Cognitive ethology, a relatively new interdisciplinary and integrative science, is under attack with respect to its scientific status. However, there also are strong supporters of research in this area. In this paper I consider (1) some of the topics in which cognitive ethologists are interested, (2) possible connections between cognitive analyses of social behavior and philosophical concepts including intentionality and representation, (3) recent work on vigilance or scanning behavior in highly social birds, Evening Grosbeaks (Coccothraustes vespertinus), that benefits from taking a cognitive perspective, and (4) what may be gained by taking a cognitive approach to the study of social behavior and what may be lost by not doing so. My study of vigilance indicates that the way in which individuals are positioned with respect to one another influences their behavior, and that when a flock contains four or more birds there are large changes in scanning and other patterns of behavior that may be related to how grosbeaks attempt to gather information about other flock members. When birds are arranged in a circular array so that they can see one another easily compared to when they are arranged in a line that makes visual monitoring of flock members more difficult, birds who have difficulty seeing one another are (i) more vigilant, (ii) change their head and body positions more often, (iii) react to changes in group size more slowly, (iv) show less coordination in head movements, and (v) show more variability in all measures. These differences in behavior argue against the pooling of data collected on individuals feeding in different geometric arrays. The variations in behavior also may say something about if and how individuals attempt visually to represent their group to themselves--how they form, store, and use records of the behavior of others to inform their own future behavior.
Key words: Cognitive ethology; Vigilance; Flock Geometry; Philosophy of mind; Representation
Introduction: Cognitive ethology and naturalizing animal minds
Researchers from many different disciplines are interested in cognitive ethology, the evolutionary and comparative study of nonhuman animal (hereafter animal) cognitive processes and mental states (e.g., thought processes, consciousness, beliefs, information processing, and rationality in animals (for references see Dennett, 1983, 1987; Griffin, 1984, 1992; Bekoff and Jamieson, 1990a,b, 1995a; Cheney and Seyfarth, 1990, 1992; de Waal, 1991; McClean and Rhodes, 1991; Yoerg, 1991; Allen, 1992a,b, 1994; Allen and Hauser, 1991, 1993; Ristau, 1991a; Beer, 1992; Bekoff and Allen, 1992, 1994; Shapiro, 1992; Heyes, 1993, 1994; Jamieson and Bekoff, 1993; Wemelsfelder, 1993; Allen and Bekoff, 1994; Bekoff, 1995a). Renewed interest in this area signifies a return to many of the ideas of Charles Darwin and early anecdotal cognitivists, especially their appeals to evolutionary theory, their interests in mental continuity, their concerns with individual and intraspecific variation, their interests in the worlds of the animals themselves, their close association with natural history and their attempts to learn more about the behavior of animals in conditions that are as close as possible to the natural environment where selection has occurred, and their reliance on anecdote and anthropomorphism to inform and to motivate more rigorous study.
Comparative cognitive ethology is an important extension of classical ethology because it explicitly licenses hypotheses about the internal states of animals in the tradition of classical ethologists such as Niko Tinbergen (1951/1991, 1963) and Konrad Lorenz (1981). In addition, cognitive ethologists, in common with other biologists, are generally concerned with the diversity of solutions that living organisms have found for common problems. Many people inform their views of cognitive ethology by appealing to the same studies over and over again, and often they seem to forget that there are many other animals who also show interesting patterns of behavior that lend themselves to cognitive analyses. Cognitive ethologists also emphasize broad taxonomic comparisons and do not focus on a few select representatives of limited taxa. They favor observations and experiments and maintain that field studies that include careful observation and experimentation can inform studies of animal cognition; cognitive ethology will not have to be brought into the laboratory to make it respectable. While some are of the opinion that advanced cognition is confined to the laboratory (e.g., Premack, 1988), those who have studied animals in the wild disagree. While it might be difficult to study animal cognition in the field, it is far too early to conclude that it is impossible to do so.
