or services. Links from the rates burden to these cost and accessibility factors complete the loops. The greater the rates burden the lower the accessibility (opposite relationship); while the greater the rates burden the greater the need to cover costs outside rates (same relationship) and the greater the personal cost of landfill or recycling (another same relationship). Both of these loops are reinforcing loops and are likely to be long term cycles. R2 describes how more waste in the environment leads to greater investment in infrastructure, a greater asset and then rates burden, meaning a greater need to cover costs outside of rates, leading to user fees, which discourages waste being disposed appropriately, thus reinforcing the prevalence of waste in the environment. R1 describes a similar path, but where an increased rates burden leads to a longer term reduction in accessibility to facilities and services, reducing their potential use and reinforcing more waste in the environment. This loop is likely to be dependent on the level of comfort with rates accommodating the ability for facilities and services to increase in line with demand, or else this will likely result in more waste in the environment.

Figure 14. Waste & recycling

1.1.6 Fly or farm tipping An extension of the dynamics of the above loops is linked to fly-tipping or farm-tipping. That is, the practice of illegal dumping either on public property (e.g. a roadside), or on your own farm property. This is represented by the factor fly or farm tipping which has a same relationship with waste in environment (visibility) and is itself influenced by an opposite relationship from the amount of landfill or recycling use. In other words, as landfill or recycling use goes down, there is likely to be an increase in fly or farm tipping. This reinforcing loop then continues around the same influences described in R1 and R2, where this results in more waste, which increases demand for infrastructure, then the asset and rates burden, eventually leading to an increased need to charge fees, which further encourages fly or farm tipping. As for R1 and R2, R3 is also likely to be dependent on the level of comfort with rates accommodating the ability for facilities and services to increase in line with demand.

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15

Figure 15. Fly or farm tipping

1.1.7 Tourism loops Tourist use of natural areas, and the subsequent risk that they may leave waste in those areas, is an area within this CLD that can be captured as a sub-set of loops. Fundamentally, there remains a similar central loop relating to waste disposal and infrastructure demand, but it is linked to the attractiveness of a site from a tourist’s perspective. Therefore, waste disposed appropriately has a same influence on attractiveness of site, which is a factor intended to capture the attractiveness of a site as viewed by tourists. Attractiveness of site has an opposite influence on the demand for infrastructure, in that if the attractiveness of a site reduces (due to waste), then there will be greater demand for infrastructure. The use of this factor creates a balancing loop (B8) that is effectively the same infrastructure demand loop as described earlier (B1). The attractiveness of site factor links into a separate tourism balancing loop (B9). Here, another goal/gap structure is in operation: there is a level of desired attractiveness for a site (For example, high or virtually pristine in many high value areas); an actual attractiveness of site; and a site attractiveness gap which captures the difference between these two. The gap (the extent to which the actual attractiveness does or does not meet the desired or expected level) has a delayed opposite influence on reputation (through word-of-mouth from tourists sharing their experiences). That is, if it does not meet expectations, word will spread via tourists sharing their experiences. In turn this has a same influence on visitor numbers, if reputation is low then visitor numbers will drop. Visitor numbers have a same influence on the amount of tourist waste, which has an opposite influence on the site attractiveness – that is if visitors numbers drop then so will the waste produced, which will help improve the site attractiveness (or at least stop it reducing any further). This loop (B9) is able to describe the delayed dynamics of site attractiveness, which is very much driven by the desired level of site attractiveness. It will operate very closely with the previous loop described (B8), which will be how infrastructure is provided to help combat the level of tourist waste. An important link between visitor numbers and the local frustration of paying for waste services was also identified by participants. As visitor numbers increased and waste increased, this was likely to generate frustration amongst locals who perceived they were having to pay for these services and the tourists were not. Therefore, this was also drawn as an influence on the frustration of paying, in addition to the personal cost of waste services.

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16

Figure 16. Tourism loops

1.1.8 Landfill erosion In addition to the dynamics already described that relate to contemporary waste disposal activities, the cumulative historical waste disposal of the region is represented by waste in landfills across the region, both active and closed. There have been cases where these have eroded into waterways, and if streambank erosion is an issue, more may still in the future. These dynamics are represented by the factor likelihood of landfill erosion, which has a same influence on landfill rubbish in waterways, which has a same influence on waste in environment (visibility). In other words, the more likely it is that a landfill will erode, the more likely that landfill rubbish will enter waterways, resulting in waste in the environment. The likelihood landfill erosion is influenced by three factors. The number of historic landfills of all sizes and ownership (there are many small private landfills on existing or former farmland), which has a same relationship; the extent to which maintenance of historic landfills is kept up to date, so that they are not erosion prone, which has an opposite relationship (the better maintained it is the less likely it is to erode), and; the amount of streambank and coastal erosion that occurs, which is a same relationship. The number of historic landfills and the maintenance of historic landfills also both have a same influence on the asset burden, as they are ‘assets’ on the books that require management. The factors represented here do not create loops, but are important exogenous factors to the waste system otherwise described.


