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ENVIRONMENT, WELL-BEING, AND BEHAVIOR |
* Animal Husbandry and Welfare, Animal Sciences, Institute for Agricultural and Fisheries Research, 9090 Melle, Belgium; Agricultural Engineering, Technology and Food, Institute for Agricultural and Fisheries Research, 9820 Merelbeke, Belgium; Group of Evolutionary Biology, Department of Biology, University of Antwerp, 2000 Antwerp, Belgium; and Terrestrial Ecology Unit, Department of Biology, Ghent University, 9000 Ghent, Belgium
1 Corresponding author: els.vanpoucke{at}ilvo.vlaanderen.be
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Key Words: farm animal welfare • developmental instability • emotional stress • physical stress • statistical power
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Recently, FA has been suggested to comprise a putative measure of animal welfare (Møller et al., 1999; Møller and Manning, 2003), because it reflects the ability of the individual to cope with the sum of challenges that it faces during its development (Swaddle and Witter, 1997; Kellner and Alford, 2003; Knierim et al., 2007). Animal welfare is a complex and multidimensional concept (Mason and Mendl, 1993; Fraser, 1995). Different definitions and perceptions concerning animal welfare exist, but it is generally accepted that animal welfare covers 2 main properties of an animal (i.e., its physical state and its emotional state; Fraser, 1995; Anonymous, 2001; Bracke, 2001). Given this multidimensional property, a wide variety of indicators are required to assess animal welfare (Mason and Mendl, 1993; Duncan and Fraser, 1997; Spoolder et al., 2003), including estimates of performance, health, behavior, and physiology. However, there is a lack of valid, sensitive, reliable, and robust animal-based indicators that can feasibly be measured or scored for monitoring animal welfare on-farm or at slaughter.
This explains the growing interest in FA as a presumably integrated, reliable, and objective welfare indicator (Møller et al., 1995, 1999; Campo et al., 2000, 2002; Kellner and Alford, 2003). At present, however, it is unclear how sensitive FA is as an indicator of the welfare of farm animals. On the one hand, strong selection by animal breeders to optimize production-related traits may have rendered farm animals particularly prone to disruption of their developmental processes, hence supporting the use of phenotypic markers (such as FA) that are designed to estimate levels of developmental stability (Møller, 1993; Møller et al., 1995, 1999). On the other hand, however, the fact that farm animals are generally fed ad libitum and housed under conditions that minimize their energy expenditure may lower the likelihood of detecting relationships with indices of DI (such as FA) that are assumed to reflect energy allocation constraints. Possibly as a result of these opposing expectations, empirical studies of the link between FA and farm animal welfare yield heterogeneous results (Tuyttens, 2003). Other factors such as the type of stress (e.g., stressors affecting the physical state of the animal are more likely to induce an effect on FA compared with emotional stressors; Tuyttens, 2003), inappropriate protocols for measuring (e.g., poor choice of traits, because DI is assumed to be trait-specific; Clarke, 2003), and analyzing FA (e.g., not integrating multiple traits; Leung et al., 2000; or low statistical power; Knierim et al., 2007) may intensify this heterogeneity.
In this study, we exposed growing broiler chickens to 4 different types of chronic or repeated stressors and measured their levels of FA at slaughter age in a suite of bilateral traits. Two of the 4 stressors were known not to affect a series of conventional welfare indicators at slaughter age (Van Nuffel et al., 2005; Van Poucke et al., 2006). These 2 stress treatments (pain and frustration) were designed to predominantly affect the emotional state of the broilers. Both other stress treatments (wet litter and high temperature and density) were predicted to negatively affect their physical state. The objectives of the present study are to test the level of stress sensitivity of FA compared with these other welfare indicators in commercial broiler chickens and to compare the strength of the relationship with FA between emotional and physical stressors.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Each treatment was replicated 5 times (1, 1, 2, and 3 wk after the start of the first round; Table 1
), and in each replicate, broilers of the different treatments were housed in separate pens within the same compartment (1 compartment was used twice). The first group of 5 x 50 broilers (replicate 1) was housed in the first compartment with broilers randomly allocated to 1 of the pens. At the beginning, stocking density was 16.7 animals/m2 (i.e., 50 broilers/pen) except for the TD treatment in which density was permanently raised to 53 kg/m2 by adjusting pen length (see below). At the age of 12 and 24 d, 10 broilers were removed in all pens as part of other welfare measurements (Van Nuffel et al., 2005; Van Poucke et al., 2006). The distribution of treatments over the pens was randomized.
