Directors' Blog
Scaling: Relationships across size, space and time
4 September 2024
This is the fourth of a series of posts on complexity. We’ll be exploring some of the ways that studying complex systems gives us a more nuanced way of understanding the world, how this is relevant to all our lives, and the unique contributions we can make to this new way of understanding the world from Aotearoa New Zealand.
The microbiome is the community of trillions of microorganisms living in, and on, the bodies of complex organisms – like people. In human beings this microbial community aids the digestion of food, supports the immune system, and protects us against pathogens – the infectious microbes that cause sickness and disease.
Do you think of yourself as a walking community of trillions of microorganisms? Probably not. Thinking of ourselves as individuals rather than a collection of microorganisms is an example of how we can classify the world into different scales.
Our knowledge systems tend to order everything into different scales to help us organise and understand our universe. These scales are typically used for convenience as well as having some meaning. It is useful to distinguish the individual from a population of people, just as it is helpful to differentiate days from years when we think of time scales.
The different levels at which a system can be observed or analysed
In complex systems, the concept of scale refers to the different levels at which a system can be observed or analysed. These levels can be thought of as micro, meso and macro. In the example of human beings, the microbiome is at the micro scale, the human individual at meso scale, and the natural and built environment that we inhabit at the macro scale.
These scales are groupings of size, but they are also sets of complex relationships which may be nested within each other. For example, interactions occur between the microbiome, the individual, and the environment. The composition of our microbiome is influenced by the food we eat, our habits and behaviours, which in turn are influenced by the natural and built environments we live in, in turn influencing those microbes themselves, which influences our health.
Understanding relationships between the system scales of the microbiome, the health of a person, and external environments is essential for knowing what to do to improve human health and prevent disease.
From the microscopic to the global, from the quantum to the cosmos
The planet that we live on is made up of interacting systems encompassing differing scales. These scales may be about size, place, organisation or time.
Spatial scales range from microscopic levels, like individual organisms or microhabitats, to broader landscapes and global ecosystems. Our universe ranges from the smallest known quantum scales to the entire cosmos.
Time scales encompass moments, seasons, years, and geological epochs, reflecting the dynamic nature of ecological processes over time from nerve impulses to annual seasonal changes in forests to the rise and fall of the large dinosaurs.
Organisational scales range from genes and individuals to populations, communities, and whole ecosystems.
Relationships between scales
Scales of any type do not have rigid boundaries. They are open systems that can be nested, interact with each other, and bonded by relationships that feed back and lead to emergent properties and adaptation.
A disruption at one scale can cause a cascade of interactions. For example, a pathogenic bacterial infection within a gut microbiome that causes disease is in reality a population of reproducing bacteria all interacting with other communities of viruses, bacteria and microorganisms – as well as the host’s own immune cells, and the non-living material inside the digestive system. The gut is an ecosystem within wider ecosystems.
Improving the health of human populations requires recognising relationships between scales. Even a very specific risk to health – like an infectious disease – has causes and impacts that will span multiple scales from the microscopic to the global. Think of the spreading and harm caused by SARS-CoV-2, the viral cause of Covid-19. The resultant pandemic showed that ignoring the ecosystem of relationships around individuals or communities not only reinforces existing patterns of harm, but reproduces harms over time.
Social scales also matter here. At the macro scale, the effectiveness of national health policies depend heavily on how they are implemented at the meso scale of local communities. Local health services that lack sufficient resources or fail to adapt to their local conditions can undermine national policy intentions. We saw this relationship in action through the Covid-19 pandemic where feedback from local Māori, Pacific and other community-led organisations – through advocacy and protest – influenced the national policy approach. This led to a faster reallocation of resources and development of more responsive and locally adapted communication strategies and health service delivery.
To understand our world, we need to look across scales
Understanding scales as systems of complex relationships helps to identify causes of phenomena such as, infectious disease spread, animal behaviour, human health or environmental degradation – but it also provides information about how we can intervene more effectively to create system change through human action that focuses on the relationships that link scales together.
To prepare for, respond to and learn from things like financial crises, natural disasters, systemic challenges to population health, or changes in the research system, we must look across the scales that influence individuals, communities, and all of humanity. This includes the connections between history, the present and the centennial and millennial time spans of collective memory.
To understand our world, we need to look across scales.
A collaboration between Te Pūnaha Matatini Principal Investigators Anna Matheson and Dave Hayman, and illustrator Hanna Breurkes. Edited by Jonathan Burgess.
Read more about the foundations of complex systems
Helping the lungs of an ancestor to breathe freely once again
19 August 2024
The sun is setting at Te Mata Hāpuku. The eelers of Ngāi Tahu have been hard at work digging kōawa, drains that stretch across the cobble flats between Te Roto o Wairewa and the ocean. Beside these drains sit pārua, pits dug into the earth waiting to be filled with the annual harvest of tuna, the eels that are the customary fishery for whānau members.
After sunset, the eelers settle in to wait. As the tide rises saltwater percolates through the beach cobbles reaching the kōawa. The smell of this saltwater sends a signal to the tuna in the lake. For them, it’s time to begin a remarkable journey, the tuna heke.
