Identity profiles based on social strategies, morphology, physiology, and cognitive abilities in goatsM. Pascual-Alonso a, G.A. María a, W.S. Sepúlveda a, M. Villarroel b, L. Aguayo-Ulloa a, F. Galindo c,G.C. Miranda-de la Lama dAbstractThe aim of this study was to analyze the structure of identity proﬁles based on social strategies, morphology, physiology, and cognitive abilities in domestic goats. Social interactions of 33 goats were recorded over a period of 16 days for 96 hours. Blood samples and morphological measurements were taken from each animal, and they were each put through a T-maze test. Using the test of factor analysis, 3 of 7 types of social interactions concentrated 76.6% of the variance. They were named the “avoider” factor (21.20%), “nonagonistic” factor (16.30%), and “agonistic” factor (39.10%). Subsequently, a hierarchical cluster analysis was performed to characterize identity proﬁles (groups of similar animals), which could help to explain the possible association between social strategies (obtained using the factor analysis) and index of success, social and individual behaviors, and morphological, physiological, and cognitive char-acteristics. The results suggest the existence of 4 clusters or identity proﬁles, which were termed “aggressive,”“afﬁliative,”“passive,” and “avoider.” When they were compared between clusters, each identity proﬁle had signiﬁcant differences regarding all social variables, feeding and resting variables, most of the physiological measures, and all the morphological characteristics. The resolution time for the T-maze was signiﬁcantly different between clusters and days. In conclusion, associating social strategies with details of behavior, physiology, and morphology provides a more robust idea of identity proﬁles adopted by goats under intensive farm conditions and suggests a richer diversity of strategies used by goats.Keywords:individual differences; social strategies; identity proﬁles; cognitive abilities; goatsIntroductionDifferences among individuals are the substrate for natural selection. Behavioral variation reﬂects the individual’s capacity to cope with social and physical environmental demands (Carere et al., 2003). Individual behavioral differences have also been viewed as an adaptation in themselves, because of either social advantages or frequency-dependent selection that operates to maintain variation. Consistent individual differences in behavior have now been documented in a broad range of animals over a variety of contexts.However, individual differences in social contexts have received less attention (Morand-Ferron et al., 2011). The behavioral ecology theory of alternative strategies raises the possibility that individuals of different rank may be following alternative and perhaps equally successful social strategies. Recent behavioral research in farm animals has focused on identifying consistent relationship between social strategies and identity proﬁles. An identity proﬁle can be deﬁned as a coherent set of social strategies as well as behavioral and morphological adaptations, which are consistent over time and characteristic of certain social groups (Miranda-de la Lama et al., 2011).Farm animals under intensive production systems are housed in barns under conditions that differ substantially from their natural habitat, with limited space and herd sizes. Under these conditions, social relationships also imply a higher competition for resources and conﬂict of interest. Particularly in groups with unstable social structures, an increase in conﬂicts of interest may increase aggression and jeopardize future cooperation (Aureli et al., 2002). As a consequence, individuals are forced to buildaDepartment of Animal Production and Food Science, Faculty of Veterinary Science, University of Zaragoza, Spain bDepartment of Animal Science, E.T.S.I.A. Polytechnic University of Madrid, Madrid, Spain cDepartment of Ethology and Wildlife, Faculty of Veterinary Medicine, National Autonomous University of Mexico,UNAM,MexicodGroup of Animal Welfare and Sustainable Livestock Production, Department of Food Science, Metropolitan Autonomous University, Lerma, UAM, State of Mexico, Mexicoadequate social strategies to respond to the social challenges posed (Miranda-de la Lama et al., 2011). Maintenance of a social hierarchy partly depends on social recognition and learning ability as animals must be able to discriminate between conspeciﬁcs to establish and maintain the social order (Croney et al., 2007).Social stress caused by intensive production disrupts cognitive processes like learning and memory. Stress appears to affect the degree of attention and the speed of decision making, whereas chronic stress may affect cognitive abilities (Mendl, 1999). Animals with higher cognitive abilities should be more capable of producing new, modiﬁed, or innovative behaviors as this ability would allow them to cope better with unpredictable social and physical envi-ronmental changes, both in terms of improving survival and ﬁtness and in terms of trying to achieve positive emotional states and avoid suffering (Wechsler and Lea, 2007). Agitated animals are less effective at making clear decisions in choice tests. Cognitive per-formance is improved when an individual is within a range of optimal stress, above or below which this performance decreases (Mendl et al., 1997). There are relatively few studies on personality or identity in domestic animals, and those that have been carried out have been concerned with understanding the effect of identity on behavior and physiology (pigs, Ruis et al., 2000; dairy cows, Van Reenen et al., 2002), social strategies and physiology (beef cows, Mülleder et al., 2003), as well as social strategies and morphology (dairy goats, Miranda-de la Lama et al., 2011). Studies