Autopoiesis: the organization of living systems, its characterization and a model

Aggregate Boid behaviour to aid in artificial autopoietic organization

Analyzing carbon-based life on earth can lead to biased inferences on the nature of life as might exist in elsewhere in the universe in alternative forms, therefore, scientists have looked into either abstracting life into constituent systems it is comprised of, or logics of life, or lists of essential criteria, or essential dynamic patterning that characterizes the living. A system-level characterization that is and referred to as a general pattern of minimal life is autopoiesis (Varela et al., 1974) including production, maintenance and replacement of required constituents for setting up and maintaining an internal environment with self/other separation that regulates and is constitutive of processes that produce the environment and components for processes that comprise this ongoing activity of self-production in 'recursively', i.e., in a manner that allows the organizational pattern to continually reconstitute the conditions, components and processes required for its own perpetuation. This seminal concept of an autopoiesis is instantiated in life as we know it, but might also be instantiated in different media and in unforeseen ways. Other researchers have argued life is more than autopoiesis and that it is a co-emergent property of autopoiesis and cognition. Life produces many emergent properties such as synchronization and patterns as seen in flocks and herds of different animal species. The mechanics of this synchrony displayed in flocks and herd animals has been extracted by Craig Reynolds into a generative model referred to as "Boids". With these concepts in mind, we address the following research question: How can the synchronous maneuvers and aggregate behaviour of Boids contribute to constitutive subsystems in realizing an autopoietic system? Can such a system exhibit minimal cognition? This work attempts to answer these questions with a bottom-up approach to constructing an artificial life system. We exhibit a computational model of autopoiesis and a minimal level of cognition in the sense of M. Bitbol and P. Luigi Luisi, whereby an autopoietic entity engages in active assimilation of external components as part of its activity of self-production.

The human side of biodiversity: coevolution of the human niche, palaeo-synanthropy and ecosystem complexity in the deep human past

Today's biodiversity crisis fundamentally threatens the habitability of the planet, thus ranking among the primary human challenges of our time. Much emphasis is currently placed on the loss of biodiversity in the Anthropocene, yet these debates often portray biodiversity as a purely natural phenomenon without much consideration of its human dimensions and frequently lack long-term vistas. This paper offers a deep-time perspective on the key role of the evolving human niche in ecosystem functioning and biodiversity dynamics. We summarize research on past hunter-gatherer ecosystem contributions and argue that human-environment feedback systems with important biodiversity consequences are probably a recurrent feature of the Late Pleistocene, perhaps with even deeper roots. We update current understandings of the human niche in this light and suggest that the formation of palaeo-synanthropic niches in other animals proffers a powerful model system to investigate recursive interactions of foragers and ecosystems. Archaeology holds important knowledge here and shows that ecosystem contributions vary greatly in relation to different human lifeways, some of which are lost today. We therefore recommend paying more attention to the intricate relationship between biodiversity and cultural diversity, contending that promotion of the former depends on fostering the latter. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Form, function, mind: What doesn't compute (and what might)

The applicability of computational and dynamical systems models to organisms is scrutinized, using examples from developmental biology and cognition. Developmental morphogenesis is dependent on the inherent material properties of developing animal (metazoan) tissues, a non-computational modality, but cell differentiation, which utilizes chromatin-based revisable memory banks and program-like function-calling, via the developmental gene co-expression system unique to the metazoans, has a quasi-computational basis. Multi-attractor dynamical models are argued to be misapplied to global properties of development, and it is suggested that along with computationalism, classic forms of dynamicism are similarly unsuitable to accounting for cognitive phenomena. Proposals are made for treating brains and other nervous tissues as novel forms of excitable matter with inherent properties which enable the intensification of cell-based basal cognition capabilities present throughout the tree of life. Finally, some connections are drawn between the viewpoint described here and active inference models of cognition, such as the Free Energy Principle.

Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging

Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here, I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors, and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode Caenorhabditis elegans. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

Dynamic Ecosystem Adaptation through Allostasis (DEA-A) Model: Conceptual Presentation of an Integrative Theoretical Framework for Global Health Change

Achieving ambitious goals in Global Health first requires an integrative understanding of how individuals and organizations adapt in a living ecosystem. The absence of a unified framework limits the consideration of the issues in their complexity, which further complicates the planning of Global Health programs aimed at articulating population-based prevention and individual-level (clinical) interventions. The aim of the conceptual contribution is to propose such a model. It introduces the Dynamic Ecosystem of Adaptation through Allostasis (DEA-A) theoretical framework, emphasizing the functional adaptation of individuals and organizations in symbiosis with their living ecosystem. The DEA-A framework articulates two central components to grasp the complexity of adaptation: the internal dynamics (intrasystem level) and the environmental dynamics (ecosystem level). It bridges diverse conceptual approaches, including stress and adaptation models, behavior-change models, and ecosystem-based perspectives. Epistemological considerations raised in the conceptual article prompt a reconsideration of methods and tools for the planning of intervention. Further contributions will present a suitable methodology for the application of the DEA-A framework along with practical recommendations.

