Ecologists use a remarkable range of methods and techniques to understand complex, inherently variable, and functionally diverse entities and processes across a staggering range of spatial, temporal and interactive scales. These multiple perspectives make ecology very different to the exemplar of science often presented by philosophers. In Philosophical Foundations for the Practices of Ecology, designed for graduate students and researchers, ecology is put into a new philosophical framework that engages with this inherent pluralism while still placing constraints on the ways (...) that we can investigate and understand nature. The authors begin by exploring the sources of variety in the practice of ecology and how these have led to the current conceptual confusion. They argue that the solution is to adopt the approach of constrained perspectivism and go on to explore the ontological, metaphysical, and epistemological aspects of this position and how it can be used in ecological research and teaching"--Provided by publisher. (shrink)

"How do we go about weighing evidence, testing hypotheses and making inferences? According to the model of 'inference to the Best explanation', we work out what to inter from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In inference to the Best Explanation, Peter Lipton gives this important and influential idea the development and assessment it deserves." "The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contractive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of Inference to the Best Explanation has also been updated throughout and incudes a new bibliography."--BOOK JACKET. (shrink)

In this paper I criticize the commonly accepted idea that the generalizations of the special sciences should be construed as ceteris paribus laws. This idea rests on mistaken assumptions about the role of laws in explanation and their relation to causal claims. Moreover, the major proposals in the literature for the analysis of ceteris paribus laws are, on their own terms, complete failures. I sketch a more adequate alternative account of the content of causal generalizations in the special sciences which (...) I argue should replace the ceteris paribus conception. (shrink)

Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...) what consequences those tradeoffs have for theoretical practice. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

Conducted almost exclusively at the epistemological level the scientific realism debate often ignores metaphysical niceties. In the face of the scientific realist’s systematic appeal to metaphysical notions like causation and natural kinds the neglect seems dissonant. Chakravartty aspires to overturn it with a bespoke metaphysics for scientific realism. In pursuing this aim, he undrapes a more comprehensive vision of the scientific realist viewpoint, including a distinctive epistemology.

Recently, several philosophers have challenged the view that evolutionary theory is usefully understood by way of an analogy with Newtonian mechanics. Instead, they argue that evolutionary theory is merely a statistical theory. According to this alternate approach, natural selection and random genetic drift are not even causes, much less forces. I argue that, properly understood, the Newtonian analogy is unproblematic and illuminating. I defend the view that selection and drift are causes in part by attending to a pair of important (...) distinctions—that between process and product and that between natural selection and fitness. (shrink)

The Nature of Selection is a straightforward, self-contained introduction to philosophical and biological problems in evolutionary theory. It presents a powerful analysis of the evolutionary concepts of natural selection, fitness, and adaptation and clarifies controversial issues concerning altruism, group selection, and the idea that organisms are survival machines built for the good of the genes that inhabit them. "Sober's is the answering philosophical voice, the voice of a first-rate philosopher and a knowledgeable student of contemporary evolutionary theory. His book merits (...) broad attention among both communities. It should also inspire others to continue the conversation."-Philip Kitcher, Nature "Elliott Sober has made extraordinarily important contributions to our understanding of biological problems in evolutionary biology and causality. The Nature of Selection is a major contribution to understanding epistemological problems in evolutionary theory. I predict that it will have a long lasting place in the literature."-Richard C. Lewontin. (shrink)

In this volume, the authors discuss what practical contributions ecology can and can't make in applied science and environmental problem solving. In the first section, they discuss conceptual problems that have often prevented the formulation and evaluation of powerful, precise, general theories, explain why island biogeography is still beset with controversy and examine the ways that science is value laden. In the second section, they describe how ecology can give us specific answers to practical environmental questions posed in individual case (...) studies, and argue for a new way to look at scientific error. A case study using the Florida panther is examined in the light of these findings. (shrink)