of identity traits in domestic animals are important, not only from an evolu- tionary perspective but also in relation to practical situations such as handling in intensive production systems. Clariﬁcation of this relationship might provide insight into how and why goats of different social ranks are able to survive, particularly when resources, such as food, water, shelter, and space, are limited. The present article aims to analyze the structure of identity proﬁles, with the hypothesis that there is a high interrelation of social strategies, morphology, physiology, and cognitive abilities in goats that characterize types of individuals.Materials and methodsThe study was carried out in the Autonomous Community of Aragon (northern Spain) in June and July 2011, at the experimental research farm of the Food Technology and Research Centre, CITA, Zaragoza province (41 430 N, 0 480 W; 225 m above the sea level). All protocols were approved by the Animal Experimentation Ethics Committee of the University of Zaragoza.Animals and housingWe used 33 female Angora goats (5-8 years of age, nonlactating, nonpregnant, multiparous, and horned) that had been housed in a 27 10 m pen (stocking density 8 m2 per goat) for 3 years before the observations were carried out. The goats were fed twice a day, in the morning between 08.00 and 08.30 hours and in the afternoon between 15.00 and 15.30 hours. All the animals were fed pellet concentrate (11.5 MJ metabolisable energy/kg dry matter and 15.5%crude protein; approximately 0.3 kg per goat), and Lucerne chaff (Medica gosativa) ad libitum. The pen was equipped with a metallic water trough (1.5 x 0.60 m) and 2 metallic feeders (4.5 x 0.80 m, 27 cm per goat), and a lick stone for minerals.Behavioral measurementsDirect observations, with a combination of scan and behavior sampling, were carried out to collect information on individual and social behaviors, respectively. All goats were individually identiﬁed and marked with 30-cm-high numbers and letters painted on the sides and rump with washable paint for sheep marking (Peinture Marquage Mouton; Laboratoires Natura A platform with a seat 3 m above the ground was used to observe the goats from a dis-tance. The goats were observed 6 hours daily, from 7:00 to 9:00, 11:00 to 13:00, and 17:00 to 19:00 for 16 consecutive days (96 hours of observation) by the same trained observer.Social behaviorA behavior sampling technique was used to record all agonistic and nonagonistic interactions, both with and without physical contact. Agonistic interactions with contact included butts, when the goat used the front of her head to make contact with another goat; pushes, when a goat used other parts of her body to make contact with another goat; and bites, when one goat bit another goat’s body using her teeth. Agonistic interactions without contact included threats, when a goat turned toward or approached another individual with her head down and then lunged without making contact; chase, when a goat actively moved toward another individual, causing the latter to walk or run away; and avoidance, when a goat actively moved away from anotherindividual whether or not previous interaction had occurred between the 2 individuals. Nonagonistic interactions with contact included licking, when a goat passed her tongue over the body of another individual; grooming, when a goat groomed another goat’s body using her teeth. Nonagonistic interactions without contact included snifﬁng, when a goat sniffed another goat’s body and the ﬂehmen response, when a goat retracted the upper lip, wrinkled the nose, and bared the gums in the presence of another goat..For each animal, the total number of times engaged in each of those social interactions was calculated. Indices of success were calculated using the data collected on interactive behaviors to reﬂect the social status of each goat according to her experiences in agonistic interactions with any other member of the herd. Taking into account those interactions that resulted in a displacement of the receptor goat, the index of each goat could therefore range from 0 to 1 and was calculated according to Mendl et al. (1992). Index of success (IS) = number of individual goats the goat is able to displace/(number of individual goats she is able to displace þ number of individual goats able to displace her). The goats were then placed, as in the study by Alvarez et al. (2003), into 3 ranking categories according to their IS: low (IS = 0.0-0.33), medium (IS = 0.34-0.66), and high ranks (IS = 0.67-1.0).Individual behaviorOn each of the observation days, a scan sampling was carried out every 10 minutes (576 samples) to obtain information on the total time spent lying down (goat resting with eyes open or closed); drinking (goat with head inside the water trough); feeding (goat with head inside the feeder trough); and walking (goat moving from one place to another). Individual goats were observed at different times of the day so that, when averaged across the study, each part of the day was equally represented. For each goat, the time spent in nonsocial behaviors during the study was expressed as a proportion of observations calculated as follows: number of observations of a behavior/total number of scan samplings.Physiological measurementsBlood samples were taken by jugular venipuncture per goat between 18:00 and 19:00 hours a day after behavioral observations ended (two 10-mL tubes were collected per animal, with and without anticoagulant, EDTA-K3). Approximately an hour before blood sampling, the site of venipuncture was clipped and covered with an anesthetizing cream to minimize the response to the initial puncturing of the skin. Restraint during blood sampling was kept to a minimum, and the total duration of the procedure did not exceed 1 minute. The