The calculus of codes - From entropy, complexity, and information to life

Exploring the core components that define living systems and their operational mechanisms within emerging biological entities is a complex endeavor. In the realm of biological systems literature, the terms matter, energy, information, complexity, and entropy are frequently referenced. However, possessing these concepts alone does not guarantee a comprehensive understanding or the ability to reconstruct the intricate nature of life. This study aims to illuminate the trajectory of these organic attributes, presenting a theoretical framework that delves into the integrated role of these concepts in biology. We assert that Code Biology serves as a pivotal steppingstone for unraveling the mechanisms underlying life. Biological codes (BCs) emerge not only from the interplay of matter and energy but also from Information. Contrary to deriving information from the former elements, we propose that information holds its place as a fundamental physical aspect. Consequently, we propose a continuum perspective called Calculus of Fundamentals involving three fundamentals: Matter, Energy, and Information, to depict the dynamics of BCs. To achieve this, we emphasize the necessity of studying Entropy and Complexity as integral organic descriptors. This perspective also facilitates the introduction of a mathematical theoretical framework that aids in comprehending continuous changes, the driving dynamics of biological fundamentals. We posit that Energy, Matter, and Information constitute the essential building blocks of living systems, and their interactions are governed by Entropy and Complexity analyses, redefined as biological descriptors. This interdisciplinary perspective of Code Biology sheds light on the intricate interplay between the controversial phenomenon of life and advances the idea of constructing a theory rooted in information as an organic fundamental.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Such stable changes can (1) alter steady-state levels while preserving the architecture, (2) induce different architectures that persist for many generations, or (3) collapse the entire architecture. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that the evolution of mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of regulatory architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode C. elegans, which range from permanent silencing to recovery from silencing within a few generations and subsequent resistance to silencing. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

The evolutionary consequences of epigenesis and neutral change: A conceptual approach at the organismal level

Living beings are autopoietic systems with highly context-dependent structural dynamics and interactions, that determine whether a disturbance in the genotype or environment will lead or not to phenotypic change. The concept of epigenesis entails how a change in the phenotype may not correspond to a change in the structure of an earlier developmental stage, including the genome. Disturbances of embryonic structure may fail to change the phenotype, as in regulated development, or when different genotypes are associated to a single phenotype. Likewise, the same genotype or early embryonic structure may develop different phenotypes, as in phenotypic plasticity. Disturbances that fail to trigger phenotypic change are considered neutral, but even so, they can alter unexpressed developmental potential. Here, we present conceptual diagrams of the "epigenic field": similar to Waddington's epigenetic landscapes, but including the ontogenic niche (organism/environment interactional dynamics during ontogeny) as a factor in defining epigenic fields, rather than just selecting among possible pathways. Our diagrams illustrate transgenerational changes of genotype, ontogenic niche, and their correspondence (or lack thereof) with changes of phenotype. Epigenic fields provide a simple way to understand developmental constraints on evolution, for instance: how constraints evolve as a result of developmental system drift; how neutral changes can be involved in genetic assimilation and de-assimilation; and how constraints can evolve as a result of neutral changes in the ontogenic niche (not only the genotype). We argue that evolutionary thinking can benefit from a framework for evolution with conceptual foundations at the organismal level.

The ecology-evolution continuum and the origin of life

Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish a broader evolutionary framework that allows for adaptive complexification prior to the emergence of bounded individuals or genetic encoding. This framework establishes the formal equivalence of cells, ecosystems and certain localized chemical reaction systems as autocatalytic chemical ecosystems (ACEs): food-driven (open) systems that can grow due to the action of autocatalytic cycles (ACs). When ACEs are organized in meta-ecosystems, whether they be populations of cells or sets of chemically similar environmental patches, evolution, defined as change in AC frequency over time, can occur. In cases where ACs are enriched because they enhance ACE persistence or dispersal ability, evolution is adaptive and can build complexity. In particular, adaptive evolution can explain the emergence of self-bounded units (e.g. protocells) and genetic inheritance mechanisms. Recognizing the continuity between ecological and evolutionary change through the lens of autocatalytic chemical ecology suggests that the origin of life should be seen as a general and predictable outcome of driven chemical ecosystems rather than a phenomenon requiring specific, rare conditions.

From autocatalysis to survival of the fittest in self-reproducing lipid systems

Studying autocatalysis - in which molecules catalyse their own formation - might help to explain the emergence of chemical systems that exhibit traits normally associated with biology. When coupled to other processes, autocatalysis can lead to complex systems-level behaviour in apparently simple mixtures. Lipids are an important class of chemicals that appear simple in isolation, but collectively show complex supramolecular and mesoscale dynamics. Here we discuss autocatalytic lipids as a source of extraordinary behaviour such as primitive chemical evolution, chemotaxis, temporally controllable materials and even as supramolecular catalysts for continuous synthesis. We survey the literature since the first examples of lipid autocatalysis and highlight state-of-the-art synthetic systems that emulate life, displaying behaviour such as metabolism and homeostasis, with special consideration for generating structural complexity and out-of-equilibrium models of life. Autocatalytic lipid systems have enormous potential for building complexity from simple components, and connections between physical effects and molecular reactivity are only just beginning to be discovered.

Using neurons to maintain autonomy: Learning from C. elegans

Understanding how biological organisms are autonomous-maintain themselves far from equilibrium through their own activities-requires understanding how they regulate those activities. In multicellular animals, such control can be exercised either via endocrine signaling through the vasculature or via neurons. In C. elegans this control is exercised by a well-delineated relatively small but distributed nervous system that relies on both chemical and electric transmission of signals. This system provides resources to integrate information from multiple sources as needed to maintain the organism. Especially important for the exercise of neural control are neuromodulators, which we present as setting agendas for control through more traditional electrical signaling. To illustrate how the C. elegans nervous system integrates multiple sources of information in controlling activities important for autonomy, we focus on feeding behavior and responses to adverse conditions. We conclude by considering how a distributed nervous system without a centralized controller is nonetheless adequate for autonomy.

Death as the Cessation of an Organism and the Moral Status Alternative

The mainstream concept of death-the biological one-identifies death with the cessation of an organism. In this article, I challenge the mainstream position, showing that there is no single well-established concept of an organism and no universal concept of death in biological terms. Moreover, some of the biological views on death, if applied in the context of bedside decisions, might imply unacceptable consequences. I argue the moral concept of death-one similar to that of Robert Veatch-overcomes such difficulties. The moral view identifies death with the irreversible cessation of a patient's moral status, that is, a state when she can no longer be harmed or wronged. The death of a patient takes place when she is no longer capable of regaining her consciousness. In this regard, the proposal elaborated herein resembles that of Veatch yet differs from Veatch's original project since it is universal. In essence, it is applicable in the case of other living beings such as animals and plants, provided that they have some moral status.