It has not been sufficiently considered in philosophical discussions of ceteris paribus (CP) laws that distinct kinds of CP-laws exist in science with rather different meanings. I distinguish between (1.) comparative CP-laws and (2.) exclusive CP-laws. There exist also mixed CP-laws, which contain a comparative and an exclusive CP-clause. Exclusive CP-laws may be either (2.1) definite, (2.2) indefinite or (2.3) normic. While CP-laws of kind (2.1) and (2.2) exhibit deductivistic behaviour, CP-laws of kind (2.3) require a probabilistic or non-monotonic reconstruction. (...) CP-laws of kind (1) may be both deductivistic or probabilistic. All these kinds of CP-laws have empirical content by which they are testable, except CP-laws of kind (2.2) which are almost vacuous. Typically, CP-laws of kind (1) express invariant correlations, CP-laws of kind (2.1) express closed system laws of physical sciences, and CP-laws of kind (2.3) express normic laws of non-physical sciences based on evolution-theoretic stability properties. (shrink)

Environmental protection isn't what it used to be. During the 1960s and 1970s, environmentalists enacted a legislative agenda that seems like a dream today: statutes like the Clean Air and Clean Wa...

In this paper, I adopt the view that if general forces or processes can be detected in ecology, then the principles or models that represent them should provide predictions that are approximately correct and, when not, should lead to the sorts of intervening factors that usually make trouble. I argue that Lotka–Volterra principles do not meet this standard; in both their simple “strategic” and their complex “tactical” forms they are not approximately correct of the findings of the laboratory experiments and (...) historical studies most likely to confirm them; nor do they instruct ecologists where to look for likely intervening factors. Evidence drawn from long-term case studies and other available data sets suggests that the populations of predators and their prey are not regulated by an interaction between them but are controlled by transient, contingent, and accidental events that affect each animal and each population individualistically. This paper argues that the presence of general forces or processes in ecology should be determined by comparing competing models of these forces not just to each other or to a null model but also to case studies that may challenge theoretical approaches with convincing individualistic causal accounts of the phenomena. (shrink)

In this essay, I argue that uneliminated idealizations pose a serious problem for scientific realism. I consider one method for “de-idealizing” models—robustness analysis. However, I argue that unless idealizations are eliminated from an idealized theory and robustness analysis need not do that, scientists are not justified in believing that the theory is true. I consider one example of modeling from the biological sciences that exemplifies the problem.

In this essay I first provide an analysis of various community concepts. Second, I evaluate two of the most serious challenges to the existence of communities—gradient and paleoecological analysis respectively—arguing that, properly understood, neither threatens the existence of communities construed interactively. Finally, I apply the same interactive approach to ecosystem ecology, arguing that ecosystems may exist robustly as well. ‡I would like to thank to the participants at the Ecology and Environmental Ethics Conference at the University of Utah, the Philosophy (...) of Ecology Conference hosted by the University of Brisbane, and those participants in a session at the Philosophy of Science Association Meeting in Vancouver, British Columbia for helpful discussions of this essay. Specific thanks go to Mark Colyvan, Greg Cooper, Steve Downes, Chris Elliott, Marc Ereshefsky, Paul Griffiths, Jesse Hendrikse, Greg Mikkelson, Anya Plutynski, Kate Ritchie, Sahotra Sarkar, Kim Sterelny, and Rob Wilson. †To contact the author, please write to: Department of Philosophy, Lewis and Clark College, 0615 SW Palatine Hill Road, Portland, OR 97219; e-mail: [email protected]. (shrink)

Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...) building is successful even when models are predictively inaccurate for at least three reasons: models allow scientists to explore the possible behaviors of ecological systems; models give scientists simplified means by which they can investigate more complex systems by determining how the more complex system deviates from the simpler model; and models give scientists conceptual frameworks through which they can conduct experiments and fieldwork. Critics often mistake the purposes of model building, and once we recognize this, we can see their complaints are unjustified. Even though models in ecology are not always accurate in their assumptions and predictions, they still contribute to successful science. (shrink)