Te Roto o Wairewa is an ICOLL (Intermittently Closing and Opening Lake and Lagoon) on the southern side of Te Pātaka o Rākaihautū, Banks Peninsula. Each summer tuna depart from here on their heke, a migration across the ocean to the Tongan Trench to breed. But like almost all of the coastal lakes around Aotearoa New Zealand, Wairewa is in bad shape, but has been improving in recent years. It is a very shallow lake, averaging only one to three metres in depth. Forest clearance, wetland drainage, pest and weed incursion and intensification of land usage have all degraded the lake and its catchment.
When the shallow waters of Wairewa are warm, stagnant and overly rich in nutrients like phosphorus and nitrogen from fertiliser runoff or septic tank overflows, cyanobacterial blooms form. These toxic blooms make it unsafe for swimming, and some species can be lethal for local tuna populations – or for anyone who might eat them. A particularly nasty bloom in the early 2000s killed 1,000 eels on the lake.
Te Pūnaha Matatini Principal Investigator Dr Matiu Prebble (Ngāti Irakehu, Ngāi Tahu) is a tangata tiaki, one of the caretakers of the lake who issue permits locally to whānau members of Ngāi Tahu who harvest eels from January to April. “It’s difficult to make a decision on whether to go ahead with eeling when there has been a bloom,” he explains. There are three monitoring stations on the lake which the Cawthron Institute and Environment Canterbury use to sample water quality. Researchers at the Cawthron Institute analyse these samples for algal cell counts of cyanobacterial blooms, and if dangerous levels are reached, a warning is sent out through Te Whatu Ora – Health New Zealand.
“This is quite a delayed approach,” says Matiu. “We don’t get any of the data until a month later showing us what is happening in the lake. So we don’t actually know what this means for the eel fishery on the lake in real time.”
This is where the tools of complex systems can be useful. The appearance of a bloom can be thought of as a tipping point, when the complex system of the lake undergoes an abrupt transition between a clear, healthy state and cloudy, polluted state based on changes in underlying conditions such as phosphorus levels.
Matiu and fellow Te Pūnaha Matatini Principal Investigator Associate Professor Graham Donovan have seed funding from Te Pūnaha Matatini to analyse the wealth of monitoring data from the lake from a temporal and spatiotemporal tipping point perspective and develop a predictive model to inform future monitoring, predictions and potential interventions.
Graham has experience modelling bodily organs, and looking at other tipping points – such as asthma attacks in asthmatic lungs. He is interested in early warning signals that can be identified in data from asthmatic lungs that signal an impending asthma attack.
This work resonated with Matiu, as Ngāi Tahu envisage Wairewa as a bodily organ. When Ngāi Tahu ancestor Makō first laid claim to the area, he was very taken by the richness of mahinga kai or traditional foods that were available there, particularly the eels. He laid claim by saying “Taku pane ki utu, aku waewae ki tai,” or “Inland a pillow for my head and on the shores a rest for my feet.”
“Wairewa is the whakatinanatia or embodiment of Makō,” says Matiu. “For the last century, it’s been a poorly functioning organ of his body. At the moment it could be though of as a poorly functioning bladder, but what we really want the lake to be like is a highly functioning organ like a lung.”
“I saw Graham speak about his work on modelling bodily organs, and this approach really resonated with me given how we think about the lake,” says Matiu. “There’s a lot of potential in utilising his complex systems approaches to bodily organs to come up with new ideas about how we can address some of the problems in these lakes.”
Seed funding has created a unique project that could only have originated within Te Pūnaha Matatini. This funding paid for two summer interns to work on the project: Tavake Tohi (Tonga) in Auckland, and Madeleine Barber-Wilson (Ngāti Kahungunu ki te Wairoa, Ngāti Ruapani mai Waikaremoana) in Christchurch.
Tavake has a background in geographic information systems, and has been analysing satellite imagery and data from a multispectral drone to explore the spatial dimensions of blooms on the lake. He also has a personal connection to the heke of the eels, as they are also harvested in his village in Tonga at the other end of their migration.
Maddie has simultaneously been analysing years of water monitoring data to understand the lake as a temporal system. “Critical transitions between cloudy, polluted states and clear, healthy states in shallow lakes can be modelled mathematically,” says Maddie, “and our goal is to use a model to find mathematical early warning signals of changes in state for Wairewa. Restoring the health of this lake means protecting a source of mātauranga and kai for iwi and hapū of the rohe. I’m excited to be putting my maths skills to work in the real world and am hoping that the results of our project will be helpful for future kaitiaki of the lake.”
Applying modelling approaches usually used for bodily organs to a lake is pushing the boundaries of complex systems theory and its real-world application. “This project is about both extending complex systems theory, and applying this to the lake as a spatiotemporal system,” says Graham. “We have water sampling data from multiple locations at different times, and visual data from satellites and drones. Where we really want to get to is what we call spatiotemporal early warning signals, looking at how the lake changes in both time and space.”
