Pan-Evo: The Evolution of Information and Biology's Part in This

Many people wonder whether biology, including humans, will benefit or experience harm from new developments in information such as artificial intelligence (AI). Here, it is proposed that biological and non-biological information might be components of a unified process, 'Panevolution' or 'Pan-Evo', based on four basic operations-innovation, transmission, adaptation, and movement. Pan-Evo contains many types of variable objects, from molecules to ecosystems. Biological innovation includes mutations and behavioural changes; non-biological innovation includes naturally occurring physical innovations and innovation in software. Replication is commonplace in and outside biology, including autocatalytic chemicals and autonomous software replication. Adaptation includes biological selection, autocatalytic chemicals, and 'evolutionary programming', which is used in AI. The extension of biological speciation to non-biological information creates a concept called 'Panspeciation'. Panevolution might benefit or harm biology, but the harm might be minimal if AI and humans behave intelligently because humans and the machines in which an AI resides might split into vastly different environments that suit them. That is a possible example of Panspeciation and would be the first speciation event involving humans for thousands of years. This event will not be particularly hostile to humans if humans learn to evaluate information and cooperate better to minimise both human stupidity and artificial simulated stupidity (ASS-a failure of AI).

Species diversity and interspecific information flow

Interspecific information flow is known to affect individual fitness, population dynamics and community assembly, but there has been less study of how species diversity affects information flow and thereby ecosystem functioning and services. We address this question by first examining differences among species in the sensitivity, accuracy, transmissibility, detectability and value of the cues and signals they produce, and in how they receive, store and use information derived from heterospecifics. We then review how interspecific information flow occurs in communities, involving a diversity of species and sensory modes, and how this flow can affect ecosystem-level functions, such as decomposition, seed dispersal or algae removal on coral reefs. We highlight evidence that some keystone species are particularly critical as a source of information used by eavesdroppers, and so have a disproportionate effect on information flow. Such keystone species include community informants producing signals, particularly about predation risk, that influence other species' landscapes of fear, and aggregation initiators creating cues or signals about resources. We suggest that the presence of keystone species means that there will likely be a positive relationship in many communities between species diversity and information through a 'sampling effect', in which larger pools of species are more likely to include the keystone species by chance. We then consider whether the number and relative abundance of species, irrespective of the presence of keystone species, matter to interspecific information flow; on this issue, the theory is less developed, and the evidence scant and indirect. Higher diversity could increase the quantity or quality of information that is used by eavesdroppers because redundancy increases the reliability of information or because the species provide complementary information. Alternatively, there could be a lack of a relationship between species diversity and information if there is widespread information parasitism where users are not sources, or if information sourced from heterospecifics is of lower value than that gained personally or sourced from conspecifics. Recent research suggests that species diversity does have information-modulated community and ecosystem consequences, especially in birds, such as the diversity of species at feeders increasing resource exploitation, or the number of imitated species increasing responses to vocal mimics. A first step for future research includes comprehensive observations of information flow among different taxa and habitats. Then studies should investigate whether species diversity influences the cumulative quality or quantity of information at the community level, and consequently ecosystem-level processes. An applied objective is to conserve species in part for their value as sources of information for other species, including for humans.

Eutrophication-driven infochemical dimethylsulfide accelerates carbon transfer in freshwater food chain

Dimethylsulfide (DMS) is a major organic sulfide in aquatic ecosystems and an infochemical that is considered as a key predictor of changes in energy and material fluxes and stocks. It is largely unknown how DMS changes and affects the food webs and material cycles in eutrophicated freshwater. In this study, field monitoring and literature surveys were conducted to analyze the effects of eutrophication on DMS concentrations. Daphnia-zebrafish microcosms were then used to investigate the effects of DMS concentrations on carbon transfer. The results demonstrated that the concentration of DMS was increased by eutrophication related indicators (chlorophyll and phosphorus). Eutrophication driven DMS altered carbon transfer in the freshwater food chain. Low concentrations (0.1-1 nM) of DMS promoted the predation of daphnia by zebrafish compared to the 0.01 nM DMS, which further stimulated the total carbon transfer from daphnia to zebrafish and altered the dissolved organic carbon (DOC) distribution in water. High concentrations (10-100 nM) of DMS did not alter zebrafish predation on daphnia and carbon transfer. DOC excreted by zebrafish altered carbon emission potential, and DMS in water showed a unimodal relationship with the carbon emission potential, peaking at 0.40 nM DMS. Keeping the DMS in water at 1.82 nM may maintain a lower carbon emission potential. These results improved the understanding of the effects of eutrophication on DMS, demonstrated the ecological role of DMS on freshwater fish and the carbon cycle, estimated the effects of DMS on the carbon emission potential of fish, and offered new insights into the management of eutrophication.

