Getting rid of interventions

According to James Woodward’s influential interventionist account of causation, X is a cause of Y iff, roughly, there is a possible intervention on X that changes Y. Woodward requires that interventions be merely logically possible. I will argue for two claims against this modal character of interventions: First, merely logically possible interventions are dispensable for the semantic project of providing an account of the meaning of causal statements. If interventions are indeed dispensable, the interventionist theory collapses into (some sort of) a counterfactual theory of causation. Thus, the interventionist theory is not tenable as a theory of causation in its own right. Second, if one maintains that merely logically possible interventions are indispensable, then interventions with this modal character lead to the fatal result that interventionist counterfactuals are evaluated inadequately. Consequently, interventionists offer an inadequate theory of causation. I suggest that if we are concerned with explicating causal concepts and stating the truth-conditions of causal claims we best get rid of Woodwardian interventions.     

Causal structure and hierarchies of models

Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson’s paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous and endogenous variables suggests partitioning the world into distinct subsystems. The tension in these practices is addressed within a structural account of causation inspired by the work of Herbert Simon’s, which defines cause with reference to complete systems adapted to deal with incomplete systems and piecemeal evidence. The focus is on understanding the constraints that a structural account of causation places on the freedom to model complex or lower-order systems as simpler or higher-order systems and on to what degree piecemeal evidence can be incorporated into a structural account.     

Use of implicit methods from general sensitivity theory to develop a systematic approach to metabolic control. II. Complex systems

In the accompanying paper (Cascante et al., this issue) we have used general sensitivity theory to develop a matrix algebra that, in the case of sequential reactions, directly relates global and local properties of a given system. In complex biochemical systems this direct relationship is not possible due to the existence of linear dependencies among fluxes and among metabolite concentrations (conserved aggregate concentrations in BST or moiety-conserved concentrations in MCT). In this paper our matrix algebra is applied to conserved cycles and branched pathways, and it is shown that with minor modifications it again relates global properties to the local properties of the enzymes in the system. In the case of conserved cycles, elasticities become modified due to the existence of linear dependencies among the concentration variables in the cycle. In branched pathways, new matrix elements involving ratios of fluxes appear. With these modifications, one can show that the so-called theorems of metabolic control theory specific to these types of pathways are special cases of more general relationships. Rules for the construction of matrices relating global and local properties are given that apply to an arbitrary system of cycles and branches. The implicit approach developed in these papers, which is a generalization of that used in MCT, allows one to make more direct comparisons with the general explicit approach originally developed in BST.     

Conservation rules, their breakdown, and optimality in Caenorhabditis sinusoidal locomotion

Undulatory locomotion is common to nematodes as well as to limbless vertebrates, but its control is not understood in spite of the identification of hundred of genes involved in Caenorhabditis elegans locomotion. To reveal the mechanisms of nematode undulatory locomotion, we quantitatively analysed the movement of C. elegans with genetic perturbations to neurons, muscles, and skeleton (cuticle). We also compared locomotion of different Caenorhabditis species. We constructed a theoretical model that combines mechanics and biophysics, and that is constrained by the observations of propulsion and muscular velocities, as well as wavelength and amplitude of undulations. We find that normalized wavelength is a conserved quantity among wild-type C. elegans individuals, across mutants, and across different species. The velocity of forward propulsion scales linearly with the velocity of the muscular wave and the corresponding slope is also a conserved quantity and almost optimal; the exceptions are in some mutants affecting cuticle structure. In theoretical terms, the optimality of the slope is equivalent to the exact balance between muscular and visco-elastic body reaction bending moments. We find that the amplitude and frequency of undulations are inversely correlated and provide a theoretical explanation for this fact. These experimental results are valid both for young adults and for all larval stages of wild-type C. elegans. In particular, during development, the amplitude scales linearly with the wavelength, consistent with our theory. We also investigated the influence of substrate firmness on motion parameters, and found that it does not affect the above invariants. In general, our biomechanical model can explain the observed robustness of the mechanisms controlling nematode undulatory locomotion.     