“The lake is very long and narrow,” continues Graham. “It’s not one dimensional, but it has a very significant length from the headwaters down to the flat, and not much width. So if you can incorporate data from all these sources in a stratified structure, can you get more accurate early warning signals than you could by just looking at the temporal data alone?”
This work is of central importance to the Wairewa community, and has broad engagement from Wairewa Rūnanga, the Birdling’s Flat community, the Christchurch City Council, Environment Canterbury and the Department of Conservation. About 20 years ago, Charisma Rangipunga put forward the wero “ka haha te tuna ki te roto, ka haha te reo ki te kāinga, ka haha te tangata ki te whenua.” If the lake is breathing and full of tuna, and the houses full of language, the people will be well. But if there are no eels or language, the people will suffer.
“If we don’t have our tuna there,” concludes Matiu, “then we might as well pack up and leave, basically.”
Illustrated by Sophie Burgess.
Wider than freshwater
16 August 2024
A collaboration between systems thinker Justin Connolly and illustrator Jean Donaldson. Edited by Jonathan Burgess.
When I was young, I wanted to be a detective. I could often be found ‘investigating’ things around the house through my father’s magnifying glass. If I looked at them through that glass, my parents would have seen me squinting – one eye closed and the other magnified to comedic proportions through the lens. As I grew into a teenager, I loved reading detective books or watching detective shows on TV.
But in all good detective stories, the case is nearly always more complicated and nuanced than what it seemed like at the start. Over time I came to realise that a good detective didn’t only look through the magnifying glass, they also put that down, opened their other eye and looked around them to understand the wider context and how that related to what they were investigating.
Now, many decades later, myself and colleagues work to apply such detective skills to freshwater. In Aotearoa, we’ve been experiencing issues with our water in recent decades. Water quality is often lower than desired and can be unsuitable for swimming or other uses, and pressures on how much gets used by humans is increasing. We recently completed work to widen our perspective on the related factors that influence and impact the state of freshwater. We sought to highlight what can be seen through the magnifying glass, and what can be seen when putting this down and looking around at the context.
Zooming out for a better view of the freshwater policy landscape – Manaaki Whenua Landcare Research
The things we see through the magnifying glass are the things that may appear obvious. These include precautions intended to help improve freshwater quality, such as: planting streambanks to buffer and mitigate contaminants flowing to water bodies, ‘green infrastructure’ such as wetlands, controlling the intensity of animals or crops on farmland, and the amount of nutrients applied to land to support them. This also includes things that relate to the amount of water used, such as: the efficiency of water use, and the storage of water for use later.
These ‘magnified’ areas are recognisable from discussions around the state of freshwater. They tend to be close to and obviously related to freshwater. But what do we see if we put down the magnifying glass and look around at the wider context?
We see that greenhouse gas emissions can result from activity closely associated with freshwater, like fertiliser use. For example, a byproduct of nitrogen fertiliser manufacture and use is greenhouse gas emissions – increased levels of which can (in the longer term) impact weather patterns and freshwater availability.
How we design our towns and cities also influences activity that has an impact on freshwater. For example, expanding suburban areas can reduce the amount of farmland. If our focus is on producing more from farmland that we have, this can encourage further intensification of activity on remaining farmland to compensate for production lost to suburban sprawl. Expanding suburban areas are also usually the result of our preference for building low-density housing and relying on cars for transport – all of which also contribute to greenhouse gas emissions.
Procedural things have an impact too. Government funding processes have an in-built bias towards things that are new (capital expenditure) and that depreciate in value. For example, money borrowed by local governments can usually only be used for capital expenditure, so it encourages the building of new assets (which are usually linked with suburban expansion and can impact on freshwater environments). Also, green infrastructure does not depreciate – it actually grows (e.g. a tree grows over time)! Therefore such infrastructure that is freshwater-friendly tends to be difficult to account for ‘on the books’ of local government, meaning it is harder to justify.
Finally, our use of energy is linked to all of these activities, which is also linked to greenhouse gas emissions, which in turn is linked to weather and rainfall patterns. While the efficiency of our energy use is important, so too is the carbon intensity of all forms of energy generation. What is often not appreciated is that even renewable energy has a carbon intensity – due to the fossil fueled-powered machinery used to build them. This still has a greenhouse gas emissions profile.
What does all this detective work highlight?
It shows that the areas where we can intervene to improve freshwater outcomes are far more varied than usually appreciated. Yes, there are some influences on freshwater that are obvious and closely related, and these need our attention (what we see through the magnifying glass). Yet there are also many less obvious areas that equally have an impact on freshwater outcomes – perhaps an even greater impact in the longer term. We need to look around at the context to see these (what the detective sees when they put down the magnifying glass and look around). They may not always appear obvious, but they can have significant impact.
Unlike fictional detective stories, when seeking to improve freshwater outcomes there is not a convenient and tidy ending point – there is no dramatic climax and a single ‘culprit’ revealed! Yet the skills of a good detective – investigating the detail and understanding the influence of the wider context – can lead to impactful insights and action in places that make a significant difference.
Let’s ensure we nurture such skills in our future generations of ‘detectives’ dealing with the complex problems we face now and in the future.
