Biology lacks a central organism concept that unambiguously marks the distinction between organism and non-organism because the most important questions about organisms do not depend on this concept. I argue that the two main ways to discover useful biological generalizations about multicellular organization--the study of homology within multicellular lineages and of convergent evolution across lineages in which multicellularity has been independently established--do not require what would have to be a stipulative sharpening of an organism concept.

Biology lacks a central organism concept that unambiguously marks the distinction between organism and non-organism because the most important questions about organisms do not depend on this concept. I argue that the two main ways to discover useful biological generalizations about multicellular organization—the study of homology within multicellular lineages and of convergent evolution across lineages in which multicellularity has been independently established—do not require what would have to be a stipulative sharpening of an organism concept.

The question of whether biology contains laws has important implications about the nature of science. Some philosophers believe that the legitimacy of the special sciences depends on whether they contain laws. In this dissertation, I defend the thesis that biology contains laws. In Chapter I, I discuss the importance of this problem and set the stage for my inquiry. In Chapter V, I summarize the results of Chapters II, III, and IV and I offer reasons why the position (...) I advance should be preferred over the alternatives. ;In Chapter II, I argue that the epistemic functions of a priori biological laws in biology are the same as those of empirical laws in physics. I establish this claim by showing that zero force laws and singleton force laws in these sciences function in the same way. I conclude that the requirement that laws must be empirical is idle in connection with how laws operate in science. ;In Chapter III, I argue that even if there are ceteris paribus sentences, it is unlikely that there are ceteris paribus laws. If there are genuine ceteris paribus laws, then 'ceteris paribus' should be a proper part of a law statement in which it occurs. I argue that if we interpret 'ceteris paribus' in this way, the containing sentence cannot be a law because it does not satisfy a minimal condition for laws---i.e., "ceteris paribus A 's are B's" and "ceteris paribus A's are not B's" should not both be true. ;In Chapter IV, I argue that the reasons offered for the non-existence of empirical biological laws don't establish the intended conclusion. I, then, argue that the kinds of law we should expect to find in biology are biophysical laws. I defend this claim by providing a priori and a posteriori arguments. The a priori argument states that the complexity of a system is no reason to think that there are no laws about that system. The a posteriori argument states that current research in evolutionary ecology indicates the existence of biophysical laws. (shrink)

Due to the variation, contingency and complexity of living systems, biology is often taken to be a science without fundamental theories, laws or general principles. I revisit this question in light of the quest for design principles in systems biology and show that different views can be reconciled if we distinguish between different types of generality. The philosophical literature has primarily focused on generality of specific models or explanations, or on the heuristic role of abstraction. This paper (...) takes a different approach in emphasizing a theory-constituting role of general principles. Design principles signify general dependency-relations between structures and functions, given a set of formally defined constraints. I contend that design principles increase our understanding of living systems by relating specific models to general types. The categorization of types is based on a delineation of the scope of biological possibilities, which serves to identify and define the generic features of classes of systems. To characterize the basis for general principles through generic abstraction and reasoning about possibility spaces, I coin the term constraint-based generality. I show that constraint-based generality is distinct from other types of generality in biology, and argue that general principles play a unifying role that does not entail theory reduction. (shrink)