Here, I discuss some aspects of cognitive ethology and present data on vigilance or scanning behavior in highly social birds, Evening Grosbeaks (Coccothraustes vespertinus), that center on major ethological questions that are also related to important philosophical notions. Some of this material has been published elsewhere in a more expanded form (Bekoff, 1995a,b). Although I and others are enthusiastic about the field of cognitive ethology (Ristau, 1991a; Allen 1992a,b; Griffin, 1992; Bekoff and Allen, 1995), we do not believe that all behavior patterns will benefit from cognitive ethological analyses or lend themselves to cognitive explanations. However, we do feel that the analysis and explanation of some behavioral phenomena surely will benefit. While appeals to well-established principles in behaviorism may serve useful explanatory purposes in some instances, there is no reason to assume that new principles in tandem with older ones will not help us to explain better the behavior of nonhuman animals; it is narrow-minded both to think that no analyses of behavior will benefit or that all analyses will benefit from a cognitive approach. As an ethologist, I am also aware that different species might perform a wide variety of behavior patterns that serve the same or similar functions (Allen and Bekoff, 1995). Furthermore, it may be the case that conspecifics or members of closely related species perform the same behavior patterns in different contexts. Thus, the cover of a recent article in Time magazine (Linden, 1993) that pictures a nonhuman primate deep in thought assumes, perhaps wrongly, that all (or most) primates, nonhuman and human, would assume the same posture while deep in thought. Though understandable in this context, this narrow perspective could lead to incorrect conclusions about the cognitive abilities of animals who behave differently from how we expect them to.
Some philosophical underpinnings of cognitive ethology
A major area of interest for philosophers of mind who are interested in animal cognition is to explain how different views of animal minds can lead to the formulation of empirically tractable hypotheses about animal behavior (Allen, 1995). There is also great interest in how to specify the content of animal mental states. One of the major problems and challenges in cognitive ethology and the study of cognition in general is getting from behavior to mental content (see Allen, 1992a,b). Some philosophers of mind (and cognitive ethologists) are also interested in naturalizing animal mentality. One way to do this is to explain how mental properties can be instantiated by biological, chemical, or physical mechanisms. Another way (Stich, 1992; Tye, 1992) is for mentalistic concepts to be incorporated into the practice of science. Millikan (1984, 1993) has had a large influence on efforts to develop a naturalistic account of intentionality (e.g., the semantic properties of mental states) in terms of function or adaptation (but see Fodor, 1987; Cummins, 1989).
Two major topics in philosophy of mind that are important to cognitive ethology include the notions of intentionality and representation. Intentionality in the philosophical sense means that mental states have propositional content, they are about or of things. There is a lot of interest in the notions of representation and misrepresentation among biologists, psychologists, and philosophers (see for example, Millikan, 1984, 1993; Brand and Harnish, 1986; Dretske, 1986a,b, 1988; Cummins, 1989; Sterelny, 1990; Perner, 1991; Dusenberry, 1992; Stich, 1992; Clark, 1993; Dear, Simmons, and Fritz, 1993; Goldman, 1993; Stein and Alexander, 1993; Wagner and Frost, 1993; Toates, this volume). Kim Sterelny (personal communication) sees the core hypothesis of cognitive ethology to be: "animals represent their world and exploit those representations in modulating their particular behaviours to their particular problems. So we can neither predict nor explain animal behaviour without an understanding of what about their world they represent, and how they represent it." A great challenge for those who study cognitive ethology is to learn more about what is represented or misrepresented in certain instances and how what is represented is represented or misrepresented.
