Explanatory unification and natural selection explanations

The debate between the dynamical and the statistical interpretations of natural selection is centred on the question of whether all explanations that employ the concepts of natural selection and drift are reducible to causal explanations. The proponents of the statistical interpretation answer negatively, but insist on the fact that selection/drift arguments are explanatory. However, they remain unclear on where the explanatory power comes from. The proponents of the dynamical interpretation answer positively and try to reduce selection/drift arguments to some of the most prominent accounts of causal explanation. In turn, they face the criticism raised by statisticalists that current accounts of causation have to be violated in some of their core conditions or otherwise used in a very loose manner in order to account for selection/drift explanations. We propose a reconciliation of both interpretations by conveying evolutionary explanations within the unificationist model of scientific explanation. Therefore, we argue that the explanatory power in natural selection arguments is a result of successful unification of individual- and population-level facts. A short case study based on research on sympatric speciation will be presented as an example of how population- and individual-level facts are unified to explain the morphological mosaic of bill shape in island scrub jays (Aphelocoma insularis).     

Explanatory models of medically unexplained symptoms: a qualitative analysis of the literature

Background Medically unexplained symptoms (MUS) are common in primary health care. Both patients and doctors are burdened with the symptoms that negatively affect patients' quality of life. General practitioners (GPs) often face difficulties when giving patients legitimate and convincing explanations for their symptoms. This explanation is important for reassuring patients and for maintaining a good doctor-patient communication and relationship.Objective To provide an overview of explanatory models for MUS.Study design We performed a systematic search of reviews in PsycINFO and PubMed about explanatory models of MUS. We performed a qualitative analysis of the data according to the principles of constant comparative analysis to identify specific explanatory models.Results We distinguished nine specific explanatory models of MUS in the literature: somatosensory amplification, sensitisation, sensitivity, immune system sensitisation, endocrine dysregulation, signal filter model, illness behaviour model, autonomous nervous system dysfunction and abnormal proprioception. The nine different explanatory models focus on different domains, including somatic causes, perception, illness behaviour and predisposition. We also found one meta-model, which incorporates these four domains: the cognitive behavioural therapy model.Conclusion Although GPs often face difficulties when providing explanations to patients with MUS, there are multiple explanatory models in the scientific literature that may be of use in daily medical practice.     

Probabilistic causation and the explanatory role of natural selection

The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that five explananda have been assigned to the theory of natural selection and that four of them may be actually considered explananda of natural selection. For the second question, we claim that a probabilistic conception of causality and the statistical relevance concept of explanation are both good models for understanding the explanatory role of natural selection. We review the biological and philosophical disputes about the explanatory role of natural selection and formalize some explananda in probabilistic terms using classical results from population genetics. Most of these explananda have been discussed in philosophical terms but some of them have been mixed up and confused. We analyze and set the limits of these problems.     

Inferential explanations in biology

Among philosophers of science, there is now a widespread agreement that the DN model of explanation is poorly equipped to account for explanations in biology. Rather than identifying laws, so the consensus goes, researchers explain biological capacities by constructing a model of the underlying mechanism.We think that the dichotomy between DN explanations and mechanistic explanations is misleading. In this article, we argue that there are cases in which biological capacities are explained without constructing a model of the underlying mechanism. Although these explanations do not conform to Hempel’s DN model (they do not deduce the explanandum from laws of nature), they do invoke more or less stable generalisations. Because they invoke generalisations and have the form of an argument, we call them inferential explanations. We support this claim by considering two examples of explanations of biological capacities: pigeon navigation and photoperiodism. Next, we will argue that these non-mechanistic explanations are crucial to biology in three ways: (i) sometimes, they are the only thing we have (there is no alternative available), (ii) they are heuristically useful, and (iii) they provide genuine understanding and so are interesting in their own right.In the last sections we discuss the relation between types of explanations and types of experiments and situate our views within some relevant debates on explanatory power and explanatory virtues.     