Information Ecology: an integrative framework for studying animal behavior

Information is simultaneously a valuable resource for animals and a tractable variable for researchers. We propose the name Information Ecology to describe research focused on how individual animals use information to enhance fitness. An explicit focus on information in animal behavior is far from novel - we simply build on these ideas and promote a unified approach to how and why animals use information. The value of information to animals favors the theoretically rich adaptive approach of field-based research. Simultaneously, our ability to manipulate information lends itself to the strong methods of laboratory-based research. Information Ecology asks three questions: What information is available? How is it used (or not)? And, why is it used (or not)?

The fitness value of ecological information in a variable world

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for 'fitness value of information' (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Ecological and evolutionary consequences of selective interspecific information use

Recent work has shown that animals frequently use social information from individuals of their own species as well as from other species; however, the ecological and evolutionary consequences of this social information use remain poorly understood. Additionally, information users may be selective in their social information use, deciding from whom and how to use information, but this has been overlooked in an interspecific context. In particular, the intentional decision to reject a behaviour observed via social information has received less attention, although recent work has indicated its presence in various taxa. Based on existing literature, we explore in which circumstances selective interspecific information use may lead to different ecological and coevolutionary outcomes between two species, such as explaining observed co-occurrences of putative competitors. The initial ecological differences and the balance between the costs of competition and the benefits of social information use potentially determine whether selection may lead to trait divergence, convergence or coevolutionary arms race between two species. We propose that selective social information use, including adoption and rejection of behaviours, may have far-reaching fitness consequences, potentially leading to community-level eco-evolutionary outcomes. We argue that these consequences of selective interspecific information use may be much more widespread than has thus far been considered.

Quantifying chemodiversity considering biochemical and structural properties of compounds with the R package chemodiv

Plants produce large numbers of phytochemical compounds affecting plant physiology and interactions with their biotic and abiotic environment. Recently, chemodiversity has attracted considerable attention as an ecologically and evolutionary meaningful way to characterize the phenotype of a mixture of phytochemical compounds. Currently used measures of phytochemical diversity, and related measures of phytochemical dissimilarity, generally do not take structural or biosynthetic properties of compounds into account. Such properties can be indicative of the compounds' function and inform about their biosynthetic (in)dependence, and should therefore be included in calculations of these measures. We introduce the R package chemodiv, which retrieves biochemical and structural properties of compounds from databases and provides functions for calculating and visualizing chemical diversity and dissimilarity for phytochemicals and other types of compounds. Our package enables calculations of diversity that takes the richness, relative abundance and - most importantly - structural and/or biosynthetic dissimilarity of compounds into account. We illustrate the use of the package with examples on simulated and real datasets. By providing the R package chemodiv for quantifying multiple aspects of chemodiversity, we hope to facilitate investigations of how chemodiversity varies across levels of biological organization, and its importance for the ecology and evolution of plants and other organisms.

Understanding emerging patterns and dynamics through the lenses of the cyber-physical universe

The complex interaction among contemporary techno- and socio-economic processes has set the stage for the emergence of a cyber-physical universe, the novel landscape in which agents behave and interact, and which is centered on the fundamental role played by information and computation at all levels. In this paper, we weave into a single analysis the different threads that lead to (and characterize) the cyber-physical universe and outline a map of its building blocks and the complex dynamics at work in the new environment. The resulting description is used to assess how decision-making processes should evolve in order to be able to address the opportunities and challenges of the current era of deep and extended changes. The analysis offers an encompassing interpretative grid to understand and unpack patterns in the contemporary socio-technical systems that experience a fundamental informational turn; this can inform new research trajectories and help open up new areas for scientific inquiry.

This paper proposes a new organizing concept—the cyber-physical universe—to describe the current overarching socio-technical-economic landscape. The cyber-physical universe is the result of information technology permeating every aspect of reality and blurring the boundaries between the physical and digital domains, at different scales, a process that changed in a fundamental manner the logic and rules of evolution of contemporary socio-economic and techno-scientific systems. By outlining the steps that lead historically to the cyber-physical universe, as well as its properties and the dynamics it enables or influences, we are able to shed a light on the higher-level “machinery” within which humans act and science (including data science) develops. In particular, we trace the path of decision-making augmentation culminating in the use of artificial intelligence technologies. As a map of the current landscape, we posit that the cyber-physical universe can help direct scientific exploration, production strategies, and decision making more generally. The analysis we conduct is useful as it offers an encompassing interpretative grid and basic principles to understand and unpack patterns in systems that experience a fundamental informational turn; this can inform new research trajectories and help open up new areas for scientific inquiry.