Justin Connolly is a principal investigator with Te Pūnaha Matatini and the director of Deliberate, a consultancy specialising in the use of qualitative research and systems thinking to help understand complexity. You can find out more about Deliberate at https://www.deliberate.co.nz/.
Jean Donaldson is a designer and native bird fanatic based in Te Whanganui-a-Tara. You can see more of her work at https://jeanmanudesign.com/.
Feedback: Processes that change the thing that caused them
15 August 2024
This is the third of a series of posts on complexity. We’ll be exploring some of the ways that studying complex systems gives us a more nuanced way of understanding the world, how this is relevant to all our lives, and the unique contributions we can make to this new way of understanding the world from Aotearoa New Zealand.
We’ve all been there. Someone steps up to a microphone to speak, and there’s a little high-pitched ringing around the edges of their voice through the speakers. In a flash, this has become a loud squeal. Jolted in their seats, the audience clasp their hands to their ears until the person with the best reflexes manages to leap across to turn down the volume.
This is feedback. A microphone placed too close to a speaker picks up the sound from the speaker and amplifies it, then sends it back out of the same speaker. The microphone now picks up the louder sound, and amplifies it further. This reinforcing feedback happens rapidly, and before long we’re being assaulted by a high-pitched squeal.
We can also imagine a thermostat in a room. We set a preferred temperature, and allow the heating to run until this temperature is reached. At that point, the thermostat switches off the heating, and the room slowly cools. This is balancing feedback. Once the room has cooled below the set temperature, the heating is switched back on.
Feedback is all around us
Feedbacks are processes that change the thing that caused them.
Let’s say that we have a system with two parts: A and B. A is connected to B by one process, and B is connected to A by another. If the state of A changes, it triggers a corresponding change of some amount in B, because they are connected. But now, B has been modified, and because it is also connected to A by a second process, the change in B also results in further change to A.
The processes connecting A to B, and B to A, are both feedbacks, and those feedbacks can be reinforcing or balancing. Audio feedback and thermostats are classic examples of these two types of feedback. A reinforcing feedback drives further change in the direction a process was already going. It is a self-sustaining, or amplifying, feedback, which can lead to exponential growth or decline. A balancing feedback, on the other hand, leads to a reversal in the direction of change. So something that was increasing starts to decrease, and vice versa, which can lead to stability or equilibrium.
The concept of feedback is key to understanding complex systems in reality, reaching well beyond the scales of the examples of audio feedback or temperature control. Systems of feedback determine patterns we can see in the world around us. These patterns can be observed over time within any complex system, whether that be from the perspective of the earth sciences, biology, how cities work, or human health.
When we observe these dynamic patterns, whether it is exponential growth (like a virus spreading) or collapse (like the Wall Street crash of 1929) or even if a system is in a state of seeming stability, it is useful to explore the feedback processes behind these patterns. It is through understanding feedback that deep insight into fundamental causes and how to make change can be found.
Reinforcing and balancing feedback on a global scale
In studying the climate we can see reinforcing and balancing feedbacks playing out on a global scale. We know the release of carbon dioxide from burning fossil fuels results in more longwave radiation being trapped in our atmosphere, which leads to warming. This warming melts sea ice and thaws permafrost. Which in turn lead to further warming, which leads to more melting, and so on. This is reinforcing feedback, just like the squeal of a microphone.
Like the way a thermostat works, rainfall is an illustration of balancing feedback. Evaporating moisture from the surface of the Earth leads to increasing water vapour in the air. This increasing humidity then makes it harder for further water to evaporate from the land or ocean. Eventually, as the air becomes saturated, it rains, humidity is reduced, evaporation resumes, and the whole cycle starts again.
Feedbacks between people and environments
There are destructive inevitabilities, such as the increase in extreme weather events, of planetary system feedbacks like warming caused by too much carbon dioxide. But there are also constructive feedbacks where relationships between people, our practices and culture, and the built and natural environments are leading to new and innovative solutions.
One helpful reinforcing loop in the area of energy, where increasing demand for solar and wind power is driving down the cost of these clean energy sources so that they become more affordable for households.
In transport, if we can understand feedback processes underpinning car dependence, we can shift from reliance on cars to more people walking, wheeling and biking. For example, we know that fewer people ride bikes when they associate them with negative experiences of car danger and injury. If traffic on busy streets is slowed and road space is allocated to bike lanes, more and more people become visible, and you will see more people riding different kinds of bikes. When people see others like themselves on bikes having fun while getting around, this is a reinforcing feedback as they feel inspired and encouraged to then give it a go.
The ways we adapt to a changing climate bring new feedback processes into play. When people’s homes and land are threatened by severe weather, flooding, sea level rise and coastal erosion, balancing feedback responses – such as the construction of sea walls – might successfully buffer a worsening crisis in the short-term. But adaptations may not be sufficient in the long term and may in fact cause greater harm through attracting further housing development and therefore increasing the number of people exposed to climate dangers.
Understanding feedback is essential for finding solutions
Identifying and understanding processes of feedback is critical to understanding the complex causes behind the issues that we face. If we understand feedback, we can find more appropriate and sophisticated solutions, and become aware of dangers and unintended consequences. If researchers and policymakers incorporate feedback in their methods and practices, we can create more effective pathways of action that result in beneficial outcomes.