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The WL and TD treatments were designed to primarily affect the physical state of the broilers. Under the WL treatment, broilers had their litter moistened daily with 5 L of tap water. Wet litter is a principal factor in causing painful foot pad dermatitis, which is considered a major welfare problem in broilers (Greene et al., 1985; Mayne, 2005). Because of the severity of these lesions, moistening was stopped at d 19 for ethical reasons. Broilers of the TD treatment group were exposed to a combination of 2 stressors: an elevated temperature of 35°C from 10 to 17 h each day (induced by two 250-W lamps) and an increased stocking density of 53 kg/m2 (by adjusting the pen length according to the estimated live weight). Heat stress in broilers may reduce feed intake, resulting in lower BW (Johnson et al., 1991; Rose, 1997; Yalçin et al., 1997), and is further known to affect their physiology (e.g., increased heterophil:lymphocyte ratio; McFarlane and Curtis, 1989; Altan et al., 2003) and behavior (e.g., longer duration of tonic immobility indicating higher fearfulness; Altan et al., 2003). Increased stocking density may lead to reduced activity levels (Lewis and Hurnik, 1990; Hall, 2001) and a higher prevalence of leg injuries, which may cause reduced mobility (Sørensen et al., 2000; Sanotra et al., 2001; Dawkins et al., 2004) and food pad dermatitis or hock burns (Proudfoot et al., 1979; Cravener et al., 1992; Hall, 2001; Dozier et al., 2005, 2006). As such, stocking density is a major issue in broiler welfare (SCAHAW, 2000), and a combined heat stress-stocking density treatment is believed to be particularly stressful, because poultry show the tendency to increase their nearest neighbor distance if temperature is raising (Rose, 1997).
Measurements of Fluctuating Asymmetry
Measurements on Intact Carcasses.
At the age of 42 d (i.e., standard slaughter age), 10 randomly chosen broilers per pen were euthanized by cervical dislocation after electrical stunning (90 V for 15 s). The left and right sides of the following 7 bilateral traits were measured twice on intact carcasses by a single person: wattle width (distance between outer junctures), eye length (distance between eye corners), first secondary feather length (total feather length after plucking), tarsometatarsus length (distance between the joint of the tarsometatarsus with the tibiotarsus and the proximal skin fold on the midtoe, holding the tibiotarsus perpendicular to the tarsometatarsus and holding the midtoe in line with the latter), outertoe length (i.e., distance between the outer skin folds on the fourth phalanx when folding the outertoe), midtoe length (i.e., distance between the outer skin folds on the third phalanx when folding the midtoe), and backtoe length (distance between the tarsometatarsus and the nail, holding the backtoe perpendicular to the tarsometatarsus). All measurements were taken with a digital caliper (to the nearest 0.01 mm), apart from the first secondary feather length, which was measured with a ruler (to the nearest 0.5 mm). We refer to Van Poucke et al. (2006) or Van Nuffel et al. (2007) for additional illustrations, protocols, and methodological details about these measurements. In a preliminary study, all these traits were deemed suitable for the study of FA in broilers based on the presence of a high signal (FA)-to-noise (measurement error) ratio and the absence of DA, AS, and correlation in the signed FA values (Van Poucke et al., 2006).
Measurements on Fleshed Bones.
Following the measurements on intact carcasses, bones were extracted from the carcasses using the method described by Mc-Donald and Vaughan (1999). Head, wings, and legs were immersed into a 60-g sodium perborate tetrahydrate solution in hot water (1 L) and incubated in a water bath (65°C) for 1 d. Afterwards, most of the flesh was removed manually, and the bones were incubated again in a 30-g sodium perborate tetrahydrate solution. The next day, remaining flesh was removed manually with a water jet pump and small brushes, after which the bones were kept in a drying oven (50°C) for 1 d. The following bilateral measurements were taken by a single person using a digital caliper (same protocols, methods, and criteria as above): humerus length, radius length, metacarpal minus length, tarsometatarsus length, radius width (i.e., the smallest width), tarsometatarsus width (i.e., width at the joint of the tarsometatarsus with the tibiotarsus), and fibula width (i.e., the largest width). See Van Poucke et al. (2006) or Van Nuffel et al. (2007) for additional illustrations and further details about these measurements.