This essay explores two strategies of inquiryin ecological science. Ecologists may regardthe sites they study either as contingentcollections of plants and animals, therelations of which are place-specific andidiosyncratic, or as structured systems andcommunites that are governed by general rules,forces, or principles. Ecologists who take thefirst approach rely on observation, induction,and experiment – a case-study or historicalmethod – to determine the causes of particularevents. Ecologists who take the secondapproach, seeking to explain by inferringevents from general patterns or principles,confront four conceptual obstacles (...) which thisessay describes. Theory in ecology must (1)define and classify the object it studies,e.g., the ecosystem, and thus determine theconditions under which it remains the ``same''system through time and change. Ecologistsmust (2) find ways to reject as well as tocreate mathematical models of the ecosystem,possibly by (3) identifying efficient causes ofecosystem organization or design. Finally,ecologists will (4) show ecological theory canhelp solve environmental problems both inpristine and in human-dominated systems. Afailure to solve – or even to address – theseobstacles suggests that theoretical ecology maybecome a formal science that studies themathematical consequences of assumptionswithout regard to the relation of theseassumptions to the world. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be made on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the data deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is non-demonstrative, or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

The world’s leading environmental advisory institutions look to ecological theory and research as an objective guide for policy and resource management decision-making. In addition to various theoretical merits of doing so, it is therefore crucially important to clear up confusions about ecology’s conceptual foundations and to make plain the basic workings of inferential methods used in the science. Through discussion of key moments in the genesis of the theoretical branch of ecology, this essay elucidates a general heuristic role of teleological (...) metaphor in ecological research and defuses certain enduring confusions and misguided criticisms of current work in ecology. (shrink)

In a (2016) paper in this journal, I defuse allegations that theoretical ecological research is problematic because it relies on teleological metaphysical assumptions. Mark Sagoff offers a formal reply. In it, he concedes that I succeeded in establishing that ecologists abandoned robust teleological views long ago and that they use teleological characterizations as metaphors that aid in developing mechanistic explanations of ecological phenomena. Yet, he contends that I did not give enduring criticisms of theoretical ecology a fair shake in my (...) paper. He says this is because enduring criticisms center on concerns about the nature of ecological networks and forces, the instrumentality of ecological laws and theoretical models, and the relation between theoretical and empirical methods in ecology that that paper does not broach. Below I set apart the distinct criticisms Sagoff presents in his commentary and respond to each in turn. (shrink)

There has recently been a renewed interest in the “force” interpretation of evolutionary biology. In this article, I present the general structure of the arguments for the force interpretation and identify a problem in its overly permissive conditions for being a Newtonian force. I then attempt a solution that (1) helps to illuminate the difference between forces and other types of causes and (2) makes room for random genetic drift as a force. In particular, I argue that forces are not (...) different in kind from other types of causes but rather that forces are situated on a continuum of causes distinguished by their unifying power. †To contact the author, please write to: Department of Philosophy, University of Wisconsin–Madison, 5185 Helen C. White Hall, Madison, WI 53706; e‐mail: [email protected]. (shrink)

Environmental advisory institutions around the world operate under the assumption that theoretical ecological models (TEMs) can guide decision-making about environmental policy and natural resource management. At the same time, leading ecologists and philosophers continue to point out that it is unclear exactly how such models can usefully inform such decision-making. Much critical debate about whether and how ecology can inform practical decisions centers on confusions that are due to the fact that the workings of TEM-based research is poorly understood outside (...) ecology. This essay addresses this issue by clarifying: what TEMs are; what limitations ecologists admit such models have; and in what general ways TEM-based analyses can inform and enable decision-making in environmental policy and resource management in spite of those limitations. (shrink)

