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I develop a distinction between two types of psychological hedonism. Inferential hedonism (or "I-hedonism") holds that each person only has ultimate desires regarding his or her own hedonic states (pleasure and pain). Reinforcement hedonism (or "R-hedonism") holds that each person's ultimate desires, whatever their contents are, are differentially reinforced in that person's cognitive system only by virtue of their association with hedonic states. I'll argue that accepting R-hedonism and rejecting I-hedonism provides a conciliatory position on the traditional altruism debate, and that it coheres well with the neuroscientist Anthony Dickinson's theory about the evolutionary function of hedonic states, the "hedonic interface theory." Finally, I'll defend R-hedonism from potential objections.

The following considers the role of historical fidelity in habitat reconstruction efforts. To what extent should habitat reconstruction be guided by the goal of recreating some past state of a damaged ecosystem? I consider Sarkar’s “replacement argument,” which holds that, in most habitat reconstruction efforts, there is little justification for appealing to historical fidelity. I argue that Sarkar does not provide adequate grounds for deprecating historical fidelity relative to other natural values such as biodiversity or wild nature.

We sketch a novel and improved version of Boorse’s biostatistical theory of functions. Roughly, our theory maintains that (i) functions are non-negligible contributions to survival or inclusive fitness (when a trait contributes to survival or inclusive fitness); (ii) situations appropriate for the performance of a function are typical situations in which a trait contributes to survival or inclusive fitness; (iii) appropriate rates of functioning are rates that make adequate contributions to survival or inclusive fitness (in situations appropriate for the performance of that function); and (iv) dysfunction is the inability to perform a function at an appropriate rate in appropriate situations. Based on our theory, we sketch solutions to three problems that have afflicted Boorse’s theory of function, namely, Kingma’s ([2010]) problem of the situation-specificity of functions, the problem of multi-functional traits, and the problem of how to distinguish between appropriate and inappropriate rates of functioning.

This article presents a distinct sense of ‘mechanism’, which I call the functional sense of mechanism. According to this sense, mechanisms serve functions, and this fact places substantive restrictions on the kinds of system activities ‘for which’ there can be a mechanism. On this view, there are no mechanisms for pathology; pathologies result from disrupting mechanisms for functions. Second, on this sense, natural selection is probably not a mechanism for evolution because it does not serve a function. After distinguishing this sense from similar explications of ‘mechanism’, I argue that it is ubiquitous in biology and has valuable epistemic benefits.

This chapter begins by showing why one standard way of describing the functions debate—as a debate between the selected effects theory, fitness-contribution theory, and causal role theory—is misguided. I then summarize three main conclusions. First, I argue that, to the extent that function statements are causal explanations, there are no current, viable alternatives to the selected effects theory. Second, I argue that, to the extent that we accept pluralism, we should not accept what I call (in Chap. 5) “between-discipline pluralism,” which seeks to restrict the applicability of the selected effects theory to some branches of evolutionary biology. Third, I advocate a specific version of the selected effects theory, the generalized selected effects theory, which I described earlier (in Chap. 3). In closing, I outline three outstanding problems for most theories of function. The first is function indeterminacy. Typically, there are a number of different activities associated with the performance of a function and most theories of function do not have the resources to specify which of those activities, precisely, constitutes an item’s function. Second, in many cases, a trait not only has a function, but it has an appropriate rate of functioning. For example, the heart not only has the function of beating, but it has the function of beating at a certain rate. How should we specify the appropriate rate of function? Third, for many traits that have functions, we can distinguish between appropriate and inappropriate situations for the performance of those functions. How should we modify our theories to take this into account?