The roots and blossoms of 4E cognition in Chile: Introduction to the Special Issue on 4E cognition in Chile

4E cognition (embodied, embedded, extended, and enactive) is a growing, open and pluralistic research tradition that offers new philosophical and scientific avenues to study the mind. Both its origins and current expansive movement are theoretically and geographically diverse. Chile, the mother country of the influential biologists Francisco Varela and Humberto Maturana, represents one of its roots, but also, as the variety of contributions in this special issue shows it, one of its fields of new blossoms. In this editorial introduction, regarding the roots, we focus on the enactive approach developed by Francisco Varela and its relationship with Maturana’s autopoietic theory. We discuss the way in which the particular theoretical and historical horizons of these two research programs conditioned, to a large extent, their philosophical stances regarding cognition. Regarding the new blossoms, we introduce the seven articles composing the present special issue and briefly comment on their contributions in terms of methodology, practical applications, theoretical extensions, and conceptual reflection.

From autopoiesis to self-optimization: Toward an enactive model of biological regulation

The theory of autopoiesis has been influential in many areas of theoretical biology, especially in the fields of artificial life and origins of life. However, it has not managed to productively connect with mainstream biology, partly for theoretical reasons, but arguably mainly because deriving specific working hypotheses has been challenging. The theory has recently undergone significant conceptual development in the enactive approach to life and mind. Hidden complexity in the original conception of autopoiesis has been explicated in the service of other operationalizable concepts related to self-individuation: precariousness, adaptivity, and agency. Here we advance these developments by highlighting the interplay of these concepts with considerations from thermodynamics: reversibility, irreversibility, and path-dependence. We interpret this interplay in terms of the self-optimization model, and present modeling results that illustrate how these minimal conditions enable a system to re-organize itself such that it tends toward coordinated constraint satisfaction at the system level. Although the model is still very abstract, these results point in a direction where the enactive approach could productively connect with cell biology.

Cartography of the multiple formal systems of molecular autopoiesis from the biology of cognition and enaction to anticipation and active inference

A rich literature has grown up over the years that bears with autopoiesis, which tends to assume that it is a model, a theory, a principle, a definition of life, a property, refers to self-organization or even to hastily conclude that it is hylomorphic, hylozoist, in need of reformulation or to be overcome, making its status even more unclear. Maturana insists that autopoiesis is none of these and rather it is the causal organization of living systems as natural systems (NS) such that when it stops, they die. He calls this molecular autopoiesis (MA), which comprises two domains of existence: that of the self-producing organization (self-fabrication) and that of the structural coupling/enaction (cognition). Like all-NS in the universe, MA is amenable to be defined in theoretical terms, i.e. encoded in mathematical models and/or formal systems (FS). Framing the multiple formal systems of autopoiesis (FSA) into the Rosen's modeling relation (a process of bringing into equivalence the causality of NS and the inferential rules of FS), allows a classification of FSA into analytical categories, most importantly Turing machine (algorithmic) vs non-Turing machine (non-algorithmic) based, and FSA with a purely reactive mathematical image as cybernetic systems, i.e. feedbacks based, or conversely, as anticipatory systems making active inferences. It is thus the intent of the present work to advance the precision with which different FS may be observed to comply (preserve correspondence) with MA in its worldly state as a NS. The modeling relation between MA and the range of FS proposed as potentially illuminating their processes forecloses the applicability of Turing-based algorithmic computational models. This outcome indicates that MA, as modelled through Varela's calculus of self-reference or more especially through Rosen's (M,R)-system, is essentially anticipatory without violating structural determinism nor causality whatsoever, hence enaction may involve it. This quality may capture a fundamentally different mode of being in living systems as opposed to mechanical-computational systems. Implications in different fields of biology from the origin of life to planetary biology as well as in cognitive science and artificial intelligence are of interest.

Autopoiesis of the artificial: From systems to cognition

In the seminal work on autopoiesis by Varela, Maturana, and Uribe, they start by addressing the confusion between processes that are history dependent and processes that are history independent in the biological world. The former is particularly linked to evolution and ontogenesis, while the latter pertains to the organizational features of biological individuals. Varela, Maturana, and Uribe reject this framework and propose their original theory of autopoietic organization, which emphasizes the strong complementarity of temporal and non-temporal phenomena. They argue that the dichotomy between structure and organization lies at the core of the unity of living systems. By opposing history-dependent and history-independent processes, methodological challenges arise in explaining phenomena related to living systems and cognition. Consequently, Maturana and Varela reject this approach in defining autopoietic organization. I argue, however, that this relationship presents an issue that can be found in recent developments of the science of artificial intelligence (AI) in different ways, giving rise to related concerns. While highly capable AI systems exist that can perform cognitive tasks, their internal workings and the specific contributions of their components to the overall system behavior, understood as a unified whole, remain largely uninterpretable. This article explores the connection between biological systems, cognition, and recent developments in AI systems that could potentially be linked to autopoiesis and related concepts such as autonomy and organization. The aim is to assess the advantages and disadvantages of employing autopoiesis in the synthetic (artificial) explanation for biological cognitive systems and to determine if and how the notion of autopoiesis can still be fruitful in this perspective.