In the next post in this series on the foundations of complex systems, we’ll be taking a look at how we can understand phenomena across different scales in order to intervene more effectively.
A collaboration between Te Pūnaha Matatini Principal Investigators Alex Macmillan and Nick Golledge, and illustrator Hanna Breurkes. Edited by Jonathan Burgess.
Read more about the foundations of complex systems
Intervening in complex food systems to improve food security
29 July 2024
In certain areas of Australia, millions of sterile male fruit flies rain from the skies every two weeks. These Queensland fruit flies are reared to the peak of health in a special facility, then sterilised through irradiation, before being loaded into an aeroplane and dropped from the air. When the sterile males mate with local females, the females are unable to lay viable eggs.
This method effectively suppresses fruit fly populations, which cost Australian growers hundreds of millions of dollars a year in damaged fruit, pest control and lost market access opportunities. But is this too many sterile fruit flies to drop from the skies? TPM Whānau member Dr Tom Moore wants to know.
The Queensland fruit fly is an important pest of concern for Aotearoa New Zealand. Although there have been multiple detections in Aotearoa, the fly has not yet established a foothold. But this comes at a cost. In the most recent incursion, 11 male flies were caught on Auckland’s North Shore – at a cost of $18 million.
Tom is a quantitative ecologist who specialises in integrating scientific hypotheses into statistical models to address causal questions. He is particularly interested in understanding how invasive species establish themselves through data that spans across time and space. Aotearoa relies heavily on its biological resources, so this sort of agricultural research plays a pivotal role in our economic prosperity and shaping a sustainable future.
“Current methods of controlling fruit fly populations are effective,” says Tom, “but without a deeper understanding of the causal processes at work these could become less efficient due to future change, resulting in unnecessary costs.”
Tom has seed funding from Te Pūnaha Matatini to explore new methods of causal inference, which is the process of determining the independent effects of the individual parts that make up larger systems. Causal inference techniques drawing on interdisciplinary methods linking mathematics, computer science and statistics have become popular in other parts of the world, but are not yet widely used in Aotearoa.
Current statistical approaches can be limited in their ability to identify causal relationships. “It’s very common to collect a lot of data without a targeted question, chuck it in all in a model, and see what comes out the other side,” says Tom. “Richard McElreath calls this a ‘causal salad’. So while a certain model might make good predictions, it may be misleading in terms of causation, and unhelpful in planning interventions.”
Causal inference is a technique that considers how variables are related. This approach has been applied in other systems like economics, but is a new and developing technique in ecology. Developing causal models to support agricultural management decisions like the suppression of fruit flies has the potential to significantly improve our understanding of how to effectively intervene in these complex systems to improve food security in an uncertain future.
“By explicitly modelling cause and effect relationships in complex systems based on ecological theory,” Tom explains, “these techniques can evaluate if, and under what conditions, cause and effect relationships can be identified.” This project is an exciting opportunity to both develop complex systems theory, and to apply it to make a real difference to agriculture in Aotearoa.
Tom is working with a team including Te Pūnaha Matatini Principal Investigators Dr Will Godsoe and Dr Giulio Valentino Dalla Riva to develop a non-linear model of population dynamics using three years of weekly fruit fly trapping data.* They are also collaborating with entomologist Dr Lloyd Stringer from Plant and Food Research, and three colleagues from the from the University of Canterbury: statisticians Professor Elena Moltchanova and Dr Phillipp Wacker, and doctoral student in computational and applied mathematical sciences, Pooja Baburaj.
Tom and his team will then use this modelling approach to test out different biocontrol scenarios – exploring whether less frequent deployment of biocontrol measures can achieve the same population suppression. “If the model shows that you can reduce the frequency of biocontrol to monthly and the data looks the same, that’s a great outcome,” says Tom, “and would save a bit of money.”
The team is motivated to explore and showcase how causal inference can be used within the scientific process when defining hypotheses to generate more meaningful insights. Tom is especially excited about sharing this approach with his colleagues at Plant and Food Research and the broader research community, and hosting a workshop with Te Pūnaha Matatini colleagues to increase the capacity of the causal modelling of complex systems in Aotearoa. He hopes that this work will inspire interdisciplinary collaboration between agriculture, ecology and statistics.
Tom says that “we can ultimately use causal inference to predict where invasive species might spread, and how their population dynamics will manifest in a system, so that we can make evidence-based decisions on how to respond.”
“This is a way that we can solve real-world problems with innovative and evidence-based research.”
Illustrated by Chelsea Sullivan.
*This data was collected as part of the post factory pilot of SITplus fly production project (FF17001) that was funded by the Hort Frontiers Fruit Fly Fund, part of the Hort Frontiers strategic partnership initiative developed by Hort Innovation Australia, with co-investment from Macquarie University, New South Wales Department of Primary Industries, Plant and Food Research New Zealand, and contributions from the Australian government.