handler grasped the halter with 1 hand and with the other groomed the goat’s neck to direct attention away from the blood sampling procedure. Samples were kept on ice for less than 1 hour and taken to the laboratory for routine hematological measurements. The EDTA plasma and serum were centrifuged at 3000 rpm for 10 minutes, and aliquots were frozen and kept at 30 C until analyzed.The concentration of cortisol was determined from plasma (EDTA-K3) by enzyme immunoassay using an “in-home kit.” Each sample was determined in duplicate from 50 mL of plasma, and the results were expressed in ngnL 1, with the corresponding controls. Variation coefﬁcients of the analysis, interassay and intraassay, were 7% and 8%, respectively. The concentration of lactate was deter-mined using a SigmaeAldrich Diagnostic kit (lactate no. 735-10; SigmaeAldrich, St Louis, MI) and spectrophotometer (Lambda 5; Perkin Elmer, Waltham, MA). Serum samples were analyzed with a Multichannel Technicon Analyser (RA-500; Bayer, Barcelona, Spain) using reagents from Bayer diagnostics (SA, Barcelona, Catalonia, Spain) for RA technicon systems to determine the concentration of glucose (mg dL∙L) (Ref. T01-1492-56) and the activity of creatine kinase (CK) (CI<), EC 2.7.3.2 (UI L∙L) (Ref. T01-1885-01). Serum concentration of nonesteriﬁed fatty acid (NEFA) levels was analyzed by a multianalyser ACE (Clinical Chemistry System; Alfa Wasser-man, Woerden, The Netherlands), with commercial kits (NEFA C Ref. 994-75409 of the Wako). Finally, the leukocyte formula was estimated from blood swabs on clean slides. Staining was performed by the rapid panoptic method using dyes from Química Clinica Aplicada, Inc. (Aposta, Catalonia, Spain). With an optic immersion microscope, we counted and identiﬁed 100 leukocytes per sample (neutrophils, lymphocytes, eosinophils, basophils, and monocytes). The neutrophil/lymphocyte (N/L) ratio was used as a stress indicator in goats according to Kannan et al. (2000) and Rajion et al. (2001).Morphological measurementsMorphological traits were measured 1 day after blood sampling, using a measuring tape. Body measurements included body length (BL), height at withers (HW), and thorax circumference (TC). Additionally, each goat was weighed using a portable digital weighing scale.Cognitive testWe used a T-maze built with 1.40-m high plastic panels (Figure 1). It consisted of a start box, isolation chamber (2 2 m) joined on 1 of its sides to a T-corridor. The start box was fully closed but large enough to enable an individual to move around. The T- corridor consisted of a 4 0.80 m path linked to 2 perpendicular arms (1.65 1.65 m each). A mirror (70 30 cm), loudspeaker, and plastic feeder (with feed pellets) were located in the target zone on the left arm. An observation platformwas located on a 3-m high platform so as not to inﬂuence animal movement, adjacent to the T-maze apparatus. The apparatus was kept in a soundproof room (9 6 m) held at constant temperature and humidity during the trial.The sounds used in the experiment were a playback of sounds present during the feeding time. The stimulating sound consisted of different components, such as metallic noise of the feeder when the goats are feeding, handling noise of the concentrate feed paper bag, and the noise of pellets falling onto the feeder. We recorded at a distance of 50 cm from the noise source using a Handy Recorder H1 (Zoom Corporation, Tokyo, Japan) numeric recorder (sampling rate: 44.1 kHz). Sounds were then imported into a computer at a sam-pling rate of 44.1 kHz and saved in WAV format at 16-bit amplitude resolution. We used Audacity� 2.0 (General Public Licence) audio software for the preparation of sound sequences that were played back. A sample of each of these sounds was combined into a 5-minute segment, and a random portion of this segment was played at each trial. The noise was played and measured using a Bioblock Scientiﬁc Sound Level Meter type 50517 (Thermo Fisher Scientiﬁc Inc.), at a set volume that ensured goats were exposed to 81 dB of intensity through most of the T-maze. For each trial, the sounds were played back by a Handy Recorder H1 connected to a loud-speaker located at ﬂoor level in left arm in the target zone.Each goat underwent the cognitive test on 2 consecutive days. Each goat entered the testing equipment 2 times in total, once on each day of test, without receiving prior training. Each animal stayed in the start box for 20 seconds before a guillotine door was lifted to allow entrance into the maze. After the goat left the start box, the guillotine door was quietly closed. At the same time, recorded playback was played and the test was started. The test was considered to be successfully passed when the individual found the target zone (which was always located in the left arm) where there was a mirror (social clue), the sound source (sound clue), and concentrate feed to reinforce behavior. Each animal was given a maximum time of 5 minutes to solve the T-corridor. No animal exceeded this time limit. The test was ﬁlmed, and the time taken by each goat to solve the T-corridor was recorded.Reactivity to handling testEach goat was subjected to reactivity to handling test in 2 stages: restraint by handler and restraint by squeeze chute. Each stage took place at an interval of 1 week. The ﬁrst stage consisted of the random capture and restraint of an animal by a handler. Restraint continued for 1 minute, during which a photograph was taken with an infrared thermography camera. In the second stage, the animals were randomly led into a squeeze chute where each animal was restrained for 1 minute and an infrared photograph was taken. An infrared thermography camera (Testo 880 Thermal Imaging Cam-era; Testo AG, Lenzkirch, Germany) was used to collect images of the eye during both