Causal and Mechanistic Explanations in Ecology

How are scientific explanations possible in ecology, given that there do not appear to be many-if any-ecological laws? To answer this question, I present and defend an account of scientific causal explanation in which ecological generalizations are explanatory if they are invariant rather than lawlike. An invariant generalization continues to hold or be valid under a special change-called an intervention-that changes the value of its variables. According to this account, causes are difference-makers that can be intervened upon to manipulate or control their effects. I apply the account to ecological generalizations to show that invariance under interventions as a criterion of explanatory relevance provides interesting interpretations for the explanatory status of many ecological generalizations. Thus, I argue that there could be causal explanations in ecology by generalizations that are not, in a strict sense, laws. I also address the issue of mechanistic explanations in ecology by arguing that invariance and modularity constitute such explanations.     

Treating Addictions: Harm Reduction in Clinical Care and Prevention

This paper examines the role of clinical practitioners and clinical researchers internationally in establishing the utility of harm-reduction approaches to substance use. It thus illustrates the potential for clinicians to play a pivotal role in health promoting structural interventions based on harm-reduction goals and public health models. Popular media images of drug use as uniformly damaging, and abstinence as the only acceptable goal of treatment, threaten to distort clinical care away from a basis in evidence, which shows that some ways of using drugs are far more harmful than others and that punitive approaches and insistence on total abstinence as the only goal of treatment often increases the harms of drug use rather than reducing drug use. Therefore the leadership and scientific authority of clinicians who understand the health impact of harm-reduction strategies is needed. Through a review of harm-reduction interventions in Canada, the United Kingdom, the United States, Australia, Switzerland, and the Netherlands, we identify three ways that clinicians have helped to achieve a paradigm shift from punitive approaches to harm-reduction principles in clinical care and in drug policy: (1) through clinical research to provide data establishing the effectiveness and feasibility of harm-reduction approaches, (2) by developing innovative clinical programmes that employ harm reduction, and thereby (3) changing the standard of care to include routine use of these evidence-based (but often misunderstood) approaches in their practices. We argue that through promotion of harm-reduction goals and methods, clinicians have unique opportunities to improve the health outcomes of vulnerable populations.     

Historical and philosophical perspectives on the study of developmental bias

Throughout the recent history of research at the intersection of evolution and development, notions such as developmental constraint, evolutionary novelty, and evolvability have been prominent, but the term “developmental bias” has scarcely been used. And one may even doubt whether a unique and principled definition of bias is possible. I argue that the concept of developmental bias can still play a vital scientific role by means of setting an explanatory agenda that motivates investigation and guides the formulation of integrative explanatory frameworks. Less crucial is a definition that would classify patterns of phenotypic variation and unify variational patterns involving different traits and taxa as all being “bias.” Instead, what we should want is a concept that generates intellectual identity across various researchers, and that unites the diverse fields and approaches relevant to the study of developmental bias, from paleontology to behavioral biology. I point to some advantages of conducting research specifically under the label of “developmental bias,” compared with employing other, more common terms such as “evolvability.”     

Levels of biological plausibility

Notions of mechanism, emergence, reduction and explanation are all tied to levels of analysis. I cover the relationship between lower and higher levels, suggest a level of mechanism approach for neuroscience in which the components of a mechanism can themselves be further decomposed and argue that scientists'' goals are best realized by focusing on pragmatic concerns rather than on metaphysical claims about what is ‘real''. Inexplicably, neuroscientists are enchanted by both reduction and emergence. A fascination with reduction is misplaced given that theory is neither sufficiently developed nor formal to allow it, whereas metaphysical claims of emergence bring physicalism into question. Moreover, neuroscience''s existence as a discipline is owed to higher-level concepts that prove useful in practice. Claims of biological plausibility are shown to be incoherent from a level of mechanism view and more generally are vacuous. Instead, the relevant findings to address should be specified so that model selection procedures can adjudicate between competing accounts. Model selection can help reduce theoretical confusions and direct empirical investigations. Although measures themselves, such as behaviour, blood-oxygen-level-dependent (BOLD) and single-unit recordings, are not levels of analysis, like levels, no measure is fundamental and understanding how measures relate can hasten scientific progress.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity''.     

Quelle scientificit�� pour la psychanalyse ?