Tourism loops

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Figure 17. Landfill erosion

1.1.9 Climate change and landfill erosion This area of potential landfill erosion is one particular place in this CLD where climate change is currently and will likely continue to have an impact. Climate change has a same influence on the frequency and intensity of weather events, which then has same influences on both actual streambank and coastal erosion and the likelihood of landfill erosion. In short, as weather events become more impactful and more frequent, more erosion will occur and it is likely more historic landfill waste will end up in waterways.

Figure 18. Climate change & landfill erosion


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1.1.10 Water quality This CLD has focused on the issue of solid waste, yet there are important links to the area of water quality that should be drawn. Water quality as used here refers to freshwater and estuarine environments. There is considerable existing policy, and ongoing development of future water quality policy in New Zealand. While solid waste is a contributor to water quality issues, it is not as large a contributor as dissolved contaminants, such as nutrients. That said, there are important influences through social perceptions, relating to water quality, which should be drawn into this solid waste CLD. Several feedback loops relating to water quality operate independently to the solid waste loops. Firstly B10, which is a balancing loop, shows that point-source pollution has an opposite influence on water quality, which has an opposite influence on regulations for point-source pollution, eventually resulting in an opposite influence on point-source pollution again. All of these links have delays and effectively describe that greater pollution generates more regulation, which reduces pollution. Secondly B11, which notes that there continues to be emerging organic contaminants in addition to those that are commonly known, which have a same influence on point-source pollution (i.e. the more we realise there are, the more pollution we have). However, this factor is similarly balanced out by the eventual creation of regulations in response to these contaminants and their resultant impact on water quality. Diffuse pollution also has an opposite influence on water quality. It is noted that there are significant policy processes underway at Environment Southland in relation to this type of pollution.

Figure 19. Water quality

Where water quality tends to link with the waste disposal habits of individuals is through their social consciousness around rubbish habits and the influence of this on compliance with correct stormwater and wastewater connections. The number of correct stormwater and wastewater connections has an opposite impact on point-source pollution; the number of new connections also has an impact on the number of correct connections. The number of correct connections itself is then impacted by the level of education about connections and regulations, which is itself influenced by the level of social consciousness around rubbish


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habits. This completes a further balancing loop (B12) where social consciousness around rubbish habits leads to improved awareness and education, more correct connections, reduced pollution and improved water quality.

1.1.11 Prevalence of plastics

This final section describes several factors which account for the prevalence of plastic. Simply put, the level of the population and the number of plastic products available to consumers combine to generate an amount of plastic waste (both same relationships). The amount of plastic waste also has a same relationship to waste in the environment (visibility).

These factors are small in number but are high in impact. While they are exogenous to the waste habits system described here, they have a large influence on it, particularly with the dominance of plastic in the production of consumer products in general.

Their exogeneity does not exclude them from being intervention points to consider, but it should be noted that they are likely to be predominantly outside of the Regional Council’s areas of influence.

Figure 20. Prevalence of plastics

This completes the last partial description of the CLD. For a complete view of the CLD again return to Figure 9, or go to the larger version of the CLD shown in Figure 25 (Appendix 1).


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6 Using the CLD to explore the anticipated dynamics of the system over time

The previous section described the CLD. This section outlines one process of using the CLD to gain insight and develop understanding. This process is referred to here as analogue simulation.

1.8. Different ways of gaining insight from a CLD Section 1.1 described how CLD, like that described in this report, sit at the lower end of the spectrum of complexity for the use of System Dynamics tools. As you move up the spectrum of complexity, small-scale simulation models can be developed and eventually large-scale and complex simulation models. Yet low complexity does not mean that only low levels of insight or stakeholder alignment are achieved. Often the opposite is true – significant insight and stakeholder alignment can be gained from participatory processes that develop CLDs. Insight can be achieved in a variety of ways, each building upon the other. All of these are subjective and are listed below:

1. At the very least, the CLD helps visually demonstrate the interconnected nature of the system that is being mapped.

2. CLD also highlight the circular nature of causality, where it has been identified. This allows insight into how much of a systems behaviour comes from endogenous influence, not exogenous. This can help reframe participant’s perceptions of how much influence is from ‘external’ sources, and how much is from ‘within’.

