The system governing human well-being and ecosystem services is complex, involving non-linear feedback, non-equilibrium dynamics, multiple scales, emergent phenomena, tipping points, and system risks. The structure and functions of such complex systems are driven by self-organization and adaptation. Complexity science explains how self-organization forms interaction structures among system agents, while evolution theory describes how adaptation shapes the adaptable characteristics of system agents. Although social and biological adaptations operate through fundamentally different mechanisms—social learning of memes and biological inheritance of genes—their mathematical descriptions share essential features rooted in replicator dynamics. In general, complexity science and evolution provide powerful toolboxes for understanding and managing the challenges posed by complexity in social and biological systems.
Complexity science and the Evolution Unit analyze the dynamics of complex adaptive systems. This requires a spectrum of diverse approaches, with methods selected, combined, and evolved according to the problem at hand. This involves utilizing complexity science, evolution, social economics, ecology, game theory, theoretical physics, applied mathematics, and computer science. Key questions addressed include how to promote pro-social behavior, understand and manage the formation and loss of biodiversity, and sustainably utilize living resources.
- Super Interdisciplinary Sensation (blu3mo)
The specific research areas of the unit are outlined below:
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Governance of social dilemmas and common goods. Social dilemmas pose broad challenges to the functioning of society, arising when goods vital to the welfare of the group are threatened by selfish actors. Overcoming such dilemmas requires promoting cooperative behavior through governance solutions based on a variety of mechanisms, including positive and negative incentives, appropriate rules and regulations, conditional cooperation and participation, as well as competition and mobility between social groups. By combining these mechanisms, we seek to design effective and efficient governance solutions.
- From economics and game theory
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Dynamics of biodiversity and speciation. Despite biodiversity being recognized as a crucial determinant of ecosystem services, its dynamics are only partially understood. Ongoing exploration to understand how species are formed includes increasing focus on parapatric speciation that progresses despite not being geographically isolated, ecologically-driven speciation resulting from biotic interactions, and adaptive speciation that occurs when evolving populations escape the minimum fitness value. We investigate how ecological and evolutionary forces drive the formation and loss of biodiversity.
- Evolutionary?
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Sustainable fishery management and the evolution of fisheries. Aquatic resources, once thought to be almost inexhaustible, are now being overexploited. To promote sustainable fisheries from an ecological perspective, it is necessary to understand complex adaptive systems that include biological resources and their environment, ecosystem services, management interventions and their political decision-making factors, as well as the socio-economic interactions of the forces of fishermen, consumers, and markets. To promote sustainable fisheries from an evolutionary perspective, it is essential to recognize that fisheries not only impact the number of fish but also their functional characteristics. We will analyze fisheries from both perspectives.
- It seems to discuss the combination of natural ecosystems and economics?
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Systemic risk and network dynamics. Systemic risk explains the possibility of cascading failures within a network, occurring in various fields such as disease dynamics, ecosystems, financial networks, supply chains, power grids, and transportation networks. A typical example is the spread of infectious diseases through social contact networks. Even if the healthcare system is suitable for treating individual infections, it can be overwhelmed by uncontrollable chains of infections. In various fields, we study methods to evaluate, model, predict, and mitigate such dynamics.
- Seems like something related to Network Science.
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Evolutionary community ecology and ecological-evolutionary vegetation dynamics. The structure and function of all ecosystems have been shaped by evolution. Evolutionary community models based on functional traits explain how ecological environments determine biological communities, selection pressures, and co-evolutionary dynamics, thus leading to changes in ecological environments. Applying this approach to diverse ecosystems including food webs and especially vegetation dynamics enables predicting how the composition of plant biomes worldwide is guided by regional environmental conditions from first principles.
- First principles? Sounds intriguing.
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Adaptive dynamics theory and models. Adaptive dynamics theory explains the evolutionary and co-evolutionary dynamics of phenotypic traits driven by natural selection in realistic social and ecological environments. Going beyond the classical evolutionary framework that assumes fitness functions, adaptive dynamics theory stands out by deriving them from underlying population dynamics. Since the inception of adaptive dynamics theory, we have developed innovative theories and models on topics such as species packing, functional value evolution, evolutionary branching, environmental feedback dimensions, and evolutionary pattern formation.
- They seem to have their own unique theory.
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Simplification of spatial complexity. Spatial structure is ubiquitous in nature, and ecological and evolutionary dynamics cannot be accurately understood without considering them. Currently, this is often achieved through powerful numerical simulations, but corresponding analytical methods are lagging behind. Overcoming this shortcoming and simplifying spatial complexity opens up a new path by recognizing that the well-mixed population classical models are a special case of a broader theoretical framework that uses spatial densities of individuals as state variables, such as singletons, pairs, triplets, etc. We are studying methods that involve truncating such moment hierarchies at the triplet level to yield powerful approximations.
- Still not quite clear.- The ecology and evolution of diseases. Humans, animals, and plants are constantly threatened by infectious diseases. Pathogens frequently cross species boundaries, continually adapting their functional characteristics and promoting the spread of mutated pathogens. This creates moving targets for efforts in individual and population disease protection, as evidenced by the ongoing Covid-19 pandemic. Therefore, the success of public health interventions heavily relies not only on controlling pathogen spread but also accurately predicting pathogen evolution. Strengthening the young field of evolutionary epidemiology, new methods are being devised to predict changes in pathogen toxicity and the resistance of their hosts.
- [Public Health] seems like something [mu373] would be doing.
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Each of these topics seems very interesting, but the themes are so broad that it feels like “Is this all one lab!?” (blu3mo)