From a strictly philosophical perspective, if one uses ??hard sciences?? as a standard to assess the scientificity of a theory, it will not be difficult to question the scientificity of psychoanalysis. But, rather than favouring such criticisms, I shall begin with the idea that different explanations may serve different explanatory goals while remaining valid, since to assess the validity of a theory, one must always consider the explanatory goals it has set. Hence, there is no such thing as an absolute, a historical and timeless criterion from which to judge the validity of a theoretical explanation. But the criteria and the epistemological constraints are normally relative to some set of explanatory goals. Therefore, the issue shifts towards the following question: what are the goals of psychoanalytic explanations and how (from which perspective) are we to judge the validity of its explanations according to the goals it aims at? I articulate together issues related to the object of psychoanalysis (what it theorises), to its explanatory goals (which dimension(s) of its object it seeks to explain) and to the epistemological constraints which are imposed on it. Which leads me to take into account the important role, in the psychoanalytic cure, of the rationalisation of pathological behaviours and of their reintegration into a story which ??makes sense??.     

Save the planet: eliminate biodiversity

Recent work in the philosophy of biology has attempted to clarify and defend the use of the biodiversity concept in conservation science. I argue against these views, and give reasons to think that the biodiversity concept is a poor fit for the role we want it to play in conservation biology on both empirical and conceptual grounds. Against pluralists, who hold that biodiversity consists of distinct but correlated properties of natural systems, I argue that the supposed correlations between these properties are not tight enough to warrant treating and measuring them as a bundle. I additionally argue that deflationary theories of biodiversity don’t go far enough, since a large proportion of what we value in the environment falls outside bounds of what could reasonably be called “diversity”. I suggest that in current scientific practice biodiversity is generally an unnecessary placeholder for biological value of all sorts, and that we are better off eliminating it from conservation biology, or at least drastically reducing its role.     

Agent-based modelling as scientific method: a case study analysing primate social behaviour

A scientific methodology in general should provide two things: first, a means of explanation and, second, a mechanism for improving that explanation. Agent-based modelling (ABM) is a method that facilitates exploring the collective effects of individual action selection. The explanatory force of the model is the extent to which an observed meta-level phenomenon can be accounted for by the behaviour of its micro-level actors. This article demonstrates that this methodology can be applied to the biological sciences; agent-based models, like any other scientific hypotheses, can be tested, critiqued, generalized or specified. We review the state of the art for ABM as a methodology for biology and then present a case study based on the most widely published agent-based model in the biological sciences: Hemelrijk's DomWorld, a model of primate social behaviour. Our analysis shows some significant discrepancies between this model and the behaviour of the macaques, the genus used for our analysis. We also demonstrate that the model is not fragile: its other results are still valid and can be extended to compensate for these problems. This robustness is a standard advantage of experiment-based artificial intelligence modelling techniques over analytic modelling.     

Gating or switching? Gating is a better model of prospective timing (a response to 'switching or gating?' by Lejeune)

Lejeune (1998) (Switching or gating? The attentional challenge in cognitive models of psychological time. Behav. Process. 44, 127-45) analyzed and compared two models of prospective timing: the classical switching model and the attentional-gate model. Lejeune argued that a modified switch notion, which can be opened and closed in a frequency which reflects the amount of attentional resources allocated for timing can provide a satisfactory explanation for the impact of attention on prospective timing, and therefore the notion of an 'attentional switch' is favored over adding an 'attentional gate.' In the present analysis, the two competing models are compared in terms of correspondence with the nature of attentional processes, as well as in terms of logical analysis and explanatory power. Based on this comparison, it is argued that gating is a better model of prospective timing than switching.     

Gating or switching? Gating is a better model of prospective timing (a response to 'switching or gating?' by Lejeune)(1)

Lejeune (1998) (Switching or gating? The attentional challenge in cognitive models of psychological time. Behav. Process. 44, 127-45) analyzed and compared two models of prospective timing: the classical switching model and the attentional-gate model. Lejeune argued that a modified switch notion, which can be opened and closed in a frequency which reflects the amount of attentional resources allocated for timing can provide a satisfactory explanation for the impact of attention on prospective timing, and therefore the notion of an 'attentional switch' is favored over adding an 'attentional gate.' In the present analysis, the two competing models are compared in terms of correspondence with the nature of attentional processes, as well as in terms of logical analysis and explanatory power. Based on this comparison, it is argued that gating is a better model of prospective timing than switching.     

Explaining embryological development: Should integration be the goal?