3. Using the CLD as a tool to guide discussion, the anticipated dynamic behaviour of some elements in the system can be discussed and explored as a group. Earlier, the development of the CLD was anchored in discussing the trends of behaviour in the system up until this point in time (see section 4). At this point, the discussion is anchored around how the system may behave from this point onwards, effectively bringing the discussion back full circle to talking about trends over time again, just this time into the future.

4. This discussion of trends over time can be aided by the use of a technique referred to here as analogue simulation. This is effectively the same subjective discussion about what the dynamics of the system will do in the future, yet it is aided by the use of tangible counters for change (up or down) in specific factors of interest, within set time steps over a period of time. As this is a manual process of determining the changes in each factor, it obviously excludes the rigour of mathematic calculations so it is not intended as a substitute for mathematical modelling. However, it is intended as an additional ‘hands on’ aid to increase insight and learning.

The process outlined in this section describes point 4 outlined above.

1.9. How analogue simulation was used In this pilot, analogue simulation was used as a demonstration of how the CLD could be used by Environment Southland. This process could be used with a group of wide attendance across interests, be that stakeholders, staff or a mixture. The scenarios outlined here were developed solely by the authors as demonstrations of how the tool could be used. This section should be considered an instructional guide as to how the CLD process may be used to help Environment Southland build and understanding of complex systems and gain insight into the behaviour of those systems.

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1.1.12 Analogue simulation methodology The methodology used for analogue simulation is outlined below in Table 1:

Table 1. Analogue simulation methodology Methodology step Description 1 Factors identified: A range of factors from the CLD are identified to explore

changes in. This number should be kept manageable (3-4 is good), too many and it becomes confusing to discuss.

2 Identify interventions to test:

A range of possible interventions are identified to consider and discuss.

3 Time steps agreed: A consistent series of time steps, across which to consider change in the system, are agreed and written on the bottom of a graph.

4 Initial values determined:

A rough initial value for each factor is estimated as a starting point on the Y-axis of the graph. This is intended to be a subjective reflection of what level each factor is at the time of beginning the analogue simulation.

For example: if it is considered that there is currently a high level of something then a higher position on the Y-axis is used; if something is considered to be diminished, or at a low level, a lower position is used.

5 Simulate a baseline: An initial test of the analogue simulation is run under a ‘business as usual’ or ‘do nothing’ approach. This provides an indicative baseline against which other runs that include interventions can be compared.

The group discusses how they expect the level of each main factor to change each time step. The feedback loops articulated in the CLD are used to guide the conversation. The expected trend of each variable is sketched for each time step (e.g. for each 5 year period).

NOTE: It is important that all variables are sketched for each time step, so that their movements are considered in conjunction with each other. Do not sketch one variable across all time steps, then proceed to the next variable. (e.g. all variables are sketched from year 0-5, then they are all sketched from year 5-10, etc.).

6 Simulate interventions: Undertake a separate analogue simulation for each intervention (or combination of interventions) being considered.

Note: If some interventions are in a specific geographical area that have significantly different baseline conditions that the baseline that has already been set, a new baseline for that area would be helpful to run.

7 Compare interventions: The results of the analogue simulations are compared and the group discusses any insights that they gained from the process. This is used to inform their discussions and decisions, including potential further research or modelling.

1.1.13 Analogue simulation scenarios Four analogue simulations were undertaken. For each, a ‘baseline’ example was set where a ‘do nothing’ approach was assumed and only the legacy effects of policy or projects currently

22

in train were taken into consideration. Then some kind of intervention was taken and the anticipated results of this were graphed. The four scenarios all looked at different parts of the CLD, so as to highlight different ways that the CLD could be used. The interventions were hypothetical and intended to demonstrate the potential use of the tool for gaining insight. These scenarios were:

1. Waste education 2. Tourism levy 3. Privatised waste infrastructure 4. Plastic tax

1.10. Analogue simulation results This section outlines the analogue simulation results for the scenarios described above. A couple of features of behaviour over time are regularly observable in simulation results (analogue or computer). These are observable in the results that follow and are outlined here so that the reader can identify them.

1. Firstly, delays can cause slow responses in a system. Depending on the number of factors at play and the delays related to cause and effect, impacts can take some time to present.