Modeling autopoiesis and cognition with reaction networks

Maturana and Varela defined an autopoietic system as a self-regenerating network of processes. We reinterpret and elaborate this conception starting from a process ontology and its formalization in terms of reaction networks and chemical organization theory. An autopoietic organization can be modelled as a network of "molecules" (components) undergoing reactions, which is (operationally) closed and self-maintaining. Such organizations, being attractors of a dynamic system, tend to self-organize-thus providing a model for the origin of life. However, in order to survive in a variable environment, they must also be resilient, i.e. able to compensate perturbations. According to the "good regulator theorem" this requires some form of cognition, i.e. knowing which action to perform for which perturbation. Such cognition becomes more effective as it learns to anticipate perturbations by discovering invariant patterns in its interactions with the environment. Nevertheless, the resulting predictive model remains a subjective construction. Such implicit model cannot be interpreted as an objective representation of external reality, because the autopoietic system does not have direct access to that reality, and there is in general no isomorphism between internal and external processes.

Semigroup models for biochemical reaction networks

The catalytic reaction system (CRS) formalism by Hordijk and Steel is a versatile method to model autocatalytic biochemical reaction networks. It is particularly suited, and has been widely used, to study self-sustainment and self-generation properties. Its distinguishing feature is the explicit assignment of a catalytic function to chemicals that are part of the system. In this work, it is shown that the subsequent and simultaneous catalytic functions give rise to an algebraic structure of a semigroup with the additional compatible operation of idempotent addition and a partial order. The aim of this article is to demonstrate that such semigroup models are a natural setup to describe and analyze self-sustaining CRS. The basic algebraic properties of the models are established and the notion of the function of any set of chemicals on the whole CRS is made precise. This leads to a natural discrete dynamical system on the power set of chemicals, which is obtained by iteratively considering the self-action on a set of chemicals by its own function. The fixed points of this dynamical system are proven to correspond to self-sustaining sets of chemicals, which are functionally closed. Finally, as the main application, a theorem on the maximal self-sustaining set and a structure theorem on the set of functionally closed self-sustaining sets of chemicals are proven.

An algebraic characterization of self-generating chemical reaction networks using semigroup models

The ability of a chemical reaction network to generate itself by catalyzed reactions from constantly present environmental food sources is considered a fundamental property in origin-of-life research. Based on Kaufmann's autocatalytic sets, Hordijk and Steel have constructed the versatile formalism of catalytic reaction systems (CRS) to model and to analyze such self-generating networks, which they named reflexively autocatalytic and food-generated. Recently, it was established that the subsequent and simultaenous catalytic functions of the chemicals of a CRS give rise to an algebraic structure, termed a semigroup model. The semigroup model allows to naturally consider the function of any subset of chemicals on the whole CRS. This gives rise to a generative dynamics by iteratively applying the function of a subset to the externally supplied food set. The fixed point of this dynamics yields the maximal self-generating set of chemicals. Moreover, the set of all functionally closed self-generating sets of chemicals is discussed and a structure theorem for this set is proven. It is also shown that a CRS which contains self-generating sets of chemicals cannot have a nilpotent semigroup model and thus a useful link to the combinatorial theory of finite semigroups is established. The main technical tool introduced and utilized in this work is the representation of the semigroup elements as decorated rooted trees, allowing to translate the generation of chemicals from a given set of resources into the semigroup language.

Collective Memory: Metaphor or Real?

Collective memory researchers predominantly in the cultural and social sciences have commonly understood the concept of collective memory as a mere metaphor, as something not existing in itself as memory but useful only as a tool for referring to the way groups construct shared representations of their past. Few have however addressed the question of whether it is a metaphor or literal in its own right. This paper looks at the plausibility of the claim that collective memory is a mere metaphor by probing its presuppositions, where the representationalist theory of mind emerges as the ground for such a claim. Then appealing to the externalist model of the mind championed in recent studies of mind in disciplines as varied as philosophy, cognitive science, evolutionary biology, and collective intentionality studies, we try to expose the presuppositions of that claim, opening up possibilities for conceiving collective memory as not merely metaphorical but literal and naturally existing as memory.

Complex adaptive phenomenology: A conceptual framework for healthcare research

RATIONALE

Healthcare research exploring the lived experiences of health care professionals from different disciplines, such as nursing, medicine, and allied health, has repeatedly highlighted many methodological challenges, especially in understanding the individual human experience within complex systems. In response, complexity theory and phenomenological approaches emerged and evolved in ways that potentially offered researchers frameworks to inform an understanding of the individual human experience. However, while these two theoretical approaches inform a method of inquiry, there is a gap in understanding the phenomenon of 'being' and how this is embodied within complex systems such as the healthcare system.

THE AIMS AND OBJECTIVES

The aim of this paper is to present an integrated theoretical framework, namely complex adaptive phenomenology (CAP). CAP aims to address this inquiry gap by offering a structured conceptual framework wherein complexity theory and phenomenology are complementary but multi-dimensional. The key objective of CAP was to synthesize and integrate two methods of inquiry that examine the relational aspects of 'being', that is the gestalt of perception, action, and context, The authors argue that CAP is well-suited to complex research contexts such as healthcare. The framework focuses on the reciprocal, co-constructive relationships extant between perception, meaning, context, and action that shape experiences of 'being' within complex systems. Complexity theory's connectionist orientation explains the relationships that are formative of the experience of being, while phenomenology explores the manifestations of these formative relationships by attending to the notion of 'being' itself.

CONCLUSION

The authors propose that an integrated framework, of phenomenology and complexity theory, can provide a platform for deeper understandings of the experiences of health professionals and contribute to healthcare scholarship.

The theoretical foundations of enaction: Precariousness

Enaction is an increasingly influential approach to cognition that grew out of Maturana and Varela's earlier work on autopoiesis and the biology of cognition. As with any relatively new scientific discipline, the enactive approach would benefit greatly from a careful analysis of its theoretical foundations. Here we initiate such an analysis for one of the core concepts of enaction, precariousness. Specifically, we consider three types of fragility: systemic, processual and thermodynamic. Using a glider in the Game of Life as a toy model, we illustrate each of these fragilities and examine the relationships between them. We also argue that each type of fragility is characterized by which aspects of a system are hardwired into its definition from the outset and which aspects are emergent and hence vulnerable to disintegration without ongoing maintenance.

