THE MEASUREMENT THEORY OF FITNESS

In this article, an approach to measure fitness is proposed that considers fitness as a measure of competitive ability among phenotypes or genotypes. This approach is based on pairwise competition tests and is related to measures of “utility” in mathematical economics. Extending the results from utility theory it is possible to recover the classical Wrightian fitness measure without reference to models of population growth. A condition, quasi‐BTL, similar to the Bradley–Terry–Luce condition of classical utility theory is shown to be necessary for the existence of frequency and context‐independent fitness measures. Testing for violations of this quasi‐BTL condition can be used to the detect genotype‐by‐genotype interactions and frequency‐dependent fitness. A method for the detection of genotype by environment interactions is proposed that avoids potential scaling artifacts. Furthermore the measurement theoretical approach allows one to derive Wright's selection equation. This shows that classical selection equations are entirely general and exact. It is concluded that measurement theory is able to give definite answers to a number theoretical and practical questions. For instance, this theory identifies the correct scale for measuring gene interaction with respect to fitness and shows that different scales may lead to wrong conclusions.     

Scale relativity theory and integrative systems biology: 2. Macroscopic quantum-type mechanics

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, which aims at describing the effects of a non-differentiable and fractal (i.e., explicitly scale dependent) geometry of space–time. The first paper of this series was devoted, in this new framework, to the construction from first principles of scale laws of increasing complexity, and to the discussion of some tentative applications of these laws to biological systems. In this second review and perspective paper, we describe the effects induced by the internal fractal structures of trajectories on motion in standard space. Their main consequence is the transformation of classical dynamics into a generalized, quantum-like self-organized dynamics. A Schrödinger-type equation is derived as an integral of the geodesic equation in a fractal space. We then indicate how gauge fields can be constructed from a geometric re-interpretation of gauge transformations as scale transformations in fractal space–time. Finally, we introduce a new tentative development of the theory, in which quantum laws would hold also in scale space, introducing complexergy as a measure of organizational complexity. Initial possible applications of this extended framework to the processes of morphogenesis and the emergence of prokaryotic and eukaryotic cellular structures are discussed. Having founded elements of the evolutionary, developmental, biochemical and cellular theories on the first principles of scale relativity theory, we introduce proposals for the construction of an integrative theory of life and for the design and implementation of novel macroscopic quantum-type experiments and devices, and discuss their potential applications for the analysis, engineering and management of physical and biological systems and properties, and the consequences for the organization of transdisciplinary research and the scientific curriculum in the context of the SYSTEMOSCOPE Consortium research and development agenda.     

Dynamic equilibrium of reconstituting hematopoietic stem cell populations

Clonal dominance in hematopoietic stem cell populations is an important question of interest but not one we can directly answer. Any estimates are based on indirect measurement. For marked populations, we can equate empirical and theoretical moments for binomial sampling, in particular we can use the well-known formula for the sampling variation of a binomial proportion. The empirical variance itself cannot always be reliably estimated and some caution is needed. We describe the difficulties here and identify ready solutions which only require appropriate use of variance-stabilizing transformations. From these we obtain estimators for the steady state, or dynamic equilibrium, of the number of hematopoietic stem cells involved in repopulating the marrow. The calculations themselves are not too involved. We give the distribution theory for the estimator as well as simple approximations for practical application. As an illustration, we rework on data recently gathered to address the question as to whether or not reconstitution of marrow grafts in the clinical setting might be considered to be oligoclonal.     

Challenging the classical notion of time in cognition: a quantum perspective

All mental representations change with time. A baseline intuition is that mental representations have specific values at different time points, which may be more or less accessible, depending on noise, forgetting processes, etc. We present a radical alternative, motivated by recent research using the mathematics from quantum theory for cognitive modelling. Such cognitive models raise the possibility that certain possibilities or events may be incompatible, so that perfect knowledge of one necessitates uncertainty for the others. In the context of time-dependence, in physics, this issue is explored with the so-called temporal Bell (TB) or Leggett–Garg inequalities. We consider in detail the theoretical and empirical challenges involved in exploring the TB inequalities in the context of cognitive systems. One interesting conclusion is that we believe the study of the TB inequalities to be empirically more constrained in psychology than in physics. Specifically, we show how the TB inequalities, as applied to cognitive systems, can be derived from two simple assumptions: cognitive realism and cognitive completeness. We discuss possible implications of putative violations of the TB inequalities for cognitive models and our understanding of time in cognition in general. Overall, this paper provides a surprising, novel direction in relation to how time should be conceptualized in cognition.     