Value claims about ecological entities, their functionality, and properties take center stage in so-called “ecological” ethical and aesthetic theories. For example, the claim that the biodiversity in an old-growth forest imbues it with “value in and for itself” is an explicit value claim about an ecological property. And the claim that one can study “the aesthetics of nature, including natural objects...such as ecosystems” presupposes that natural instances of a type of ecological entity exist and can be regarded as more or (...) less aesthetically valuable. My discussion below will bear wide implications for how claims like... (shrink)

Well-known epistemologies of science have implications for how best to understand knowledge transfer (KT). Yet, to date, no serious attempt has been made explicate these particular implications. This paper infers views about KT from two popular epistemologies; what we characterize as incommensurabilitist views (after Devitt 2001; Bird 2002, 2008; Sankey and Hoyningen-Huene 2013) and voluntarist views (after van Fraassen 1984; Dupré 2001; Chakravartty 2015). We argue views of the former sort define the methodological, ontological, and social conditions under which research (...) operates within ‘different worlds’ (to use Kuhn’s expression), and entail that genuine KTs under those conditions should be difficult or even impossible. By contrast, more liberal voluntarist views recognize epistemological processes that allow for transfers across different sciences even under such conditions. After outlining these antithetical positions, we identify two kinds of KTs of two kinds present in well-known episodes in the history of ecology—specifically, successful model transfers from chemical kinetics and thermodynamics into areas of ecological research—which reveal significant limitations of incommensurabilitist views. We conclude by discussing how the selected examples support a pluralistic voluntarism regarding KT. (shrink)

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities to the (...) explanation of the role of causality in quantum mechanics. (shrink)

In this sequence of philosophical essays about natural science, the author argues that fundamental explanatory laws, the deepest and most admired successes of modern physics, do not in fact describe regularities that exist in nature. Cartwright draws from many real-life examples to propound a novel distinction: that theoretical entities, and the complex and localized laws that describe them, can be interpreted realistically, but the simple unifying laws of basic theory cannot.

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of _Inference to the Best Explanation_ has also been updated throughout and includes a new bibliography. (shrink)

The increasingly lively controversy over scientific realism has become one of the principal themes of recent philosophy. 1 In watching this controversy unfold in the rather technical way currently in vogue, it has seemed to me that it would be useful to view these contemporary disputes against the background of such older epistemological issues as fallibilism, scepticism, relativism, and the traditional realism/idealism debate. This, then, is the object of the present book, which will recon sider the newer concerns about scientific (...) realism in the context of these older philosophical themes. Historically, realism concerns itself with the real existence of things that do not "meet the eye" - with suprasensible entities that lie beyond the reach of human perception. In medieval times, discussions about realism focused upon universals. Recognizing that there are physical objects such as cats and triangular objects and red tomatoes, the medievels debated whether such "abstract objects" as cathood and triangularity and redness also exist by way of having a reality indepen dent of the concretely real things that exhibit them. Three fundamen tally different positions were defended: (1) Nominalism. Abstracta have no independent existence as such: they only "exist" in and through the objects that exhibit them. Only particulars (individual substances) exist. Abstract "objects" are existents in name only, mere thought fictions by whose means we address concrete particular things. (2) Realism. Abstracta have an independent existence as such. (shrink)

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems (...) scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

This book is a sustained examination of issues in the philosophy of ecology that have been a source of controversy since the emergence of ecology as an explicit scientific discipline. The controversies revolve around the idea of a balance of nature, the possibility of general ecological knowledge and the role of model-building in ecology. The Science of the Struggle for Existence is also a detailed treatment of these issues that incorporates both a comprehensive investigation of the relevant ecological literature and (...) the development of an explicit theoretical framework in the philosophy of science. It addresses issues in the philosophy of ecology that are of particular importance for the deployment of ecology in the solution of environmental problems. It will have a cross-disciplinary appeal and will interest students and professionals in science, the philosophy of science, and environmental studies as well as policy-makers. (shrink)

