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Meta-analysis, 1
Running head: Breed Differences in Dogs Sensitivity to Human Points
Nicole R. Dorey, Monique A. R. Udell, Clive D. L. Wynne
Address correspondence to:
Clive Wynne
Department of Psychology
University of Florida
P.O. Box 112250
Gainesville, Florida 32611
Email : wynne@ufl.edu
Phone : (352) 273 2175
Fax : (352) 392-7985
University of Florida

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Abstract
The last decade has seen a substantial increase in research on the behavioral and cognitive abilities of pet dogs, Canis familiaris.
The most commonly used experimental paradigm is the object choice task in which a dog is given a choice of two containers and guided to the reinforced object by human pointing gestures. We review here studies of this type and attempt a meta-analysis of the available data. In the meta-analysis breeds of dogs were grouped into the eight categories of the American Kennel Club, and into four clusters identified by Parker and Ostrander (2005) on the basis of a genetic analysis. No differences in performance between breeds categorized in either fashion were identified.
Rather, all dog breeds appear to be similarly and highly successful in following human points to locate desired food. We suggest this result could be due to the paucity of data available in published studies, and the restricted range of breeds tested.
Keywords:
Breed Differences, Domestic Dog, Human gestures, Meta-analysis

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A search for Canis familiaris on the Web of Science database shows that in the past 20 years, research on dogs has increased dramatically -- from approximately ten articles published in 1989, to almost 90 in 2008. In the last decade there has been a particularly rapid increase in the use of pet dogs as subjects in animal cognition research. The focus of this resurgence has been this species’ exquisite sensitivity to human cues. Dogs have been shown to attend to whether a human is looking at them in selecting whether to obey a command (Brauer, Call & Tomasello 2004; Call, Brauer, Kaminski & Tomasello 2003), dogs can guide humans to find hidden toys (Miklósi, Polgárdi, Topál & Csányi 2000), and can use human-given cues to locate hidden items (Hare & Tomasello 1999; Miklósi et al. 1998; Soproni, Miklósi, Topál & Csányi 2001; Soproni, Miklósi, Topál & Csányi
2002; Udell, Giglio & Wynne 2008).
Probably the most popular experimental paradigm in this literature is the investigation of dogs’ responsiveness to human cues in object-choice tasks. In these tasks, a human experimenter kneels or stands between the two containers. Once the dog is attending to the experimenter, he or she points or gestures towards one of the containers.
Selection of the pointed-to container reveals a desired piece of food which serves as the animal’s reinforcement for correct choice.
Experiments using this paradigm vary considerably in how the procedure is administered. Some of the common differences include the types of gestures given, the time available to the subject to make a choice, and the number of trials presented.
Variations in the type of point can be classified in four ways: Proximal points are those in which the distance between the tip of the finger and the container is less than 40 cm. If the distance is greater than 50 cm the point is coded as distal (Miklosi & Soproni 2006).
Momentary points are those where the subject sees the arm extend towards the container and come back to a resting position. In dynamic points the subject watches the arm extend and point to a container, where it remains until a choice is made (Miklosi &
Soproni 2006). Typically, in the demonstration of a dynamic point, the arm is extended and brought back to rest several times before it remains in the pointing position. The age of the subjects and their breed also varies both within and between studies.
Not withstanding these numerous methodological differences, the consistent result of these studies is that dogs are extremely proficient in following a variety of human pointing cues under a range of conditions (see Miklosi and Soproni 2006; Reid
2008; and Udell and Wynne 2008 for reviews).
This paper presents a meta-analysis, or pooling of results from independent experiments (Gurevitch and Hedges 1993), of the many reports of the behavior of dogs on the object-choice task with a view to identifying breed differences in the sensitivity of
Canis familiaris to human points.
The origin of the domestic dog has been estimated from genetic studies to lie between 40 and 135 thousand years ago (Savolainen et al. 2002). The available archeological record provides no evidence of dogs older than 15 thousand years (Brewer,
Clark & Phillips 2002). The first evidence of distinct breeds in the historical record can be seen only around three to four thousand years BP (Brewer et al. 2002; Hacourt 1974).
Breeds may have arisen because of geographic isolation of early dog populations, but they were then maintained – and new breeds developed – by direct human action. People actively bred for animals that were best suited to perform different tasks. The behaviors selected for in each breed are not new to canid species, but have been enhanced or