Authors frequently refer to gene-based selection in biological evolution, the reaction of the immune system to antigens, and operant learning as exemplifying selection processes in the same sense of this term. However, as obvious as this claim may seem on the surface, setting out an account of “selection” that is general enough to incorporate all three of these processes without becoming so general as to be vacuous is far from easy. In this target article, we set out such (...) a general account of selection to see how well it accommodates these very different sorts of selection. The three fundamental elements of this account are replication, variation, and environmental interaction. For selection to occur, these three processes must be related in a very specific way. In particular, replication must alternate with environmental interaction so that any changes that occur in replication are passed on differentially because of environmental interaction. One of the main differences among the three sorts of selection that we investigate concerns the role of organisms. In traditional biological evolution, organisms play a central role with respect to environmental interaction. Although environmental interaction can occur at other levels of the organizational hierarchy, organisms are the primary focus of environmental interaction. In the functioning of the immune system, organisms function as containers. The interactions that result in selection of antibodies during a lifetime are between entities (antibodies and antigens) contained within the organism. Resulting changes in the immune system of one organism are not passed on to later organisms. Nor are changes in operant behavior resulting from behavioral selection passed on to later organisms. But operant behavior is not contained in the organism because most of the interactions that lead to differential replication include parts of the world outside the organism. Changes in the organism's nervous system are the effects of those interactions. The role of genes also varies in these three systems. Biological evolution is gene-based (i.e., genes are the primary replicators). Genes play very different roles in operant behavior and the immune system. However, in all three systems, iteration is central. All three selection processes are also incredibly wasteful and inefficient. They can generate complexity and novelty primarily because they are so wasteful and inefficient. Key Words: evolution; immunology; interaction; operant behavior; operant learning; replication; selection; variation. (shrink)

This is the first of two articles in which I reflect on “generalized Darwinism” as currently discussed in evolutionary economics. I approach evolutionary economics by the roundabouts of evolutionary epistemology and the philosophy of biology, and contrast evolutionary economists’ cautious generalizations of Darwinism with “imperialistic” proposals to unify the behavioral sciences. I then discuss the continued resistance to biological ideas in the social sciences, focusing on the issues of naturalism and teleology. In the companion article (Callebaut, Biol Theory 6. (...) doi: 10.1007/s13752-013-0087-1, 2011, this issue) I assess generalized Darwinism, concentrating on the roles of theory and model building, generative replication, and the relation between selection and self-organization; and I point to advances in biology that promise to be more fruitful as sources of inspiration for evolutionary economics than the project to generalize Darwinism in its current, “hardened Modern Synthesis” form. (shrink)

Understanding biological systems in terms of scientific materialism has arguably reached a frontier, leaving fundamental questions about their complexity unanswered. In 1998, Friedrich Cramer proposed a general resonance theory as a way forward. His theory builds on the extension of the quantum physical duality of matter and wave to the macroscopic world. According to Cramer’ theory, agents constituting biological systems oscillate, akin to musical soundwaves, at specific eigenfrequencies. Biological system dynamics can be described as “Symphonies of Life” emerging from (...) the resonance (and dissonance) of eigenfrequencies within the interacting collective. His theory has potential for studying biological problems of increasing complexity in a fast‐changing Anthropocene from a new and transdisciplinary angle. Despite data becoming increasingly available for analyses, Cramer's theory remains ignored and therefore untested a quarter century after its publication. This paper discusses how the theory can move to quantitative assessments and application. Cramer's general resonance theory deserves revival. (shrink)

A standard norm of reaction (NoR) is a graphical depiction of the phenotypic value of some trait of an individual genotype in a population as a function of an environmental parameter. NoRs thus depict the phenotypic plasticity of a trait. The topological properties of NoRs for sets of different genotypes can be used to infer the presence of (non-linear) genotype-environment interactions. While it is clear that many NoRs are adaptive, it is not yet settled whether their evolutionary etiology should be (...) explained by selection on the mean phenotypic trait values in different environments or whether there are specific genes conferring plasticity. If the second alternative is true the NoR is itself an object of selection. Generalized NoRs depict plasticity at the level of populations or subspecies within a species, species within a genus, or taxa at higher levels. Historically, generalized NoRs have routinely been drawn though rarely explicitly recognized as such. Such generalized NoRs can be used to make evolutionary inferences at higher taxonomic levels in a way analagous to how standard NoRs are used for microevolutionary inferences. (shrink)