While classical ethologists such as Lorenz and Tinbergen (1952) have used terms such as "intention movements," they are used quite differently from the philosophical sense. Lorenz and Tinbergen were referring more to preparatory movements that might communicate what individuals were likely to do next, and not necessarily to their beliefs and desires, although one might suppose that the individuals did indeed want to fly and believed that if they moved their wings, they would fly. This distinction is important to mark because the use of these terms does not necessarily add a cognitive dimension to classical ethological notions, although it could. Having made this clarification, cognitive ethological studies lead us to consider questions such as "What does it mean to claim that Jethro (my domestic dog companion) behaves intentionally? "What does it mean to claim that he has a belief?" "What does it mean to have a representation of something?" For example, in my work on social play behavior (e.g., Allen and Bekoff, 1994; Bekoff, 1995a,b), I am interested in questions such as "Does Jethro want Henrietta (another dog) to play with him?" Does Jethro believe that Henrietta wants to play with him?" "Does Jethro believe that Henrietta believes that he wants to play with her?" "Do individuals cooperate to maintain a 'play mood'?" "Do individuals' own experiences play a role in their ability to understand the body movements of others and might this facilitate the sharing of intentions (beliefs and desires)" (e.g., Gopnik, 1993)? And, in my work on vigilance I am interested in questions that center on if and how birds represent other individuals in their flocks to themselves, how they form, store, and use records of the behavior of others to inform their own future behavior, and whether they have beliefs about the behavior of other individuals. Specifically, we can ask if a bird represents his flock to himself as being in a certain geometric distribution or as being of a certain size. These are questions for empirical cognitive studies to answer.
Vigilance, information gathering, and representation:
Why are grosbeaks busy and nosy?
Vigilance or scanning patterns in individuals and groups are typically studied in the context of antipredator behavior. Many people are interested in antipredator behavior because studies of patterns of predator avoidance can inform ideas concerning the evolution of sociality (Pulliam, 1973; Elgar, 1989; Lazarus, 1990; Lima, 1990, 1994; Quenette, 1990; Hailman, McGowan, and Woolfenden, 1994; Lima and Dill, 1990; Pöysä 1994; Rose and Fedigan, 1994; Scheel, 1994; Yáber and Herrera, 1994). One major question centers on the question of "Why do animals live in groups?" Suggestions include the idea that sociality has evolved for group hunting, predator detection, and predator deterrence. Analyses of vigilance can also help us to learn more about intentional behavior and representation in animals. Here I will concentrate on vigilance behavior, a pattern of behavior that involves, among other things, scanning for potential predators. When scanning, in addition to gaining information about the detection of possible predators, an individual can also gain information about events such as what other group members are doing, where they are, or about resources including the type of food on which others are feeding or the quantity of food that is available. That is, they can acquire knowledge about the behavior of other group members or about (local) resources, information that might influence what a scanning bird does next.
For the present discussion I will be concerned primarily with the types of information about the behavior of other flock members that individuals might acquire while scanning (some of this discussion is from Bekoff, 1995a, and data are presented in Bekoff, 1995c). While it is possible that auditory cues are important (e.g., Sullivan, 1984), I will not consider this here. Furthermore, it still is unclear whether birds actually see or hear what we think that they see or hear (for detailed discussions see Keeling and Duncan, 1989 and chapters in Zeigler and Bischof, 1993; see also McBride, James, and Shoffner, 1963). With respect to whether or not an individual is really being vigilant, Lazarus (1990, p. 65) notes that " . . . researchers have simply assumed that the behaviour in question is vigilance, and have then sought its function." Lima (1990) also claims that there seem to be no studies that have directly examined the question of whether foragers pay any attention to the behavior of other group members. He concludes that very little is known about the perceptions of the animals being studied and that many models of vigilance reflect mainly the perceptions of the modelers themselves.
A central question in the comparative study of vigilance is "How does the behavior of individuals vary in groups of different sizes" (Elgar, 1989; Lima, 1990; Lima and Dill, 1990)? Generally, it has been found that there is a negative relationship between group size and rates of scanning by individuals and a positive relationship between group size and the probability of predator detection. This is because there are more eyes and perhaps other sense organs that can be used to scan for or to detect predators. Another, and perhaps more important question to which very little attention has been directed, is "Why is the relationship between group size and scanning rates not found?" This question has received little attention. Nonetheless, these data should not be viewed as noise. Rather they can be used to inform and motivate new research as well as reanalyses of old data. As I will discuss below, the pooling of data from individuals living in flocks of the same size, but organized in different geometric arrays, can mask interesting differences that might inform not only the question of why the relationship between group size and scanning rates is not found, but also cognitive analyses of scanning behavior.
A cognitive analysis of vigilance in which we are concerned with what an individual might know about himself and others would involve asking various questions, some of which may not be directly related to cognitive inquiry, but all of which could inform and motivate such an approach (Bekoff, 1995a). Some are also very basic, but this return to basics is necessary (see also Lima, 1995).