2. Secondly, if a trend is to stop or change direction, the rate of change must first drop to zero and the trend must first plateau, even if only briefly. This can be seen in many of the lines in the following scenarios.

3. The combination of the above two points often (or usually) mean that undesirable trends continue in the same direction for some time after an intervention is made, as the impact of that intervention takes time to work through the system.

1.1.14 Scenario 1: Waste education Undertaking education and building awareness about waste management is an existing and regularly exercised function of territorial authorities. The business-as-usual (BAU) case for this scenario assumed a moderate increase in waste education over time, in response to increased waste in the environment. The intervention scenario explored the potential result of a dramatic increase in these efforts.

Figure 21. Scenario 1: Waste education

Key insights identified from this scenario:

Waste education

Awareness of issue(s)

Social consciousness

around waste habits

Waste in the

environment

BAU: Gradually increasing waste education

Possible intervention:Dramatically increasing waste education

2 4 6 8 10YEARS

2 4 6 8 10YEARS

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• The broad trends remain the same. However, the increased investment in waste education within a shorter period of time, reduces the waste in the environment more dramatically over time.

• The delays in the system still mean that immediate investment in education take time to present, first needing to awareness of the issue, then change people’s social consciousness and their practices, which only then impacts waste in the environment. This is seen by all the changes in trends moving relatively earlier in each case.

1.1.15 Scenario 2: Tourism levy A form of tourism levy is charged and used by the regions to deal with waste issues. The BAU scenario assumes that an increasing number of tourists remains the norm, meaning that locals continue to be frustrated at paying for tourist waste services. The increased pressure of tourists still has an impact on site attractiveness, as much through waste as through realising a crowding factor, and the international reputation of New Zealand plateaus and begins to decline in the longer term.

Figure 22. Scenario 2: Tourism levy

Two interventions are explored – A tourism levy being administered by central government at the border and distributed to regions; or a localised tourism levy or user-pays waste infrastructure, administered at a regional level. Key insights identified from this scenario:

• The BAU scenario is likely to lead to an unsustainable level of tourists, which in the longer term will result in increased waste and decreased international reputation.

# tourists

Frustration at paying

Site attractiveness

International reputation

BAU: Focus on increased tourism

Possible intervention: Regional cut of national border tax

Possible intervention: Localised user pays waste system

5 10 15 20 25YEARS

5 10 15 20 25YEARS

5 10 15 20 25YEARS

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• A central government border tax distributed to the regions may have an impact on the rate at which tourist numbers grow, yet they would still be expected to grow. It is definitely expected to decrease the frustration of local residents if they know that tourists are contributing to their waste costs. However, in the longer term, given the continued (but slower) increase in tourists, there is still likely to be a gradual impact on waste in the environment and consequently international reputation. In the longer term, increased tourist numbers may also negate the reduced frustration of locals. Overall this maintain the same trends but delay their impact.

• A locally administered tourist tax may not reduce the overall number of tourists, yet it is likely to reduce the frustration of locals that tourists aren’t contributing to the costs they generate. Conversely though, at an individual level, tourists may not respond well to a local tax, or to user-pays waste infrastructure, resulting in more waste in the environment. Ironically, while this may keep local frustration levels lower for a period of time, the non-use of waste infrastructure is likely to lead to a reduction in New Zealand’s international reputation in the medium term rather than the longer term.

1.1.16 Scenario 3: Privatised waste infrastructure A hypothetical example where waste infrastructure is privatised so that it is not a cost incurred by Councils. The BAU scenario has several rounds of significant investment in waste infrastructure, while a possible intervention is that waste infrastructure could be privatised and provided as some kind of user-pays service.

Figure 23. Scenario 3: Privatised waste infrastructure


• Both scenarios end up with similar overall investments in waste infrastructure, yet whether it is public or private has significant flow-on effects to the other factors.

• The major difference between the two is that asset burden and therefore rates burden of Council remains fairly constant under the private proposal. Yet with BAU both of these will continue to increase.

• The personal cost under the private option increases much more dramatically than the public.

• Both would anticipate reduced waste in the environment, but much less so under the private proposal, as there are likely to be a number of both locals and tourists who would litter instead of pay for a private waste function.

BAU: public waste infrastructure

Possible intervention: private waste infrastructure

Waste infrastructure

Asset burden

Rates burden

Personal cost (direct

cost to user, not in

rates)

Waste in the

environment

5 10 15 20 25YEARS

5 10 15 20 25YEARS

25

1.1.17 Scenario 4: Plastic tax The final scenario proposed here is a hypothetical plastic tax that singularly targets a major single-use plastic product. The BAU scenario is that the amount of plastic in circulation continues to increase. Whereas the possible intervention imposes a tax on a plastic product, in an effort to try and reduce it. For the purpose of this hypothetical exercise, it is assumed that the plastic tax is centrally administered.

