The Structure of Causal Explanations in Population Biology

The scope of this paper can be clarified by means of a well-known phenomenon that is usually called ‘industrial melanism’: the fact that the melanic form of the peppered moth became dominant in industrial areas in England in the second half of the nineteenth century. Such changes in relative phenotype frequencies are important explananda for population biologists. Apart from trying to explain such changes over time, population biologists also often try to explain differences between populations, e.g. why yellow shell colour is dominant in certain colonies of land snails and almost absent in other colonies. The causal explanations that are given to address such explananda are the objects of analysis in this paper. Our primary aim is to explicate their structure: we want to capture the typical ingredients of causal explanations in population biology, and their organisation. Based on this explication, we discuss how natural selection fits into recent mechanical philosophy of science, and engage in the debate on the nature of evolutionary theory.

     

Mechanistic Explanations for Restricted Evolutionary Paths That Emerge from Gene Regulatory Networks

The extent and the nature of the constraints to evolutionary trajectories are central issues in biology. Constraints can be the result of systems dynamics causing a non-linear mapping between genotype and phenotype. How prevalent are these developmental constraints and what is their mechanistic basis? Although this has been extensively explored at the level of epistatic interactions between nucleotides within a gene, or amino acids within a protein, selection acts at the level of the whole organism, and therefore epistasis between disparate genes in the genome is expected due to their functional interactions within gene regulatory networks (GRNs) which are responsible for many aspects of organismal phenotype. Here we explore epistasis within GRNs capable of performing a common developmental function – converting a continuous morphogen input into discrete spatial domains. By exploring the full complement of GRN wiring designs that are able to perform this function, we analyzed all possible mutational routes between functional GRNs. Through this study we demonstrate that mechanistic constraints are common for GRNs that perform even a simple function. We demonstrate a common mechanistic cause for such a constraint involving complementation between counter-balanced gene-gene interactions. Furthermore we show how such constraints can be bypassed by means of “permissive” mutations that buffer changes in a direct route between two GRN topologies that would normally be unviable. We show that such bypasses are common and thus we suggest that unlike what was observed in protein sequence-function relationships, the “tape of life” is less reproducible when one considers higher levels of biological organization.     

Mechanistic Approaches to Community Ecology: A New Reductionism

Mechanistic approaches to community ecology are those whichemploy individual— ecological concepts—those ofbehavioral ecology, physiological ecology, and ecomorphology—as theoretical bases for understanding community patterns. Suchapproaches, which began explicitly about a decade ago, are justnow coming into prominence. They stand in contrast to more traditionalapproaches, such as MacArthur and Levins (1967),which interpretcommunity ecology almost strictly in terms of "megaparameters.". Mechanistic approaches can be divided into those which use populationdynamics as a major component of the theory and those whichdo not; examples of the two are about equally common. The firstapproach sacrifices a highly detailed representation of individual—ecological processes; the second sacrifices an explicit representationof the abundance and persistence of populations. Three subdisciplines of ecology—individual, populationand community ecology—form a "perfect" hierarchy in Beckner's(1974) sense. Two other subdisciplines—ecosystem ecologyand evolutionary ecology—lie somewhat laterally to thishierarchy. The modelling of community phenomena using sets ofpopulation-dynamical equations is argued as an attempt at explanationvia the reduction of community to population ecology. Much ofthe debate involving Florida State ecologists is over whetheror not such a relationship is additive (or conjunctive), a verystrong form of reduction. I argue that reduction of communityto individual ecology is plausible via a reduction of populationecology to individual ecology. Approaches that derive the population-dynamicalequations used in population and community ecology from individual-ecologicalconsiderations, and which provide a decomposition of megaparametersinto behavioral and physiological parameters, are cited as illustratinghow the reduction might be done. I argue that "sufficient parameters"generally will not enhance theoretical understanding in communityecology. A major advantage of the mechanistic approach is that variationin population and community patterns can be understood as variationin individual-ecological conditions. In addition to enrichingthe theory, this allows the best functional form to be chosenfor modeling higher-level phenomena, where "best" is definedas biologically most appropriate rather than mathematicallymost convenient. Disadvantages of the mechanistic approach arethat it may portend an overly complex, massive and special theory,and that it naturally tends to avoid many-species phenomenasuch as indirect effects. The paper ends with a scenario fora mechanistic-ecological utopia.     