Regulative feedback in pattern formation: towards a general relativistic theory of positional information

Positional specification by morphogen gradients is traditionally viewed as a two-step process. A gradient is formed and then interpreted, providing a spatial metric independent of the target tissue, similar to the concept of space in classical mechanics. However, the formation and interpretation of gradients are coupled, dynamic processes. We introduce a conceptual framework for positional specification in which cellular activity feeds back on positional information encoded by gradients, analogous to the feedback between mass-energy distribution and the geometry of space-time in Einstein's general theory of relativity. We discuss how such general relativistic positional information (GRPI) can guide systems-level approaches to pattern formation.     

Fluctuating resource availability increases invasibility in microbial microcosms

The fluctuating resource hypothesis (FRH) proposes that fluctuations in resource supply can temporally reduce competitive pressure from resident species, thereby providing ephemeral opportunities for invading species. Although FRH has the potential to integrate many existing hypotheses regarding mechanisms of community invasibility, previous tests and evaluations of FRH were based on single trophic level, did not take the timing effect into account, and had difficulties in distinguishing the effects of resource pulses from other simultaneous processes. Here we test FRH in multi‐trophic aquatic microcosms by creating resource pulses, by controlling resource quantity, propagule supply and pulse recurrence frequency, and by manipulating the timing of pulses relative to the timing of the arrival of new species (i.e. invaders) to local communities. The novelty of our work lies in that we directly manipulate resource pulse timing relative to invader introduction events and thus demonstrate the importance of this timing effect for community invasibility. Our study supports FRH in general: invasion success was positively related to resource pulses, and invaders had strong performance in treatments receiving coincident pulses, although not all invaders gained more benefit when resources were supplied at large‐magnitude than supplied at continuous rates. Since many ecosystems worldwide are experiencing high rates of anthropogenic nutrient input and increasing rates of precipitation, these ecosystems are potentially more fragile and susceptible to invasion. More experiments across multiple ecosystem types are needed to help formulate a general theory of community invasibility.     

Reciprocal causation and the proximate–ultimate distinction

Laland and colleagues have sought to challenge the proximate–ultimate distinction claiming that it imposes a unidirectional model of causation, is limited in its capacity to account for complex biological phenomena, and hinders progress in biology. In this article the core of their argument is critically analyzed. It is claimed that contrary to their claims Laland et al. rely upon the proximate–ultimate distinction to make their points and that their alternative conception of reciprocal causation refers to phenomena that were already accounted for by standard theory.     

Ecological stress and sex evolution in soil microfungi

The elucidation of the origin and maintenance of sex is a major unsolved problem in evolutionary biology. A number of hypotheses have been elaborated, but the scarcity of empirical data limits further progress. During recent years, the general inclination has changed towards pluralistic models of sex evolution, due partly to an increased diversity of studied organisms. Fungi are among the most promising organisms for testing sexual causation, as demonstrated in recent laboratory experiments. However, reconciling theory and evidence necessitates critical field observations. Here, we report new estimates of the distribution of morphologically sexual and asexual soil microfungi in nature, which indicate a remarkable trend towards increased sexuality with increasing climatic stress.     

On some theoretical grounds for an organism-centered biology: Property emergence, supervenience, and downward causation

In this paper, we investigate some theoretical grounds for bridging the gap between an organism-centered biology and the chemical basis of biological explanation, as expressed in the prevailing molecular perspective in biological research. First, we present a brief survey of the role of the organism concept in biological thought. We advance the claim that emergentism (with its fundamental tenets: ontological physicalism, qualitative novelty, property emergence, theory of levels, irreducibility of the emergents, and downward causation) can provide a metaphysical basis for a coherent sort of organicism. Downward causation (DC) is the key notion in emergentist philosophy, as shown by the tension between the aspects of dependence and nonreducibility in the concept of supervenience, preferred by many philosophers to emergence as a basis for nonreductive physicalism. As supervenience physicalism does not lead, arguably, to a stable nonreductive physicalist account, we maintain that a philosophical alternative worthy of investigation is that of a combination of supervenience and property emergence in the formulation of such a stance. Taking as a starting-point O’Connor’s definition of an emergent property, we discuss how a particular interpretation of downward causation (medium DC), inspired by Aristotelian causal modes, results in an explanation of property emergence compatible with both physicalism and non-reductionism. In this account of emergence, one may claim that biology, as a science of living organization, is and remains a science of the organism, even if completely explained by the laws of chemistry. We conclude the paper with a new definition of an emergent property.     

