The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research. My purpose is not only to suggest a new taxonomy of robustness, but also to argue that previous authors have concentrated on a narrow sense of robustness analysis, which they have inadequately distinguished (...) from other investigations of models such as sensitivity analysis. (shrink)

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. (shrink)

There appear to be no biological regularities that have the properties traditionally associated with laws, such as an unlimited scope or holding in all or many possible background conditions. Mitchell, Lange, and others have therefore suggested redefining laws to redeem the lawlike status of biological regularities. These authors suggest that biological regularities are lawlike because they are pragmatically or paradigmatically similar to laws or stable regularities. I will review these re-definitions by arguing both that there are difficulties in applying their (...) accounts to biology and difficulties in the accounts themselves, which suggests that the accounts are not adequate to redeem the lawlike status of biological regularities. Finally, I will suggest a new account of laws that also shows how non-laws might function in some of the roles of laws. (shrink)

The contingency of biological regularities—and its implications for the existence of biological laws—has long puzzled biologists and philosophers. The best argument for the contingency of biological regularities is John Beatty’s evolutionary contingency thesis, which will be re-analyzed here. First, I argue that in Beatty’s thesis there are two versions of strong contingency used as arguments against biological laws that have gone unnoticed by his commentators. Second, Beatty’s two different versions of strong contingency are analyzed in terms of two different stabilities (...) of regularities. Third, I argue that Beatty and his commentators have focused on the more ineffective trajectory stability version of the argument, whereas the constancy stability version provides a more substantial and applicable argument against the existence of biological laws. Fourth, I develop a counterexample to Beatty’s thesis. Finally, I discuss the possibility of evolution producing repeatable and general non-lawlike regularities and patterns by utilizing the notion of generative entrenchment and by criticizing the thesis of multiple realizability of biological properties. (shrink)

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)

We critically analyze Alexander Rosenberg’s argument based on the multiple realizability of biological properties that there are no biological laws. The argument is intuitive and suggestive. Nevertheless, a closer analysis reveals that the argument rests on dubious assumptions about the nature of natural selection, laws of nature, and multiple realizability. We also argue that the argument is limited in scope, since it applies to an outmoded account of laws and the applicability of the argument to other more promising accounts of (...) laws is questionable. Another concern of ours is that the relation between multiple realizability and natural selection is more complex than Rosenberg acknowledges. Finally, we claim that an explanation for why Rosenberg’s argument appears persuasive and appealing is that the argument is based on an inflated concept of multiple realizability that rests on unreliable intuitions concerning what counts as a different realization of the same property. Consequently, we argue that the argument is at best inconclusive and at worst false insofar as its implications for the existence of biological laws are concerned. (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)

I analyze here biological regression equations known in the literature as allometries and scaling laws. My focus is on the alleged lawlike status of these equations. In particular I argue against recent views that regard allometries and scaling laws as representing universal, non-continent, and/or strict biological laws. Although allometries and scaling laws appear to be generalizations applying to many taxa, they are neither universal nor exceptionless. In fact there appear to be exceptions to all of them. Nor are the constants (...) in allometries and scaling laws truly constant, stable, or universal in character, but vary in value across different taxa and background conditions. Moreover, these equations represent evolutionary, strongly contingent generalizations, which threatens their lawlike status. Lastly, allometries and scaling laws do not offer stable probabilities to which they hold in different backgrounds. I further suggest that many allometries and scaling laws function to elucidate explananda rather than explanantia or covering laws. (shrink)

This paper provides the first systematic epistemological account of simulated data in empirical science. We focus on the epistemic issues modelers face when they generate simulated data to solve problems with empirical datasets, research tools, or experiments. We argue that for simulated data to count as epistemically reliable, a simulation model does not have to mimic its target. Instead, some models take empirical data as a target, and simulated data may successfully mimic such a target even if the model does (...) not. We show how to distinguish between simulated and empirical data, and we also offer a definition of simulation that can accommodate Monte Carlo models. We shed light on the epistemology of simulated data by providing a taxonomy of four different mimicking relations that differ concerning the nature of the relation or relata. We illustrate mimicking relations with examples from different sciences. Our main claim is that the epistemic evaluation of simulated data should start with recognizing the diversity of mimicking relations rather than presuming that only one relation existed. (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)