Biological information: why we need a good measure and the challenges ahead

On the fitness of informative cues in complex environments

To be able to deal with uncertainty is of primary importance to most living organisms. When cues provide information about the state of the environment, organisms can use them to respond flexibly. Life forms have evolved complex adaptations and sensory mechanisms to use these environmental cues and extract valuable information about the environment. Previous work has shown a theoretical limit to the amount of fitness benefit possible to be extracted from the cues. We show that the previously used information theoretical approaches can be generalised to scenarios involving any potential relationship between the number of possible phenotypes and environmental states. Such cases are relevant when physiological constraints or complex ecological scenarios lead to the number of environmental states exceeding potential phenotypes. We illustrate cases in which these scenarios can emerge: along environmental gradients, such as geographical transects or complex environments, where organisms adopt different bet-hedging strategies, switching stochastically between phenotypes or developing intermediate ones. In conclusion, we develop an information-theoretic extensible approach for investigating and quantifying fitness in ecological studies.

Life in fluctuating environments

Variability in the environment defines the structure and dynamics of all living systems, from organisms to ecosystems. Species have evolved traits and strategies that allow them to detect, exploit and predict the changing environment. These traits allow organisms to maintain steady internal conditions required for physiological functioning through feedback mechanisms that allow internal conditions to remain at or near a set-point despite a fluctuating environment. In addition to feedback, many organisms have evolved feedforward processes, which allow them to adjust in anticipation of an expected future state of the environment. Here we provide a framework describing how feedback and feedforward mechanisms operating within organisms can generate effects across scales of organization, and how they allow living systems to persist in fluctuating environments. Daily, seasonal and multi-year cycles provide cues that organisms use to anticipate changes in physiologically relevant environmental conditions. Using feedforward mechanisms, organisms can exploit correlations in environmental variables to prepare for anticipated future changes. Strategies to obtain, store and act on information about the conditional nature of future events are advantageous and are evidenced in widespread phenotypes such as circadian clocks, social behaviour, diapause and migrations. Humans are altering the ways in which the environment fluctuates, causing correlations between environmental variables to become decoupled, decreasing the reliability of cues. Human-induced environmental change is also altering sensory environments and the ability of organisms to detect cues. Recognizing that living systems combine feedback and feedforward processes is essential to understanding their responses to current and future regimes of environmental fluctuations.

This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

Innovation: an emerging focus from cells to societies

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability.This article is part of the theme issue 'Process and pattern in innovations from cells to societies'.

Information theory, evolutionary innovations and evolvability

How difficult is it to 'discover' an evolutionary adaptation or innovation? I here suggest that information theory, in combination with high-throughput DNA sequencing, can help answer this question by quantifying a new phenotype's information content. I apply this framework to compute the phenotypic information associated with novel gene regulation and with the ability to use novel carbon sources. The framework can also help quantify how DNA duplications affect evolvability, estimate the complexity of phenotypes and clarify the meaning of 'progress' in Darwinian evolution.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.

Language: A fresh concept to integrate syntactic and semantic information in life sciences

Several fields in biology tend to view the concept of information from one or the other of two extreme positions. Exclusionists base their stance of total rejection on gene-centrism and gene-determinism, typified by the recently-established endo-Darwinist school of life sciences. At the other end of the spectrum, there is total acceptance, as in the newly developed information-centred paradigms that populate biosemiotics. We propose in this paper to split the informational concepts into two irreducible (but linked) poles: the syntactic (concerned with the quantification of the information structure or complexity in a system), and the semantic (concerned with the organization rules and causality weights of interactions in a system). We claim that the past and present uses of the concept could then be classified as various degrees of oscillation between the two poles. The concept of language presents itself as a good tool with which to bridge the syntactic and the semantic poles, combining as it does the form-related and the meaning-related aspects of information, while methodologically supporting formal grammatical models in life sciences. We aim to show, at the same time, that neither of these poles alone can suffice to efficiently and holistically describe, model, and predict natural phenomena.

The information landscape of plant constitutive and induced secondary metabolite production

Resistance against antagonist organisms, such as herbivores, has been identified as a major function of constitutive and stress-inducible production of plant secondary metabolites (PSMs). The mechanism through which constitutive expression and inducibility mediate resistance and, hence physiological and ecological factors that affect their evolution are still little understood. Here I propose information transfer as the least common denominator function of PSM production. In this framework constitutively produced PSMs represent the first line of defense through functioning as toxins, cues associated with toxicity and as detractants that interfere with antagonist host-search patterns. Information made available and utilizable by inducibility of secondary metabolite production allows plants to include the associated biological communities to cope with antagonists and to more efficiently target a specific attacker.

Modelling biological evolution: recent progress, current challenges and future direction

Mathematical modelling is widely recognized as a powerful and convenient theoretical tool for investigating various aspects of biological evolution and explaining the existing genetic complexity of the real world. It is increasingly apparent that understanding the key mechanisms involved in the processes of species biodiversity, natural selection and inheritance, patterns of animal behaviour and coevolution of species in complex ecological systems is simply impossible by means of laboratory experiments and field observations alone. Mathematical models are so important because they provide wide-ranging exploration of the problem without a need for experiments with biological systems—which are usually expensive, often require long time and can be potentially dangerous. However, as the number of theoretical works on modelling biological evolution is constantly accelerating each year as different mathematical frameworks and various aspects of evolutionary problems are considered, it is often hard to avoid getting lost in such an immense flux of publications. The aim of this issue of Interface Focus is to provide a useful guide to important recent findings in some key areas in modelling biological evolution, to refine the existing challenges and to outline possible future directions. In particular, the following topics are addressed here by world-leading experts in the modelling of evolution: (i) the origins of biodiversity observed in ecosystems and communities; (ii) evolution of decision-making by animals and the optimal strategy of populations; (iii) links between evolutionary and ecological processes across different time scales; (iv) quantification of biological information in evolutionary models; and (v) linking theoretical models with empirical data. Most of the works presented here are in fact contributed papers from the international conference ‘Modelling Biological Evolution’ (MBE 2013), which took place in Leicester, UK, in May 2013 and brought together theoreticians and empirical evolutionary biologists with the main aim of creating debates and productive discussions between them. Finally, we should emphasize that the individual papers in this issue are not limited to only one of the topics mentioned above, but often lie at the interface of them.