Figure 24. Scenario 4: Plastic tax


• BAU assumes an increasing use of plastic, although an increasing awareness of it and therefore use of recycling is also assumed. This eventually leads to reduced waste in the environment, although this is likely to result in frustration at paying amongst locals, in the longer term.

• A tax intervention would be expected to significantly reduce plastic in a short period of time. However, this would also likely be a contributing factor to a frustration at having to pay, as locals realise an increased cost of these plastic products.

• Recycling would be expected to increase under both scenarios, although likely more rapidly under a taxed scenario.

• Waste in the environment is expected to drop much more significantly under a possible tax intervention.

Amount of plastic

in circulation

Frustration at

paying

Recycling use

Waste in

environment

BAU: Ongoing plastic use

Possible intervention:Some form of plastic tax

2 4 6 8 10YEARS

2 4 6 8 10YEARS

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7 Summary and recommendations This report responds to the desire of Environment Southland to further expand the use of systems thinking within their daily business. It has piloted one potential approach to systems thinking, based on System Dynamics, which could be practically applied. While the example of solid waste was the focus in this pilot, the versatility of the systems thinking approach outlined ensures that it can be utilised across a range of subject matters within Council’s business. The below perspectives of people’s experience of the process of building the CLD, are provided by the authors. These are based on anecdotal evidence and speaking to participants who were involved. Participants generally found the experience useful and engaging. They tended to agree that this way of thinking about problems was different to how they usually thought about things, yet at the same time it was accessible and reasonably quick to learn. The general feedback from participants was that it was an enjoyable experience that engaged them. A number of benefits were identified and these are listed below:

• The process is able to shows complexity clearly and also make the assumptions around how things are related explicit and clear.

• The approach helped to widens participants thinking about the complexity of the issue. It helped to draw connections between factors (usually via an indirect path of causal links) that would likely usually remain un-connected.

• The CLD was able to incorporate both tangible and non-tangible factors, as well as both measurable and non-measurable.

• The process and the resulting CLD helped participants identify possible intervention areas.

• When a full CLD map is explained in stages, it can enhance its effectiveness. Systems maps can appear busy when they identify numerous loops within an overall system. A layering approach, whereby a core loop is explained first and subsequently built upon with other loops, helps individuals understand how these elements interact and are dependent upon each other. From a presentation perspective, this can help capture audiences and help them understand the true worth of the mapping. It reinforces where maps can help understand what other influencing factors could be considered within potential projects.

• It allows quick iteration of multiple options to be considered. Particularly in a participatory way. So this was seen as quite an efficient use of effort and resource.

• It was thought to be good as a complimentary tool. Other more detailed tools are still likely to be required for many aspects of Council’s work, yet it was thought that CLD would be highly useful in conjunction with other such tools. Here, CLDs can provide greater understanding of the various influences that project managers may not have initially thought of. This is not to say that it completely alter the project scope, but it can ensure that the initial thinking can remain at a higher level, negating the trappings of becoming too narrow-focused and unaware of the broader influences that may need to be taken into account.

• The resulting CLD and insights generated by it can both INFORM other detailed analyses. It may also be useful to help highlight or remind decision-makers what is NOT in other detailed analyses, when the results of those other analyses are being considered.

27

• Continued support of systems thinking can also challenge the thinking processes of Council staff involved in particular projects. It can open new perspectives on the way a project is viewed. Individuals are challenged to view factors as ‘loops’, acknowledging the revolving causality between presented nodes. This moves individuals away from traditional linear thinking, where an issue is not simply influenced by another once, but continually when a part of a ‘loop’ is moving (increasing or decreasing through action). This helps in acknowledging that complex issues are never static, but constant moving as time moves and projects progress.

A few challenges were also identified:

• If the CLD gets too complex it can be overwhelming. This reinforced the need to keep it simple and focus on aggregated core tensions, not disaggregated detail.

• The application of the CLD can be challenging in the Council environment, given the nature of the work that is being undertaken:

o Getting buy-in was sometimes a bit of a challenge. People are very focused on their ‘day-to-day’ which is usually in only a small detailed section of the CLD.

o Some technical people may be uncomfortable with the subjective and synthesis nature of the tool.

o Some people can get caught in the detail analysis, rather than the synthesis approach that the CLD takes. This may result in tensions of scale and detail.