Why art? The role of arts in arts and health

This article is an answer to a report called "What is the evidence on the role of the arts in improving health and well-being?" The authors conclude that the arts have an impact on mental and physical health. Yet, the question of the role of the arts remains unanswered. What is and what is not an art effect? Recently, embodied theory has inspired articles on the perception of art. These articles have not yet received attention in the field of Arts and Health. Scholars in psychosomatic medicine have argued for an approach based on recent work in enactive embodied theory to investigate the connection between the body and the mind. The present article examines how key concepts in this theory relate to art. This leads to a discussion of art in terms of empathy-the relation between the internal state of the artist and the internal state of the beholder. I exemplify with a conceptual framework of musical empathy. Implications for health are addressed.

Fake cells and the aura of life: A philosophical diagnostic of synthetic life

Synthetic biology is often seen as the engineering turn in biology. Philosophically speaking, entities created by synthetic biology, from synthetic cells to xenobots, challenge the ontological divide between the organic and inorganic, as well as between the natural and the artificial. Entities such as synthetic cells can be seen as hybrid or transitory objects, or neo-things. However, what has remained philosophically underexplored so far is the impact these hybrid neo-things will have on (our phenomenological experience of) the living world. By extrapolating from Walter Benjamin's account of how technological reproducibility affects the aura of art, we embark upon an exploratory inquiry that seeks to fathom how the technological reproducibility of life itself may influence our experience and understanding of the living. We conclude that, much as technologies that enabled reproduction corroded the aura of original artworks (as Benjamin argued), so too will the aura of life be under siege in the era of synthetic lifeforms. This article zooms in on a specific case study, namely the research project Building a Synthetic Cell (BaSyC) and its mission to create a synthetic cell-like entity, as autonomous as possible, focusing on the properties that differentiate organic from synthetic cells.

Configurations of Proto-Cell Aggregates with Anisotropy: Gravity Promotes Complexity in Theoretical Biology

This contribution considers proto-cell structures associated with asymmetries, mainly gravity, in the framework of reaction-diffusion. There are equivalent solutions for defined morphogen parameters in the equations that allow for defining proto-tissue complexity and configurational entropy. Using RNA data, improvements to the complexity and entropy due to the Earth's gravity are presented. The theoretical proto-tissues complexity estimation, as a function of arbitrary surface gravity, is likewise proposed. In this sense, hypothetical aggregates of proto-cells on Mars would have a lower complexity than on Earth, which is equally valid for the Moon. Massive planets, or exoplanets like BD+20594b, could have major proto-tissue complexity and, eventually, rich biodiversity.

Who tailors the blanket?

The gap between the Markov blanket and ontological boundaries arises from the former's inability to capture the dynamic process through which biological and cognitive agents actively generate their own boundaries with the environment. Active inference in the free-energy principle (FEP) framework presupposes the existence of a Markov blanket, but it is not a process that actively generates the latter.

The hierarchical organization of autocatalytic reaction networks and its relevance to the origin of life

Prior work on abiogenesis, the emergence of life from non-life, suggests that it requires chemical reaction networks that contain self-amplifying motifs, namely, autocatalytic cores. However, little is known about how the presence of multiple autocatalytic cores might allow for the gradual accretion of complexity on the path to life. To explore this problem, we develop the concept of a seed-dependent autocatalytic system (SDAS), which is a subnetwork that can autocatalytically self-maintain given a flux of food, but cannot be initiated by food alone. Rather, initiation of SDASs requires the transient introduction of chemical “seeds.” We show that, depending on the topological relationship of SDASs in a chemical reaction network, a food-driven system can accrete complexity in a historically contingent manner, governed by rare seeding events. We develop new algorithms for detecting and analyzing SDASs in chemical reaction databases and describe parallels between multi-SDAS networks and biological ecosystems. Applying our algorithms to both an abiotic reaction network and a biochemical one, each driven by a set of simple food chemicals, we detect SDASs that are organized as trophic tiers, of which the higher tier can be seeded by relatively simple chemicals if the lower tier is already activated. This indicates that sequential activation of trophically organized SDASs by seed chemicals that are not much more complex than what already exist could be a mechanism of gradual complexification from relatively simple abiotic reactions to more complex life-like systems. Interestingly, in both reaction networks, higher-tier SDASs include chemicals that might alter emergent features of chemical systems and could serve as early targets of selection. Our analysis provides computational tools for analyzing very large chemical/biochemical reaction networks and suggests new approaches to studying abiogenesis in the lab.

The level of complexity seen in even the simplest living system is too great to have arisen in its current form without a long history of complexification. In this paper, we explore the view that open environments on the early Earth that received an ongoing flux of food chemicals could have complexified gradually by the sequential activation of autocatalytic chemical reaction systems. We develop the concept of seed-dependent autocatalytic systems (SDASs)–subnetworks whose components can self-propagate once activated by “seed” molecules, which might result from rare reactions or import from other environments. We developed new computational tools for detecting SDASs in reaction databases and determining if they are hierarchically organized, such that the activation of a lower-tier SDAS allows a higher-tier SDAS to then be seeded, much like the relationship between producers and consumers in an ecosystem. We apply our algorithms to two chemical reaction networks, one biological and the other abiotic, and find that both contain hierarchically organized SDASs. These results support the fundamental continuity of the way that the chemistry of non-life and life is organized and suggest new classes of laboratory experiment.

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms

The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.

