Ecological laws: what would they be and why would they matter?

There remains considerable debate over the existence of ecological laws. However, this debate has not made use of an adequate account of what a relationship would have to be like in order for it to qualify as an ecological law. As a result, confusions have persisted not only over how to show that ecological laws do (or do not) exist, but also regarding why their existence would matter – other than to whether ecology looks like physics. I argue that ecological laws would have to possess collectively a distinctive kind of invariance under counterfactual perturbations. I call this invariance "stability." A law of physics, such as the law that all bodies travel no faster than the speed of light, is not only true, but also necessary in a physically significant sense. (A body must travel no faster than light; it couldn't do otherwise, even if it were subjected to a greater force.) Likewise, the stability of ecological laws would render them necessary in an ecologically relevant sense. Furthermore, ecological laws would differ from fundamental laws of physics in the range of counterfactual perturbations under which they are invariant. Therefore, I argue, the existence of ecological laws would make ecological explanations irreducible to even the most complete possible physical explanations of the same phenomena. Ecological laws would make ecology genuinely autonomous from physics.     

Generalizations in Ecology: A Philosophical Taxonomy

There has been a significant amount of uncertainty and controversy over the prospects for general knowledge in ecology. Environmental decision makers have begun to despair of ecology's capacity to provide anything more than case by case guidance for the shaping of environmental policy. Ecologists themselves have become suspicious of the pursuit of the kind of genuine nomothetic knowledge that appears to be the hallmark of other scientific domains. Finally, philosophers of biology have contributed to this retreat from generality by suggesting that there really are no laws in biology. This paper addresses these issues by providing a framework for thinking about general knowledge claims in ecology. It introduces a philosophical taxonomy that classifies generalizations into three broad categories – phenomenological, causal and theoretical. It then turns to the difficult problem of laws, arguing that, while there are probably no laws as that term has been understood in philosophy of science, it doesn't follow that everything in ecology is equally contingent. A mechanism for recognizing degrees of contingency in ecological generalizations is developed. The paper concludes by examining the implications of the analysis for the controversies noted at the outset.     

The anarchist's guide to ecological theory. Or, we don't need no stinkin' laws

Several ecologists have recently suggested that ecology has several laws. This conclusion contrasts with the views of some philosophers of science, who have suggested that biology cannot have laws. I argue that the debate has been confused because two very different types of law can be recognised: correlative and causal laws. Once we recognise that there is a difference, the argument against causal laws becomes stronger, and instead I suggest that ecologists should recognise that they can and do produce generalisations that are used to build models – nomological machines – that describe the ecological systems they are studying.     

Causal Regularities in the Biological World of Contingent Distributions

Former discussions of biological generalizations have focused on the question of whether there are universal laws of biology. These discussions typically analyzed generalizations out of their investigative and explanatory contexts and concluded that whatever biological generalizations are, they are not universal laws. The aim of this paper is to explain what biological generalizations are by shifting attention towards the contexts in which they are drawn. I argue that within the context of any particular biological explanation or investigation, biologists employ two types of generations. One type identifies causal regularities exhibited by particular kinds of biological entities. The other type identifies how these entities are distributed in the biological world.     

The Central Dogma as a thesis of causal specificity

I present a reconstruction of F.H.C. Crick's two 1957 hypotheses 'Sequence Hypothesis' and 'Central Dogma' in terms of a contemporary philosophical theory of causation. Analyzing in particular the experimental evidence that Crick cited, I argue that these hypotheses can be understood as claims about the actual difference-making cause in protein synthesis. As these hypotheses are only true if restricted to certain nucleic acids in certain organisms, I then examine the concept of causal specificity and its potential to counter claims about causal parity of DNA and other cellular components. I first show that causal specificity is a special kind of invariance under interventions, namely invariance of generalizations that range over finite sets of discrete variables. Then, I show that this notion allows the articulation of a middle ground in the debate over causal parity.     

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).     

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.     