restriction practices to evaluate acute stress response. All images were collected from the left side of the goat (approximate distance of 1.5 m). The built-in lens (24 ) was used, and the camera was calibrated for the current room temperature and relative humidity. The emissivity value used was 0.98, which is the recommendation of the camera manufacturer for biological tissues. A good-quality infrared image (precise location and perfect focus) was chosen for each animal. Image analysis software (IRSoft software; Testo AG, Lenzkirch, Germany) was used to determine the maximum temperature within an oval area traced around the eye, including the eyeball and approximately 1 cm surrounding the outside of the eyelids (Stewart et al., 2007).Statistical analysisAll statistical analyses were carried out with the SPSS (IBM� SPSS�), version 14.0 software package. As an initial measurement, univariate analyses were carried out for all the variables studied to understand individual behavior and to detect atypical data.Factor analysisA factor analysis was used to summarize the data of 7 social behavioral variables and to understand their correlational struc-ture. Agonistic and nonagonistic behaviors were grouped in the classes described in behavioral sampling to analyze them: no. of times each goat initiates an agonistic interaction with physical contact; no. of times each goat initiates an agonistic interaction without physical contact; no. of times each goat receives an agonistic interaction with physical contact; no. of times each goat receives an agonistic interaction without physical contact; no. of times each goat initiates a nonagonistic interaction with physical contact; no. of times each goat receives a nonagonistic interaction with physical contact; and no. of times avoiding another goat.The factors were extracted using principal components. The KaisereMeyereOlkin index and Bartlett test of sphericity were used as a measure of high correlation between variables. The factors selected had eigenvalues greater than 1. To gain a better under- standing of the factors obtained, a Varimax method of orthogonal rotation was carried out. Accordingly, the factor scores in the analysis were estimated by means of the regression method and were consequently used to carry cluster analysis.Cluster analysisA hierarchical cluster analysis was performed to identify dif-ferences in social interactions. The cluster analysis enables segments of individuals to be identiﬁed, so that the characteristics of individuals that belong to the same group are as similar as possible, although, when compared with other groups, they are as different as possible. The distance used was the squared Euclidean distance, and the Ward method was used for agglomeration. The variables used to calculate the squared Euclidean distances were the scores of the 3 factors obtained and the 2 variables corre-sponding to conﬂict resolution. To reduce the effects of scale when forming the clusters, both groups of variables were standardized. The graphic solution used was the dendogram (Figure 2). Once the membership to cluster variables had been created, they were then characterized using different variables, such as IS, classes of behavior (factorial scores), individual behavior variables, physio-logical, morphological traits, cognitive abilities, and acute response to 2 methods of physical restriction. To select the most signiﬁcant variables that would enable differentiation between clusters ob-tained, a nonparametric KruskaleWallis test and several nonpara-metric paired ManneWhitney tests were carried out, bearing in mind the characteristics of the study and variables.ResultsFactor analysisThree factors explained 76.6% of the variance. The parameters loaded high on those factors (Table 1). The ﬁrst factor accounted for 21.2% of the total variance and was characterized by 2 of the 7 vari-ables that were used: number of times each goat received an agonistic interaction with physical contact and number of times it avoided another goat. These variables had a very signiﬁcant loading ( 0.7), and this factor was labeled as the “avoidance factor.” The second factor accounted for 16.30% of the total variance and was character-ized by 2 variables: number of times each goat initiated a nonagonistic interaction with physical contact and number of times each goat received a nonagonistic interaction with physical contact. These var-iables had a very signiﬁcant loading ( 0.7), and this factor was labeled as the “nonagonistic factor.” Factor 3 accounted for the remaining 39.10% of the total of variance. It was characterized by 2 variables, which had very signiﬁcant loadings ( 0.9): number of times each goat initiated an agonistic interaction without physical contact and number of times each goat initiated an agonistic interaction with physical contact. Factor 3 was labeled the “agonistic factor.”Cluster analysisThis multivariate analysis suggests the existence of 4 clusters or identity proﬁles that explain their association with behavioral, physiological, and morphological traits as well as the acute response to 2 methods of physical restriction (Table 2) and cogni-tive abilities (Table 3). The distribution of animals by strata is not homogeneous (cluster 1: 11 goats, cluster 2: 2 goats, cluster 3: 15 goats, and cluster 4: 5 goats). Given the associations that were found in each cluster, 1 was termed “aggressive,” 2 “afﬁliative,” 3 “passive,” and 4 “avoider,” according to the social strategy prefer-entially used for each proﬁle.Social and individual behaviorsAs expected, all the social variables were different among clus-ters. The aggressive proﬁle was characterized by highly dominant individuals (IS ¼ 0.70) with highly agonistic behavior values. The afﬁliative proﬁle was characterized by animals of