Due to the variation, contingency and complexity of living systems, biology is often taken to be a science without fundamental theories, laws or general principles. I revisit this question in light of the quest for design principles in systems biology and show that different views can be reconciled if we distinguish between different types of generality. The philosophical literature has primarily focused on generality of specific models or explanations, or on the heuristic role of abstraction. This paper (...) takes a different approach in emphasizing a theory-constituting role of general principles. Design principles signify general dependencyrelations between structures and functions, given a set of formally defined constraints. I contend that design principles increase our understanding of living systems by relating specific models to general types. The categorization of types is based on a delineation of the scope of biological possibilities, which serves to identify and define the generic features of classes of systems. To characterize the basis for general principles through generic abstraction and reasoning about possibility spaces, I coin the term constraint-based generality. I show that constraintbased generality is distinct from other types of generality in biology, and argue that general principles play a unifying role that does not entail theory reduction. (shrink)

This paper presents an alternative conceptual foundation for biological evolution. First the causal and statistical perspectives on evolutionary fitness are analyzed, finding them to implicitly depend on each other, and hence cannot be individually fundamental. It is argued that this is an instance of a relativistic perspective over evolutionary phenomena. New accounts of fitness, the struggle for life, and Natural Selection are developed under this interpretation. This biological relativism is unique in that it draws from General Relativity in physics, (...) unlike previous theories that drew upon statistical mechanics or Newtonian dynamics. A mathematical law of evolutionary change, as well as new theoretical biological concepts to underpin it, are likewise developed. The law and theory are then applied to give examples of how both cornerstones and edge cases can be understood using these new methods. Using General Relativistic Biology provides fresh insight into evolution, all while preserving the core, canonical scientific research program. (shrink)

Activity anorexia illustrates selection of behavior at the biological, behavioral, and neural levels. Based on evolutionary history, food depletion increases the reinforcement value of physical activity that, in turn, decreases the reinforcement effectiveness of eating – resulting in activity anorexia. Neural opiates participate in the selection of physical activity during periods of food depletion.

Hull et al.'s analysis of operant behavior in terms of interaction and replication does not seem consistent with a genuine selection model. The putative replicators do not replicate, and the overall process is more reminiscent of directed mutation than of natural selection. General analogies between natural selection and operant reinforcement are too superficial to be of much scientific use.

Many analogies exist between the process of evolution by natural selection and of learning by reinforcement and punishment. A full extension of the evolutionary analogy to learning to include analogues of the fitness, genotype, development, environmental influences, and phenotype concepts makes possible a single theory of the learning process able to encompass all of the elementary procedures known to yield learning.

The interaction of the organism with the environment requires not only reactive, but also active behavior which helps subject to meet the challenge of the uncertainty of the environment. A positive feedback between active behavior and immune system makes the selection process effective.

In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian.

Seeking parallels among disciplines can have both risks and benefits. Finding parallels may be a vacuous exercise in categorization, generating no new insights. And pointing to analogous functions may cause us to treat them as homologous. Hull et al. have provided a basis for the generation of insights in different selectionist areas, without confusing analogy with homology.