This chapter focuses on the fitness-contribution theory of function, which holds, roughly, that the function of a trait consists in its typical contribution to the fitness of the organisms that possess it. I begin by surveying several different theories within this family, and I show why any plausible version must include a statistical element. I then pose three questions that any proponent of the fitness-contribution theory must answer. First, is fitness a relative notion? When one says a trait “contributes to fitness,” is one saying it contributes to fitness better than some alternative? If so, when we attribute a function to a trait, how do we specify the relevant alternatives? Second, is fitness relative to specific environments? If so, then when we attribute a function to a trait, how do we specify the relevant environments? Third, what precisely must a trait contribute to in order to have a function? Is it survival, reproduction, inclusive fitness, or something else? I then critically assess a major argument in its favor, namely, that it coheres well with the way biologists actually use the term. I consider three different interpretations of this claim and I argue that it does not, in fact, provide an advantage over the selected effects theory in this regard. I close by considering how well it satisfies the adequacy conditions set out in Chap. 1. Theorists disagree about whether the fitness-contribution theory can make sense of the explanatory and normative aspects of function and I survey those disagreements.

In this chapter, I consider three theories of function that are relatively new, in the sense that they have been developed over the last twenty years. The “weak etiological theory” says, roughly, that a trait token in an organism has a function so long as that kind of trait contributed to the fitness of that organism’s ancestors and it is inherited. It defines function in terms of inheritance and past contributions to fitness, but not selection. I assess some differences between this theory and the standard selected effects account and question the motivation for the account. A second group of theories is known as the “systems-theoretic” or “organizational” view. This is not a single theory but a family of theories based on the idea that a trait token can acquire a function by virtue of the way that very token contributes to a complex, organized, system, and thereby to its own continued persistence, as a token. I argue that the organizational approach faces liberality problems. Finally, the modal theory of function holds that the function of a trait token has to do with the behavior of that token in certain nearby possible worlds. I assess the theory and survey some problems. Bence Nanay developed the modal theory as an attempt to solve a certain circularity problem that he believes afflicts most other theories of function, but it is not clear whether there is a real problem here to be resolved.

This chapter focuses on the selected effects theory of function. According to this view, a function of a trait is whatever it was selected for by natural selection or some natural process of selection. I show how the theory plausibly accounts for the explanatory and normative aspects of function. First, if a function of a trait is whatever it was selected for by natural selection, then when one attributes a function to a trait one provides a causal explanation for why the trait currently exists. Second, since the function of a trait is determined by its history rather than current performance, it is easy to see how a trait can have a function that it cannot perform (“dysfunction”). I sketch the somewhat complex historical background of this theory. The theory was actually developed by biologists throughout the twentieth century, and in the 1970s philosophers began to explore it systematically. I survey the major criticisms of the theory and show why they are not compelling. Critics say that it does not really account for the explanatory and normative features of function; that it is inconsistent with the way biologists actually use the term; that there are (real or imaginary) counterexamples; and that it is committed to adaptationism. I close by presenting a new version of the theory, the generalized selected effects theory, which shows how brain structures (such as synapses) can acquire new functions during an individual’s lifetime through a process that is analogous in some ways to natural selection itself.

Biological functions are central to several debates in science and philosophy. In science, they play a role in debates in genetics, neuroscience, biomedicine, and ecology. In philosophy, they play a role in debates about the nature of teleological reasoning, biological information, trait classification, normativity, meaning and mental representation, health, disease, and the nature of artifacts. Yet philosophers and scientists disagree about what biological functions are, or whether there are different kinds of functions. One problem is that they do not agree about what, precisely, a philosophical theory of biological function is supposed to be or to do. I begin this chapter by discussing why functions matter to philosophy and science. I lay out three very traditional desiderata for a theory of function: namely, that the theory account for the function/accident distinction and the explanatory and normative features of function. I review three main approaches to thinking about what a theory of function should be: a conceptual analysis, a theoretical definition, and a Carnapian-style explication. I argue that it does not matter which one we accept so long as we agree that a theory of function should be reasonably constrained by actual biological usage.