On Reciprocal Causation in the Evolutionary Process

Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause–effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist. Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach might have been underestimated by critics of contemporary evolutionary biology.     

Complexity measures of brain wave dynamics

To understand the nature of brain dynamics as well as to develop novel methods for the diagnosis of brain pathologies, recently, a number of complexity measures from information theory, chaos theory, and random fractal theory have been applied to analyze the EEG data. These measures are crucial in quantifying the key notions of neurodynamics, including determinism, stochasticity, causation, and correlations. Finding and understanding the relations among these complexity measures is thus an important issue. However, this is a difficult task, since the foundations of information theory, chaos theory, and random fractal theory are very different. To gain significant insights into this issue, we carry out a comprehensive comparison study of major complexity measures for EEG signals. We find that the variations of commonly used complexity measures with time are either similar or reciprocal. While many of these relations are difficult to explain intuitively, all of them can be readily understood by relating these measures to the values of a multiscale complexity measure, the scale-dependent Lyapunov exponent, at specific scales. We further discuss how better indicators for epileptic seizures can be constructed.     

Fluxes and metabolic pools as model traits for quantitative genetics. I. The L-shaped distribution of gene effects

The fluxes through metabolic pathways can be considered as model quantitative traits, whose QTL are the polymorphic loci controlling the activity or quantity of the enzymes. Relying on metabolic control theory, we investigated the relationships between the variations of enzyme activity along metabolic pathways and the variations of the flux in a population with biallelic QTL. Two kinds of variations were taken into account, the variation of the average enzyme activity across the loci, and the variation of the activity of each enzyme of the pathway among the individuals of the population. We proposed analytical approximations for the flux mean and variance in the population as well as for the additive and dominance variances of the individual QTL. Monte Carlo simulations based on these approximations showed that an L-shaped distribution of the contributions of individual QTL to the flux variance (R(2)) is consistently expected in an F(2) progeny. This result could partly account for the classically observed L-shaped distribution of QTL effects for quantitative traits. The high correlation we found between R(2) value and flux control coefficients variance suggests that such a distribution is an intrinsic property of metabolic pathways due to the summation property of control coefficients.     

Mutual information in protein multiple sequence alignments reveals two classes of coevolving positions

Information theory was used to identify nonconserved coevolving positions in multiple sequence alignments from a variety of protein families. Coevolving positions in these alignments fall into two general categories. One set is composed of positions that coevolve with only one or two other positions. These positions often display direct amino acid side-chain interactions with their coevolving partner. The other set comprises positions that coevolve with many others and are frequently located in regions critical for protein function, such as active sites and surfaces involved in intermolecular interactions and recognition. We find that coevolving positions are more likely to change protein function when mutated than are positions showing little coevolution. These results imply that information theory may be applied generally to find coevolving, nonconserved positions that are part of functional sites in uncharacterized protein families. We propose that these coevolving positions compose an important subset of the positions in an alignment, and may be as important to the structure and function of the protein family as are highly conserved positions.     

