The basic idea behind the Competitive Exclusion Principle is that species that have similar or identical niches cannot stably coexist in the same place for long periods of time when their common resources are limiting. A more exact definition of the CEP states that, in equilibrium, n number of sympatric species competing for a common set of limiting resources cannot stably coexist indefinitely on fewer than n number of resources. The magnitude or intensity of competition between species is proportional to (...) the degree of overlap in their niches or use of resources. Species that stably coexist do so because there are “important differences” in their niches or use of common limiting resources. (shrink)

It is often argued that biological generalizations have a distinctive and special status by comparison with the generalizations of other natural sciences, such as that biological generalizations are riddled with exceptions defying systematic and simple treatment. This special status of biology is used as a premise in arguments that posit a deprived explanatory, nomological, or methodological status in the biological sciences. I will discuss the traditional and still almost universally held idea that the biological sciences cannot deal with exceptions and (...) application conditions of their generalizations with their own distinctive and proprietary explanantia, but need the help of lower-level sciences to carry out this task. The idea of lower-level explanations of exceptions is connected to the idea that the biological sciences need lower-level sciences to better themselves and to the idea that biological sciences cannot provide reliable and extrapolatable results or explanations by themselves. I present counterexamples to the idea of lower-level explanations of exceptions in biology. I also discuss and refute more general arguments why the idea of lower-level explanations of exceptions has been held to hold in the special sciences, such as the screening-off and openness arguments. This suggest that there might be nothing special about the biological sciences vis-à-vis the more fundamental natural sciences, such as physics insofar as explanations of exceptions are concerned, and that the biological sciences can provide reliable and extrapolatable results or explanations by themselves. (shrink)

In addition to their core explanatory and predictive assumptions, scientific models include simplifying assumptions, which function as idealizations, approximations, and abstractions. There are methods to investigate whether simplifying assumptions bias the results of models, such as robustness analyses. However, the equally important issue – the focus of this paper – has received less attention, namely, what are the methodological and epistemic strengths and limitations associated with different simplifying assumptions. I concentrate on one type of simplifying assumption, the use of mega (...) parameters as abstractions in ecological models. First, I argue that there are two kinds of mega parameters qua abstractions, sufficient parameters and aggregative parameters, which have gone unnoticed in the literature. The two are associated with different heuristics, holism and reductionism, which many view as incompatible. Second, I will provide a different analysis of abstractions and the associated heuristics than previous authors. Reductionism and holism and the accompanying abstractions have different methodological and epistemic functions, strengths, and limitations, and the heuristics should be viewed as providing complementary research perspectives of cognitively limited beings. This is then, third, used as a premise to argue for epistemic and methodological pluralism in theoretical ecology. Finally, the presented taxonomy of abstractions is used to comment on the current debate whether mechanistic accounts of explanation are compatible with the use of abstractions. This debate has suffered from an abstract discussion of abstractions. With a better taxonomy of abstractions the debate can be resolved. (shrink)

Philosophers have traditionally addressed the issue of scientific unification in terms of theoretical reduction. Reductive models, however, cannot explain the occurrence of unification in areas of science where successful reductions are hard to find. The goal of this essay is to analyse a concrete example of integration in biology—the developmental synthesis—and to generalize it into a model of scientific unification, according to which two fields are in the process of being unified when they become explanatorily relevant to each other. I (...) conclude by suggesting that this methodological conception of unity, which is independent of the debate on the metaphysical foundations of science, is closely connected to the notion of interdisciplinarity. 1 Introduction2 Some Troubles with Theory Reduction3 Interfield and Mechanistic Unification4 Foundations of the Developmental Synthesis5 Explanatory Relevance6 Concluding Remarks. (shrink)

Biologists employ a suggestive metaphor to describe the complexities of molecular interactions within cells and embryos: cytological components are said to be part of “ecosystems” that integrate them in a complex network of relations with many other entities. The aim of this essay is to scrutinize the molecular ecosystem, a metaphor that, despite its longstanding history, has seldom be articulated in detail. I begin by analyzing some relevant analogies between the cellular environment and the biosphere. Next, I discuss the applicability (...) of the molecular ecosystem concept in actual scientific practice. (shrink)

Biologists and philosophers of science have recently called for an extension of evolutionary theory. This so-called ‘extended evolutionary synthesis’ seeks to integrate developmental processes, extra-genetic forms of inheritance, and niche construction into evolutionary theory in a central way. While there is often agreement in evolutionary biology over the existence of these phenomena, their explanatory relevance is questioned. Advocates of EES posit that their perspective offers better explanations than those provided by ‘standard evolutionary theory’. Still, why this would be the case (...) is unclear. Usually, such claims assume that EES’s superior explanatory status arises from the pluralist structure of EES, its different problem agenda, and a growing body of evidence for the evolutionary relevance of developmental phenomena. However, what is usually neglected in this debate is a discussion of what the explanatory standards of EES actually are, and how they differ from prevailing standards in SET. In other words, what is considered to be a good explanation in EES versus SET? To answer this question, we present a theoretical framework that evaluates the explanatory power of different evolutionary explanations of the same phenomena. This account is able to identify criteria for why and when evolutionary explanations of EES are better than those of SET. Such evaluations will enable evolutionary biology to find potential grounds for theoretical integration. (shrink)

Evolutionary developmental biology represents a paradigm shift in the understanding of the ontogenesis and evolutionary progression of the denizens of the natural world. Given the empirical successes of the evo-devo framework, and its now widespread acceptance, a timely and important task for the philosophy of biology is to critically discern the ontological commitments of that framework and assess whether and to what extent our current metaphysical models are able to accommodate them. In this paper, I argue that one particular model (...) is a natural fit: an ontology of dispositional properties coherently and adequately captures the crucial casual-cum-explanatory role that the fundamental elements of evo-devo play within that framework. (shrink)

This paper sketches a causal account of scientific explanation designed to sustain the judgment that high-level, detail-sparse explanations—particularly those offered in biology—can be at least as explanatorily valuable as lower-level counterparts. The motivating idea is that complete explanations maximize causal economy: they cite those aspects of an event’s causal run-up that offer the biggest-bang-for-your-buck, by costing less (in virtue of being abstract) and delivering more (in virtue making the event stable or robust).