 Self-organization is one of the most fascinating and pervasive phenomena in our world. From sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies to the coordinated movement of a school of fish. What these diverse systems hold in common is their emergent global patterns being derived solely from the local interactions among relatively simple components. Researchers are finding in such patterns a new approach to understanding ecosystems through the process of self-organization. Understanding biological systems challenges us because they consume energy and are therefore far from equilibrium. Thus classical thermodynamics, which has been so successful in developing an atomic understanding of physical and chemical properties such as temperature and pressure does not apply to these systems. Instead of self-assembling into lower energy states such as the crystal, these energy dissipating components self-organize into highly dynamic structures through which there is a constant flux of energy and materials. Self-organization is a process in which patterns at the global level of a system emerge solely from numerous interactions among the lower level components of the system. The rules specifying interactions among the system's components are executed using only local information without reference to the global pattern. What is also intriguing about this pattern formation in biological systems and lends excitement to the study of self-organization in animal groups is the recent realization that interactions among systems components can be surprisingly simple even when extremely sophisticated patterns are built such as the complex nests of termites, the coordinated movement of birds in a flock or even human consciousness. Out of a network of non-linear interactions between simple components self-organization can give rise to complex phenomena on the macro level which then in turn feeds back to both enable and constrain the components on the local level. The theory of self-organization helps us to approach one of the big questions within biology and ecology that of organization and order. How and why do we get this extraordinary level of organization we see within ecosystems? As we've previously discussed the second law of thermodynamics tells us that the disorder or entropy of a physical or chemical system and its surroundings must increase over time. In other words systems left to themselves must become increasingly random. The ordered energy of a system must degrade eventually to this randomness. But there are many instances in which physical systems spontaneously create emergent patterns of order. For example despite the destruction that they cause hurricanes have a very orderly vortex motion when compared to the random motion of the air molecules in a closed environment. Even more spectacular is the order created by chemical systems the most dramatic being the order associated with life of all kind. But of course the second law only really tells us about closed systems. What we're dealing with in ecology though are in fact open systems. If the system has a high enough exchange with its environment order can be created in the system by an even greater decrease in order of the system's surroundings. In the hurricane example hurricanes are formed from unequal heating within the atmosphere. The Earth's atmosphere is then far from thermal equilibrium. The order of the Earth's atmosphere increases but at the expense of the order of the Sun. The Sun is becoming more disorderly as it ages and throws off light and material to the rest of the universe. The total disorder of the Sun and Earth increases despite the fact that orderly hurricanes are generated on Earth. These examples help to illustrate the nature of dissipative systems. Such as the Bernard cells created by boiling water can exhibit dynamic self-organization. Such structures are necessarily open systems. Energy and all matter are flowing through them. The system is continuously generating entropy but this entropy is actively dissipated or exported out of the system. Thus it manages to increase its own organization at the expense of the order in the environment. The system circumvents the second law of thermodynamics simply by getting rid of excess entropy. Plants and animals take in energy and matter in a low energy form as light or food. They export it back in a high entropy form as waste product. This allows them to reduce their internal entropy. Thus counteracting the degradation implied by the second law. It is this dissipative catabolic process within ecosystems that constantly produces disorder in the form of exported low grade heat that paradoxically makes possible the maintenance of order in the system through self-organization. It is this feature to dissipative systems like ecologies that creates the conditions for self-organization. Where we can think of a dissipative system as a context where energy is imported and entropy is exported. Given that context elements within the system will then self-organize to process whatever resource is flowing through the system. This is part of the essence of biological creatures. Not only are biological systems dissipative but also they perform some internal function. All biological creatures process energy and matter in some form and elements internal to the system have to self-organize to do that. That is to say biological creatures somehow have evolved orderly internal structures that enable their functionality and this internal functionality to biological entities has no equivalent within inert physical systems. This can be understood with reference to the maximum power principle and construct law previously talked about. Where during self-organization the system designs develop and prevail that maximize power intake energy transformation and those uses that reinforce production and efficiency. Or according to the construct law for a flow system to persist in time it must evolve freely such that it provides greater access to its currents. Thus where the second law commands that things should flow from higher to lower energy potential. The construct law posits that they evolve in configurations that flow more and more easily over time and elements in the system will self-organize to achieve this in so doing producing some macro level pattern of organization. We can ask then why do all the different parts of an ecosystem appear to fit together so well. What is responsible for organizing all the parts, their functional connections and resulting feedback loops in a way that allows everything to function together. The amazing answer is that ecosystems organize themselves because the ecosystem is a dissipative system inside of which is available free energy. This exergy can be used to create some form of order and functionality through the process of self-organization. We've been talking about self-organization on a generalized level but we'll use the rest of this video to discuss in more detail its basic workings. Today this process of self-organization is understood to take place through a number of key stages. The