One question in which I have been interested for a long time is "Does the size of a group or the geometric distribution or orientation of individuals influence individual vigilance?" It seems likely that there are confounding variables such as the geometric relationships among group members and how individuals are oriented in space--in a circle, a triangle, or in a straight line, for example--that might influence scanning rates of individuals. Little attention has been paid to group geometry. Some authors write about visual obstructions but do not consider the actual geometry of the group (Elgar, 1989; Quenette, 1990). For example, Elgar does not directly refer to geometry as a variable influencing scanning for predators, but he does write about visual obstructions in terms of how they might influence vigilance and risk of predation. Likewise, in his review of vigilance in mammals, Quenette (1990) writes about visual obstructions and their effect on vigilance because they influence how information is received from the environment. Elgar, Burren, and Posen (1984, p. 221) report data that strongly suggest that in house sparrows, "it is necessary for them to be able to continuously see their flockmates." They also review literature that shows that in general, scanning rates in small passerines do not decrease significantly with flocks larger than eight or nine birds. They write: "It is possible that sparrows simply cannot estimate the number of birds in larger flocks . . . " Of course, it is possible that birds and other animals cannot estimate the number of birds in flocks that are organized in a way such that visual inspection is difficult or impossible.
Answers to the question "How does the geometric distribution of individuals influence individual vigilance?" will likely have something to say about animal cognitive abilities. Thus, while it is known that the location of an individual in her group (center or periphery) can influence her pattern of vigilance, it remains to be studied how the geometry of the group influences the ease with which an individual is able to assess what others are doing by seeing (or hearing or listening to) them. For example, it seems that it would be easier to see and to estimate (see below) how many animals are in a group and what others are doing if individuals were organized in a circle rather than in a straight line. While in a straight line, individuals could block the view of other individuals.
To answer questions about possible relationships among flock size, flock geometry, and individual patterns of vigilance and other behaviors, I studied Evening Grosbeaks outside of Boulder, Colorado. No previous studies have attempted to analyze these relationships in any detail (for details see Bekoff, 1995c). A circular array was one where each bird in the flock was oriented so that it had a clear line of sight to all other birds, and a linear array was a noncircular array in which each bird was oriented so that it had a clear line of sight to at most two other birds; a triangle was considered to be a circular array. Data that did not fit into either of these categories were discarded for the present analysis. Single birds and flocks of two birds were included in the present analysis but were not classified as being in circles or lines for obvious reasons. It is important to stress that the seeds that were provided to birds (and thus, handling time), the field site and feeding platforms, distance to cover, and potential predators (mainly domestic cats, Felis catus), variables that could influence scanning and feeding behavior, were similar from year-to-year. The high turnover in marked birds (Bekoff and Scott, 1989) suggested that familiarity among individuals did not influence patterns of vigilance. Birds standing on a feeding platform or along a narrow rail were considered to be members of a single group when the distance between them was less than or equal to 0.5 meters.
The only visual obstructions were the birds themselves. Data showed that when individuals are arranged in a line so that it is difficult to see one another compared to when they are arranged in a circular array that makes visual monitoring of flock members less difficult, birds who have difficulty seeing one another are (i) more vigilant, (ii) change their head and body positions more often to orient toward other flock members, (iii) react more slowly to changes in group size, (iv) show less coordination in head movements, and (v) show more variability on all measures (Bekoff, 1995c). Differences between birds organized in a circular array when compared to those organized in a linear array were most pronounced in groups larger than four birds for the percentage of time spent scanning, changes in head and body position, and latency to reaction to changes in group size, and large and consistent differences in the degree of coordination in head movements also emerged when group size equaled four or more. Mean interscan intervals, which are often resistant to variations in group size in different species (Desportes et al., 1990), were about the same for individuals in circular and linear flocks of the same size, and do not account for differences in patterns of vigilance (see also Lima, 1987). Regression analyses showed that the relationship between the mean proportion of time spent scanning by individuals and the mean number of changes in body and head position were significantly and negatively related to group size when birds were organized in circles, but neither of these measures was significantly related to group size when birds were organized in lines. For both measures, adjusted coefficients of determination (r2) were higher for birds organized in circles, indicating that a larger percentage of variation in each measure was explained by group size. With respect to the delay shown in response to a change in group size, birds organized in lines showed a longer and more significant delay, and adjusted r2 values indicated that 76% of the variation in delay was accounted for by group size when birds were in lines, whereas only 1% of the variation in delay was accounted for by group size when birds were in circles.