Method and metaphysics in Clements's and Gleason's ecological explanations

To generate explanatory theory, ecologists must wrestle with how to represent the extremely many, diverse causes behind phenomena in their domain. Early twentieth-century plant ecologists Frederic E. Clements and Henry A. Gleason provide a textbook example of different approaches to explaining vegetation, with Clements allegedly committed, despite abundant exceptions, to a law of vegetation, and Gleason denying the law in favor of less organized phenomena. However, examining Clements's approach to explanation reveals him not to be expressing a law, and instead to be developing an explanatory structure without laws, capable of progressively integrating causal complexity. Moreover, Clements and Gleason largely agree on the causes of vegetation; but, since causal understanding here underdetermines representation, they differ on how to integrate recognized causes into general theory--that is, in their methodologies. Observers of the case may have mistakenly assumed that scientific representation across the disciplines typically aims at laws like Newton's, and that representations always reveal scientists' metaphysical commitments. Ironically, in the present case, this assumption seems to have been made even by observers who regard Clements as nai ve for his alleged commitment to an ecological law.     

Innateness as an explanatory concept

Although many of the issues surrounding innateness have received a good deal of attention lately, the basic concept of token innateness has been largely ignored. In the present paper, I try to correct this imbalance by offering an account of the innateness of token traits. I begin by explaining Stephen Stich's account of token innateness and offering a counterexample to that account. I then clarify why the contemporary biological approaches to innateness will not be able to resolve the problems that beset Stich's account. From there, I develop an alternative understanding of the innateness of token traits, what I call a causal/explanatory account. The argument to be made is that token innateness is both a causal, and an explanatory, concept. After clarifying this understanding of innateness, and showing how it handles several counterexamples to other accounts, I end with some comments on what the causal/explanatory account suggests for our understanding of innateness in general.     

Natural Selection and Drift as Individual-Level Causes of Evolution

In this paper I critically evaluate Reisman and Forber’s (Philos Sci 72(5):1113–1123, 2005) arguments that drift and natural selection are population-level causes of evolution based on what they call the manipulation condition. Although I agree that this condition is an important step for identifying causes for evolutionary change, it is insufficient. Following Woodward, I argue that the invariance of a relationship is another crucial parameter to take into consideration for causal explanations. Starting from Reisman and Forber’s example on drift and after having briefly presented the criterion of invariance, I show that once both the manipulation condition and the criterion of invariance are taken into account, drift, in this example, should better be understood as an individual-level rather than a population-level cause. Later, I concede that it is legitimate to interpret natural selection and drift as population-level causes when they rely on genuinely indeterministic events and some cases of frequency-dependent selection.     

Red-shifts and red herrings in geographical ecology

I draw attention to the need for ecologists to take spatial structure into account more seriously in hypothesis testing. If spatial autocorrelation is ignored, as it usually is, then analyses of ecological patterns in terms of environmental factors can produce very misleading results. This is demonstrated using synthetic but realistic spatial patterns with known spatial properties which are subjected to classical correlation and multiple regression analyses. Correlation between an autocorrelated response variable and each of a set of explanatory variables is strongly biased in favour of those explanatory variables that are highly autocorrelated - the expected magnitude of the correlation coefficient increases with autocorrelation even if the spatial patterns are completely independent. Similarly, multiple regression analysis finds highly autocorrelated explanatory variables "significant" much more frequently than it should. The chances of mistakenly identifying a "significant" slope across an autocorrelated pattern is very high if classical regression is used. Consequently, under these circumstances strongly autocorrelated environmental factors reported in the literature as associated with ecological patterns may not actually be significant. It is likely that these factors wrongly described as important constitute a red-shifted subset of the set of potential explanations, and that more spatially discontinuous factors (those with bluer spectra) are actually relatively more important than their present status suggests. There is much that ecologists can do to improve on this situation. I discuss various approaches to the problem of spatial autocorrelation from the literature and present a randomisation test for the association of two spatial patterns which has advantages over currently available methods.     