Emergence: How interactions create complexity from simplicity
26 July 2024
This is the second of a series of posts on complexity. We’ll be exploring some of the ways that studying complex systems gives us a more nuanced way of understanding the world, how this is relevant to all our lives, and the unique contributions we can make to this new way of understanding the world from Aotearoa New Zealand.
The Makarora River sparkles in a distinctive blue as it winds its way from the Southern Alps into Lake Wānaka. When it reaches Boiler Flat, it splits into shallow channels that flow around ever-shifting small islands in its gravel bed. This river is a braided river – an iconic feature of Te Waiponamu, the South Island of Aotearoa New Zealand.
It’s hard to imagine much life thriving among the floods, droughts, instability and tonnes of gravel that characterise braided rivers. But if we zoom out to consider their entire breadth, braided rivers support an immense diversity of life.
Braided rivers are complex systems made up of interweaving channels that change continuously as water flow shifts and deposits sediments. This creates a changing mosaic of habitats from pools, to fast-flowing channels, to islands, that are the result of interactions between flow, sediment, and organisms like plants.
The groups of species found in different parts of a braided river are constantly changing. Depending on environmental conditions and how recently it was ripped apart by a flood, a patch could be empty or comprise any combination of species. Within each of these patches, the species interact with each other in the form of competition for resources or predation.
A complex, tangled web of life holds things together across braided rivers.
What is emergence?
Surprisingly, when all these local patches of a braided river are considered together, the composition and diversity of species in the overall system tends to stabilise through time.
This stability is explained by ‘emergence’ – a key concept in complex systems. Emergence is a process we see everywhere, and occurs when small things interact to create larger things which also interact, behaving in new and unexpected ways.
The stability of whole braided rivers results from the complex interplay between physical and biological processes, feedbacks between different elements and systems, and their ability to self-organise. That is, the stability of the whole river system emerges from its unstable component parts.
Where else can we see emergence?
Complex systems cannot be described by simply adding together their parts. Instead, a higher property is made possible by the interactions or relationships operating within, and between, their parts.
Perhaps the poster child for all this is consciousness. This phenomenon has baffled scientists for centuries. Where does consciousness come from? How does it work? Although consciousness remains unexplained in many ways, scientists know that it emerges from complex interactions among a wide range of parts and processes in the brain.
We now know what the brain comprises, and how neurons – of which there are around 86 billion – work by sending electrical and chemical signals to each other. But consciousness itself remains unexplained, emerging from the interaction of neurons and the collective activity of this network in the brain. Like the whole braided river, consciousness cannot be reduced to any single neuron or neural circuit.
Emergence occurs in the social world as well. Every day, over eight billion people wake up, and go about the mundane tasks that take up most of our human lives. We get dressed, we eat, we imagine, we create, and we do what we can to survive. But our individual behaviour does not necessarily predict how societies function, because of the diverse connections and resulting complex feedbacks among humans.
We can see this in market economies where companies, civil society and governments interact. Prices and trends arise from the interaction of many buyers and sellers and government rules. These interactions can lead to outcomes and outputs not necessarily anticipated from a single exchange.
Although these interactions can have positive outcomes, such as efficient resource allocation, innovation, and overall economic welfare, they can also be undesirable. The 2007-08 Global Financial Crisis provides an example of this. In this case, emergent behaviours within financial markets, driven by complex interactions and systemic risks, led to substantial global economic and financial disruption that was largely unanticipated.
Emergence is one of the key processes that explains how our world works
Emergence is about how complex patterns, structures, and behaviours arise from interactions – giving rise to new system properties not found in the individual components alone.
In the next post in this series on the foundations of complex systems, we’ll be taking a look at how systems self-organise, adapt and evolve over time through a process known as feedback.
A collaboration between Te Pūnaha Matatini Principal Investigators Jonathan Tonkin and Julia Talbot-Jones, and illustrator Hanna Breurkes. Edited by Jonathan Burgess.
Read more about the foundations of complex systems
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Caring for our earthly kin
11 July 2024
A collaboration between environmental geographer Emma Sharp and illustrator Jean Donaldson. Edited by Anna Brown and Jonathan Burgess.
Soil is complex. Beautiful. Wondrous. It gives us food, foundations and filters the air we breathe and water we drink.
In a very literal way, soil is also a part of us. Our bodies are not discrete entities. Our bodies are networks; we are but an assemblage of a host organism with microbial communities living in and around us. Our interdependencies with the soil we eat make for healthy microbial communities of our gut, of ourselves. Our insides are the outsides — the world.
Understanding soil, or land, as ‘kin’ is not a new concept in Indigenous knowing of the world, providing a perspective on the responsibility of treating, nurturing and caring for it as one would a relation. Kaupapa Māori researcher, activist and grower Jessica Hutchings has proposed that in our relationships with land, or soil, reciprocity is vital. This is understood and practised in some communities. It might seem a stretch to others.
Is ‘legal personhood’ a tool or a distraction for Māori relationships with nature? – Mongabay
If we accept that soil is part of us, then we must admit that we are at war with ourselves. We see this in political decisions to develop prime agricultural soils through ‘financialising’ land. We see it in national investment into intensive agrichemical use, and its endorsement through lax regulations. And we find it in individual behaviours of everyday (over)consumption of plastics, of wasted food, of the marketing of unnecessary convenience-chemistry that means that our soils bear the legacy of contamination.