average domi-nance (0.41), with nonagonistic behavior. The passive proﬁle group was made up of low-dominance individuals (0.33) that displayed negative values toward the 3 social strategies. Finally, the avoider proﬁle had low-dominance individuals (0.31), with high evasive factor scores.In the case of individual behaviors, only the feeding and resting variables were statistically signiﬁcant. In the aggressive proﬁle, more time was spent feeding compared with the other proﬁles (P<= 0.001), whereas the least amount of time was spent resting. Individuals of the afﬁliative proﬁle spent the most amount of time resting, along with the passive proﬁle (P<=0.013). Like the afﬁliative animals, passive goats spent less time feeding and intermediate values for resting. Avoider animals had intermediate values for feeding and resting.Physiological measurementsPhysiological measures had a signiﬁcant effect on all variables, except for lactate, CK, and N/L ratio. Aggressive goats had the lowest levels of cortisol and NEFA but the highest glucose levels. Afﬁliative goats had the highest cortisol and NEFA levels and the second highest glucose levels. Passive animals had intermediate values of cortisol and NEFA. Cortisol levels of the avoider proﬁle were the lowest in the study (along with the aggressive proﬁle), and glucose levels were similar to those of the afﬁliative and the passive proﬁle, but they had the highest NEFA levels along with the afﬁliative proﬁle.Morphological measurementsFor the morphological characteristics, signiﬁcant differences were observed within all the variables studied. Morphologically, aggressive goats were the largest and heaviest individuals. The afﬁliative proﬁle had the smallest BLs and an intermediate height, compared with the rest of the proﬁles. TC and body weight were statistically similar to evasive and passive proﬁles but smaller than the aggressive goats (P <=0.01). Passive goats had a lower HW (P <=0.05) and the second shortest BL in the study. TC and body weight were statistically the same as evasive and afﬁliative goats but less than that of the aggressive animals. Avoider goats had the longest body and greatest HW, after the aggressive goats. Their TC and body weight were statistically similar to those of the afﬁliative and passive proﬁles but less than the aggressive proﬁle.Cognitive testIn the case of the cognitive test, resolution time was statistically signiﬁcant between clusters and also days. Aggressive goats took the second longest time in solving the T-corridor during the ﬁrst exposure (P <=0.01) and the longest time during the second expo-sure (P <= 0.05). However, comparing the difference between days, this proﬁle did not show any signiﬁcant difference and took the same time to solve the T-corridor on day 1 and 2. Afﬁliative goats spent the longest time to solve the T-corridor during the ﬁrst exposure and an intermediate time for the second exposure. When compared between days, this proﬁle solved the T-corridor in less time (P <=0.001). Passive proﬁle solved the T-corridor in less time than the rest of the proﬁles in the study during the ﬁrst exposure. When the difference between days was compared, this proﬁle was the quickest of all the groups, reducing the time by half on day 2 with respect to day 1 (P <= 0.01). Avoider goats behaved similarly to the passive proﬁle.Reactivity to handling testFinally, for the reactivity to handling test, only restriction by squeeze chute had a signiﬁcant effect (P <=0.05). The aggressive goats obtained intermediate temperature values along with the passive proﬁle. The temperature of the afﬁliative goats was the lowest of all proﬁles after the squeeze chute restraint phase. Passive goats had intermediate temperature values, similar to those of the aggressive proﬁle. Body temperature of the avoider goats after the handling reactivity test was the highest of the study (squeeze chute restraint phase).DiscussionIn our study, a series of behavioral and morphological traits suggest the existence of 4 types of proﬁles: aggressive, afﬁliative, passive, and evasive. We have furthermore found an association between physiological and cognitive characteristics that strengthen the identity proﬁles. Although the characterization of each proﬁle is closely related with social strategies and dominance order, we have found that there are certain differences in individual behaviors and morphological characteristics vary from the study by Miranda-de la Lama et al. (2011), who worked with dairy goats using methodology similar to ours. These differences may indicate that although social strategies may be stable in a species, individual behavior and morphology may reveal adaptive variations. Differences between animals with different levels of dominance may increase in more demanding environments in production terms (Andersen and Bøe, 2007). In this context, dairy production systems are more demanding productively than goat meat or goat hair production systems, and this stimulates each proﬁle to make behavioral and morphological adjustments to improve inclusive ﬁtness that will allow the animals to survive. This would explain the differences between the results of observations in hair production goats in this study and dairy goats in that of Miranda-de la Lama et al. (2011).Feeding and resting behaviors are clearly 2 traits that are affected by the identity proﬁle. This relationship may be because of the fact that both behaviors are inﬂuenced by social facilitation (Nicol, 1995) and dominance order (Barroso et al., 2000), so that it is reasonable to assume that highly dominant individuals obtain more beneﬁts from their social status because they have priority access to resources such as food and resting places (Robitaille and Prescott, 1993). Our results show that the animals in the aggressive