Beauty and Uncertainty as Transformative Factors: A Free Energy Principle Account of Aesthetic Diagnosis and Intervention in Gestalt Psychotherapy

Drawing from field theory, Gestalt therapy conceives psychological suffering and psychotherapy as two intentional field phenomena, where unprocessed and chaotic experiences seek the opportunity to emerge and be assimilated through the contact between the patient and the therapist (i.e., the intentionality of contacting). This therapeutic approach is based on the therapist’s aesthetic experience of his/her embodied presence in the flow of the healing process because (1) the perception of beauty can provide the therapist with feedback on the assimilation of unprocessed experiences; (2) the therapist’s attentional focus on intrinsic aesthetic diagnostic criteria can facilitate the modification of rigid psychopathological fields by supporting the openness to novel experiences. The aim of the present manuscript is to review recent evidence from psychophysiology, neuroaesthetic research, and neurocomputational models of cognition, such as the free energy principle (FEP), which support the notion of the therapeutic potential of aesthetic sensibility in Gestalt psychotherapy. Drawing from neuroimaging data, psychophysiology and recent neurocognitive accounts of aesthetic perception, we propose a novel interpretation of the sense of beauty as a self-generated reward motivating us to assimilate an ever-greater spectrum of sensory and affective states in our predictive representation of ourselves and the world and supporting the intentionality of contact. Expecting beauty, in the psychotherapeutic encounter, can help therapists tolerate uncertainty avoiding impulsive behaviours and to stay tuned to the process of change.

Complexification of eukaryote phenotype: Adaptive immuno-cognitive systems as unique Gödelian block chain distributed ledger

The digitization of inheritable information in the genome has been called the 'algorithmic take-over of biology'. The McClintock discovery that viral software based transposable elements that conduct cut-paste (transposon) and copy-paste (retrotransposon) operations are needed for genomic evolvability underscores the truism that only software can change software and also that viral hacking by internal and external bio-malware is the Achilles heel of genomic digital systems. There was a paradigm shift in genomic information processing with the Adaptive Immune System (AIS) 500 mya followed by the Mirror Neuron System (MNS), latterly mostly in primate brains, which reaches its apogee in human social cognition. The AIS and MNS involve distinctive Gödelian features of self-reference (Self-Ref) and offline virtual self-representation (Self-Rep) for complex self-other interaction with prodigious open-ended capacity for anticipative malware detection and novelty production within a unique blockchain distributed ledger (BCDL). The role of self-referential information processing, often considered to be central to the sentient self with origins in the immune system 'Thymic self', is shown to be part of the Gödel logic behind a generator-selector framework at a molecular level, which exerts stringent selection criteria to maintain genomic BCDL. The latter manifests digital and decentralized record keeping where no internal or external bio-malware can compromise the immutability of the life's building blocks and no novel blocks can be added that is not consistent with extant blocks. This is demonstrated with regard to somatic hypermutation with novel anti-body production in the face of external non-self antigen attacks.

A New Approach to Disease, Risk, and Boundaries Based on Emergent Probability

The status of risk factors and disease remains a disputed question in the theory and practice of medicine and healthcare, and so does the related question of delineating disease boundaries. I present a framework based on Bernard Lonergan's account of emergent probability for differentiating (1) generically distinct levels of systematic function within organisms and between organisms and their environments and (2) the methods of functional, genetic, and statistical investigation. I then argue on this basis that it is possible to understand disease in terms of biological or higher intra-level dysfunction, risk factors-including genetic risk factors-in terms of statistical inter-level conditioning of a given stage or developmental sequence of systematic functioning, and the empirical boundaries of disease in terms of the limits of both functional categorization (from an epistemic standpoint) and upper-level integration of lower-level processes and events (from an ontological standpoint).

Neuroscience and architecture: Modulating behavior through sensorimotor responses to the built environment

As we move through the world, natural and built environments implicitly guide behavior by appealing to certain sensory and motor dynamics. This process can be motivated by automatic attention to environmental features that resonate with specific sensorimotor responses. This review aims at providing a psychobiological framework describing how environmental features can lead to automated sensorimotor responses through defined neurophysiological mechanisms underlying attention. Through the use of automated processes in subsets of cortical structures, the goal of this framework is to describe on a neuronal level the functional link between the designed environment and sensorimotor responses. By distinguishing between environmental features and sensorimotor responses we elaborate on how automatic behavior employs the environment for sensorimotor adaptation. This is realized through a thalamo-cortical network integrating environmental features with motor aspects of behavior. We highlight the underlying transthalamic transmission from an Enactive and predictive perspective and review recent studies that effectively modulated behavior by systematically manipulating environmental features. We end by suggesting a promising combination of neuroimaging and computational analysis for future studies.

How much do model organism phenotypes contribute to the computational identification of human disease genes?

Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past decade, cross-species phenotype comparisons have proven valuble, and several ontologies have been developed for this purpose. The relative contribution of different model organisms to computational identification of disease-associated genes is not fully explored. We used phenotype ontologies to semantically relate phenotypes resulting from loss-of-function mutations in model organisms to disease-associated phenotypes in humans. Semantic machine learning methods were used to measure the contribution of different model organisms to the identification of known human gene–disease associations. We found that mouse genotype–phenotype data provided the most important dataset in the identification of human disease genes by semantic similarity and machine learning over phenotype ontologies. Other model organisms' data did not improve identification over that obtained using the mouse alone, and therefore did not contribute significantly to this task. Our work impacts on the development of integrated phenotype ontologies, as well as for the use of model organism phenotypes in human genetic variant interpretation.

This article has an associated First Person interview with the first author of the paper.

Editor's choice: We investigated the use of model organism phenotypes in the computational identification of disease genes, identifying several data biases and concluding that mouse model phenotypes contribute most to computational disease gene identification.