Moral Reasoning and the Meaning of Cancer: Causal Explanations of Oncologists and Patients in Southern Mexico

Moral themes were a striking feature of the causal explanations for female cancers discussed by oncologists and patients in an ethnographic study of hospital-based cancer care in southern Mexico. These explanations integrate general biomedical explanations with everyday expectations and experiences, giving meaning to otherwise arbitrary events. Analysis of case examples shows that causal models incorporate local constructs about what constitutes a virtuous life, especially in terms of class- and gender-based values. Although patients and physicians draw on similar concepts of moral order, they apply these constructs in distinct ways. Because physicians' explanations are necessarily framed in terms of object, their causal stories employ generalized presumptions about how categories of persons behave (e.g., women, the lower class). In contrast, patients' explanations are framed in terms of subject; they are based on the specific details of their personal history. The article examines the distinct perspectives of physicians and patients, and provides an illustration of how biomedical culture articulates with the local moral constructs of a particular community, [cancer; Mexico; culture of biomedicine; concepts of illness; oncology, models of illness]     

Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the ‘peril’. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the ‘peril ratio index of synergy based on multiplicativity’ (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of ‘relative excess risk due to interaction’. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.     

Asymmetry and Explanations

In Colless’ (1995,Syst. Biol. 44, 102–108) results, cladograms for randomly generated matrices were strongly asymmetrical, and he used this to maintain that real cladograms provide little evidence on asymmetry of phylogeny. His position, however, depended on retaining poorly supported groups as if they were well-supported. If poorly supported groups are removed, as with parsimony jackknifing, well-structured real data can still give strong asymmetry, while random matrices simply yield unresolved trees, obviating Colless’ argument.     

Explanations in search of observations

The paper explores how, in economics and biology, theoretical models are used as explanatory devices. It focuses on a modelling strategy by which, instead of starting with an unexplained regularity in the world, the modeller begins by creating a credible model world. The model world exhibits a regularity, induced by a mechanism in that world. The modeller concludes that there may be a part of the real world in which a similar regularity occurs and that, were that the case, the model would offer an explanation. Little concrete guidance is given about where such a regularity might be found. Three modelling exercises in evolutionary game theory—one from economics and two from biology—are used as case studies. Two of these (one from each discipline) exemplify ‘explanation in search of observation’. The third goes a step further, analysing a regularity in a model world and treating it as informative about the real world, but without saying anything about real phenomena. The paper argues that if the relation between the model and real worlds is understood in terms of similarity, and if modelling is understood as an ongoing discovery process rather than as the demonstration of empirical truths, there can be value in creating explanations before finding the regularities that are to be explained.     

On Pluralism and Competition in Evolutionary Explanations

A controversy arose concerning the adaptive significance ofclitoral orgasm, disputing whether the presence of the traitin females is explained by appeal to developmental processesor natural selection (Gould, 1987a, b; Alcock, 1987). In response,Sherman (1988) offered a pluralistic solution in terms of levelsof analysis in which Gould and Alcock's disagreement was construedas semantic and not substantial. I argue that Sherman's solutionis mistaken. I suggest that the nature of the Gould/Alcock disputeis better understood by considering the abstract structure ofscientific theories and their role in explanation. This accountleads to a representation of science as having a plurality oftheoretical models which are integrated piecemeal in the explanationof concrete phenomena.     

Causal biostratigraphy

Causal biostratigraphy means an approach to stratigraphic problems based on ecosystem analysis of interrelations between geological events and organic evolution. Thc succession of ecosystems is controlled mainly by climatic cycles. Stratigraphic units correspond to palececosystems. The units of higher ranks which are defined by changes of major biomes correspond to paleobiospheres. Their boundaries are designated by replacement of dominant types within the stratoecotones. Reconstruction of catenae, analysis of vicarious catenae systems, and correlation by cliserer are among the most useful methods of causal biostratigraphy.     

Evaluating Alternative Explanations in Ecosystem Experiments

Unreplicated ecosystem experiments can be analyzed by diverse statistical methods. Most of these methods focus on the null hypothesis that there is no response of a given ecosystem to a manipulation. We suggest that it is often more productive to compare diverse alternative explanations (models) for the observations. An example is presented using whole-lake experiments. When a single experimental lake was examined, we could not detect effects of phosphorus (P) input rate, dissolved organic carbon (DOC), and grazing on chlorophyll. When three experimental lakes with contrasting DOC and food webs were subjected to the same schedule of P input manipulations, all three impacts and their interactions were measurable. Focus on multiple alternatives has important implications for design of ecosystem experiments. If a limited number of experimental ecosystems are available, it may be more informative to manipulate each ecosystem differently to test alternatives, rather than attempt to replicate the experiment.     