proﬁle spent more time feeding, followed by the evasive animals. This is perhaps because both proﬁles constantly compete for food. Although the time devoted to this activity is not necessarily pro-portional to a large intake of food, perhaps the aggressive in- dividuals selectively consume good-quality forage (Matsuzawa and Hagiya, 1991), in comparison with afﬁliative and passive animals that probably consume the food that remains, with different thresholds of selective efﬁciency (Miranda-de la Lama et al., 2011).Several measures can be used to evaluate the animal welfare, including behavior and biological functions related to stress phys- iology. These evaluations should be based on multicriteria ap-proaches because no single measure can unequivocally be related to the level of welfare. Among those, neuroendocrine parameters are probably the most widely used because corticosteroid hormone secretion by the adrenal cortex has been equated with stress level since the very beginning of the stress concept. Indeed, circulating levels of corticosteroid hormones are very sensitive to a wide range of stimuli including low level of emotional activation such as induced by social stress (Mormède et al., 2007). Various studies of domestic ruminants indicate that highly dominant animals have lower levels of cortisol than animals of average and low dominance in socially stable groups (Galindo et al., 2000). However, in our study, the animals with an afﬁliative proﬁle (average dominance) had the highest levels of cortisol in the study. In intensive farming systems, afﬁliation as a strategy is not useful; when competing for resources, an aggressive strategy is more effective (Miranda-de la Lama et al., 2012). On average, dominant animals are highlighted as being more efﬁcient in metabolic terms, with greater production yields (Barroso et al., 2000). However, it is possible that this inclusive ﬁtness is impaired in competitive social environments (Conway et al., 1996). In this context, the afﬁliative and evasive proﬁles had higher levels of NEFA and lower values of glucose, although they were within the reference values for the species (Piccione et al., 2010).NEFA is considered a biomarker of the negative energy balance when glucose supply is insufﬁcient to satisfy energy requirements (Adewuyi et al., 2005). In the case of the evasive animals, the relationship of high cortisol and NEFA values and low glucose values is not fulﬁlled. One possible explanation could be related to evasive animals that had a higher threshold of susceptibility to social stress than the afﬁliative proﬁle because they would be used to social stress, although they would suffer some energy repercussions in adjusting to the social environment.Morphological traits may be honest signals that communicate a certain genetic value (Smith et al., 2009), biological efﬁcacy (Rowe, 1999), and information for social recognition, providing, for example, information on the age, sex, and individual identity(Keil et al., 2012). From our results, these signals are linked to the char-acterization of the identity proﬁles. Although some have a greater power of discrimination (such as BL and HW compared with TC and weight), with the exception of the aggressive proﬁle, all the other proﬁles were statistically similar. In this respect, the aggressive proﬁle was found to be heaviest and have the greatest measure-ments. That conﬁrms what has already been described by other authors in the case of highly dominant goats (Barroso et al., 2000). However, body sizes are not proportional to the dominance scale, and some of the measurements of evasive animals were higher than the afﬁliate and passive proﬁles. It is probable that in meat and hair production goats, morphological variables are distributed differ-ently because the selection programs are less strict when compared with dairy animals in intensive production systems.The time taken by goats to solve the T-corridor was interpreted as the ability to learn from speciﬁc stimuli, actions, and results to be able to solve a challenge (Morton and Avanzo, 2011). Our results indicate that aggressive goats took longer to locate the sound source the ﬁrst and second day of exposure, unlike the other pro-ﬁles which, even on the second day of exposure, signiﬁcantly reduced the time it took to solve the T-corridor by more than half. It is possible that the low-dominance goats have to learn quickly how to relate socially (compared with the high-dominant goats), to avoid aggressions (Croney and Newberry, 2007). Thus, they must be more ﬂexible to adopt alternative strategies to obtain valuable resources such as food (Croney et al., 2007). This mental ﬂexibility would mean that the association between the stimulus used and food would be more attractive for animals that have restricted access to it.The handling practices to which animals are subjected can cause fear, anxiety, and reactivity to humans as well as affect the way in which animals adapt to production environments (Nordquist et al., 2011). These practices can be measured using noninvasive tech-niques such as infrared thermography, which can determine heat loss gradients in the ocular area caused by blood kinetics, as part as the sympatheticeadrenal response during acute stress (Stewart et al., 2007). Our results indicate that physical restraint by a handler does not signiﬁcantly alter the response of the 4 proﬁles in our experimental conditions. This may be because the quality of the humaneanimal relationship has a greater inﬂuence on fear and reactivity during handling than the innate reactivity of the animal to humans (Waiblinger et al., 2006). Nevertheless, squeeze chute re-straint does increase temperature, and this indicates a heightened state of reactivity in the evasive proﬁle. The evasive animals are