Scientific realism is the view that our best scientific theories give approximately true descriptions of both observable and unobservable aspects of a mind-independent world. Debates between realists and their critics are at the very heart of the philosophy of science. Anjan Chakravartty traces the contemporary evolution of realism by examining the most promising strategies adopted by its proponents in response to the forceful challenges of antirealist sceptics, resulting in a positive proposal for scientific realism today. He examines the core principles (...) of the realist position, and sheds light on topics including the varieties of metaphysical commitment required, and the nature of the conflict between realism and its empiricist rivals. By illuminating the connections between realist interpretations of scientific knowledge and the metaphysical foundations supporting them, his book offers a compelling vision of how realism can provide an internally consistent and coherent account of scientific knowledge. (shrink)

Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across disciplines.

This article analyzes the view of evolutionary theory as a theory of forces. The analogy with Newtonian mechanics has been challenged due to the alleged mismatch between drift and the other evolutionary forces. Since genetic drift has no direction several authors tried to protect its status as a force: denying its lack of directionality, extending the notion of force and looking for a force in physics which also lacks of direction. I analyse these approaches, and although this strategy finally succeeds, (...) this discussion overlooks the crucial point on the debate between causalists and statisticalists: the causal status of evolutionary theory. (shrink)

While many recognize that rigid historical and compositional goals are inadequate in a world where climate and other global systems are undergoing unprecedented changes, others contend that promoting ecosystem services and functions encourages practices that can ultimately lower the bar of ecological management. These worries are foregrounded in discussions about Novel Ecosystems (NEs); where some researchers and conservationists claim that NEs provide a license to trash nature as long as some ecosystem services are provided. This criticism arises from what we (...) call the " anything goes " problem created by the release of historical conditions. After explaining the notion of NE, we identify numerous substantive motivations for worrying about the anything-goes-problem and then go on to show the problem can be solved by correcting two mistaken assumptions. In short, we argue that the problem is a product of adopting an overly sparse functional perspective and one that assumes an unrealistically high degree of convergence in the trajectories of natural processes. Our analysis illuminates why such assumptions are unwarranted. Finally, we further argue that adopting an appropriate ethical framework is essential to overcoming the anything-goes-problem and suggest that a certain virtue ethics conception of ecological management provides useful resources for framing and resolving the problem. (shrink)

A community, for ecologists, is a unit for discussing collections of organisms. It refers to collections of populations, which consist (by definition) of individuals of a single species. This is straightforward. But communities are unusual kinds of objects, if they are objects at all. They are collections consisting of other diverse, scattered, partly-autonomous, dynamic entities (that is, animals, plants, and other organisms). They often lack obvious boundaries or stable memberships, as their constituent populations not only change but also move in (...) and out of areas, and in and out of relationships with other populations. Familiar objects have identifiable boundaries, for example, and if communities do not, maybe they are not objects. Maybe they do not exist at all. The question this possibility suggests, of what criteria there might be for identifying communities, and for determining whether such communities exist at all, has long been discussed by ecologists. This essay addresses this question as it has recently been taken up by philosophers of science, by examining answers to it which appeared a century ago and which have framed the continuing discussion. (shrink)

In this essay, I consider three philosophical issues that arise in the environmental sciences. First, these sciences depend on mathematical models and simulations which are highly idealized and are coupled with very uncertain data. Why should we trust these models and simulations? Second, in standard hypothesis testing, the burden of proof is in favor of the null hypothesis which claims some causal factor has no effect. The alternative hypothesis is accepted only when the likelihood of the null hypothesis is very (...) low. Recently, some have argued that we should minimize Type II errors (not rejecting a false null) rather than Type I errors (rejecting a true null) given the environmental risks involved. I consider arguments for shifting this burden of proof when possible environmental harms are significant. Finally, in debates over global climate change, much is made of the apparent consensus concerning the effects of human induced greenhouse gas emissions on average surface temperatures. However, scientific methods are structured around dissent and criticism. Is consensus-based science orthogonal are even harmful to science? (shrink)