Contemporary philosophical debates about biological function started in the early 1970s, and they originated from earlier, related, debates about the nature of goal directed systems. These discussions were rooted in scientific advances in the 1920s and 1930s pertaining to cybernetic machines and homeostatic systems, which appear to be purposeful or goal-directed despite not having any conscious intentions. By the 1950s, there were two major philosophical traditions for analyzing goal directedness, the behavioristic and the mechanistic. According to the behavioristic approach, favored by theorists like Gerd Sommerhoff and Richard Braithwaite, a goal directed system is one that exhibits plasticity and persistence in its outward behavior. According to the mechanistic tradition, favored by Ernest Nagel and Norbert Wiener, a goal directed system must be governed by the right sort of mechanism (such as negative feedback). Both of those traditions faced severe philosophical criticism in the 1960s and 1970s. I begin this chapter by sketching the historical background of the earlier debates about goal directedness. I then present the behavioristic analyses of Sommerhoff and Braithwaite, and enumerate several serious criticisms. I discuss mechanistic approaches, namely those of Nagel and the cyberneticists, and their critics.

This chapter is about the causal role theory of function. According to this view, roughly, a function of a part of a system consists in its contribution to some system-level effect, which effect has been picked out as especially interesting by a group of researchers. I will discuss Robert Cummins’ original formulation of the view, and then present a more sophisticated variation, the mechanistic causal role theory, due to Carl Craver and Paul Sheldon Davies. I then discuss the classic problem of overbreadth, namely, that it seems to attribute functions too liberally. I distinguish two different versions of this problem: the problem of non-functional traits and the problem of dysfunctional traits. I provide a critical assessment of the ways causal role theorists have tried to solve these problems. Many philosophers of biology today have accepted a pluralistic stance, according to which both the selected effects theory, and the causal role theory, capture important elements of biological usage. I distinguish two forms of pluralism. The first (and most popular), between-discipline pluralism, holds that the selected effects theory mainly captures the way evolutionary biologists use the term “function” and the causal role theory mainly captures the way “function” is used in other disciplines. I object to this division of labor and recommend a new form of pluralism, within-discipline pluralism, which emphasizes the co-existence of function concepts within any given discipline.

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima facie superiority of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature.

Scientists, philosophers, and even the lay public commonly accept that schizophrenia stems from a biological or internal ``dysfunction.`` However, this assessment is typically accompanied neither by well-defined criteria for determining that something is dysfunctional nor empirical evidence that schizophrenia satisfies those criteria. In the following, a concept of biological function is developed and applied to a neurobiological model of schizophrenia. It concludes that current evidence does not warrant the claim that schizophrenia stems from a biological dysfunction, and, in fact, that unusual neural structures associated with schizophrenia may have functional or adaptive significance. The fact that current evidence is ambivalent between these two possibilities (dysfunction versus adaptive function) implies that schizophrenia researchers should be much more cautious in using the ``dysfunction`` label than they currently are. This has implications for both psychiatric treatment as well as public perception of mental disorders.

ArgumentAs historian Henning Schmidgen notes, the scientific study of the nervous system would have been “unthinkable” without the industrialization of communication in the 1830s. Historians have investigated extensively the way nerve physiologists have borrowed concepts and tools from the field of communications, particularly regarding the nineteenth-century work of figures like Helmholtz and in the American Cold War Era. The following focuses specifically on the interwar research of the Cambridge physiologist Edgar Douglas Adrian, and on the technology that led to his Nobel-Prize-winning research, the thermionic vacuum tube. Many countries used the vacuum tube during the war for the purpose of amplifying and intercepting coded messages. These events provided a context for Adrian's evolving understanding of the nerve fiber in the 1920s. In particular, they provide the background for Adrian's transition around 1926 to describing the nerve impulse in terms of “information,” “messages,” “signals,” or even “codes,” and for translating the basic principles of the nerve, such as the all-or-none principle and adaptation, into such an “informational” context. The following also places Adrian's research in the broader context of the changing relationship between science and technology, and between physics and physiology, in the first few decades of the twentieth century.