Klinische Ethik systemisch betrachtet – Vom Einfluss systemischer Grundannahmen und Methoden auf die Gestaltung einer effektiven Ethikberatung

Krankenhäuser müssen sich an der ethischen Qualität ihrer Versorgung messen lassen. Es geht dabei um einen Zustand, in dem allgemein anerkannte moralische Normen in der Patient:innenversorgung konsequent berücksichtigt werden. Damit sind zwei Ebenen angesprochen: die der ethisch-normativen Deutung und die der Gestaltung intra- und interpersonaler Prozesse. Die Klinische Ethik ist die Disziplin, die in der Verbindung beider ihre zentrale Aufgabe sieht. Um sie zu erfüllen, muss Ethikarbeit auf der Basis komplexer Kompetenzen erfolgen. Neben fundiertem Ethikwissen ist das Beherrschen von geeigneten Methoden für die Steuerung solcher Prozesse eine unabdingbare Voraussetzung. Dazu aber ist die Studienlage vergleichsweise dünn. Die vorliegende Arbeit greift dieses Desiderat auf und geht dabei von der Hypothese aus, dass die Systemik einen wichtigen Beitrag zu einer im obigen Sinne effektiven Ethikarbeit leisten kann. Die Darstellung gibt einen Einblick in das systemische Denken und diskutiert die Möglichkeiten, die systemisches Handwerkszeug für die Herausforderungen der Klinischen Ethik bereithält. Die Ausführungen laden dazu ein, über den Einfluss systemischer Grundannahmen und Methoden auf die Gestaltung einer effektiven Ethikarbeit nachzudenken. Darüber hinaus ruft dieser Beitrag dazu auf, die Beratungsmethodik als solche mehr in den Fokus zu rücken.

Navigating in the Gray Area of Coach-Athlete Relationships in Sports: Toward an In-depth Analysis of the Dynamics of Athlete Maltreatment Experiences

Several studies have revealed the abusive behaviors directed against athletes in various sports contexts, but knowledge about the processes by which the athletes realize and accept or reject maltreatment is underdeveloped. Thus, it is difficult to establish a solid scientific basis for characterizing the mechanisms of maltreatment from the athletes' perspective regarding the forms of maltreatment they endure and the impact on their performance and wellbeing. The main goals of this paper are to show how the enactive approach (including theoretical assumptions and methodological standards) can meet these challenges, as it is well-suited to (a) describe the evolving interactions between athletes and the sports situations that lead to maltreatment (i.e., navigating in the gray area of coach-athlete relationships), (b) identify those alert landmarks that help us assess the level of risk of athlete maltreatment, and (c) provide concrete guidelines to prevent and deal with sports-related maltreatment. We illustrate our approach by a case study that examines the experience of a retired high-level boxer who faced several forms of maltreatment. Our results reveal a dynamic change in the interactions between the boxer and the maltreatment situations that led her through (a) Acceptance (i.e., future-oriented positive involvement), (b) Regulation attempt (i.e., negative feelings about weight loss, exhaustion and loneliness, questioning the compromise between performance and health, acceptance and loneliness), (c) Distancing (i.e., reopening to others) and (d) Rejection (i.e., rebellion and the decision to stand up to her coach and leave). Based on our results, we present concrete guidelines to prevent and address sports-related maltreatment, with four progressive alert landmarks that help situate the athlete in the gray area of coach-athlete relationships and suggest a “timeline” of maltreatment escalation with key warnings.

Information systems as a nexus of information technology systems: A new view of information systems practice

The close relationship between the concepts of information systems and information technology creates issues for researchers. Usefully distinguishing between the concepts is problematic. We investigate the use of the systems concept in practice, finding a pragmatic distinction between an information system (IS) and an information technology system (IT system). In a practice view, an IS incorporates an emphasis on both a technical and a social subsystem, while an IT system predominantly emphasizes the technical elements. This distinction becomes useful in practice because contemporary IS practitioners are often involved in acquiring and integrating IT systems into an organizational IS. This involvement leads to a viewpoint on the organizational IS (including the social subsystem) as a nexus of multiple IT systems. This nexus creates issues in practice for not only integrating IT systems into the organizational IS, but also integrating multiple IT systems with each other in the context of the organizational IS. These issues lead to research opportunities such as the need for new methodologies for IT system acquisitions and new theories that accommodate the social integration of IT systems and IS.

The role of self-maintaining resilient reaction networks in the origin and evolution of life

We characterize living systems as resilient "chemical organizations", i.e. self-maintaining networks of reactions that are able to resist a wide range of perturbations. Dissipative structures, such as flames or convection cells, are also self-maintaining, but much less resilient. We try to understand how life could have originated from such self-organized structures, and evolved further, by acquiring various mechanisms to increase resilience. General mechanisms include negative feedback, buffering of resources, and degeneracy (producing the same resources via different pathways). Specific mechanisms use catalysts, such as enzymes, to enable reactions that deal with specific perturbations. This activity can be regulated by "memory" molecules, such as DNA, which selectively produce catalysts when needed. We suggest that major evolutionary transitions take place when living cells of different types or species form a higher-order organization by specializing in different functions and thus minimizing interference between their reactions.

Attribution of autonomy and its role in robotic language acquisition

The false attribution of autonomy and related concepts to artificial agents that lack the attributed levels of the respective characteristic is problematic in many ways. In this article, we contrast this view with a positive viewpoint that emphasizes the potential role of such false attributions in the context of robotic language acquisition. By adding emotional displays and congruent body behaviors to a child-like humanoid robot’s behavioral repertoire, we were able to bring naïve human tutors to engage in so called intent interpretations. In developmental psychology, intent interpretations can be hypothesized to play a central role in the acquisition of emotion, volition, and similar autonomy-related words. The aforementioned experiments originally targeted the acquisition of linguistic negation. However, participants produced other affect- and motivation-related words with high frequencies too and, as a consequence, these entered the robot’s active vocabulary. We will analyze participants’ non-negative emotional and volitional speech and contrast it with participants’ speech in a non-affective baseline scenario. Implications of these findings for robotic language acquisition in particular and artificial intelligence and robotics more generally will also be discussed.