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14 suppressed by the selection process (Hart 1995). Different breeds now exist that are specialized for herding, retrieving, hunting, guarding, and various other forms of aid to humans. In recent years the intensity of selection for practical purposes has been fading as the importance of dog companionship and breeding for appearance has risen (Hart
1995; Svartberg 2006).
Traditionally the over 400 recognized dog breeds are ordered into a small number of broad groupings by common ancestry, geographic origin, and the nature of the task for which they are reputed to be useful (e.g. herding, livestock guarding, etc.) (Gersenfeld
1999; Houpt 2007). According to the American Kennel Club (AKC), dog breeds can be split into eight major groups. Dogs in the sporting breed group are said to possess high levels of energy and were mainly bred for hunting various game animals on different types of terrain (Gersenfeld 1999). Breeds in this group include Cocker Spaniels, Golden
Retrievers and Pointers. Dogs categorized as hounds are quite diverse, with some breeds in this group possessing an acute sense of smell, and others having great stamina and the ability to run extremely fast (Gersenfeld 1999; Cohen 2007). Examples of breeds in this category are Beagles, Basset Hounds and Dachshunds. The AKC places dogs that were bred to guard, protect property, pull sleds or loads of materials, or execute water rescue into the working breed group (Cohen 2007). Working breeds include Doberman
Pinschers, Bullmastiffs and Boxers. Dogs in the Terrier group were bred to hunt and kill vermin (Cohen 2007). Breeds in this group include Wired Haired Terriers, Scottish
Terriers and Staffordshire Terriers. Herding breeds are dogs that were bred to herd cattle and sheep. This breed group ranges from cattle herders such as Australian Cattle dogs, to sheep herders such as the Belgian Sheepdog. Another category recognized by the AKC is the toy breed group. This group consists of dogs that are small in stature, were bred solely for companionship and perceived attractiveness, and includes Pugs, Pomeranians, and
Poodles. The last two AKC breed groups are the non-sporting group (e.g., Dalmatians and Lhaso Apsos) and the miscellaneous group (e.g., Icelandic Sheepdog, Leonberger and Bluetick Coonhound). The non-sporting group are AKC recognized dogs that do not fit into the other AKC groups, whereas the miscellaneous group are dog breeds that are acknowledged by the AKC, but not formally recognized as pure bred.
With the recent sequencing of the dog genome (Lindblad-Toh et al. 2005), geneticists have moved on to an examination of the genetic differences and similarities between breeds. Parker and Ostrander (2005) analyzed the genetic relationships among
85 dog breeds that were available for analysis. These breeds were ordered by genetic similarity into four clusters; one cluster consisted of the Asian breeds (e.g., Chow, Akita, and Sled Dogs). The second cluster included mastiff-type dogs (e.g., Rottweiler,
Newfoundland, Boxer). The third cluster consisted of herding breeds (e.g., Collie,
Shetland Sheepdog, Belgian Sheepdog) and some sight hounds (e.g., Greyhound, Irish
Wolfhound). The final cluster included hunting breeds (e.g., Pointer, Irish Setter, Golden
Retriever) (Parker & Ostrander 2005). These groupings are not entirely distinct, and some dog breeds, for example Pomeranians, have been assigned to more than one cluster
(Figure 1).
Given the widespread acknowledgement that breeds of dogs differ in behavior – indeed differences in typical behavior patterns, particularly hunting behaviors, are part of the definitions of many breeds (Coppinger and Coppinger 2001), it is remarkable that the recent literature on dogs’ sensitivity to human actions contains, to our knowledge, only