MultCSync is a software package designed to aid incorporation of multiple criteria into conservation planning though it can be used in other similar contexts. During such planning, conservation area networks are selected primarily to represent biodiversity but must: (i) incorporate spatial design criteria such as size, dispersion, and connectivity of individual areas; and (ii) negotiate competing social claims on land use including recreation, resource extraction, and development. The social claims can also usually be modeled as (potentially incompatible) criteria to be simultaneously optimized along with the spatial design criteria. MultCSync enables the prioritization of alternative networks on the basis of such criteria after all biodiversity representation targets are satisfied. It begins by computing the set of non-dominated alternatives. If this set is sufficiently small, these alternatives can be presented to political decision makers. However, if this set is intractably large, further prioritization among the non-dominated alternatives is necessary. MultCSync accomplishes this prioritization using the Analytic Hierarchy Process (AHP) as well as a modification of the AHP in accordance with multi-attribute value theory (MAVT). MultCSync is freely downloadable via the world wide web and can be used in conjunction with different place prioritization software packages.

Rapid biodiversity assessment and conservation planning require the use of easily quantified and estimated surrogates for biodiversity. Using data sets from Quand Queensland, we applied four methods to assess the extent to which environmental surrogates can represent biodiversity components: (1) surrogacy graphs; (2) marginal representation plots; (3) Hamming distance function; and (4) Syrjala statistical test for spatial congruence. For Quwe used 719 faunal and floral species as biodiversity components, and for Queensland we used 2348 plant species. We used four climatic parameter types (annual mean temperature, minimum temperature during the coldest quarter, maximum temperature during the hottest quarter, and annual precipitation), along with slope, elevation, aspect, and soil types, as environmental surrogates. To study the effect of scale, we analyzed the data at seven spatial scales ranging from 0.01 ◦ to 0.10 ◦ longitude and latitude. At targeted representations of 10% for environmental surrogates and biodiversity components, all four methods indicated that using a full set of environmental surrogates systematically provided better results than selecting areas at random, usually ensuring that ≥90% of the biodiversity components achieved the 10% targets at scales coarser than 0.02 ◦ .T he performance of surrogates improved with coarser spatial resolutions. Thus, environmental surrogate sets are useful tools for biodiversity conservation planning. A recommended protocol for the use of such surrogates consists of randomly selecting a set of areas for which distributional data are available, identifying an optimal surrogate set based on these areas, and subsequently prioritizing places for conservation based on the optimal surrogate set.

We analyse optimal and heuristic place prioritization algorithms for biodiversity conservation area network design which can use probabilistic data on the distribution of surrogates for biodiversity. We show how an Expected Surrogate Set Covering Problem (ESSCP) and a Maximal Expected Surrogate Covering Problem (MESCP) can be linearized for computationally efficient solution. For the ESSCP, we study the performance of two optimization software packages (XPRESS and CPLEX) and five heuristic algorithms based on traditional measures of complementarity and rarity as well as the Shannon and Simpson indices of α-diversity which are being used in this context for the first time. On small artificial data sets the optimal place prioritization algorithms often produced more economical solutions than the heuristic algorithms, though not always ones guaranteed to be optimal. However, with large data sets, the optimal algorithms often required long computation times and produced no better results than heuristic ones. Thus there is generally little reason to prefer optimal to heuristic algorithms with probabilistic data sets.

The first use of the term “information” to describe the content of nervous impulse occurs in Edgar Adrian's The Basis of Sensation (1928). What concept of information does Adrian appeal to, and how can it be situated in relation to contemporary philosophical accounts of the notion of information in biology? The answer requires an explication of Adrian's use and an evaluation of its situation in relation to contemporary accounts of semantic information. I suggest that Adrian's concept of information can be to derive a concept of arbitrariness or semioticity in representation. This in turn provides one way of resolving some of the challenges that confront recent attempts in the philosophy of biology to restrict the notion of information to those causal connections that can in some sense be referred to as arbitrary or semiotic.