Multiple Explanations in Darwinian Evolutionary Theory

Variational evolutionary theory as advocated by Darwin is not a single theory, but a bundle of related but independent theories, namely: (a) variational evolution; (b) gradualism rather than large leaps; (c) processes of phyletic evolution and of speciation; (d) causes for the formation of varying individuals in populations and for the action of selective agents; and (e) all organisms evolved from a common ancestor. The first four are nomological-deductive explanations and the fifth is historical-narrative. Therefore evolutionary theory must be divided into nomological and historical theories which are both testable against objective empirical observations. To be scientific, historical evolutionary theories must be based on well corroborated nomological theories, both evolutionary and functional. Nomological and general historical evolutionary theories are well tested and must be considered as strongly corroborated scientific theories. Opponents of evolutionary theory are concerned only with historical evolutionary theories, having little interest in nomological theory. Yet given a well corroborated nomological evolutionary theory, historical evolutionary theories follow automatically. If understood correctly, both forms of evolutionary theories stand on their own as corroborated scientific theories and should not be labeled as facts.     

Causal Relationship between Microbial Ecology Dynamics and Proteolysis during Manufacture and Ripening of Protected Designation of Origin (PDO) Cheese Canestrato Pugliese

Pyrosequencing of the 16S rRNA gene, community-level physiological profiles determined by the use of Biolog EcoPlates, and proteolysis analyses were used to characterize Canestrato Pugliese Protected Designation of Origin (PDO) cheese. The number of presumptive mesophilic lactococci in raw ewes'' milk was higher than that of presumptive mesophilic lactobacilli. The numbers of these microbial groups increased during ripening, showing temporal and numerical differences. Urea-PAGE showed limited primary proteolysis, whereas the analysis of the pH 4.6-soluble fraction of the cheese revealed that secondary proteolysis increased mainly from 45 to 75 days of ripening. This agreed with the concentration of free amino acids. Raw ewes'' milk was contaminated by several bacterial phyla: Proteobacteria (68%; mainly Pseudomonas), Firmicutes (30%; mainly Carnobacterium and Lactococcus), Bacteroidetes (0.05%), and Actinobacteria (0.02%). Almost the same microbial composition persisted in the curd after molding. From day 1 of ripening onwards, the phylum Firmicutes dominated. Lactococcus dominated throughout ripening, and most of the Lactobacillus species appeared only at 7 or 15 days. At 90 days, Lactococcus (87.2%), Lactobacillus (4.8%; mainly Lactobacillus plantarum and Lactobacillus sakei), and Leuconostoc (3.9%) dominated. The relative utilization of carbon sources by the bacterial community reflected the succession. This study identified strategic phases that characterized the manufacture and ripening of Canestrato Pugliese cheese and established a causal relationship between mesophilic lactobacilli and proteolysis.     

Causal inference in multisensory perception

Perceptual events derive their significance to an animal from their meaning about the world, that is from the information they carry about their causes. The brain should thus be able to efficiently infer the causes underlying our sensory events. Here we use multisensory cue combination to study causal inference in perception. We formulate an ideal-observer model that infers whether two sensory cues originate from the same location and that also estimates their location(s). This model accurately predicts the nonlinear integration of cues by human subjects in two auditory-visual localization tasks. The results show that indeed humans can efficiently infer the causal structure as well as the location of causes. By combining insights from the study of causal inference with the ideal-observer approach to sensory cue combination, we show that the capacity to infer causal structure is not limited to conscious, high-level cognition; it is also performed continually and effortlessly in perception.     

Complexity and Demographic Explanations of Cumulative Culture

Formal models have linked prehistoric and historical instances of technological change (e.g., the Upper Paleolithic transition, cultural loss in Holocene Tasmania, scientific progress since the late nineteenth century) to demographic change. According to these models, cumulation of technological complexity is inhibited by decreasing— while favoured by increasing—population levels. Here we show that these findings are contingent on how complexity is defined: demography plays a much more limited role in sustaining cumulative culture in case formal models deploy Herbert Simon''s definition of complexity rather than the particular definitions of complexity hitherto assumed. Given that currently available empirical evidence doesn''t afford discriminating proper from improper definitions of complexity, our robustness analyses put into question the force of recent demographic explanations of particular episodes of cultural change.