Organization needs organization: Understanding integrated control in living organisms

Organization figures centrally in the understanding of biological systems advanced by both new mechanists and proponents of the autonomy framework. The new mechanists focus on how components of mechanisms are organized to produce a phenomenon and emphasize productive continuity between these components. The autonomy framework focuses on how the components of a biological system are organized in such a way that they contribute to the maintenance of the organisms that produce them. In this paper we analyze and compare these two accounts of organization and argue that understanding biological organisms as cohesively integrated systems benefits from insights from both. To bring together the two accounts, we focus on the notions of control and regulation as bridge concepts. We start from a characterization of biological mechanisms in terms of constraints and focus on a specific type of mechanism, control mechanisms, that operate on other mechanisms on the basis of measurements of variables in the system and its environment. Control mechanisms are characterized by their own set of constraints that enable them to sense conditions, convey signals, and effect changes on constraints in the controlled mechanism. They thereby allow living organisms to adapt to internal and external variations and to coordinate their parts in such a manner as to maintain viability. Because living organisms contain a vast number of control mechanisms, a central challenge is to understand how they are themselves organized. With the support of examples from both unicellular and multicellular systems we argue that control mechanisms are organized heterarchically, and we discuss how this type of control architecture can, without invoking top-down and centralized forms of organizations, succeed in coordinating internal activities of organisms.

Capture and express, question and understand: Gloves in gestural electronic music performance

Gesture-based musical performance with on-body sensing represents a particular case of wearable connection. Gloves and hand-sensing interfaces connected to real-time digital sound production and transformation processes enable empty-handed, expressive musical performance styles. In this article, the origins and developments of this practice as well as a specific use case are investigated. By taking the technical, cognitive, and cultural dimensions of this media performance as foundation, a reflection on the value, limitations, and opportunities of computational approaches to movement translation and analysis is carried out. The insights uncover how the multilayered, complex artistic situations produced by these performances are rich in intersections and represent potent amplifiers for investigating corporeal presence and affective engagement. This allows to identify problems and opportunities of existing research approaches and core issues to be solved in the domain of movement, music, interaction technology, and performance research.

Brains as Computers: Metaphor, Analogy, Theory or Fact?

Whether electronic, analog or quantum, a computer is a programmable machine. Wilder Penfield held that the brain is literally a computer, because he was a dualist: the mind programs the brain. If this type of dualism is rejected, then identifying the brain to a computer requires defining what a brain “program” might mean and who gets to “program” the brain. If the brain “programs” itself when it learns, then this is a metaphor. If evolution “programs” the brain, then this is a metaphor. Indeed, in the neuroscience literature, the brain-computer is typically not used as an analogy, i.e., as an explicit comparison, but metaphorically, by importing terms from the field of computers into neuroscientific discourse: we assert that brains compute the location of sounds, we wonder how perceptual algorithms are implemented in the brain. Considerable difficulties arise when attempting to give a precise biological description of these terms, which is the sign that we are indeed dealing with a metaphor. Metaphors can be both useful and misleading. The appeal of the brain-computer metaphor is that it promises to bridge physiological and mental domains. But it is misleading because the basis of this promise is that computer terms are themselves imported from the mental domain (calculation, memory, information). In other words, the brain-computer metaphor offers a reductionist view of cognition (all cognition is calculation) rather than a naturalistic theory of cognition, hidden behind a metaphoric blanket.

Situated Neural Representations: Solving the Problems of Content

Situated approaches to cognition maintain that cognition is embodied, embedded, enactive, and affective (and extended, but that is not relevant here). Situated approaches are often pitched as alternatives to computational and representational approaches, according to which cognition is computation over representations. I argue that, far from being opposites, situatedness and neural representation are more deeply intertwined than anyone suspected. To show this, I introduce a neurocomputational account of cognition that relies on neural representations. I argue not only that this account is compatible with (non-question-begging) situated approaches, but also that it requires embodiment, embeddedness, enaction, and affect at its very core. That is, constructing neural representations and their semantic content, and learning computational processes appropriate for their content, requires a tight dynamic interaction between nervous system, body, and environment. Most importantly, I argue that situatedness is needed to give a satisfactory account of neural representation: neurocognitive systems that are embodied, embedded, affective, dynamically interact with their environment, and use feedback from their interaction to shape their own representations and computations (1) can construct neural representations with original semantic content, (2) their neural vehicles and the way they are processed are automatically coordinated with their content, (3) such content is causally efficacious, (4) is determinate enough for the system's purposes, (5) represents the distal stimulus, and (6) can misrepresent. This proposal hints at what is needed to build artifacts with some of the basic cognitive capacities possessed by neurocognitive systems.

Relating Social and Ecological Resilience: Dutch Citizen’s Initiatives for Biodiversity

Social resilience and ecological resilience are related and distinguished, and the potential of social resilience to enhance resilience of encompassing social-ecological systems is discussed. The value of resilience thinking is recognized, yet social resilience needs to be better understood in its distinctive qualities, while resisting identification of social resilience with one particular form of governance or organization. Emerging self-organizing citizen’s initiatives in The Netherlands, initiatives involving re-relating to nature in the living environment, are analyzed, using a systems theoretical framework which resists reduction of nature to culture or vice versa. It is argued that space for self-organization needs to be cultivated, that local self-organization and mobilization around themes of nature in daily life and space have the potential to re-link social and ecological systems in a more resilient manner, yet that maintaining the diversity of forms of knowing and organizing in the overall governance system is essential to the maintenance of social resilience and of diverse capacities to know human-environment relations and to reorganize them in an adaptive manner. Conclusions are drawn in the light of the new Biodiversity Strategy.