The comparison between biological and social macroevolution is a very important (though insufficiently studied) subject whose analysis renders new significant possibilities to comprehend the processes, trends, mechanisms, and peculiarities of each of the two types of macroevolution. Of course, there are a few rather important (and very understandable) differences between them; however, it appears possible to identify a number of fundamental similarities. One may single out at least three fundamental sets of factors determining those similarities. First of all, those similarities (...) stem from the fact that in both cases we are dealing with very complex non-equilibrium (but rather stable) systems whose principles of functioning and evolution are described by the General Systems' Theory, as well as by a number of cybernetic principles and laws. -/- Secondly, in both cases we do not deal with isolated systems; in both cases we deal with a complex interaction between systems of organic systems and external environment, whereas the reaction of systems to external challenges can be described in terms of certain general principles (that, however, express themselves rather differently within the biological reality, on the one hand, and within the social reality, on the other). -/- Thirdly, it is necessary to mention a direct ‘genetic’ link between the two types of macroevolution and their mutual influence. -/- It is important to emphasize that the very similarity of the principles and regularities of the two types of macroevolution does not imply their identity. Rather significant similarities are frequently accompanied by enormous differences. For example, genomes of the chimpanzees and the humans are very similar – with differences constituting just a few per cent; however, there are enormous differences with respect to intellectual and social differences of the chimpanzees and the humans hidden behind the apparently ‘insignificant’ difference between the two genomes. Thus, in certain respects it appears reasonable to consider the biological and social macroevolution as a single macroevolutionary process. This implies the necessity to comprehend the general laws and regularities that describe this process, though their manifestations may display significant variations depending on properties of a concrete evolving entity (biological, or social one). An important notion that may contribute to the improvement of the operationalization level as regards the comparison between the two types of macroevolution is the one that we suggested some time ago – the social aromorphosis (that was developed as a counterpart to the notion of biological aromorphosis well established within Russian evolutionary biology). We regard social aromorphosis as a rare qualitative macrochange that increases in a very significant way complexity, adaptability, and mutual influence of the social systems, that opens new possibilities for social macrodevelopment. In our paper we discuss a number of regularities that describe biological and social macroevolution and that employ the notions of social and biological aromorphosis such as ones of the module evolution (or the evolutionary ‘block assemblage’), ‘payment for arogenic progress’ etc. (shrink)

We argue that broad, simplegeneralizations, not specifically linked tocontingencies, will rarely approach truth in ecologyand evolutionary biology. This is because mostinteresting phenomena have multiple, interactingcauses. Instead of looking for single universaltheories to explain the great diversity of naturalsystems, we suggest that it would be profitable todevelop general explanatory frameworks. A frameworkshould clearly specify focal levels. The process orpattern that we wish to study defines our level offocus. The set of potential and actual states at thefocal level interacts with (...) conditions at thecontiguous lower and upper levels of organization,through sets of many-to-one and one-to-manyconnections. The number of initiating conditions andtheir permutations at the lower level define thepotential states at the focal level, whereas theactual state is constrained by the upper-levelboundary conditions. The most useful generalizationsare explanatory frameworks, which are road maps tosolutions, rather than solutions themselves. Suchframeworks outline what is understood about boundaryconditions and initiating conditions so that aninvestigator can pick and choose what is required toeffectively understand a specific event or situation. We discuss these relationships in terms of examplesinvolving sex ratio and mating behavior, competitivehierarchies, insect life-histories and the evolutionof sex. (shrink)

Abstract.Stuart Kauffman's proposal in Investigations to ground a “general biology” in the laws of self‐organization governing systems of autonomous agents runs up against the methodological problem of how to integrate formal mathematical with semantic and semiotic approaches to the study of evolutionary development. Gilles Deleuze's concept of the virtual and C. S. Peirce's system of existential graphs provide a theoretical framework and practical art for answering this problem of method by modeling the creative event of collective self‐organization as (...) both represented and practiced in the scientific community. (shrink)

Habituation, a form of non‐associative learning, isno longer studied exclusively within the fields of psychology and neuroscience. Indeed, the same stimulus–response pattern is observed at the molecular, cellular, and organismal scales and is not dependent upon the presence of neurons. Hence, a more inclusive theory is required to accommodate aneural forms of habituation. Here an abstraction of the habituation process that does not rely upon particular biological pathways or substrates is presented. Instead, five generalizable elements that define the habituation process (...) are operationalized. The formulation can be applied to interrogate systems as they respond to several stimulation paradigms, providing new insights and supporting existing behavioral data. The model can be used to deduce the relative contribution of elements that contribute to the measurable output of the system. The results suggest that habituation serves as a general biological strategy that any system can implement to adaptively respond to harmless, repetitive stimuli. (shrink)