A framework is presented in which the role ofdevelopmental rules in phenotypic evolution canbe studied for some simple situations. Usingtwo different implicit models of development,characterized by different developmental mapsfrom genotypes to phenotypes, it is shown bysimulation that developmental rules and driftcan result in directional phenotypic evolutionwithout selection. For both models thesimulations show that the critical parameterthat drives the final phenotypic distributionis the cardinality of the set of genotypes thatmap to each phenotype. Details of thedevelopmental map do not matter. If phenotypesare randomly assigned to genotypes, the lastresult can also be proved analytically.

The place prioritization problem in conservation biology is that of establishing a sequentially prioritized list of places on the basis of biodiversity content. Such a list can then be used to select reserve networks that are designed to be fully representative of the biodiversity of an area as efficiently as possible (for instance, with minimum area or cost). The usual goal is the representation of all chosen biodiversity surrogates up to or beyond a required target, or to the greatest available extent. The purpose of this paper is to compare the respective performances of two place prioritization software packages, SITES and ResNet, on four datasets (distributions of termite genera in Namibia, breeding bird species in the Falkland Islands/Islas Malvinas, vertebrate species in Texas and flora and fauna species that are at risk in Quebec), to determine their respect- ive merits. The two software packages imple- ment radically different algorithms: SITES is based on a simulated annealing procedure for finding (local) optima; ResNet uses an algorithm based on rarity and complementarity. This ana- lysis indicates that the rarity-complementarity based algorithm of ResNet surpasses the simu- lated annealing approach of SITES with respect to time and completeness. SITES, however, contains other features that are useful in conser- vation planning. Ways in which the two packages can be used together effectively are suggested.

The prioritization of places on the basis of biodiversity content is part of any systematic biodiversity conservation planning process. The place prioritization procedure implemented in the ResNet software package is described. This procedure is primarily based on the principles of rarity and complementarity. Application of the procedure is demonstrated with two analyses, one data set consisting of the distributions of termite genera in Namibia, and the other consisting of the distributions of bird species in the Islas Malvinas/Falkland Islands. The attributes that data sets should have for the effective and reliable application of such procedures are discussed. The procedure used here is compared to some others that are also currently in use.

The Harvard physiologists Alexander Forbes (1882-1965) and Walter Bradford Cannon (1871-1945) had an enormous impact on the physiology and neuroscience of the twentieth century. In addition to their voluminous scientific output, they also used literature to reflect on the nature of science itself and its social significance. Forbes wrote a novel, The Radio Gunner, a literary memoir, Quest for a Northern Air Route, and several short stories. Cannon, in addition to several books of popular science, wrote a literary memoir in the last year of his life, The Way of an Investigator. The following will provide a brief overview of the life and work of Forbes and Cannon. It will then discuss the way that Forbes used literature to express his views about the changing role of communications technology in the military, and his evolving view of the nervous system itself as a kind of information-processing device. It will go on to discuss the way that Cannon used literature to articulate the horrors he witnessed on the battlefield, as well as to contribute to the philosophy of science, and in particular, to the logic of scientific discovery. Finally, it will consider the historical and philosophical value of deeper investigation of the literary productions of scientists.

Surrogacy analysis consists of determining a set of biotic or environmental parameters which can be rapidly assessed in the field and reliably used to prioritize places for biodiversity conservation. Whether adequate surrogate sets exist remains an open and relatively unexplored question though its solution is central to the aims of conservation biology. This paper analyses the surrogacy problem by prioritizing places using surrogate lists and comparing these results with those obtained by using more comprehensive species lists. More specifically, it explores (i) the possibility of using bird distributions, which are often easily available, as surrogates for species at risk (endangered and threatened species), which are presumed to be an important component of biodiversity; and (ii) the methodological question of how spatial scale influences surrogate success. The data set analysed, from southern Quebec, is one of the most complete biotic data sets available at the regional scale. Contrary to some previous analyses, the results obtained suggest that the surrogacy problem is potentially solvable.