The soil in our landfills, and what leaches out of them, tells us a lot about what our society really cares (or doesn’t care) about.
A drive for profit-focussed empire-building and an obsession with technological futurism has led us from sustainable ways of living with our environment to modern-day purposeful destruction of nature. This shows up in soil as erosion, depletion, dust bowls, contamination, or suffocation.
Aotearoa New Zealand, while branding ourselves as natural, has constructed an identity around producing off the land that is dependent on pesticides. New Zealand does not keep track of chemical use and release. We don’t have decent monitoring in place to understand the extent of the problem.
Humanity has exceeded planetary boundaries, threatening the safe operating space for humans, and for non-human others. We have entered a period of triple planetary crisis: of biodiversity loss, pollution and climate change, all of which have a bearing on the state of our soils.
Outside the safe operating space of the planetary boundary for novel entities – Environmental Science & Technology
Humans have caused this, so humans can change this.
It requires bold, brave leadership to do what is ethical, care-full and in the interests of our common planetary future: to call for environmental disarmament, to dismantle infrastructures of violence against nature.
We might (re)value soil in ways that mobilise what we think about as our ethical responsibilities to and in the world. These ethics recognise the complexities of the communities in and of soil: human and microbe, food-waste collector and māra kai kaimahi, invertebrate and farmer. These complexities can never be reduced down to a calculus of yield and profit.
So, let’s notice our soils. This might be in exploring the beauty of fungi, in growing food, or on a walk in the ngāhere to breathe the sweetened air and mood boosting, ‘friendly’ bacteria.
Identification of an immune-responsive mesolimbocortical serotonergic system: Potential role in regulation of emotional behavior – Neuroscience
Slowing down to attune ourselves to the natural rhythms and temporalities of soil is effective, and it is affective: it changes us, and it changes our capacity to be in the world. It changes our imaginations of what a cared-for soil world might look like. Let’s then live with a soil ethic that asks not what if we nurtured our soils, but rather as if we did, by performing a politics of soil care, and enacting – making – a different world.
Emma Sharp is a principal investigator with Te Pūnaha Matatini who works on soil and food politics, care and community economies at Waipapa Taumata Rau the University of Auckland.
Jean Donaldson is a designer and native bird fanatic based in Te Whanganui-a-Tara. You can see more of her work at https://jeanmanudesign.com/.
Yes, you should mention the myth when you correct it
14 June 2024
A collaboration between doctoral researcher Laura Kranz and Illustrator Jean Donaldson. Edited by Jonathan Burgess.
You’ve probably had to study for a test or exam at some point in your life. When faced with a lot of material, how do you go about learning it? Perhaps you listen to it through your headphones while commuting because you’re an auditory learner.
But are you?
The idea that everybody has a specific learning style (visual, auditory, or kinaesthetic) is remarkably persistent. It seems to make sense that people learn best when they study information in their given learning style. However, there’s no evidence to support learning styles. Hundreds of studies in cognitive science show that people learn best when we receive new information in multiple ways, but that people don’t learn any better in their preferred style.
If you believe that learning styles are a thing, you’re not alone. Learning styles is a pervasive myth – in my research, more than 95% of people believe it to be true. We are taught it in schools, and unless you’ve specifically researched it yourself, or have been told it’s a myth, you have no reason not to believe it to be true.
People believe many false ideas. Most are pretty benign – it makes minimal difference to society if I believe that we swallow eight spiders a year in our sleep or that chewing gum stays in your stomach for seven years if you swallow it. But some false beliefs can have harmful impacts, like reduced vaccination rates or increased greenhouse gases. We all benefit from correcting myths that cause harm.
Attempting to replace belief in myths with correct information can be frustrating, but there are strategies that can help. One recommendation from research – including my own – is to mention a myth when debunking it. By mentioning a myth you are encouraging people to mentally link the pre-existing false belief with the correct information.
When people believe a false idea, they have a representation of this in their brain. When they are told new information that counters a pre-existing belief, the new information doesn’t simply erase and replace the old belief. Instead the new information forms its own, independent, representation in the brain.
Even if people believe the new information, the old false information is still around and can continue to influence thinking and behaviour. If somebody has a mental link between a false belief and a correction then when they bring to mind the false belief they are more likely to bring to mind the correction too. This reduces the likelihood that they use the false information to guide thinking and behaviour.
In my research I look at how to effectively correct scientific misinformation – both controversial myths (such as myths about vaccines) and non-controversial myths (such as myths about learning styles). We used to think that mentioning a myth when debunking it could be harmful. We know that people use familiarity as a proxy for truth – that is, the more familiar an idea feels to a person, the more likely they are to believe it to be true.
By mentioning a myth when debunking it we thought we might inadvertently strengthen belief in the myth by boosting its familiarity. However, it turns out that the relative benefit of mentally linking the myth and correction overrides any potential familiarity effect. This looks to be the case for both controversial and non-controversial myths.