Direct investment by stepfathers can mitigate effects on educational outcomes but does not improve behavioural difficulties

In contemporary developed populations, stepfather presence has been associated with detrimental effects on child development. However, the proximate mechanisms behind such effects are yet to be fully explored. From a behavioural ecological perspective, the negative effects associated with stepfathers may be due to the reduced quantity and quality of investments children receive within stepfather households. Here, we build on previous studies by investigating whether the effects of stepfather presence on child outcomes are driven by differences in maternal and partner (i.e., father or stepfather) direct investments. We use data from the Avon Longitudinal Study of Parents and Children to explore stepfather effects on children’s educational achievement and behavioural difficulties at age 7. Our results indicate that, for educational achievement, stepfather effects are due to the lower levels of direct investments children receive. For behavioural difficulty, stepfather effects are due to multiple factors whereby stepfather presence is associated with greater difficulties independent of investment levels, and direct investments from stepfathers are ineffective. Our results suggest that the negative effects of stepfathers on child outcomes can be explained, in part, by the reduced quantity and the ineffectiveness of direct investments children receive from stepfathers. Furthermore, the effects of stepfather direct investments seem to vary between child outcomes.     

Causation in the sciences: An inferentialist account

I present an alternative account of causation in the biomedical and social sciences according to which the meaning of causal claims is given by their inferential relations to other claims. Specifically, I will argue that causal claims are (typically) inferentially related to certain evidential claims as well as claims about explanation, prediction, intervention and responsibility. I explain in some detail what it means for a claim to be inferentially related to another and finally derive some implication of the proposed account for the epistemology, semantics and metaphysics of causation.     

Making sense of downward causation in manipulationism: illustrations from cancer research

Many researchers consider cancer to have molecular causes, namely mutated genes that result in abnormal cell proliferation (e.g. Weinberg 1998). For others, the causes of cancer are to be found not at the molecular level but at the tissue level where carcinogenesis consists of disrupted tissue organization with downward causation effects on cells and cellular components (e.g. Sonnenschein and Soto 2008). In this contribution, I ponder how to make sense of such downward causation claims. Adopting a manipulationist account of causation (Woodward 2003), I propose a formal definition of downward causation and discuss further requirements (in light of Baumgartner 2009). I then show that such an account cannot be mobilized in support of non-reductive physicalism (contrary to Raatikainen 2010). However, I also argue that such downward causation claims might point at particularly interesting dynamic properties of causal relationships that might prove salient in characterizing causal relationships (following Woodward 2010).     

Getting the most out of Shannon information

Shannon information is commonly assumed to be the wrong way in which to conceive of information in most biological contexts. Since the theory deals only in correlations between systems, the argument goes, it can apply to any and all causal interactions that affect a biological outcome. Since informational language is generally confined to only certain kinds of biological process, such as gene expression and hormone signalling, Shannon information is thought to be unable to account for this restriction. It is often concluded that a richer, teleosemantic sense of information is needed. I argue against this view, and show that a coherent and sufficiently restrictive theory of biological information can be constructed with Shannon information at its core. This can be done by paying due attention some crucial distinctions: between information quantity and its fitness value, and between carrying information and having the function of doing so. From this I construct an account of how informational functions arise, and show that the “subject matter” of these functions can easily be seen as the natural information dealt with by Shannon’s theory.     

Taming fitness: Organism‐environment interdependencies preclude long‐term fitness forecasting

Fitness is a central but notoriously vexing concept in evolutionary biology. The propensity interpretation of fitness is often regarded as the least problematic account for fitness. It ties an individual's fitness to a probabilistic capacity to produce offspring. Fitness has a clear causal role in evolutionary dynamics under this account. Nevertheless, the propensity interpretation faces its share of problems. We discuss three of these. We first show that a single scalar value is an incomplete summary of a propensity. Second, we argue that the widespread method of “abstracting away” environmental idiosyncrasies by averaging over reproductive output in different environments is not a valid approach when environmental changes are irreversible. Third, we point out that expanding the range of applicability for fitness measures by averaging over more environments or longer time scales (so as to ensure environmental reversibility) reduces one's ability to distinguish selectively relevant differences among individuals because of mutation and eco‐evolutionary feedbacks. This series of problems leads us to conclude that a general value of fitness that is both explanatory and predictive cannot be attained. We advocate for the use of propensity‐compatible methods, such as adaptive dynamics, which can accommodate these difficulties.