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21 one published study that has explicitly compared different breeds of dogs. McKinley and
Sambrook (2000) tested 16 dogs that were split into three groups: Non-gundog pets (one
Terrier cross, four German Shepherds and a Standard Poodle), Gundog pets (three
Labrador Retrievers, a Golden Retriever and a Cocker Spaniel), and trained Gundogs
(three Labrador Retrievers and two Springer Spaniels). After warm-up trials each dog was shown three different types of point to a location in which food was hidden, and a control condition in which no human cues were given. McKinley and Sambrook concluded that working gundogs were significantly more successful than pet gundogs and other pet dogs in following the human point to locate hidden food. It is difficult to draw strong conclusions from this study however, because each group of dogs contained different numbers of dogs from different breeds, the number of dogs in each group was very small, and any breed differences are confounded by the different rearing conditions of working dogs as compared to pet dogs.
One possible reason for the paucity of behavioral studies comparing the sensitivity of dogs of different breeds to human-given cues, is the large number of animals that would need to be tested even to cover a representative subset of the 400 breeds currently recognized. Thus the purpose of this meta-analysis is to investigate breed differences in responsiveness to human pointing. We wanted to see whether any differences between breeds that are observed relate to the traditional grouping of breeds by function and geographic origin (Gersenfeld 1999) or to the more recent genetic clustering analysis of Parker & Ostrander (2005).
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Method
Databases Web of Knowledge, PsycINFO and Medline were searched for studies addressing canine understanding of human social cues published in any year. The keywords “human cue,” “human gesture,” “pointing,” “communication,” “social cognition,” and “object-choice task” were used as major descriptors in combination with
“canine” and “dog.” We also searched relevant journals in animal cognition and animal behavior, as well as some more general journals (Animal Behaviour, Animal Cognition,
Applied Animal Behavior Science, Behavioral Processes, the Journal of Comparative
Psychology, Nature and Science). Abstracts were read to determine the type of human cue used and the general methodology. We wanted to compare studies that used similar types of gestures, so we did not include any studies that exclusively deployed more complex forms of point such as cross-lateral points, pointing with objects, markers, pointing with the torso or pointing with the head. We also excluded studies solely on juvenile animals (less than five months of age). We included studies that demonstrated any combination of proximal, momentary, distal and dynamic pointing features. We also included studies of points that were accompanied by eye gaze of different forms.
We found 14 peer-reviewed studies that met the above criteria. To maximize the comparability of our analyses we planned to evaluate individual results at a trial by trial level because the studies to be analyzed varied considerably in the number of trials administered. Analyzing trial data would also have allowed us to compare the learning curves of the different dog breeds. The corresponding author of each study was contacted with a request for trial by trial data from each subject, as well as information on any trials dropped from analysis. Of the nine authors that were contacted, three supplied us with the data we requested (corresponding authors of Brauer et al. 2006, Riedel et al. 2006, Udell,

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Dorey and Wynne 2008 and Udell, Giglio and Wynne 2008). Since we could not conduct a meta-analysis based on only four studies, we dropped the attempt at comparable trialby-trial analysis and instead present an analysis based on the seven published papers that provided individual subject results with a record of each dog’s breed (Table 1). Because the total number of dogs in each breed was very small, we analyzed the breeds clumped into AKC breed groups and Parker & Ostrander’s (2005) breed clusters. For the seven articles with sufficient data, we documented how the dogs were raised (e.g., pets, working, etc.), AKC breed group, Parker and Ostrander breed cluster, type of point used, number of trials correct, and number of trials given. In one case results were given at two different points in testing (after the first 15 trials and the last 15 out of a total number of trials varying between 30 and 80: Miklosi et al. 1998). For this study we only considered the results after 15 trials since this number was more comparable to the total number of trials used in other studies.
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Data Analysis
We grouped the dog breeds in two different ways. First by sorting the breeds into their AKC groups. Mongrels were not included in this analysis, but if the author stated the dog was a cross or mix breed and both of the breeds were assigned to the same AKC category, the dog was placed into that category (e.g. A German Shepherd and Collie mix was put into the AKC herding category).
Dog breeds were also grouped for analysis according to their genetic similarity as determined by Parker and Ostrander (2005). On this analysis, as shown in Figure 1, some breeds belonged in more than one cluster. For example, according to Parker and
Ostrander (2005), Dachshunds show a patterning of allele frequencies similar to the mastiff-type cluster, the herding/sight hound cluster and the modern sporting dog cluster.
In cases of this type the AKC breed categories were used as a ‘tie breaker,’ and the dog breed was assigned to whichever cluster most closely matched the AKC breed group.
Thus, in the case of Dachshunds, they were placed in the herding/sight hound cluster because the AKC labels this breed as a hound. Likewise, Labrador Retrievers, were categorized into the Modern Hunting cluster.
Individual performance of each dog was calculated as the percentage of correct responses (number of successful trials divided by the total number of trials x 100).
Performance of each dog was also coded as successful or unsuccessful depending on whether its performance level was significantly above chance (binomial p <= .05).
Proximal and distal points were analyzed separately. Results were aggregated across
AKC breed groups and Parker and Ostrander breed clusters for groups and clusters available from more than one study. Fisher’s exact test was then used to determine whether the number of successful individuals differed across breed groups and clusters.
One sample t-tests were used to determine if the average performance of each breed group or cluster differed significantly from chance. ANOVAs with the single factor breed group or cluster were used to determine if there were differences in the average performance of dogs belonging to the different groups and clusters.
An alpha level of .05 was adopted for all statistical tests.