Does biology have general laws that apply to all levels of biological organisation, across all evolutionary time? In their book “Biology’s first law: the tendency for diversity and complexity to increase in evolutionary systems” (2010), Daniel McShea and Robert Brandon propose that the most fundamental law of biology is that all levels of biological organisation have an underlying tendency to become more complex and diverse over time. A range of processes, most notably selection, can prevent the (...) expression of this tendency, but they predict that, on average, we should see that lineages tend toward greater diversity and complexity, driven by fundamentally neutral processes. Their hypothesis can be summarised as “diversity is easy, stasis is hard”. Here, I consider evidence for this “zero force evolutionary law”. It provides a fair description of evolutionary change at the genomic level, but the predictions of the proposed law are not met for broad scale patterns in the evolution of the animal kingdom. (shrink)

Despite wide acceptance that the attributes of living creatures have appeared through a cumulative evolutionary process guided chiefly by natural selection, many human activities have seemed analytically inaccessible through such an approach. Prominent evolutionary biologists, for example, have described morality as contrary to the direction of biological evolution, and moral philosophers rarely regard evolution as relevant to their discussions. -/- The Biology of Moral Systems adopts the position that moral questions arise out of conflicts of interest, and that moral (...) systems are ways of using confluences of interest at lower levels of social organiation to deal with conflicts of interest at higher levels. Moral systems are described as systems of indirect reciprocity: humans gain and lose socially and reproductively not only by direct transactions, but also by the reputations they gain from the everyday flow of social interactions. -/- The author develops a general theory of human interests, using senescence and effort theory from biology, to help analye the patterning of human lifetimes. He argues that the ultimate interests of humans are reproductive, and that the concept of morality has arisen within groups because of its contribution to unity in the context, ultimately, of success in intergroup competition. He contends that morality is not easily relatable to universals, and he carries this argument into a discussion of what he calls the greatest of all moral problems, the nuclear arms race. (shrink)

The biological functions debate is a perennial topic in the philosophy of science. In the first full-length account of the nature and importance of biological functions for many years, Justin Garson presents an innovative new theory, the 'generalized selected effects theory of function', which seamlessly integrates evolutionary and developmental perspectives on biological functions. He develops the implications of the theory for contemporary debates in the philosophy of mind, the philosophy of medicine and psychiatry, the philosophy of biology, and (...) class='Hi'>biology itself, addressing issues ranging from the nature of mental representation to our understanding of the function of the human genome. Clear, jargon-free, and engagingly written, with accessible examples and explanatory diagrams to illustrate the discussion, his book will be highly valuable for readers across philosophical and scientific disciplines. (shrink)

Is it possible to know anything about life we have not yet encountered? We know of only one example of life: our own. Given this, many scientists are inclined to doubt that any principles of Earth’s biology will generalize to other worlds in which life might exist. Let’s call this the “N = 1 problem.” By comparison, we expect the principles of geometry, mechanics, and chemistry would generalize. Interestingly, each of these has predictable consequences when applied to biology. (...) The surface-to-volume property of geometry, for example, limits the size of unassisted cells in a given medium. This effect is real, precise, universal, and predictive. Furthermore, there are basic problems all life must solve if it is to persist, such as resistance to radiation, faithful inheritance, and energy regulation. If these universal problems have a limited set of possible solutions, some common outcomes must consistently emerge. In this chapter, I discuss the N = 1 problem, its implications, and my response (Mariscal 2014). I hold that our current knowledge of biology can justify believing certain generalizations as holding for life anywhere. Life on Earth may be our only example of life, but this is only a reason to be cautious in our approach to life in the universe, not a reason to give up altogether. In my account, a candidate biological generalization is assessed by the assumptions it makes. A claim is accepted only if its justification includes principles of evolution, but no contingent facts of life on Earth. (shrink)