Glucocorticoid receptor expression as an integrative measure to assess glucocorticoid plasticity and efficiency in evolutionary endocrinology: A perspective

Organisms have to cope with the changes that take place in their environment in order to keep their physical and psychological stability. In vertebrates, the hypothalamic-pituitary-adrenal (HPA) axis plays a key role in mediating phenotypic adjustments to environmental changes, primarily by regulating glucocorticoids (GCs). Although circulating GCs have widely been used as proxy for individual health and fitness, our understanding of HPA regulation is still very limited, especially in free-living animals. Circulating GCs only exert their actions when they are bound to receptors, and therefore, GC receptors play a pivotal role mediating HPA regulation and GC downstream phenotypic changes. Because under challenging conditions GC actions (as well as negative feedback activation) occur mainly through binding to low-affinity glucocorticoid receptors (GR), we propose that GR activity, and in particular GR expression, may play a crucial role in GC regulation and dynamics, and be ultimately related to organismal capacity to appropriately respond to environmental changes. Thus, we suggest that GR expression will provide more comprehensive information of GC variation and function. To support this idea, we compile previous evidence demonstrating the fundamental role of GR on GC responses and the fine-tuning of circulating GCs. We also make predictions about the phenotypic differences in GC responsiveness - and ultimately HPA regulation capacity - associated with differences in GR expression, focusing on GC plasticity and efficiency. Finally, we discuss current priorities and limitations of integrating measures of GR expression into evolutionary endocrinology and ecology studies, and propose further research directions towards the use of GR expression and the study of the mechanisms regulating GR activity to gather information on coping strategies and stress resilience. Our goals are to provide an integrative perspective that will prompt reconsideration on the ecological and physiological interpretation of current GC measurements, and motivate further research on the role of GR in tuning individual responses to dynamic environments.

Information theory in vertebrate stress physiology

Information theory has been applied productively across biology, but it has been used minimally in endocrinology. Here, we advocate for the integration of information theory into stress endocrinology. Presently, the majority of models of stress center on the regulation of hormone concentrations, even though what interests most endocrinologists and matters in terms of individual health and evolutionary fitness is the information content of hormones. In neuroscience, the free energy principle, a concept offered to explain how the brain infers current and future states of the environment, could be a guide for resolving how information is instantiated in hormones such as the glucocorticoids. Here, we offer several ideas and promising options for research addressing how hormones encode and cells respond to information in glucocorticoids.

Untangling the complexity of priority effects in multispecies communities

The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this framework, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of history-dependent community assembly.

Reintegrating Biology Through the Nexus of Energy, Information, and Matter

Information, energy, and matter are fundamental properties of all levels of biological organization, and life emerges from the continuous flux of matter, energy, and information. This perspective piece defines and explains each of the three pillars of this nexus. We propose that a quantitative characterization of the complex interconversions between matter, energy, and information that comprise this nexus will help us derive biological insights that connect phenomena across different levels of biological organization. We articulate examples from multiple biological scales that highlight how this nexus approach leads to a more complete understanding of the biological system. Metrics of energy, information, and matter can provide a common currency that helps link phenomena across levels of biological organization. The propagation of energy and information through levels of biological organization can result in emergent properties and system-wide changes that impact other hierarchical levels. Deeper consideration of measured imbalances in energy, information, and matter can help researchers identify key factors that influence system function at one scale, highlighting avenues to link phenomena across levels of biological organization and develop predictive models of biological systems.

Disentangling the Information in Species Interaction Networks

Shannon's entropy measure is a popular means for quantifying ecological diversity. We explore how one can use information-theoretic measures (that are often called indices in ecology) on joint ensembles to study the diversity of species interaction networks. We leverage the little-known balance equation to decompose the network information into three components describing the species abundance, specificity, and redundancy. This balance reveals that there exists a fundamental trade-off between these components. The decomposition can be straightforwardly extended to analyse networks through time as well as space, leading to the corresponding notions for alpha, beta, and gamma diversity. Our work aims to provide an accessible introduction for ecologists. To this end, we illustrate the interpretation of the components on numerous real networks. The corresponding code is made available to the community in the specialised Julia package EcologicalNetworks.jl.