As a result of this pilot, the authors conclude that this subjective approach to understanding complex problems has merit in the Council environment. Further application of this approach should be considered and supported. To enable this, the following recommendations are made:

• Continue to explore opportunities to apply this approach to the issues being dealt with in Council.

• Seek opportunities to use this approach in the early stages of thinking about policies or issues, etc. It is likely to have merit right through the process of dealing with issues, but it is likely to be particularly useful the earlier it is used to help understand an issue.

• Seek to socialise the approach outlined in this report amongst Council staff and elected representatives, so that there is a consistent understanding of this definition of ‘systems thinking’ across the organisation. Note that this does not mean that this is the only possible approach to systems thinking, but this can help to avoid misunderstandings of definition.

• Continue to support staff to explore the use of systems thinking methods, in order to strengthen their problem solving and analytical abilities in relation to complexity. While the basic foundations are easy to grasp, the application of the approach can be very nuanced, so the availability of ongoing external specialist support is considered beneficial.

28

8 References Meadows, D.H. (edited by Diana Wright) (2008). Thinking in systems – a primer. White River

Junction, VT: Sustainability Institute. Senge, P.M. (2006). The fifth discipline: The art and practice of the learning organisation (2nd

ed.). London, UK: Random House. Sterman, J.D. (2000). Business dynamics: Systems thinking and modelling for a complex

world. New York, NY, USA: McGraw-Hill. Wilson, K., McLachlan, S., and Norton, N. (2019) Community Values for Southland’s

Freshwater Management Units. Environment Southland publication number 2019-08, Invercargill: Environment Southland.

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Appendix 1 Glossary of factor names and complete image of Waste CLD

Table 2. Glossary of factors portrayed in the CLD. Factor name Description Waste in environment (visibility)

Solid waste visible in the environment. Where it is not contained in an allocated rubbish receptacle.

Waste disposed appropriately

The likelihood that, and/or quantity of, waste that is disposed of appropriately in/via the correct receptacles/services.

Demand for infrastructure The demand for waste infrastructure to meet the perceived needs of waste disposal in the community. This covers all sorts of waste but primarily those in public places, not those as part of solid waste collections.

New infrastructure New solid waste infrastructure like that described in demand for infrastructure.

Total infrastructure The total amount of solid waste infrastructure that is owned and maintained by Council(s) (or other organisations on their behalf). This will be a stock of infrastructure that increases as new infrastructure is added. It will only decrease if infrastructure in a certain place is retired or destroyed (assumed to be minimal).

Quality of infrastructure The quality of any piece(s) of waste infrastructure in relation to its ‘as new’ quality. In other words, how well it operates in relation to how well it was intended to operate. Is it fully functioning and operating as it should?

Maintenance The maintenance required to upkeep waste infrastructure owned by Council(s) (or other organisations on their behalf).

Asset burden The level of waste-related assets that Council(s) (or organisations on their behalf) own and are required to maintain. The concept of asset burden can apply to all Council(s) infrastructure, but in this report it is focused on waste infrastructure.

Rates burden The level of rates required to be raised by Council(s) in order to provide and maintain waste-related infrastructure and services. It could be expressed in several ways including total rates burden and/or average rates per person in the region/district.

Level of comfort with rates A node used to denote the level of comfort that constituents have, as a whole, with the level of rates that they are required to pay. This could also be interpreted as ‘willingness to pay’. The higher their level of comfort with rates (their ‘willingness to pay’), the higher the Council(s) can increase their rates burden.

Ability to fund The ability of Council to fun waste-related infrastructure or services from Council(s) rates/funds.

Active use of rivers and outdoor areas

The active use of rivers and outdoor areas by people. This includes both locals and visitors.

Education about rubbish disposal

Assorted education or communication activities that Council(s) (or others) may undertake to make people aware of waste issues and required practices.

30

Factor name Description Awareness and concern relating to rubbish

The level of awareness and concern that waste and rubbish are an issue. This is primarily intended as applying to resident populations but could apply to visitors also.

Note that this is only the awareness and concern relating to this issue. It is not the manifestation of that awareness into changing waste habits. That is denoted by social consciousness around rubbish habits.

This separation is intentional, as a person being aware of something does not necessarily mean that they will do something about it.

Positive perception bias of historical waste habits ('we were never this bad')

This is indicative of individuals who recall their historic relationships with waste disposal to be positive and appropriate, without actual factual basis to support such claims.