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Results
The studies included in this analysis tested 52 dogs that could be assigned to 24
AKC recognized breeds, ranging in age from five months to 11 years old, on a range of human pointing types using from six to 24 trials (Table 1). Fifty two dogs could be assigned to one of four AKC breed groups (herding, hound, sporting, and working), leaving four breed groups with no representation (non-sporting, miscellaneous, terrier, and toy). Forty six of the dogs could be assigned to one of Parker and Ostrander’s (2005) breed clusters. Three clusters were represented (herding and sight hounds, mastiff-type dogs and modern Hunters) leaving one cluster (Asian dogs) unrepresented.
Figure 2 shows the percentage of dogs in each of the four represented AKC breed groups that were successful according to the binomial criterion for individual success, for proximal and distal points. Fisher’s exact test revealed no significant differences in the proportions of successful individuals in the four groups for either type of point (proximal p = .69, distal p = .27).
---Figure 2 About Here---
The mean performance of subjects in each of the AKC groups, shown in Figure 3, was significantly above chance levels for all four groups (one sample t tests: herding t(23) = 12.91, p < .0001; sporting t(24) = 9.97, p < .0001; working t(10) = 3.87, p < .01;
Hound t(5) = 4.17, p < .01). This analysis was performed pooled across both point types
(proximal and distal) because of the small ns in some groups. A single factor ANOVA revealed no significant differences in the mean percentage successful performance of the four breed groups (F(3,62) = 1.37, p = .26).
---Figure 3 About Here---
The percentage of dogs successful according to the binomial criterion for each of the three breed clusters defined by Parker and Ostrander (2005) represented in the studies analyzed is shown in Figure 4. There was no difference in the proportion of successful animals in the different dog breed clusters on a proximal point (Fisher’s exact p = .26).
However, there were significant differences between the proportions of successful dogs in the different breed clusters on the distal point (p = .02). Inspection of Figure 4 shows that for each point type, at least one breed cluster has very few dogs represented, thus the analysis was repeated pooled across proximal and distal points and this time the proportions of successful animals in each cluster did not differ from chance (p = .57).
---Figure 4 About Here---
Figure 5 shows the mean performance of subjects in each of the three breed clusters represented in the available studies. Each cluster was able to follow a human point at above chance levels (one sample t test: herding and sight hounds t(20) = 7.13, p
< .0001; mastiff-type dogs t(22) = 9.18, p < .0001; modern hunters t(10) = 5.80, p < .01).
Comparison of the mean percent correct performances of the breed clusters with a single factor ANOVA revealed no significant difference between the clusters F(2,52) = .08, p =
.92).
---Figure 5 About Here---
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Discussion
The present meta-analysis suggests few if any differences between breed groups or clusters in their ability to follow human pointing gestures to locate hidden food. Our analysis did suggest significant differences between breed clusters on the distal point,