FKBP5: A Key Mediator of How Vertebrates Flexibly Cope with Adversity

Flexibility in the regulation of the hypothalamic–pituitary–adrenal (HPA) axis is an important mediator of stress resilience as it helps organisms adjust to, avoid, or compensate for acute and chronic challenges across changing environmental contexts. Glucocorticoids remain the favorite metric from medicine to conservation biology to attempt to quantify stress resilience despite the skepticism around their consistency in relation to individual health, welfare, and fitness. We suggest that a cochaperone molecule related to heat shock proteins and involved in glucocorticoid receptor activity, FKBP5, may mediate HPA flexibility and therefore stress resilience because it affects how individuals can regulate glucocorticoids and therefore capacitates their abilities to adjust phenotypes appropriately to prevailing, adverse conditions. Although the molecule is well studied in the biomedical literature, FKBP5 research in wild vertebrates is limited. In the present article, we highlight the potential major role of FKBP5 as mediator of HPA axis flexibility in response to adversity in humans and lab rodents.

Converting Ecological Currencies: Energy, Material, and Information Flows

Understanding how the three currencies of life - energy, material, and information - interact is a key step towards synthesis in ecology and evolution. However, current theory focuses on the role of matter as a resource and energy, and typically ignores how the same matter can have other important effects as a carrier of information or modifier of the environment. Here we present the hypothesis that the dynamic conversion of matter by organisms among its three currencies mediates the structure and function of ecosystems, and that these effects can even supersede the effects of matter as a resource. Humans are changing the information in the environment and this is altering species interactions and flows of matter within and among ecosystems.

Life's Energy and Information: Contrasting Evolution of Volume- versus Surface-Specific Rates of Energy Consumption

As humanity struggles to find a path to resilience amidst global change vagaries, understanding organizing principles of living systems as the pillar for human existence is rapidly growing in importance. However, finding quantitative definitions for order, complexity, information and functionality of living systems remains a challenge. Here, we review and develop insights into this problem from the concept of the biotic regulation of the environment developed by Victor Gorshkov (1935-2019). Life's extraordinary persistence-despite being a strongly non-equilibrium process-requires a quantum-classical duality: the program of life is written in molecules and thus can be copied without information loss, while life's interaction with its non-equilibrium environment is performed by macroscopic classical objects (living individuals) that age. Life's key energetic parameter, the volume-specific rate of energy consumption, is maintained within universal limits by most life forms. Contrary to previous suggestions, it cannot serve as a proxy for "evolutionary progress". In contrast, ecosystem-level surface-specific energy consumption declines with growing animal body size in stable ecosystems. High consumption by big animals is associated with instability. We suggest that the evolutionary increase in body size may represent a spontaneous loss of information about environmental regulation, a manifestation of life's algorithm ageing as a whole.

Proteomics and Metaproteomics Add Functional, Taxonomic and Biomass Dimensions to Modeling the Ecosystem at the Mucosal-luminal Interface

Recent efforts in gut microbiome studies have highlighted the importance of explicitly describing the ecological processes beyond correlative analysis. However, we are still at the early stage of understanding the organizational principles of the gut ecosystem, partially because of the limited information provided by currently used analytical tools in ecological modeling practices. Proteomics and metaproteomics can provide a number of insights for ecological studies, including biomass, matter and energy flow, and functional diversity. In this Mini Review, we discuss proteomics and metaproteomics-based experimental strategies that can contribute to studying the ecology, in particular at the mucosal-luminal interface (MLI) where the direct host-microbiome interaction happens. These strategies include isolation protocols for different MLI components, enrichment methods to obtain designated array of proteins, probing for specific pathways, and isotopic labeling for tracking nutrient flow. Integration of these technologies can generate spatiotemporal and site-specific biological information that supports mathematical modeling of the ecosystem at the MLI.