The differences in behavior between birds organized in circular arrays when compared to birds organized in linear arrays, when taken together, can be explained by individuals' attempts to learn, via visual monitoring, about what other flock members are doing, and this may say something about if and how birds attempt to and do represent their flock, or at least certain other individuals, to themselves. It may be that individuals form beliefs about what others are most likely doing and predicate their own future behavior on these beliefs. Along these lines, Elgar et al. (1984) and Metcalfe (1984a,b) hypothesize that some birds do attempt to inspect visually other flock members (see also McBride, James, and Shoffner, 1963). However, as Lima (1994) points out, changes in behavior with changes in group size do not necessarily imply that group members monitor each other's behavior. In agreement with the data presented here, Metcalfe (1984a) and Redpath (1988) found that obscured vision can lead to increases in vigilance in other birds (but see Lima, 1987). Lima (1995) also reported that house sparrows (Passer domesticus) who are vigilant at the initiation of an "alarm flight" depart more quickly than non-vigilant sparrows. With respect to possible influences of group geometry, Joel Berger (personal communication) notes that in his work on group size and foraging efficiency in bighorn sheep, differences in group geometry might account for the large range of variances in behavior that was influenced by group size (see Berger, 1991, pp. 68-69).
My data suggest that visual obstructions--other birds in a flock--can interfere with an individual's monitoring of the behavior of other individuals, and that individuals change their behavior based on what they are able to see--grosbeaks are busy and nosy, spending a good deal of time scanning for predators, and are also socially vigilant (see also Yáber and Herrera, 1994), probably gathering information about flock size, what others are doing, where others are, which individuals are present, phenotypic features of flock members, and food resources (Bekoff, 1995c). Grosbeaks seem to change their behavior based on what they are able to represent to themselves. It is too early to discard representational explanations for at least some of the flexible behavior of birds living in flocks of different sizes and of different geometric arrays. Scheel (1994) noted that various herbivores also vary scan rates in response to environmental changes, and it should be noted that adaptive versatility or flexibility is the principal criterion that Griffin (1992) used to argue for cognition in animals.
More data are needed for other taxa to assess if the inverse relationship between group size and individual scanning rate levels off or fails because of the inability of individuals to monitor the behavior of "too many other animals" who might also be difficult to see. (It is also important to note that there may be trade-offs such that although it is easier to see what other flock members are doing when birds are arranged in a specific geometric array, it may also easier for potential predators to see the group or specific individuals.) Suggesting that birds make assessments of group size or postulating that they do attempt to assess group size is not asking them to do too much (see Warburton and Lazarus 1991 for discussion of how group cohesion may be maintained in the absence of monitoring all individuals in the group). Dharmaretnam and Andrew (1994), in their developmental study of vision in domestic chickens (Gallus gallus domesticus), recently discovered that one cerebral hemisphere seems to be used by the other. This important result " . . . shows how phenomena which might have been considered as peculiarly human, and integral to the highest level of cognition, are in fact accessible to study in other vertebrates . . . " (Dharmaretnam and Andrew, 1994, p. 1405). Many species can also learn and remember the location of numerous food caches and show other types of spatial memory that suggest the use of cognitive maps (Speakman, 1987; Bingman, 1992). Birds also display category and concept formation (Pepperberg, 1990, 1994), perceive pictures as representations of objects (Watanabe, Lea, and Dittrich, 1993), discriminate between stimulus arrays on the basis of the number of items they contain, and can form an internal representation of a moving stimulus and extrapolate the movement of a stimulus that is no longer visible (Emmerton and Delius, 1993; see also Regolin, Vallortigara, and Zanforlin, 1994). There also are some data that show that some birds can store precise information of up to 7 items in a set (Emmerton and Delius, 1993). Perhaps this limitation influences patterns of vigilance for groups of about this size. Recall Elgar et al.'s (1984) observation that scanning rates in small passerines do not decrease significantly in flocks larger than eight or nine birds because of the possibility that individuals cannot estimate the number of birds in larger flocks. Whether or not birds are subitizing (rapidly assigning a numerical tag to small quantities of items in a simultaneously presented array) or actually counting (discriminating the absolute number of a set of items on an ordinal scale) the number of other individuals in a flock awaits empirical studies (for detailed discussion of subitizing and counting see Davis and Pérusse, 1988 and Boysen and Capaldi, 1993).