Even when people don’t shift their beliefs to be in line with new information, people don’t tend to show increased belief in a myth when it is mentioned in debunking efforts. This is great news for science communicators: you don’t need to avoid mentioning a myth when debunking it.
Laura Kranz is a TPM Whānau member who has been exploring the role of cognition and emotion in science communication for her doctoral research.
Jean Donaldson is a designer and native bird fanatic based in Te Whanganui-a-Tara. You can see more of her work at https://jeanmanudesign.com/.
Complex is different from complicated, and why that matters
5 June 2024
This is the first of a series of posts on complexity. We’ll be exploring some of the ways that studying complex systems gives us a more nuanced way of understanding the world, how this is relevant to all our lives, and the unique contributions we can make to this new way of understanding the world from Aotearoa New Zealand.
An aeroplane is pretty complicated. The large commercial planes that criss-cross our skies are made up of millions of parts, each one carefully designed and engineered. There are hundreds of years of scientific enquiry behind these machines that lift us off the ground and transport us at tremendous speeds around the world.
Each part of an aeroplane has a particular purpose, and contributes to achieving flight. You can reduce an aeroplane to the parts that make it up, and you can reduce flight to four basic principles: lift, weight, drag and thrust.
Aeroplanes are a great example of understanding the world by breaking it down into parts, and then understanding the whole system as the sum of these parts. Over the last few centuries, scientists have gotten pretty good at this approach.
But if you took an aeroplane apart, it would just be a big pile of parts again. Without a team of humans who understand how to rebuild it, this pile of parts would continue being a big pile of parts, rather than an aeroplane.
An aeroplane is very complicated, but it’s not complex. In the 21st century, as human societies are growing, becoming more interconnected, and having an increasing influence on planetary systems, it’s complexity that we need to understand.
On planet Earth, we’re surrounded by big piles of water. These big piles of water are made up of water molecules. As these molecules are heated, they rise up into the sky, and form clouds as they cool. They travel around the world, and become mist, fog, rain, snow and hail. They coat mountaintops, and they feed plants. They carve out landscapes, and they flow down rivers and back into the sea.
Where aeroplane parts create aeroplanes, water molecules are one of the components that create weather, and our climate. Weather is different from an aeroplane because it doesn’t need anything external – like a group of aeroplane engineers – to create it. This is why weather is a complex system, and an aeroplane isn’t. And where aeroplanes are reasonably consistent, the weather is never the same. Those piles of water molecules interact with each other and other elements of the weather system to produce infinitely different weather patterns.
Complex systems are all around you. And you as a human have arisen through the behaviour of complex systems. Biological cells organise themselves into animals and plants, and can create wondrous structures like the human brain.
When biological cells have self-organised into humans, those humans create societies, and those societies interact with the systems around them to influence things like the climate system, which in turn influences those societies. Everyone and everything exists within this interwoven system of systems with complex relationships that feed back and influence each other. These interwoven systems challenge our common understanding of cause and effect.
When Cyclone Gabrielle ravaged the local environment in Aotearoa New Zealand in 2023, the complexity of the situation became strikingly evident. Many factors determined the extent of the damage and the effectiveness of recovery efforts, from the interactions of atmospheric conditions to the vulnerabilities of built environments and the different ways that communities reacted.
Where wind patterns, topography, infrastructure resilience, and human actions and decision-making interact, they give rise to outcomes that cannot be predicted by analysing each component in isolation. We call this emergence, an important process resulting from the relationships within complex systems.
A better understanding of complex systems can help us to see the whole context of situations like extreme weather events, including their emergent properties. This will help us to better predict, understand and act when disasters strike.
To understand complex systems, breaking them down into their individual bits doesn’t cut it, as it is the relationships between the parts that have the most influence.
The challenges that we face in the twenty-first century are complex. The interrelated problems of economic crises, social inequality, food insecurity, migration, urban and rural living conditions, and globalisation have shown us the limitations of understanding the world as only complicated.
Although we have become very good at understanding and building the complicated, we have more work to do on understanding and acting on the complex. How does anything, like disease, information, and cultural practices, spread through systems?
Over the last century or so, the study of complex systems has given us a detailed way of understanding our world. We have learned a lot about how complex systems behave which can assist prediction and change. We have learned that how they evolve is quite similar across many different areas, and that understanding one system can give surprising insights into another. As we have learned more about complex systems behaviour, we have also learned more about how this behaviour is tied together through theories of complexity that enable structures and processes to be defined, detected and studied.
As humans grow as an influential force on Earth and beyond, we need to better understand our relationships with each other and with the systems that we encounter. The developing field of complex systems is giving us the concepts, language, and tools to do this. In this blog series, we will explore some of the foundations of complex systems and how they can help us to understand our world.
In the next post in this series on the foundations of complex systems, we’ll be taking a look at emergence – when small things interact to create larger things which also interact, behaving in new and unexpected ways.
A collaboration between Te Pūnaha Matatini Principal Investigators Anna Matheson and Markus Luczak-Roesch, and illustrator Hanna Breurkes. Edited by Jonathan Burgess.