An influential position in the philosophy of biology claims that there are no biological laws, since any apparently biological generalization is either too accidental, fact-like or contingent to be named a law, or is simply reducible to physical laws that regulate electrical and chemical interactions taking place between merely physical systems. In the following I will stress a neglected aspect of the debate that emerges directly from the growing importance of mathematical models of biological phenomena. My main aim is (...) to defend, as well as reinforce, the view that there are indeed laws also in biology, and that their difference in stability, contingency or resilience with respect to physical laws is one of degrees, and not of kind . (shrink)

History and Philosophy of Biology summarizes the major philosophical ideas that have attended the development of science in general and of biology in particular. The book then explores how the techniques and the concepts of the physical sciences have impacted biology. A reductionist approach to biology -- anatomy, physiology, genetics -- complements the study of evolution by natural selection and an ecological perspective. The final section of the book explores several examples of the influence of (...) science on society, and of society on science. Each of 46 chapters of History and Philosophy of Biology has been or could be the topic of a major tome. The book is unique in that it explores the web of interactions among issues of philosophy, techniques and concepts of the physical sciences, fields of biology, and the diverse relationships between society and science. The book should appeal to readers of Scientific American or the New York Review of Books even if they are not trained biologists. It is a good text, or additional reading, for an advanced undergraduate course treating history and/or philosophy of biology or of science in general. (shrink)

The article defends the doctrine that Linnaean taxa, including species, have essences that are, at least partly, underlying intrinsic, mostly genetic, properties. The consensus among philosophers of biology is that such essentialism is deeply wrong, indeed incompatible with Darwinism. I argue that biological generalizations about the morphology, physiology, and behavior of species require structural explanations that must advert to these essential properties. The objection that, according to current “species concepts,” species are relational is rejected. These concepts are primarily concerned (...) with what it is for a kind to be a species and throw little light on the essentialist issue of what it is for an organism to be a member of a particular kind. Finally, the article argues that this essentialism can accommodate features of Darwinism associated with variation and change. (shrink)

“Biological Naturalism” is a name I have given to an approach to what is traditionally called the mind-body problem. The way I arrived at it is typical of the way I work: try to forget about the philosophical history of a problem and remind yourself of what you know for a fact. Any philosophical theory has to be consistent with the facts. Of course, something we think is a fact may turn out not to be, but we have to start (...) with our best information. Biological Naturalism is a theory of mental states in general but as this book is about consciousness I will present it here as a theory of consciousness. (shrink)

This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism for countering (...) heat shock—the heat shock response system—in Escherichia coli bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation. (shrink)

‘‘Theoretical biology’’ is a surprisingly heter- ogeneous field, partly because it encompasses ‘‘doing the- ory’’ across disciplines as diverse as molecular biology, systematics, ecology, and evolutionary biology. Moreover, it is done in a stunning variety of different ways, using anything from formal analytical models to computer sim- ulations, from graphic representations to verbal arguments. In this essay I survey a number of aspects of what it means to do theoretical biology, and how they compare with the (...) allegedly much more restricted sense of theory in the physical sciences. I also tackle a recent trend toward the presentation of all-encompassing theories in the biological sciences, from general theories of ecology to a recent attempt to provide a conceptual framework for the entire set of biological disciplines. Finally, I discuss the roles played by philosophers of science in criticizing and shap- ing biological theorizing. (shrink)

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss (...) how mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena, where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations. I offer general conclusions for philosophical accounts of explanation. (shrink)

In his famous article “The Unreasonable Effectiveness of Mathematics in the Natural Sciences” Eugen Wigner argues for a unique tie between mathematics and physics, invoking even religious language: “The miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve”. The possible existence of such a unique match between mathematics and physics has been extensively discussed by philosophers and historians of mathematics. Whatever the merits (...) of this claim are, a further question can be posed with regard to mathematization in science more generally: What happens when we leave the area of theories and laws of physics and move over to the realm of mathematical modeling in interdisciplinary contexts? Namely, in modeling the phenomena specific to biology or economics, for instance, scientists often use methods that have their origin in physics. How is this kind of mathematical modeling justified? (shrink)