A general model for ontogenetic growth under food restriction

Food restriction (FR) retards animals' growth. Understanding the underlying mechanisms of this phenomenon is important to conceptual problems in life-history theory, as well as to applied problems in animal husbandry and biomedicine. Despite a considerable amount of empirical data published since the 1930s, there is no relevant general theoretical framework that predicts how animals vary their energy budgets and life-history traits under FR. In this paper, we develop such a general quantitative model based on fundamental principles of metabolic energy allocation during ontogeny. This model predicts growth curves under varying conditions of FR, such as the compensatory growth, different age at which FR begins, its degree and its duration. Our model gives a quantitative explanation for the counterintuitive phenomenon that under FR, lower body temperature and lower metabolism lead to faster growth and larger adult size. This model also predicts that the animals experiencing FR reach the same fraction of their adult mass at the same age as their ad libitum counterparts. All predictions are well supported by empirical data from mammals and birds of varying body size, under different conditions of FR.     

Natural selection can favour ‘irrational’ behaviour

Understanding decisions is the fundamental aim of the behavioural sciences. The theory of rational choice is based on axiomatic principles such as transitivity and independence of irrelevant alternatives (IIA). Empirical studies have demonstrated that the behaviour of humans and other animals often seems irrational; there can be a lack of transitivity in choice and seemingly irrelevant alternatives can alter decisions. These violations of transitivity and IIA undermine rational choice theory. However, we show that an individual that is maximizing its rate of food gain can exhibit failure of transitivity and IIA. We show that such violations can be caused because a current option may disappear in the near future or a better option may reappear soon. Current food options can be indicative of food availability in the near future, and this key feature can result in apparently irrational behaviour.     

Medical professionalism and the social contract

Conceptions of professionalism in medicine draw on social contract theory; its strengths and weaknesses play out in how we reason about professionalism. The social contract metaphor may be a heuristic device prompting reflection on social responsibility, and as such is appealing: it encourages reasoning about privilege and responsibility, the broader context and consequences of action, and diverse perspectives on medical practice. However, when this metaphor is elevated to the status of a theory, it has well-known limits: the assumed subject position of contractors engenders blind spots about privilege, not critical reflection; its tendency to dress up the status quo in the trappings of a theoretical agreement may limit social negotiation; its attempted reconciliation of social obligation and self-interest fosters the view that ethics and self-interest should coincide; it sets up false expectations by identifying appearance and reality in morality; and its construal of prima facie duties as conditional misdirects ethical attention in particular situations from current needs to supposed past agreements or reciprocities. Using philosophical ideas as heuristic devices in medical ethics is inevitable, but we should be conscious of their limitations. When they limit the ethical scope of debate, we should seek new metaphors.     

The genetic architecture of hybrid incompatibilities and their effect on barriers to introgression in secondary contact

Genetic incompatibilities are an important component of reproductive isolation. Although theoretical studies have addressed their evolution, little is known about their maintenance when challenged by potentially high migration rates in secondary contact. Although theory predicts that recombination can erode barriers, many empirical systems have been found to retain species‐specific differences despite substantial gene flow. By simulating whole genomes in individuals of hybridizing species, we find that the genetic architecture of two contrasting models of epistatic hybrid incompatibilities and the context of hybridization can substantially affect species integrity and genomic heterogeneity. In line with theory, our results show that intergenomic incompatibilities break down rapidly by recombination, but can maintain genome‐wide differentiation under very limited conditions. By contrast, intragenomic interactions that arise from genetic pathways can maintain species‐specific differences even with high migration rates and gene flow, whereas introgression at large parts of the genome can simultaneously remain extensive, consistent with empirical observations. We discuss the importance of intragenomic interactions in speciation and consider how this form of epistatic fitness variation is implicated and supported by other theoretical and empirical studies. We further address the relevance of replicates and knowledge of context when investigating the genomics of speciation.     