When logic fails ecology

Ecology plays an important role in society, informing policy and management decisions across a variety of issues. As such, regularities in processes would indicate higher levels of predictive outcomes and would reduce the amount of research required for specific issues that policy makers need addressed. Scientific laws are considered the pinnacle of success and usefulness in addressing regularities or universal truths. Ecology studies complex interactions of individuals with unique behaviors, making the identification of laws problematic. Two equations, Malthusian growth and the logistic equation, continue to receive attention and are frequently cited as exemplar laws in ecology. However, an understanding of scientific laws shows that neither are good candidates for law status. In this paper, I will discuss why ecology is not well structured for scientific laws, as they are currently understood. Finally, I will consider alternative proposals for the role of laws in ecology and alternate forms of laws that may be applicable.     

Agential autonomy and biological individuality

What is a biological individual? How are biological individuals individuated? How can we tell how many individuals there are in a given assemblage of biological entities? The individuation and differentiation of biological individuals are central to the scientific understanding of living beings. I propose a novel criterion of biological individuality according to which biological individuals are autonomous agents. First, I articulate an ecological–dynamical account of natural agency according to which, agency is the gross dynamical capacity of a goal-directed system to bias its repertoire to respond to its conditions as affordances. Then, I argue that agents or agential dynamical systems can be agentially dependent on, or agentially autonomous from, other agents and that this agential dependence/autonomy can be symmetrical or asymmetrical, strong or weak. Biological individuals, I propose, are all and only those agential dynamical systems that are strongly agentially autonomous. So, to determine how many individuals there are in a given multiagent aggregate, such as multicellular organism, a colony, symbiosis, or a swarm, we first have to identify how many agential dynamical systems there are, and then what their relations of agential dependence/autonomy are. I argue that this criterion is adequate to the extent that it vindicates the paradigmatic cases, and explains why the paradigmatic cases are paradigmatic, and why the problematic cases are problematic. Finally, I argue for the importance of distinguishing between agential and causal dependence and show the relevance of agential autonomy for understanding the explanatory structure of evolutionary developmental biology.     

Biodiversity is a chimera,and chimeras aren’t real

A recent article by Burch-Brown and Archer (Biol Philos, 2017) provides compelling arguments that biodiversity is either a natural kind or a pragmatically-valid scientific entity. I call into question three of these arguments. The first argument contends that biodiversity is a Homeostatic Property Cluster (HPC). I respond that there is no plausible homeostatic mechanism that would make biodiversity an HPC natural kind. The second argument proposes that biodiversity is a multiply-realizable functional kind. I respond that there is no shared function to ground this account. The final, and strongest, argument, is that biodiversity is an ineliminable explanans and explanandum in various subdisciplines of biology. I argue that once we look at the details of the relevant research, not only does biodiversity in a broad sense not function in explanatory roles, but we must eliminate biodiversity in favor of more specific concepts in order to make sense of the leading explanations in contemporary ecology and conservation science.     

Mechanistic analogy: how microcosms explain nature

Microcosm studies of ecological processes have been criticized for being unrealistic. However, since lack of realism is inherent to all experimental science, if lack of realism invalidates microcosm models of ecological processes, then such lack of realism must either also invalidate much of the rest of experimental ecology or its force with respect to microcosm studies must derive from some other limitation of microcosm apparatus. We believe that the logic of the microcosm program for ecological research has been misunderstood. Here, we respond to the criticism that microcosm studies play at most a heuristic role in ecology with a new account of scientific experimentation developed specifically with ecology and other environmental sciences in mind. Central to our account are the concepts of model-based reasoning and analogical inference. We find that microcosm studies are sound when they serve as models for nature and when certain properties, referred to as the essential properties, are in positive analogy. By extension, our account also justifies numerous other kinds of ecological experimentation. These results are important because reliable causal accounts of ecological processes are necessary for sound application of ecological theory to conservation and environmental science. A severe sensitivity to reliable representation of causes is the chief virtue of the microcosm approach.     

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??.