Thermodynamics in Ecology-An Introductory Review

How to predict the evolution of ecosystems is one of the numerous questions asked of ecologists by managers and politicians. To answer this we will need to give a scientific definition to concepts like sustainability, integrity, resilience and ecosystem health. This is not an easy task, as modern ecosystem theory exemplifies. Ecosystems show a high degree of complexity, based upon a high number of compartments, interactions and regulations. The last two decades have offered proposals for interpretation of ecosystems within a framework of thermodynamics. The entrance point of such an understanding of ecosystems was delivered more than 50 years ago through Schrödinger's and Prigogine's interpretations of living systems as "negentropy feeders" and "dissipative structures", respectively. Combining these views from the far from equilibrium thermodynamics to traditional classical thermodynamics, and ecology is obviously not going to happen without problems. There seems little reason to doubt that far from equilibrium systems, such as organisms or ecosystems, also have to obey fundamental physical principles such as mass conservation, first and second law of thermodynamics. Both have been applied in ecology since the 1950s and lately the concepts of exergy and entropy have been introduced. Exergy has recently been proposed, from several directions, as a useful indicator of the state, structure and function of the ecosystem. The proposals take two main directions, one concerned with the exergy stored in the ecosystem, the other with the exergy degraded and entropy formation. The implementation of exergy in ecology has often been explained as a translation of the Darwinian principle of "survival of the fittest" into thermodynamics. The fittest ecosystem, being the one able to use and store fluxes of energy and materials in the most efficient manner. The major problem in the transfer to ecology is that thermodynamic properties can only be calculated and not measured. Most of the supportive evidence comes from aquatic ecosystems. Results show that natural and culturally induced changes in the ecosystems, are accompanied by a variations in exergy. In brief, ecological succession is followed by an increase of exergy. This paper aims to describe the state-of-the-art in implementation of thermodynamics into ecology. This includes a brief outline of the history and the derivation of the thermodynamic functions used today. Examples of applications and results achieved up to now are given, and the importance to management laid out. Some suggestions for essential future research agendas of issues that needs resolution are given.

Information arms race explains plant-herbivore chemical communication in ecological communities

Plants emit an extraordinary diversity of chemicals that provide information about their identity and mediate their interactions with insects. However, most studies of this have focused on a few model species in controlled environments, limiting our capacity to understand plant-insect chemical communication in ecological communities. Here, by integrating information theory with ecological and evolutionary theories, we show that a stable information structure of plant volatile organic compounds (VOCs) can emerge from a conflicting information process between plants and herbivores. We corroborate this information "arms race" theory with field data recording plant-VOC associations and plant-herbivore interactions in a tropical dry forest. We reveal that plant VOC redundancy and herbivore specialization can be explained by a conflicting information transfer. Information-based communication approaches can increase our understanding of species interactions across trophic levels.

Self-organizing cicada choruses respond to the local sound and light environment

Periodical cicadas exhibit an extraordinary capacity for self-organizing spatially synchronous breeding behavior. The regular emergence of periodical cicada broods across the United States is a phenomenon of longstanding public and scientific interest, as the cicadas of each brood emerge in huge numbers and briefly dominate their ecosystem. During the emergence, the 17-year periodical cicada species Magicicada cassini is found to form synchronized choruses, and we investigated their chorusing behavior from the standpoint of spatial synchrony.Cicada choruses were observed to form in trees, calling regularly every five seconds. In order to determine the limits of this self-organizing behavior, we set out to quantify the spatial synchronization between cicada call choruses in different trees, and how and why this varies in space and time.We performed 20 simultaneous recordings in Clinton State Park, Kansas, in June 2015 (Brood IV), with a team of citizen-science volunteers using consumer equipment (smartphones). We use a wavelet approach to show in detail how spatially synchronous, self-organized chorusing varies across the forest.We show how conditions that increase the strength of audio interactions between cicadas also increase the spatial synchrony of their chorusing. Higher forest canopy light levels increase cicada activity, corresponding to faster and higher-amplitude chorus cycling and to greater synchrony of cycles across space. We implemented a relaxation-oscillator-ensemble model of interacting cicadas, finding that a tendency to call more often, driven by light levels, results in all these effects.Results demonstrate how the capacity to self-organize in ecology depends sensitively on environmental conditions. Spatially correlated modulation of cycling rate by an external driver can also promote self-organization of phase synchrony.

Effects of Fish Predators on the Mass-Related Energetics of a Keystone Freshwater Crustacean

Little is known about how predators or their cues affect the acquisition and allocation of energy throughout the ontogeny of prey organisms. To address this question, we have been comparing the ontogenetic body-mass scaling of various traits related to energy intake and use between populations of a keystone amphipod crustacean inhabiting freshwater springs, with versus without fish predators. In this progress report, we analyze new and previously reported data to develop a synthetic picture of how the presence/absence of fish predators affects the scaling of food assimilation, fat content, metabolism, growth and reproduction in populations of Gammarus minus located in central Pennsylvania (USA). Our analysis reveals two major clusters of ‘symmorphic allometry’ (parallel scaling relationships) for traits related to somatic versus reproductive investment. In the presence of fish predators, the scaling exponents for somatic traits tend to decrease, whereas those for reproductive traits tend to increase. This divergence of scaling exponents reflects an intensified trade-off between somatic and reproductive investments resulting from low adult survival in the face of size-selective predation. Our results indicate the value of an integrated view of the ontogenetic size-specific energetics of organisms and its response to both top-down (predation) and bottom-up (resource supply) effects.