Are aposematic signals honest? A review

We explore the relevance of honest signalling theory to the evolution of aposematism. We begin with a general consideration of models of signal stability, with a focus on the Zahavian costly signalling framework. Next, we review early models of signalling in the context of aposematism (some that are consistent and some inconsistent with costly honest signalling). We focus on controversies surrounding the idea that aposematic signals are handicaps in a Zahavian framework. Then, we discuss how the alignment of interests between signaller and predator influences the evolution of aposematism, highlight the distinction between qualitative and quantitative honesty and review theory and research relevant to these categories. We also review recent theoretical treatments of the evolution of aposematism that have focused on honest signalling as well as empirical research on a variety of organisms, including invertebrates and frogs. Finally, we discuss future directions for empirical and theoretical research in this area.     

Graphical integrity issues in open access publications: Detection and patterns of proportional ink violations

Academic graphs are essential for communicating complex scientific ideas and results. To ensure that these graphs truthfully reflect underlying data and relationships, visualization researchers have proposed several principles to guide the graph creation process. However, the extent of violations of these principles in academic publications is unknown. In this work, we develop a deep learning-based method to accurately measure violations of the proportional ink principle (AUC = 0.917), which states that the size of shaded areas in graphs should be consistent with their corresponding quantities. We apply our method to analyze a large sample of bar charts contained in 300K figures from open access publications. Our results estimate that 5% of bar charts contain proportional ink violations. Further analysis reveals that these graphical integrity issues are significantly more prevalent in some research fields, such as psychology and computer science, and some regions of the globe. Additionally, we find no temporal and seniority trends in violations. Finally, apart from openly releasing our large annotated dataset and method, we discuss how computational research integrity could be part of peer-review and the publication processes.     

On mathematical modelling of insect flight dynamics in the context of micro air vehicles

We discuss some aspects of mathematical modelling relevant to the dynamics of insect flight in the context of insect-like flapping-wing micro air vehicles (MAVs). MAVs are small flying vehicles developed to reconno?tre in confined spaces. This requires power-efficient, highly-manoeuvrable, low-speed flight with stable hover. All of these attributes are present in insect flight and hence the focus on reproducing the functionality of insect flight by engineering means. Empirical research on insect flight dynamics is limited by experimental difficulties. Force and moment measurements require tethering the animal whose behaviour may then differ from free flight. The measurements are made when the insect actively tries to control its flight, so that its open-loop dynamics cannot be observed. Finally, investigation of the sensory-motor system responsible for flight is even more challenging. Despite these difficulties, much empirical progress has been made recently. Further progress, especially in the context of MAVs, can be achieved by the complementary information derived from appropriate mathematical modelling. The focus here is on a means of computing the data not easily available from experiments and also on making mathematical predictions to suggest new experiments. We consider two aspects of mathematical modelling for insect flight dynamics. The first one is theoretical (computational), as opposed to empirical, generation of the aerodynamic data required for the six-degrees-of-freedom equations of motion. For this purpose we first explain insect wing kinematics and the salient features of the corresponding flow. In this context, we show that aerodynamic modelling is a feasible option for certain flight regimes, focusing on a successful example of modelling hover. Such modelling progresses from the first principles of fluid mechanics, but relies on simplifications justified by the known flow phenomenology and/or geometric and kinematic symmetries. This is relevant to six types of fundamental manoeuvres, which we define as those flight conditions for which only one component of the translational and rotational body velocities is nonzero and constant. The second aspect of mathematical modelling for insect flight dynamics addressed here deals with the periodic character of the aerodynamic force and moment production. This leads to consideration of the types of solutions of nonlinear equations forced by nonlinear oscillations. In particular, the mechanism of synchronization seems relevant and should be investigated further.     

A spatial theory for emergent multiple predator–prey interactions in food webs

Predator–prey interaction is inherently spatial because animals move through landscapes to search for and consume food resources and to avoid being consumed by other species. The spatial nature of species interactions necessitates integrating spatial processes into food web theory and evaluating how predators combine to impact their prey. Here, we present a spatial modeling approach that examines emergent multiple predator effects on prey within landscapes. The modeling is inspired by the habitat domain concept derived from empirical synthesis of spatial movement and interactions studies. Because these principles are motivated by synthesis of short‐term experiments, it remains uncertain whether spatial contingency principles hold in dynamical systems. We address this uncertainty by formulating dynamical systems models, guided by core habitat domain principles, to examine long‐term multiple predator–prey spatial dynamics. To describe habitat domains, we use classical niche concepts describing resource utilization distributions, and assume species interactions emerge from the degree of overlap between species. The analytical results generally align with those from empirical synthesis and present a theoretical framework capable of demonstrating multiple predator effects that does not depend on the small spatial or temporal scales typical of mesocosm experiments, and help bridge between empirical experiments and long‐term dynamics in natural systems.     