Two approaches to an integration of evolution and development are often distinguished, one “neo-Darwinian” and the other “structuralist”. Should these approaches in turn be integrated? Kelly Smith recently stated that we need a “more complete” theory of biological order, suggesting integration as the ideal. In response to him, I argue that a recognition of different types of scientific questions and causal explanation is more urgent. Do we understand development when we know the crucial factors in the process of differentiation, or rather when we know the laws that govern the transformations of fields? Without a recognition of these different explanatory ideals, “integration” is likely to have the character of annexation.     

A comparison of community and physician explanatory models of AIDS in Mexico and the United States

The goal of this research was to explore differences between lay and professional explanatory models both within and between two countries. We test which effect is stronger, country of residence or professional/lay status, in determining similarities and differences of explanatory models of AIDS. Interviews conducted in Guadalajara, Jalisco (Mexico) and the Edinburg-McAllen area of south Texas (United States) elicited explanatory models of AIDS. Two pairs of samples were interviewed: a physician and community sample in Mexico and a physician and community sample in the United States. Comparisons of the explanatory models indicated that there was a shared core model of AIDS across all four samples, but that physicians' models were more similar to those of lay people in their own communities than either was to samples across the border.     

Extinction, colonization, and species occupancy in tidepool fishes

Despite the increasing sophistication of ecological models with respect to the size and spatial arrangement of habitat, there is relatively little empirical documentation of how species dynamics change as a function of habitat size and the fraction of habitat occupied. In an assemblage of tidepool fishes, I used maximum-likelihood estimation to test whether models which included habitat size provided a better fit to empirical data on extinction and colonization probabilities than models that assumed constant probabilities over all habitats. I found species differences in how extinction and colonization probabilities scaled with habitat size (and hence local population size). However, there was little evidence for a relationship between extinction and colonization probabilities and the fraction of occupied tidepools, as assumed in simple metapopulation models. Instead, colonization and extinction were independent of the fraction of occupied tidepools, favoring a MacArthur-Wilson island-mainland model. When I incorporated declines in extinction probability with tidepool volume in a simple simulation model, I found that predicted occupancy could change greatly, especially when colonization was low. However, the predicted fraction of occupied patches in the simulation model changed little when I incorporated the range of values reported here for extinction and colonization and the rate at which they scale with habitat size. Quantifying extinction and colonization patterns of natural populations is fundamental to understanding how species are distributed spatially and whether metapopulation models of species occupancy provide explanatory power for field populations. Received: 14 March 1997 / Accepted: 21 September 1997     

Extinction

In the life of any species, extinction is the final evolutionary process. It is a common one at present, as the world is entering a major extinction crisis. The pattern of extinction and threat is very non-random, with some taxa being more vulnerable than others. Explaining why some taxa are affected and some escape is a major goal of conservation biology. More ambitiously, a predictive model could, in principle, be built by integrating comparable studies of past and present extinctions. We review progress towards both explanatory and predictive frameworks, comparing correlates of extinction in different groups at different times. Progress towards explanatory models for the current crisis is promising, at least in some well-studied taxa, but the development of a truly predictive model is hampered by the formidable difficulties of integrating studies of present and past extinctions.     

The significance of assemblage-level thinning for species richness

1 A unimodal relationship between species richness and primary productivity is commonly reported. To explain this pattern, the mechanisms proposed in the many hypotheses are generally complex and almost all are without a strong empirical foundation. Here we evaluate the role of self-thinning in plant assemblages: assemblage-level thinning.
2 We developed a simple two-parameter model of species richness that predicts that plant species richness will be determined by a unimodal relationship between total plant density and above-ground biomass. This model provides a very narrowly defined set of testable quantitative predictions, and thus is the first falsifiable model of assemblage-level thinning. We fit this model to the species richness–above-ground biomass data from 14 empirical studies that are often cited as evidence of a general diversity–productivity relationship. In addition, we compared our model to two other models, one more flexible and one more constrained than our own.
3 We found that our model of species richness explained a substantial and statistically significant portion of the species richness observed in 11 of the 14 empirical studies of species richness–biomass patterns. Therefore, given the conservative nature of our model, and the number of previously published data sets explained by this model, we argue that assemblage-level thinning not only provides a viable and exceedingly parsimonious explanation, but may also be a widespread phenomenon.