those that actively participate in social interactions but with few results and they occupy a low position in the dominance order. This characteristic perhaps makes them prone to displaying a greater reactivity, as was seen in the physical restraint test. The infrared thermography camera is a useful tool for measuring handling reac- tivity in a noninvasive way and to evaluate acute responses to stress.Conclusions and implicationsThe identity proﬁles of the group of stabled goats observed were characterized by social strategies, behavioral, physiological, morphological traits, as well as cognitive abilities. Four proﬁles were distinguished (aggressive, afﬁliative, passive, and evasive), which were associated with social strategies to create, adjust, and use a series of behavioral solutions to adapt to intensive productive systems. These adaptations are evidence of the behavioral adaptive strategies that the individuals develop to survive in a competitive and artiﬁcial environment such as the production system. Although social strategies are closely linked to the creation of each proﬁle,there are variations in certain behavioral, physiological, or even morphological traits in animals of the same species but which are destined for different production purposes.The identity proﬁles based on social strategies, morphology, physiology, and cognitive abilities may be a valuable tool to assessment of the animal welfare. Insight into this individuality can be used to carry out recommendations on changes in herd handling aimed at improving social cohesion and achieving more efﬁcient management procedures. To characterize types of goats would permit to establish relationships between certain behavioral or morphological traits of interest and other traits of interest such as stress response or cognitive ability and thus the possible susceptibility to stress-related diseases and the efﬁcacy of a given strategy for attaining ﬁtness of the animals.REFERENCESAdewuyi, A.A., Gruys, E., van Eerdenburg, F.J., 2005. Non esteriﬁed fatty acids (NEFA) in dairy cattle. A review. Vet. Q. 27, 117-126.Alvarez, L., Martin, G.B., Galindo, F., Zarco, L.A., 2003. Social dominance of female goats affects their response to the male effect. Appl. Anim. Behav. Sci. 84, 119-126.Andersen, I.L., Bøe, K.E., 2007. Resting pattern and social interactions in goatsdthe impact of size and organization of lying space. Appl. Anim. Behav. Sci. 108, 89-103.Aureli, F., Cords, M., Van Schaik, C.P., 2002. Conﬂict resolution following aggression in gregarious animals: a predictive framework. Anim. Behav. 64, 325-343.Barroso, F.G., Alados, C.L., Boza, J., 2000. Social hierarchy in the domestic goat: effect on food habits and production. Appl. Anim. Behav. Sci. 69, 35-53.Carere, C., Groothuis, T.G.G., Möstl, E., Daan, S., Koolhaas, J.M., 2003. Fecal cortico- steroids in a territorial bird selected for different personalities: daily rhythm and the response to social stress. Horm. Behav. 43, 540-548.Conway, M.L.T., Blackshaw, J.K., Daniel, R.C.W., 1996. The effects of agonistic behaviour and nutritional stress on both the success of pregnancy and various plasma constituents in Angora goats. Appl. Anim. Behav. Sci. 48, 1-13.Croney, C.C., Newberry, R.C., 2007. Group size and cognitive processes. Appl. Anim. Behav. Sci. 103, 215-228.Croney, C.C., Prince-Kelly, N., Meller, C.L., 2007. A note on social dominance and learning ability in the domestic chicken (Gallus gallus). Appl. Anim. Behav. Sci. 105, 254-258.Galindo, F.M., Broom, D.M., Jackson, P.G., 2000. A note on possible link between behaviour and occurrence of lameness in dairy cows. Appl. Anim. Behav. Sci. 67, 335-341.Kannan, G., Terrill, T.H., Kouakou, B., Gazal, O.S., Gelaye, S., Amoah, E.A., Samake, S., 2000. Transportation of goats: effects on physiological stress responses and live weight loss. J. Anim. Sci. 78, 1450-1457.Keil, N.M., Imfeld-Mueller, S., Aschwanden, J., Wechsler, B., 2012. Are head cues necessary for goats (Capra hircus) in recognizing group members? Anim. Cogn. 15, 913-921.Matsuzawa, Y., Hagiya, K., 1991. Relationship between feeding behavior and social dominance in a small herd of goats. Scient. Rep. Fac. Agric. 39, 1-6.Mendl, M., 1999. Performing under pressure: stress and cognitive function. Appl. Anim. Behav. Sci. 65, 221-244.Mendl, M., Laughlin, K., Hitchcock, D., 1997. Pigs in space: spatial memory and its susceptibility to interference. Anim. Behav. 54, 1491-1508.Mendl, M., Zanella, A.J., Broom, D.M., 1992. Physiological and reproductive correlates of behavioural strategies in female domestic pigs. Anim. Behav. 44, 1107-1121.Miranda-de la Lama, G.C., Sepúlveda, W.S., Montaldo, H.H., María, G.A., Galindo, F., 2011. Social strategies associated with identity proﬁles in dairy goats. Appl. Anim. Behav. Sci. 134, 48-55.Miranda-de la Lama, G.C., Villarroel, M., Maria, G.A., 2012. Behavioural and physi- ological proﬁles following exposure to novel environment and social mixing in lambs. Small Rumin. Res. 103, 158-163.Morand-Ferron, J., Wu, G., Giraldeau, L., 2011. Persistent individual differences in tactic use in a producerescrounger game are group dependent. Anim. Behav. 82, 811-816.Mormède, P., Andanson, S., Aupérin, B., Beerda, B., Guémené, D., Malmkvist, J., Manteca, X., Manteuffel, G., Prunet, P., van Reenen, C.G., Richard, S., Veissier, I., 2007. Exploration of the hypothalamic-pituitary-adrenal function as a tool to evaluate animal welfare. Physiol. Behav. 