Why cognitive ethology?
Many models in ethology and behavioral ecology presuppose cognition. Thus, it would be useful to have informed ideas about the types of knowledge that nonhumans might have about their social and nonsocial environments and how they use this information. Two important questions need to be given serious attention. These are "What is gained by appealing to the possibility of cognitive explanations?" and "What is lost by dismissing the possibility of cognitive explanations?" It seems clear that we would lose a lot of information about the possible richness of animals' lives if we ignored the possibilities that they behaved intentionally at least on some occasions. Even if we discover that some animals do not appear "all that cognitive," this does not mean that they are not cognitive at all (Bekoff, 1994).
What are some reasons for advocating cognitive ethological analyses and intentional or representational explanations of animal behavior? As Watanabe, Lea, and Dittrich (1993, p. 372) state: "The question is not whether pigeons have been proved beyond a reasonable doubt to possess and use concepts, but whether it has proved fruitful to ask whether they do." McClean and Rhodes (1991) also recognize the utility of using cognitive models and intentional explanations in studies of enemy recognition in birds (see also Cheney and Seyfarth, 1990, 1992; Ristau, 1991b; Bekoff, 1995a). Why might cognitive explanations be the best explanations to which we appeal in some instances to help us come to terms with the comparative and evolutionary study of animal minds? That the explanatory power of our theorizing is increased is one reason. Furthermore, it is obvious that a cognitive approach will generate new ideas that can be tested empirically, help in evaluations of extant explanations, lead to the development of new predictive models, and perhaps, lead to the reconsideration of old data, some of which might have resisted explanation without a cognitive perspective. For example, the ways in which flock size and flock geometry might interact to produce changes in the behavior of individuals that were previously explained (or unexplained) by appealing solely to flock size would not have been pursued without taking into account questions about representation. Furthermore, consideration of the possibility of the importance of visual representations for group living birds motivated study of other aspects of behavior including rates of body and head movements and delays in response to changes in group size. When the results of all of these analyses were combined, a stronger case could be made for the utility of representational accounts to explain both the failure of finding a significant negative relationship between group size and the proportion of time spent scanning and other differences in the behavior of birds living in different geometric arrays.
When selecting among competing, but not necessarily mutually exclusive explanations (McClean and Rhodes, 1991; Bekoff, 1995a), it is important to ask questions such as is the explanation doing the work that we want it to do--where does it lead heuristically, how much noise does it account for, and what is its predictive power? Different sorts of explanations apply to different situations, and there seems to be little justification for advocating one type of explanation to the exclusion of others for all (or even many) of the diverse patterns of behavior shown by different animals. It may be more economical or parsimonious to assume that not everything that an individual needs to be able to do in all situations in which he finds himself is preprogrammed; cognitive explanations can be simpler than cumbersome stimulus-response explanations (de Waal, 1991 and Bekoff and Allen, 1995). While general rules of thumb may be laid down genetically during evolution, specific rules of conduct that account for all possible contingencies may be too numerous to be hard-wired. Furthermore, while behavioristic learning schemes appealing to notions such as conditioning, generalizing, and substituting can account to a limited extent for behavioral fexibility, behavioral integration, and the use of internal states and images of absent objects in some organisms (e.g., Holland, 1990), learning at high degrees of abstraction from sensory stimulation seems less amenable to behavioristic analysis (Bekoff and Allen, 1992). Cognitive models of learning provide explanatory schemes for such cases. It might actually be more parsimonious to appeal to cognitive explanations in terms of accounting for complex patterns of behavior with fewer explanations. For example, the results of the present study, that flock geometry influences various patterns of behavior, are more simply explained in terms of the representational needs or information-gathering goals of grosbeaks than by an attempt to account for the effects of group geometry in terms of (numerous and diverse) stimulus-response contingencies or generalizations from earlier experiences (e.g., birds are somehow conditioned [or innately predisposed] to produce certain behavioral patterns in response to group geometry). For in this case it is difficult to conceive that an individual grosbeak's experience could have included explicit conditioning about the factors that influence when and how it should scan or move its head and body. Similarly, Speakman (1987) found that theories of spatial learning in birds (and other animals) that postulate mental or cognitive maps provide better predictions of behavior than theories that reject the idea of internal constructs. The applicability of representational information gathering approaches to the study of different behavior patterns in a wider array of species awaits further empirical study.
