Pheromone

Symbiotic organs in insects: diversity, functional implications, and terminology

Abstract With over a million described species, insects represent the most successful group of animals on Earth. One of the drivers of insect diversity is their ability to engage in multifold beneficial symbioses with microorganisms, often involving specialized host organs to accommodate intra- or extracellular symbionts. The existence of such organs and their importance for sustaining and transmitting beneficial symbionts has been known for over a century, and specific terms have been established for categorizing organs harbouring intracellular bacteria (bacteriomes) or fungi (mycetomes), or cuticular crypts containing extracellular fungi (mycetangia). For others, however, general terms are lacking, e.g. organs containing extracellular bacteria associated with the cuticle or with the digestive tract. Furthermore, previously established terms have been misused in other contexts. Notably, ‘bacteriome’ has been increasingly employed in the microbiome field to refer to bacterial communities, instead of the term’s original meaning of specialized organs housing intracellular bacterial symbionts. Here, we review and categorize the diversity of symbiotic organs in insects and propose a unified terminology. Our hope is that this common language will facilitate communication and thereby support the field of symbiosis research in unravelling commonalities and differences in the evolution, ecology, development, physiology and molecular basis across symbiotic interactions. This article is part of the theme issue ‘Life in natural microcosms’.

EPISTEMIC STIGMERGY: NATURAL VS. ARTIFICIAL INTELLIGENCE

The article\(^{1}\) defends the thesis that intelligent behavior might require not internal complexity but complex interaction. This is demonstrated by the various forms of stigmergy that can be observed both in social insects and in humans. The exposition is structured as follows: (§0) explains how the term “intelligence” is interpreted in the following text; (§1) clarifies the relation between intelligence and complexity; (§2) shows that intelligent behavior does not require internal complexity; (§3) introduces the concept of stigmergy; (§4) presents the mechanisms that give rise to this phenomenon; (§5) distinguishes several types of stigmergic interaction; (§6) briefly discusses the evolutionary mechanisms that could have produced them; (§7) sketches the possible ways in which the concept of stigmergy is used outside biology; (§8) examines collaborative stigmergy in humans; (§9) points to its epistemic projections; (§10) outlines some conclusions concerning the role of artificial intelligence systems and their place in human society.

Swarm Intelligence: From Natural to Artificial Systems

Abstract. Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Co

Termite

Termites are a group of eusocial insects which consume a variety of decaying plant material, generally in the form of wood, leaf litter, and soil humus. They are distinguished by their beaded (moniliform) antennae and the soft-bodied, unpigmented worker caste for which they have been commonly termed "white ants"; however, they are not ants but highly derived cockroaches; they are genetically closer to some cockroach groups than these are to other cockroaches. About 2,997 extant species are currently described, 2,125 of which are members of the family Termitidae.

The cognitive cell: bacterial behavior reconsidered

Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction, and signal transduction provides the foundation of the information-processing approach that is the hallmark of the ‘cognitive revolution,’ which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found.

Reciprocal signaling in honeyguide-human mutualism

Honeyguide birds recognize human honey-hunters calls and help them find wild bees’ nests.

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics

Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt).

Antenna (zoology)

An antenna is one of a pair of appendages used for sensing in arthropods. Antennae are sometimes referred to as feelers.

Holobiont

A holobiont is an assemblage of a host and the many other species living in or around it, which together form a discrete ecological unit through symbiosis, though there is controversy over this discreteness. The components of a holobiont are individual species or bionts, while the combined genome of all bionts is the hologenome. The holobiont concept was initially introduced by the German theoretical biologist Adolf Meyer-Abich in 1943, and then apparently independently by Dr. Lynn Margulis in her 1991 book Symbiosis as a Source of Evolutionary Innovation. The concept has evolved since the original formulations. Holobionts include the host, virome, microbiome, and any other organisms which contribute in some way to the functioning of the whole. Well-studied holobionts include reef-building corals and humans.

Cognition without brains? Learning and memory in microorganisms

Memory and learning are cognitive abilities typically associated with animals that possess a complex nervous system. Interestingly, recent studies suggest that microorganisms might also display learning-like behaviours. However, a factor limiting progress in this field is the lack of shared, microbe-specific frameworks that allow microbiologists to easily compare discoveries with concepts developed in cognitive sciences. In this review, we aim to bridge this gap by providing a conceptual overview of the definitional requirements for memory and learning to classify microbial behaviours and capabilities. Additionally, we identify and address problems that cause conceptual ambiguity in the microbial cognition literature, thereby facilitating more productive debates on the topic. Finally, we provide a novel perspective on how microbes might ‘learn’ from each other.