For flux's sake: General considerations for energy‐flux calculations in ecological communities

Global change alters ecological communities with consequences for ecosystem processes. Such processes and functions are a central aspect of ecological research and vital to understanding and mitigating the consequences of global change, but also those of other drivers of change in organism communities. In this context, the concept of energy flux through trophic networks integrates food‐web theory and biodiversity‐ecosystem functioning theory and connects biodiversity to multitrophic ecosystem functioning. As such, the energy‐flux approach is a strikingly effective tool to answer central questions in ecology and global‐change research. This might seem straight forward, given that the theoretical background and software to efficiently calculate energy flux are readily available. However, the implementation of such calculations is not always straight forward, especially for those who are new to the topic and not familiar with concepts central to this line of research, such as food‐web theory or metabolic theory. To facilitate wider use of energy flux in ecological research, we thus provide a guide to adopting energy‐flux calculations for people new to the method, struggling with its implementation, or simply looking for background reading, important resources, and standard solutions to the problems everyone faces when starting to quantify energy fluxes for their community data. First, we introduce energy flux and its use in community and ecosystem ecology. Then, we provide a comprehensive explanation of the single steps towards calculating energy flux for community data. Finally, we discuss remaining challenges and exciting research frontiers for future energy‐flux research.     

Do we need a ‘theory’ of development?

Edited by Alessandro Minelli and Thomas Pradeu, Towards a Theory of Development gathers essays by biologists and philosophers, which display a diversity of theoretical perspectives. The discussions not only cover the state of art, but broaden our vision of what development includes and provide pointers for future research. Interestingly, all contributors agree that explanations should not just be gene-centered, and virtually none use design and other engineering metaphors to articulate principles of cellular and organismal organization. I comment in particular on the issue of how to construe the notion of a ‘theory’ and whether developmental biology has or should aspire to have theories, which four of the contributions discuss in detail while taking opposing positions. Beyond construing a theory in terms of its empirical content (established knowledge about biological phenomena), my aim is to shift the focus toward the role that theories have for guiding future scientific theorizing and practice. Such a conception of ‘theory’ is particularly important in the context of development, because arriving at a theoretical framework that provides guidance for the discipline of developmental biology as a whole is more plausible than a unified representation of development across all taxa.     

Pyramids and cascades: a synthesis of food chain functioning and stability

Food chain theory is one of the cornerstones of ecology, providing many of its basic predictions, such as biomass pyramids, trophic cascades and predator–prey oscillations. Yet, ninety years into this theory, the conditions under which these patterns may occur and persist in nature remain subject to debate. Rather than address each pattern in isolation, we propose that they must be understood together, calling for synthesis in a fragmented landscape of theoretical and empirical results. As a first step, we propose a minimal theory that combines the long‐standing energetic and dynamical approaches of food chains. We chart theoretical predictions on a concise map, where two main regimes emerge: across various functioning and stability metrics, one regime is characterised by pyramidal patterns and the other by cascade patterns. The axes of this map combine key physiological and ecological variables, such as metabolic rates and self‐regulation. A quantitative comparison with data sheds light on conflicting theoretical predictions and empirical puzzles, from size spectra to causes of trophic cascade strength. We conclude that drawing systematic connections between various existing approaches to food chains, and between their predictions on functioning and stability, is a crucial step in confronting this theory to real ecosystems.     

How phenological tracking shapes species and communities in non-stationary environments

Climate change alters the environments of all species. Predicting species responses requires understanding how species track environmental change, and how such tracking shapes communities. Growing empirical evidence suggests that how species track phenologically – how an organism shifts the timing of major biological events in response to the environment – is linked to species performance and community structure. Such research tantalizingly suggests a potential framework to predict the winners and losers of climate change, and the future communities we can expect. But developing this framework requires far greater efforts to ground empirical studies of phenological tracking in relevant ecological theory. Here we review the concept of phenological tracking in empirical studies and through the lens of coexistence theory to show why a community-level perspective is critical to accurate predictions with climate change. While much current theory for tracking ignores the importance of a multi-species context, basic community assembly theory predicts that competition will drive variation in tracking and trade-offs with other traits. We highlight how existing community assembly theory can help understand tracking in stationary and non-stationary systems. But major advances in predicting the species- and community-level consequences of climate change will require advances in theoretical and empirical studies. We outline a path forward built on greater efforts to integrate priority effects into modern coexistence theory, improved empirical estimates of multivariate environmental change, and clearly defined estimates of phenological tracking and its underlying environmental cues.     