92, 317-339.Morton, A.J., Avanzo, L., 2011. Executive decision-making in the domestic sheep. PLoS One 6, e15752.Mülleder, C., Palme, R., Menke, C., Waiblinger, S., 2003. Individual differences in behaviour and in adrenocortical activity in beef-suckler cows. Appl. Anim. Behav. Sci. 84, 167-183.Nicol, C.J., 1995. The social transmission of information and behavior. Appl. Anim. Behav. Sci. 44, 79-98.Nordquist, R.E., Heerkens, J.L.T., Rodenburg, T.B., Boks, S., Ellen, E.D., van der Staay, F.J., 2011. Laying hens selected for low mortality: behaviour in tests of fearfulness, anxiety and cognition. Appl. Anim. Behav. Sci. 131, 110-122.Piccione, G., Casella, S., Lutri, L., Vazzana, I., Ferrantelli, V., Caola, G., 2010. Reference values for some haematological, haematochemical, and electrophoretic pa- rameters in the Girgentana goat. Turk. J. Vet. Anim. Sci. 34, 197-204.Rajion, M.A., Mohamed, I.S., Zulkiﬂi, I., Goh, Y.M., 2001. The effects of road trans- portation on some physiological stress measures in goats. Asian Austral. J. Anim. Sci. 14, 1250-1252.Robitaille, J.F., Prescott, J., 1993. Use of space and activity budgets in relation to age and social status in a captive herd of American bison, Bison bison. Zoo Biol. 12, 367-379.Rowe, C., 1999. Receiver psychology and the evolution of multicomponent signals. Anim. Behav. 58, 921e-931.Ruis, M.A.W., te Brake, J.H.A., van de Burgwal, J.A., de Jong, I.C., Blokhuis, H.J., Koolhaas, J.M., 2000. Personalities in female domesticated pigs: behavioural and physiological indications. Appl. Anim. Behav. Sci. 66, 31-47.Smith, H.F., Fisher, R.E., Everett, M.L., Thomas, A.D., Bollinger, R., Parker, W., 2009. Comparative anatomy and phylogenetic distribution of the mammalian cecal appendix. J. Evol. Biol. 22, 1984-1999.Stewart, M., Webster, J.R., Verkerk, G.A., Schaefer, A.L., Colyn, J.J., Stafford, K.J., 2007. Non-invasive measurement of stress in dairy cows using infrared thermog- raphy. Physiol. Behav. 92, 520e-525.Van Reenen, C.G., Van der Werf, J.T., Bruckmaier, R.M., Hopster, H., Engel, B., Noordhuizen, J.P., Blokhuis, H.J., 2002. Individual differences in behavioral and physiological responsiveness of primiparous dairy cows to machine milking. J. Dairy Sci. 85, 2551-2561.Waiblinger, S., Boivin, X., Pedersen, V., Tosi, M.V., Janczak, A.M., Visser, E.K., Jones, R.B., 2006. Assessing the humaneanimal relationship in farmed species: a critical review. Appl. Anim. Behav. Sci. 101, 185-242.Wechsler, B., Lea, S.E.G., 2007. Adaptation by learning: its signiﬁcance for farm animal husbandry. Appl. Anim. Behav. Sci. 108, 197-214Miranda-de la Lama, G.C., Villarroel, M., Liste, G., Escós, J., María, G.A., 2010b. Critical points in the pre-slaughter logistic chain of lambs in Spain that may compro- mise the animal’s welfare. Small Rumin. Res. 90, 174-178.Miranda-de la Lama, G.C., Villarroel, M., Maria, G.A., 2012. Behavioural and physi- ological proﬁles following exposure to novel environment and social mixing in lambs. Small Rumin. Res. 103, 158-163.Morton, A.J., Avanzo, L., 2011. Executive decision-making in the domestic sheep. PLoS One 6, e15752.Nicol, C.J., 1992. Effects of environmental enrichment and gentle handling on behaviour and fear responses of transported broilers. Appl. Anim. Behav. Sci. 33, 367-380.Pascual-Alonso, M., María, G.A., Sepúlveda, W.S., Villarroel, M., Aguayo-Ulloa, L., Galindo, F., Miranda-de la Lama, G.C., 2013. Identity proﬁles based on social strategies, morphology, physiology, and cognitive abilities in goats. J. Vet. Behav.: Clin. Appl. Res. 8, 458-465.Pethick, D.W., 1993. Carbohydrate and lipid oxidation during exercise. Aust. J. Agr. Res. 44, 431-441.Redbo, I., 1992. The inﬂuence of restraint on the occurrence of oral stereotypies in dairy cows. Appl. Anim. Behav. Sci. 35, 115-123.Redbo, I., Nordblad, A., 1997. Stereotypies in heifers are affected by feeding regime. Appl. Anim. Behav. Sci. 53, 193-202.Ripoll, G., Joy, M., Muñoz, F., Albertí, P., 2008. Meat and fat color as a tool to trace grass feeding systems in light lamb production. Meat Sci. 80, 239-248.Schaefer, A.L., Jones, S.D., Stanley, R.W., 1997. The use of electrolytes solutions for reducing transport stress. J. Anim. Sci. 75, 258-265.Schetini de Azevedo, C.S., Cipreste, C.F., Young, R.J., 2007. Environmental enrich- ment: a GAP analysis. Appl. Anim. Behav. Sci. 102 (3e4), 329-343.Statistical Analysis System Institute, 1988. SAS/STATS User’s Guide (Release 6.03). SAS Institute, Cary, NC.Stewart, M., Webster, J.R., Verkerk, G.A., Schaefer, A.L., Colyn, J.J., Stafford, K.J., 2007. Non-invasive measurement of stress in dairy cows using infrared thermog- raphy. Physiol. Behav. 92 (3), 520-525.Teixeira, D.L., Miranda-de la Lama, G.C., Villarroel, M., Garcia-Belenguer, S., Sañudo, C., María, G.A., 2012. Effect of straw on lamb welfare, production per-formance and meat quality during the ﬁnishing phase of fattening. Meat Sci. 92, 829- 836.Teixeira, D.L., Miranda-de la Lama, G.C., Pascual-Alonso, M., Aguayo-Ulloa, L., Villarroel, M., María, G.A., 2013. A note on lamb’s choice for different types of bedding materials. J. Vet. Behav.: Clin. Appl. Res. 8, 175-179.Terlouw, E.M.C., Arnould, C., Auperin, B., Berri, C., Le Bihan-Duval, E., Deiss, V., Lefèvre, F., Lensink, B.J., Mounier, L., 2008. Pre-slaughter conditions, animal stress and welfare: current status and possible future research. Animal 2, 1501-1517.Torres-Hernandez, G., Hohenboken, W., 1979. An attempt to assess traits of emotionality in crossbred ewes. Appl. Anim. Ethol. 5, 71-83.Tuyttens, F.A.M., 2005. The importance of straw for pig and cattle welfare: a review. Appl. Anim. Behav. Sci. 92, 261-282.Wilson, S.C., MitloÈhner, F.M., Morrow-Tesch, J., Dailey, J.W., McGlone, J.J., 2002. An assessment of several potential enrichment devices for feedlot cattle. Appl. Anim. Behav. Sci. 76, 259-265.Winter, M., Fry, C., Carruthers, S.P., 1998. European agricultural policy and farm animal welfare. Food Pol. 23, 305-323.2018-07-26T00:00:00Z2018-07-28T00:00:00Z011719839589Microsoft Office Word032993falseTítulo1false46694falsefalse16.0000Margarito Filomeno NicolasMargarito Filomeno Nicolas22018-07-28T22:16:00Z2018-07-28T22:16:00Z