Biophoton signal transmission and processing in the brain

The transmission and processing of neural information in the nervous system plays a key role in neural functions. It is well accepted that neural communication is mediated by bioelectricity and chemical molecules via the processes called bioelectrical and chemical transmission, respectively. Indeed, the traditional theories seem to give valuable explanations for the basic functions of the nervous system, but difficult to construct general accepted concepts or principles to provide reasonable explanations of higher brain functions and mental activities, such as perception, learning and memory, emotion and consciousness. Therefore, many unanswered questions and debates over the neural encoding and mechanisms of neuronal networks remain. Cell to cell communication by biophotons, also called ultra-weak photon emissions, has been demonstrated in several plants, bacteria and certain animal cells. Recently, both experimental evidence and theoretical speculation have suggested that biophotons may play a potential role in neural signal transmission and processing, contributing to the understanding of the high functions of nervous system. In this paper, we review the relevant experimental findings and discuss the possible underlying mechanisms of biophoton signal transmission and processing in the nervous system.

Social Insects : Ecology and Behavioural Biology

1 online resource; Here is a guide to the ecology of social insects. It is intended for general ecologists and entomologists as well as for undergraduates and those about to start research on social insects; even the experienced investigator may find the comparison between different groups of social insects illuminating. Most technical terms are translated into common language as far as can be done without loss of accuracy but scientific names are unavoidable. Readers will become familiar with the name even though they cannot visualize the animal and could reflect that only a very few of the total species have been studied so far! References too are essential and with these it should be possible to travel more deeply into the vast research literature, still increasing monthly. When I have cited an author in another author's paper, this implies that I have not read the original and the second author must take responsi bility for accuracy! Many hands and heads have helped to make this book. I thank all my colleagues past and present for their enduring though critical support, and I thank with special pleasure: E.]. M. Evesham who fashioned the diagrams;]. Free, D.J. Stradling and]. P.E.C. Darlington who supplied photographs; D.Y. Brian and R.A. Weller who were meticulous on the linguistic side; and G. Frith and R.M. Jones who collated the references. List of plates 1. Fungus combs of Acromyrmex octospinosus and Macrotermes michaelseni. 13 2. Mouthparts of larval Myrmica; 1 Introduction -- 2 Food -- 2.1 Termites as decomposers -- 2.2 Wasps and ants as predators -- 2.3 Sugars as fuel save prey -- 2.4 Seed eaters -- 2.5 Leaf eaters -- 2.6 Pollen eaters -- 3 Foraging by individuals -- 3.1 Foraging strategy -- 3.2 Worker variability -- 4 Foraging in groups -- 4.1 Communication about food -- 4.2 Group slave-raiding -- 4.3 Tunnels and tracks -- 4.4 Nomadic foraging -- 5 Cavity nests and soil mounds -- 5.1 Cavities and burrows -- 5.2 Soil mounds -- 6 Nests of fibre, silk and wax -- 6.1 Mounds of vegetation and tree nests -- 6.2 Combs of cells -- 7 Microclimate -- 7.1 Environmental regulation -- 7.2 Metabolic regulation -- 8 Defence -- 8.1 Painful and paralysing injections -- 8.2 Toxic smears and repellants -- 9 Food processing -- 9.1 Mastication, extraction and regurgitation -- 9.2 Yolk food supplements -- 9.3 Head food glands -- 10 Early population growth -- 10.1 Food distribution -- 10.2 Colony foundation -- 10.3 The growth spurt -- 11 Maturation -- 11.1 Simple models of reproduction -- 11.2 Social control over caste -- 11.3 Males in social Hymenoptera -- 11.4 Maturation in general -- 12 Reproduction -- 12.1 Caste morphogenesis -- 12.2 Copulation and dispersal -- 12.3 Production -- 12.4 Summary -- 13 Evolution of insect societies -- 13.1 Theories of individual selection -- 13.2 Models of these theories -- 13.3 Group selection -- 13.4 Conclusions -- 14 Colonies -- 14.1 The colony barrier -- 14.2 Queen number and species ecology -- 14.3 Queen interaction and queen relatedness -- 15 Comparative ecology of congeneric species -- 15.1 Ant and termite races -- 15.2 Desert ants and termites -- 15.3 Ants and termites in grassland -- 15.4 Forest ants and termites -- 15.5 Wasps and bumblebees -- 15.6 Advanced bees -- 16 Communities -- 16.1 Temperate zone communities in grass and woodland -- 16.2 Desert communities -- 16.3 Tropical rain forest -- 16.4 Conclusions -- 17 Two themes -- 17.1 Plant mutualism -- 17.2 Social organization -- References -- Author index

Self-Organization in Biological Systems

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns—phenomena that have fascinated naturalists for centuries—a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology—a field of study at the forefront of life sciences research.

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A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote

Dexter et al. replicate the disputed, century-old observations of Jennings, confirming by video microscopy and statistical analysis that the single-cell ciliate Stentor roeseli exhibits a hierarchy of avoidance behaviors. They show further that each organism’s decision between contracting and detaching resembles a fair coin toss.