Alternative statistical approaches to the use of data as evidence for hypotheses in human behavioral ecology

In their ambitious Evolutionary Anthropology paper, Winterhalder and Smith 1 review the history, theory, and methods of human behavioral ecology (HBE). In establishing how HBE differs from traditional approaches within sociocultural anthropology, they and others laud its hypothetical‐deductive research method. 1 - 3 Our aim is to critically examine how human behavioral ecologists conduct their research, specifically how they analyze and interpret data as evidence for scientific hypotheses. Through computer simulations and a review of empirical studies of human sex ratios, we consider some limitations of the status quo and present alternatives that could strengthen the field. In particular, we suggest that because human behavioral ecologists often consider multiple hypotheses, they should use statistical approaches that can quantify the evidence in empirical data for competing hypotheses. Although we focus on HBE, the principles of this paper apply broadly within biological anthropology.     

Challenges in modelling complexity of fungal entomopathogens in semi-natural populations of insects

The use of fungal entomopathogens as microbial control agents has driven studies into their ecology in crop ecosystems. Yet, there is still a lack of understanding of the ecology of these insect pathogens in semi-natural habitats and communities. We review the literature on prevalence of fungal entomopathogens in insect populations and highlight the difficulties in making such measurements. We then describe the theoretical host-pathogen models available to examine the role that fungal entomopathogens could play in regulating insect populations in semi-natural habitats, much of the inspiration for which has been drawn from managed systems, particularly forests. We further emphasise the need to consider the complexity, and particularly the heterogeneity, of semi-natural habitats within the context of theoretical models and as a framework for empirical studies. We acknowledge that fundamental gaps in understanding fungal entomopathogens from an ecological perspective coupled with a lack of empirical data to test theoretical predictions is impeding progress. There is an increasing need, especially under current rapid environmental change, to improve our understanding of the role of fungi in insect population dynamics beyond the context of forestry and agriculture.     

How life‐history traits affect ecosystem properties: effects of dispersal in meta‐ecosystems

The concept of life‐history traits and the study of these traits are the hallmark of population biology. Acknowledging their variability and evolution has allowed us to understand how species adapt in response to their environment. The same traits are also involved in how species alter ecosystems and shape their dynamics and functioning. Some theories, such as the metabolic theory of ecology, ecological stoichiometry or pace‐of‐life theory, already recognize this junction, but only do so in an implicitly non‐spatial context. Meanwhile, for a decade now, it has been argued that ecosystem properties have to be understood at a larger scale using meta‐ecosystem theory because source–sink dynamics, community assembly and ecosystem stability are all modified by spatial structure. Here, we argue that some ecosystem properties can be linked to a single life‐history trait, dispersal, i.e. the tendency of organisms to live, compete and reproduce away from their birth place. By articulating recent theoretical and empirical studies linking ecosystem functioning and dynamics to species dispersal, we aim to highlight both the known connections between life‐history traits and ecosystem properties and the unknown areas, which deserve further empirical and theoretical developments.     

Methods for estimating and mitigating errors in spotted, dual-color DNA microarrays

The conceptual simplicity of DNA microarray technology often belies the complex nature of the measurement errors inherent in the methodology. As the technology has developed, the importance of understanding the sources of uncertainty in the measurements and developing ways to control their influence on the conclusions drawn has become apparent. In this review, strategies for modeling measurement errors and minimizing their effect on the outcome of experiments using a variety of techniques are discussed in the context of spotted, dual-color microarrays. First, methods designed to reduce the influence of random variability through data filtering, replication, and experimental design are introduced. This is followed by a review of data analysis methods that partition the variance into random effects and one or more systematic effects, specifically two-sample significance testing and analysis of variance (ANOVA) methods. Finally, the current state of measurement error models for spotted microarrays and their role in variance stabilizing transformations are discussed.