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14 however this was due to the small numbers of subjects tested on that procedure in certain clusters.
What stands out when reviewing the current literature on dogs’ responsiveness to human cues is the similarity of performance levels obtained by research groups on different continents, working with groups of dogs varying in breed, age and presumably at least to some extent rearing conditions, and then tested under conditions which vary in many of their details.
There are several possible reasons for this lack of variability. One is the similarities in breed choices that have been made by researchers at different sites. Of the
58 dogs used in the studies obtained for this analysis, 19 were Retrievers or Retriever mixes and 17 were German Shepherds or mixes. The next largest population used in these studies was Dachshunds, represented by just five individuals. No other breed was represented by more than three dogs. Consequently the tested dogs only constituted four of the AKC’s eight breed groups and three of Parker and Ostrander’s (2005) four genetic breed clusters. This lack of breed diversity could be due simply to the popularity of certain breeds in the pet dog population. However, it is also possible that researchers are biased towards selection of these breeds as a result of their success in past experiments on these types of tasks. Possibly a wider range of breeds tested might reveal a wider range of performance levels.
Another possible explanation of the lack of any breed group or cluster differences in the present analysis is the lack of detail in the available results from prior studies. We had to abandon our intention to carry out an analysis at the individual trial level in face of the unwillingness of study authors to provide raw data. It is possible that such an analysis would have revealed differences in the rate of acquisition of the task that are not apparent in the total proportions of correct responses across all trials.
A final possibility is that there truly are no differences in the abilities of dogs to follow human points that can be assigned to the dog’s breed categorization. The recent evidence that suitably socialized grey wolves ( Canis lupus ) succeed on the object choice task at a high level without explicit training (Udell, Dorey & Wynne 2008; see also Gacsi et al. 2008) shows that this ability is present in the ancestral population of the modern dog, and this might lead to the prediction that this skill should be expected in all breeds of dog.
We do not, however, think it likely that this is the case. The argument against the view that all breeds of dog are equally proficient at following human points rests on the diversity of behavior found in different breeds of dog. Indeed, breeds of dog are defined, at least in part, by their different behaviors. This is seen most clearly in the characteristic pattern of canine hunting behaviors. Coppinger and Coppinger (2001) identified the seven functional motor patterns that constitute the hunting behavior of a wolf, starting by orienting towards its prey, through eye stalking, chasing, etc., and ending in consumption.
Coppinger and Coppinger (2001) point out how, in different breeds of dogs, different components of this hunting behavior have either been weakened or strengthened, so that we end up with breeds such as the Border collie, which orients to prey, eye stalks it to an exaggerated degree, can chase, but seldom proceeds to grab and kill its target. At its most extreme, livestock guarding dog breeds, such as the Anatolian shepherd dog, show very little tendency to orient, chase, bite or do anything except consume food placed in front of them. Studies of breed differences in other aspects of behavior are not numerous, but

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1965; Svartberg 2006), handling of novel situations (Plutchik 1971), working performance (Brenoe, Larsgard, Johannessen, & Uldal 2002), activity and playfulness
(Hart and Miller 1985) and trainability (Serpell and Hsu 2005). Many of these studies are complicated, however, by the fact that different breeds of dogs may be customarily raised under differing conditions. Nonetheless this diversity of behavior correlated with breed shows that there is little force to the argument that because a behavior is present in wolves it must be identifiable equally in all breeds of dog.
Several hypotheses can readily be derived that lead to predictions of differential success in different dog breeds in following human pointing gestures. These predictions could be related to the characteristic behavioral patterns of a breed of dogs which in part define the reasons for the existence of different AKC breed groups, or genetic arguments developed around Parker and Ostrander’s (2005) breed clusters.
As an example of a prediction based on breed-specific behavioral patterns, one might hypothesize that the ability of dogs to follow human points is related to their ability to track prey. If this were the case then breeds with very limited prey-following tendencies, such as the livestock guarding Anatolian shepherds and Pyrenees, would be expected to perform poorly on the object choice task.
Alternatively, it might be hypothesized that dogs bred solely for appearance, such as dogs in the AKC’s toy breed category, might lack the ability to ability to follow human gestures because this capacity has not been emphasized in the development of these breeds.
Finally, although at the present time, behavioral genetic research on dog breeds is still in its infancy, some behavioral deficits have been linked to particular breeds (see
Ostrander & Wayne 2008, for a review). Thus in the near future it may be possible to trace the genetic bases for abilities such as following human pointing cues and predict success or failure on this task in different breeds or breed clusters of dogs.
One thing that any future breed studies will have to ensure is to test animals which have been raised, housed and tested under strictly comparable conditions. It is clear that rearing, holding and testing conditions can have a major impact on performance on object choice tasks (Udell, Dorey & Wynne 2008).
In conclusion, the major limitation of this meta-analysis was the unwillingness of most authors to share their raw data. This prevented a trial-by-trial analysis of performance and severely restricted the number of animals’ data available for comparison. In a field where even the definition of a trial is not uniform (some authors score refusals of the dog to select one of the two containers as a incorrect response, others silently ignore these “balks” and repeat the trial), the importance of peer access to raw data is paramount. Sharing raw data is also an ethical principle of the American
Psychological Association and other professional societies, and a requirement for publication in many journals. The databases used in this field are not large and thus there exists no practical obstacle to completely free access to raw data. Such sharing of raw data would also reduce the need for unnecessary replication of studies and enable the exciting field of canine cognition and behavior research to move forward more rapidly.