Cognitive ethology can also raise new questions that may be approached from other levels of analysis. For example, detailed descriptive information about subtle behavior patterns and neuroethological data may be important for informing further studies in animal cognition, and might also be useful for explaining data that are already available. Such analyses will not make cognitive ethological investigations superfluous (as some eliminativists think), because behavioral evidence is primary over anatomical or physiological data in assessments of cognitive abilities.
A concentration on individuals and not on species should also form an important part of the agenda for future research in cognitive ethology. There is a lot of individual variation in behavior within species and sweeping generalizations about what an individual ought to do because she is classified as a member of a given species must be taken with great caution. Furthermore, people often fail to recognize that in many instances sweeping generalizations about the cognitive skills (or lack thereof) of species and not of individuals are based on small data sets from a limited number of individuals representing few taxa, individuals who have been exposed to a narrow array of behavioral challenges. The importance of studying animals under field conditions, rather than the often " . . . contrived and impoverished conditions of the laboratory . . . " (Mcgrew, 1994, p. 35; see also Griffin, 1992; Bekoff, Townsend, and Jamieson, 1994) cannot be emphasized too strongly. Field research, that includes careful and well-thought out observation, description, and experimentation that does not result in mistreatment of the animals (Bekoff, 1994; Bekoff and Jamieson, 1995b) is extremely difficult to duplicate in captivity. While it may be easier to study animals in captivity, they must provided with the complexity of social and other stimuli to which they are exposed in the field; in some cases this might not be possible. Furthermore, the use on animals of techniques that have proven valuable in studies of human minds and cognition (e.g., positron emission tomography, or PET; Posner and Raichle, 1994) is still forthcoming.
To summarize, interdisciplinary and integrative efforts, the borrowing of ideas from different areas, are essential in our quest for knowledge about animal minds. Assuming a strong cognitive stance will not be a deterrent to learning more about animal behavior and animal minds. Subjectivity, indeterminacy, and intractability present stumbling blocks, but not impenetrable barriers, and the "privacy" of mental states does not necessarily present more or less of a problem for cognitive ethology than the invisibility of electrons does for chemistry (Lawrence Shapiro, personal communication; see also Bekoff and Allen, 1995). Claims about minds and electrons are posited as hypothetical constructs because they make the most sense of the data that have been collected. To allow such claims in chemistry but not in cognitive ethology is to adopt a double standard, which is unfair to cognitive ethology. Shapiro recommends that cognitive ethologists no longer worry about subjectivity, because this characterization serves to stigmatize their subject matter, distinguishing it in a way that leads to an undeserved skepticism.
I thank Colin Allen, Kim Sterelny, Dale Jamieson, Larry Shapiro, Eric Saidel, David Rosenthal, Carolyn Ristau, Donald Griffin, Ruth Millikan, Susan Townsend, John Lazarus, Joel Berger, Cecilia Heyes, Jeff Galef, Daniel Dennett, Gordon Burghardt, Steve Lima, and Thomas Valone for discussing many of these issues with me over the past few years. Steve Lima, Colin Allen, John Lazarus, and an anonymous reviewer provided comments on an ancestral version of this paper, and Michael C. Grant did the statistical analyses.
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