Average age of long term population

The average age of the population with concern to the example being considered.

Social consciousness around rubbish habits

The active adaption of rubbish habits to be more socially conscious and to dispose of rubbish in the correct way.

Note that this a manifestation of an increased awareness and concern relating to this issue.

This separation between these two factors is intentional, as a person being aware of something does not necessarily mean that they will do something about it.

Awareness of pollution effects on human health

The level of awareness that pollution has an effect on human health. This is likely to have been increasing over time as knowledge of such things improves.

Availability of information How easily accessible information regarding appropriate rubbish disposal and its environmental impacts are, for community members.

Likelihood of reading information

How likely it is that the information that is available on rubbish disposal and its environmental impacts is consumed/read by community members.

Accessibility of landfill or recycling

In particular, this concerns the availability of new licensed landfill or recycling facilities, for community members to use.

Landfill or recycling use The rate at which, or extent that, licensed infrastructure for waste and recycling disposal is used.

Need to cover costs outside of rates

The amount of investment required to either build or maintain waste disposal facilities, which cannot be funded through rates. This suggests is it likely that councils will not be in a position to suggests rates increases for such projects, owing to particular circumstances.

Personal cost of landfill or recycling

This can be in the form of paying per use at landfill or recycling stations, or through targeted rates with council curb-side waste removal.

Frustration of paying Individual concern and anger in paying for the provision/maintenance/use of waste disposal facilities.

Fly or farm tipping Fly tipping concerns the illegal dumping of waste on public or conservation land.

Farm tipping concerns the disposal of waste on privately-owned land, that is not in accordance with the provisions in the plan.

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Factor name Description Likelihood of capture/prosecution

How likely an individual is to be caught and fined for illegally disposing waste.

Attractiveness of site How an individual actually views or experiences the aesthetic beauty of a particular location. This may change depending on how the individual would want to use the site.

Desired attractiveness The aesthetic beauty of a particular location that an individual would expect to experience. This may change depending on how the individual would want to use the site.

Site attractiveness gap The difference between the desired or expected attractiveness of a site and the actual experienced attractiveness. This will differ depending on the expectations of a particular individual or demographic group.

Reputation How New Zealand (or Southland, depending on the scale you are considering) is perceived and therefore recommended, as a tourist destination.

Visitor numbers The number of tourists visiting New Zealand (or Southland).

Tourist waste Specific waste that can be attributed to tourists who visit New Zealand (or Southland). This is predominantly in the form of solid waste.

Amount of plastic waste The volume of plastic waste that is produced and consumed by the demographic being considered when looking at this diagram.

Plastic products The wide range of plastic products that are consumed in various ways by the global population, of which New Zealand and Southland are a part..

Population The total volume of the combined demographic of a particular place being considered. This is to account for the pressure that population numbers place on any local community.

Landfill rubbish in waterways

Rubbish from landfills (current/active or historic/closed) that directly enter particular waterways that they are beside.

Likelihood of landfill erosion How likely that erosion of current/active or historic/closed landfills may occur.

Number of historic landfills (all sizes)

The collection of landfills that are known to exist but are no longer active (are closed). These were likely to have been in use across previous generations.

Maintenance of historic landfills

The effort and resources required to ensure historic landfills are contained and cause limited environmental impacts.

Streambank and coastal erosion

Forces that are applied to streambank and coastal areas that exceed that natural resisting forces of the bank or vegetation, resulting in the erosion of such streambanks or coastal areas.

Frequency and intensity of weather events

This refers to the frequency/regularity and the intensity/potency of weather events, over a measured period of time.

Climate change The rising average temperature of the Earth’s climatic systems, and the various environmental changes that can we witnessed as a result.

Water quality The condition of water, in respect to its suitability for a particular purpose. In this instance, it relates to the chemical and biological characteristics in waterways.

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Factor name Description Diffuse pollution Pollution that makes its way into waterways through the process

of overland flow or leaching through groundwater. Generally, from landuse activities where there is no associated constructed infrastructure to contain such pollutants.

Point-source pollution Contained and identifiable pollutant discharges to waterways, usually characterised by being constructed infrastructure (e.g. pipes, channels, industrial and municipal discharges etc).

Regulations for point-source pollution

Refers to both local and national regulations that control and restrict forms of singularly contained and identifiable pollutant discharges into waterways.

Emerging organic contaminants

Natural or manufactured chemicals that are not commonly monitored in the environment. There may be a growing awareness and/or concerns of these contaminants. They may require more direct action to address in the future.