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1 Tables
Table 1:
Number of trials, age range, number of dogs used in each grouping and the point features of each study utilized in the meta-analysis. Abbreviations: “mo” – month; “yr” – year; “w/” - with.
Hare & Tomasello
(1999)
Source
Brauer, et al. (2006)
Number testing trials
Age range
6
24
Miklosi, et al. (1998) 15
1 - 11 yr
5 mo -
4 yr
1 yr 5 mo - 7 yrs 5 mo 9
Number of dogs in breed group analysis
16
7
Number of dogs in breed cluster analysis
12
7
Pointing procedure
Momentary
Proximal and
Dynamic
Proximal
Dynamic
Distal w/human gaze
9
Riedel et al. (2008)
Udell, Giglio &
Wynne (2008)
8
Soproni et al., (2002) 8
10
6.9 ±
3.9 yrs
2 - 7 yrs
2
7
11 mo -
5 yrs 4
0
7
4
Momentary
Distal
Dynamic
Distal w/human gaze
Momentary
Distal
Momentary
Proximal
Udell, Dorey &
Wynne (2008)
Totals
10
5 mo -
6 yrs 7
52
7
46
Momentary
Distal
2

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1 Figure Legends
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Figure 1:
Cluster placement of each of the 85 breeds of dogs analyzed by Parker and
Ostrander (2005). Redrawn from Parker and Ostrander (2005).
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Figure 2:
Top panel, percentage of dogs in each AKC breed group successful in following a proximal pointing gesture according to a binomial probability criterion, p <= .05. Bottom panel, percentage of dogs in each breed group successful in following a distal point.
Numbers in each column are the total number of dogs in each group for that point type.
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Figure 3:
Mean percent correct performance of each of the AKC breed groups. Dashed line shows chance (50%) level. Asterisks indicate performance significantly above chance.
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Figure 4:
Top panel, percentage of dogs in each Parker and Ostrander (2005) breed cluster successful in following a proximal pointing gesture according to a binomial probability criterion, p <= .05. Bottom panel, percentage of dogs in each breed cluster successful in following a distal point. Numbers in each column are the total number of dogs in each cluster for that point type.
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Figure 5:
Mean percent correct performance of each of the Parker and Ostrander (2005) breed clusters. Dashed line shows chance (50%) level. Asterisks indicate performance significantly above chance.

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Figure 1:
MASTIFF-TYPE
Presa Canario
MODERN
HUNTING
Pointer
Irish Setter
German Shorthaired Pointer
Welsh Springer Spaniel
English Cocker Spaniel
American Cocker Spaniel
American Water Spaniel
Cavalier King Charles Spaniel
Chesapeake Bay Retriever
Golden Retriever
Portuguese Water Dog
Clumber Spaniel
Australian Shepherd
Rhodesian Ridgeback
Irish Terrier
Bedlington Terrier
Kerry Blue Terrier
Soft Coated Wheaten Terrier
Flat-Coated Retriever
Labrador Retriever
Chihuahua
Rottweiler
Bullmastiff
Newfoundland
German Shepherd Dog
French Bulldog
Miniature Bull Terrier
Bulldog
Boxer
Mastiff
Saint Bernard
Bernese Mountain dog
Pomeranian Greater Swiss
Dachshund Mountain dog
Miniature Schnauze
Standard Schnauzer
Giant Schnauzer
American Hairless Terrier
West Highland White Terrier
Cairn Terrier
Australian Terrier
Airedale Terrier
Doberman Pinscher
Italian Greyhound
Ibisan Hound
Pharaoh Hound
Old English Sheepdog
Border Collie
Schipperke
Beagle
Basset Hound
Bloodhound
Pug
Dachshund
Bischon Frise
HERDING DOGS
Standard Poodle
Whippet
AND SIGHT HOUNDS
Irish Wolfhound
Manchester Terrier
Keeshond
Greyhound
Norwegian Elkhound
Komondor
Belgian Sheepdog
Kuvasz
Great Dane
Borzoi
Belgian Tervuren
Collie
Shetland Sheepdog
Samoyed
Lhasa Apso
Pekingese
Shin Tzu
Tibetan Terrier
Afghan Hound
Saluki
ASIAN/AFRICAN
Akita
Shiba Inu
Chow Chow
Chinese Shar-Pei
Alaskan Malamute
Siberian Husky
Basenji
2
3

Meta-analysis, 13
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2
Figure 2
3
4

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Meta-analysis, 14
Figure 3
2

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5
6
Meta-analysis, 15
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Figure 4

Meta-analysis, 16
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Figure 5:
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3

Meta-analysis, 17
1
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