dynamics of a self-organizing system is typically non-linear because of circular or feedback relations between the components. This involves some form of initial randomness or fluctuation. Positive feedback loops that can then amplify these small events. When this positive feedback reaches its limits it dies out creating negative feedback with closed detractors forming and finally out of all of this we get the emergence of some global pattern. Similar systems have in general several stable states and this number tends to increase or bifurcate as an increasing input of energy pushes the system further from its thermodynamic equilibrium. The basic dynamics underlining self-organization is one of variation which explores different regions in the system's state space until it enters an attractor. This precludes further variation outside the attractor and thus restricts the freedom of the system's components. This is equivalent to the increase of order or decrease of statistical entropy that defines self-organization. We'll go over each of these stages in the process separately in more detail. Many theories surrounding self-organization involve an initial state of randomness within which fluctuations or noise can take hold. For example, Prigashin proposes the principle of order from fluctuations. This may be understood with reference to a simple observation that if the components in the system are already held within some global form of organization this will likely resist alteration. When an ecosystem, organism or some other system is held in an orderly strong base of attraction it is difficult for small events to take hold through self-organization. We need some initial state of entropy and randomness for this process to take hold. Some small fluctuation can only really gain traction given positive feedback. Positive feedback can take hold around some small event and by compounding on its presence with every iteration work to amplify it into a large systemic effect. One example of this will be the process whereby bees form swarm attacks against enemies. When a potential enemy is identified a bee may attack but the bee also releases a pheromone communicating to others to do likewise. Thus for every new bee that attacks we get a stronger accumulation of pheromones placing an ever greater attraction on other bees to join. This is an example of a positive feedback process synchronizing the states of the bees as they come to form a swarm around the enemy. Similarly, positive feedback through pheromone excretion is present in the formation of patterns within ant colonies. Another example would be any form of autocatalytic chemical process. A single chemical reaction is said to have undergone autocatalysis if one of the reaction products is also a reactant and therefore a catalyst in the same or coupled reaction. The more reactions we get the more catalysts we'll have which will then generate more reactions and so on. These are examples of runaway positive feedback that works to cascade through the system aligning all the elements into some coordinated regime. As self-organization is an inherently nonlinear process the transition to order as the distance from equilibrium increases is not usually continuous. Order typically appears abruptly as characteristic of nonlinear systems. The threshold between the disorder of chemical equilibrium and order is known as a phase transition. The conditions for phase transitions can be determined with the mathematics of non-equilibrium thermodynamics. Once the process of positive feedback has run its course and met some boundary or formed a number of different local attractors, their negative feedback starts to take hold once again creating a stable state. The British cybernetician W. Ross Ashby proposed what he called the principle of self-organization noting that a dynamical system independently of its type of components always tends to evolve towards a state of equilibrium or what we'd now call an attractor. This reduces the uncertainty that we have about the system state and therefore reduces the system's statistical entropy. This is equivalent to self-organization. The resulting equilibrium can be interpreted as a state where the different parts of the system are mutually adapted and balanced as they form local attractors closing in on themselves creating what we call closure. For the outside observer closure determines a clear distinction between inside and outside and therefore a boundary separating system from environment. This boundary can encompass all components of the original system. If the system settles into a negative feedback regime it will be relatively impervious to external perturbations. The system has now become responsible for its own maintenance and thus become largely independent from its environment. It is thus also closed against influences from the outside. Although in general there will still be exchanges of matter and energy between the system and environment, the organization is determined largely by its initial dynamics. Thus we may say that the system is at this stage thermodynamically open but organizationally closed. More generally a self-organizing system may settle into a number of relatively autonomous organizationally closed subsystems but these subsystems will continue to interact. These interactions too will tend to settle into self-sufficient closed configurations defining subsystems at a higher hierarchical level which contain the organizational subsystems as components. These higher level systems themselves may interact until they hit on a closed pattern of interactions thus defining a system of yet higher order. This goes some way to explaining why complex systems tend to have the hierarchical architecture we previously discussed, where at each level we can distinguish a number of relatively autonomous closed organizations. For example a cell is an organizationally closed system encompassing a complex metabolic network of interacting chemical cycles within a membrane that protects it from external disturbances. However cells are themselves organized into networks and tissues that together form multicellular organisms. These organisms themselves are connected by a multitude of food webs collectively forming the ecosystem. In this video we've been covering the topic of self-organization within biological systems. We talked about how the theory of self-organization helps us to approach one of the big questions in biology and ecology that of organization or order. In particular how biological systems can evolve to exhibit greater structure and complexity over time by harnessing a dissipative process to enable the self-organization of their constituent elements into a functioning organism. We then discussed the basic workings to this process of self-organization as one that requires some initial state of entropy or randomness where small fluctuations can gain hold and become amplified through positive feedback into new patterns as they come to form stable basins of attraction that close in on themselves producing an emergent global pattern.