Correct stormwater (SW) and wastewater (WW) connections

Those stormwater and wastewater connections that are legally and correctly connected into stormwater and wastewater networks.

New connections The number of stormwater and wastewater connections from new residential and commercial builds within a town or a city.

Education about connections and regulations

Educational material of various types that informs the public on the regulations and standards relating to connecting new properties to stormwater and wastewater infrastructure.

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Appendix 2 Additional information for running analogue simulation interactively

The analogue simulation for this pilot was run online and sketched directly onto graphs, due to the isolation of participants due to COVID-19. This section outlines additional information for running analogue simulation interactively in person. This process would utilise a system of marbles or counters being added or subtracted by participants every time step. This process is effectively the same as that described earlier, only with this slight difference. Here, the process is outlined with some slightly different steps added in (Table 3); and a template table with which to collate answers is provided (Table 4). In the table below, steps that are in addition to the methodology shown earlier, have been italicised and shown with an asterisk (*).

Table 3. In-person Analogue simulation methodology Methodology step Description 1 Factors identified: A range of factors from the CLD are identified to explore changes in.

This number should be kept manageable (3-4 is good), too many and it becomes confusing to discuss.

2 Identify interventions to test:

A range of possible interventions are identified to consider and discuss.

3 *CLD & cups set up: A large printout of the CLD is placed on a table. Clear plastic cups are placed on the map for each of the factors being discussed (and labelled if necessary).

Make sure that you have a large number of counters of some kind to add and take out from the cups. For example: marbles, counters, dry lima beans.

(for an example see Figure 26)

4 Time steps agreed: A consistent series of time steps, across which to consider change in the system, are agreed and written on the bottom of a graph.

5 Initial values determined:

A rough initial value for each factor is estimated as a starting point for marbles/counters in the cups. This is intended to be a subjective reflection of what level each factor is at the time of beginning the analogue simulation.

For example,: if it is considered that there is currently a high level of something then a higher position on the Y-axis is used; if something is considered to be diminished or at a low level, a lower position is used.

The number determined is represented by that number of marbles being deposited in each cup.

6 *Determine scale of change:

The scale of possible change for each time step should be determined.

For example, a scale of 0-3. Where 0 = no change; 1 = a small amount of change; 2 = moderate change; and 3 = significant change.

35

Methodology step Description 7 Simulate a baseline: An initial run of the analogue simulation is run under a ‘business as

usual’ or ‘do nothing’ approach. This provides an indicative baseline against which other runs that include interventions can be compared.

The group discusses how they expect the level of each main factor to change each time step. The feedback loops articulated in the CLD are used to guide the conversation. The expected change in each variable at each time step is captured by adding or removing marbles/counters to the cups for each time step (e.g. for each 5 year period).

NOTE: It is important that all variables are considered for each time step, so that their movements are considered in conjunction with each other.

8 Simulate interventions:

Undertake a separate analogue simulation for each intervention (or combination of interventions) being considered.

Note: If some interventions are in a specific geographical area that have significantly different baseline conditions that the baseline that has already been set, a new baseline for that area would be helpful to run.

9 Compare interventions:

The results of the analogue simulations are compared and the group discusses any insights that they gained from the process. This is used to inform their discussions and decisions, including potential further research or modelling.

Figure 26. Example of analogue simulation set up with cups and marbles

The below table (Table 4) provides a template for how to capture results of an analogue simulation. The factors of interest are labelled across the top (the solid red outline). Time steps are outlined in the left hand column (the dashed red outline).

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Table 4. Example table

Under each factor label is a pair of columns. The left hand column captures the change in each factor at each time step (indicated by ‘T’); at the top of the right hand cumulative total column is a space for the initial value of a factor to be recorded (indicated by ‘I’); the balance of this column is where cumulative totals at each time step are recorded (indicated by ‘C’). These tabulated results can then be graphed to discuss as a group.

Factor

Chan

ge p

er

time

step

Cum

ulat

ive

tota

l

Chan

ge p

er

time

step

Cum

ulat

ive

tota

l

Chan

ge p

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time

step

Cum

ulat

ive

tota

l

Chan

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time

step

Cum

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time

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Cum

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time

step

Cum

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ive

tota

l

Time step Initial value I Initial

value I Initial value I Initial



value I

0-5 years T C T C T C T C T C T C T C T C






Legend: = Factor name I = Initial value of factor

= Time step T = Change to that factor in that time step

C = Cumulative value of factor

Factor 8

Factor 1

0-5 years

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7

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