Statistical Analysis and Power Simulations
A mixed regression model (Van Dongen et al., 1999) was used to test for DA (by F-tests) and significance of FA (by likelihood ratio tests) and to obtain unbiased, trait-specific FA estimates at individual broiler level. Based on variance components estimated for the random side effects (reflecting variation between trait sides) and residual variance (reflecting variation within trait sides), the signal (FA)-to-noise (measurement error) ratio was estimated for each trait. The kurtosis values of the distributions of the signed asymmetries were estimated, and values smaller than –1 were considered as indicative for the presence of AS. Only traits that showed significant FA and did not show DA nor AS were used in subsequent analyses.
Differences in mean FA among treatments were tested with linear mixed models. Individual FA estimates, standardized to zero mean and unit variance for each trait, were included as dependent variable; factor treatment and its interaction with trait were included as fixed effects; and factor replicate and its interaction with factor treatment were included as random effects. Different traits were modeled as repeated measurements at the individual broiler level (see above), and the covariance between the residual values was modeled by a compound symmetry structure. Analyses were also done for each trait separately.
To assess the power of our experiment and analyses, we performed post hoc simulations. We sampled 1,000 datasets from a distribution with mean asymmetry values equal to the observed ones in our study and determined the proportion of tests that would be statistically significant. This was done for both the overall F-test and the pairwise comparison between the 2 treatments that showed the highest difference in average FA.
All analyses were performed in SAS, version 8, and we refer to Verbeke and Molenberghs (2000) for more details on the mixed model approach.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). Of the remaining 13 traits, 6 were excluded from further analysis, because they showed significant levels of DA after sequential Bonferroni correction. None of the traits showed kurtosis values smaller than –1, so based on this criterion, there was no indication of AS. Based on the combined selection criteria, the following traits were used in further analyses: tarsometatarsus length, outertoe length, wattle width, midtoe length, and eye length for the measurements on intact carcasses, metacarpal minus length, and tarsometatarsus width for the measurements on fleshed bones. Two individuals were removed from the analysis, because they were considered to be outliers with standardized residuals above 5.
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). For the trait midtoe, the treatment effects approached significance (P = 0.06). On average, asymmetry was lowest in the control group and highest in the TD treatment. Yet, none of the 2 x 2 comparisons nor the comparison between emotional-physical stressors were statistically significant after correction for multiple testing.
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The power of the overall F-test with a sample size of 50 individuals (10 individuals per replicate and 5 replicates) equaled 35%. Increasing the number of replicates to 10 (and thus 100 individuals in each treatment) resulted in a power of 70%. For 15 replicates, power became reasonably high at 90%. Thus, we would have needed over 100 individuals per treatment to achieve a reasonably high power when the expected differences in average FA would have been equal to the observed values. Comparable results were obtained when comparing control and TD treatments (showing the highest difference in average FA).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Previous measurements of conventional welfare indicators at slaughter age confirmed that broilers from the physical stress treatments experienced elevated stress levels. Compared with the other treatment groups, these broilers scored worse on the latency-to-lie test (a test for leg health), on the tonic immobility test (a test for fearfulness), and on the physical scores (the condition of the foot pad, hock, breast, and thigh), whereas performance, frequency of behavioral activities, and physiological data were not influenced (Van Nuffel et al., 2005; Van Poucke et al., 2006). The emotional stress treatments did not affect any of these welfare indicators, despite prior evidence for stress effects in related species and stressors (see references in materials and methods section) and circumstantial data from our experiment (e.g., withdrawing legs and uttering distress calls when feathers were plucked in the PAIN group, running to the opposite side of the pen or sitting motionless when exposed to a dummy raptor, and eliciting alarm calls when physically isolated from group members in the FRUS group, all suggesting elevated stress levels). Given that our physical stress treatments did not result in increased FA, either, severe welfare problems stemming from long-term selection for increased BW and improved feed efficiency (i.e., skeletal disorder, muscle disorder, contact dermatitis, ascites, and respiratory problems; SCAHAW, 2000) may have masked additional (experimental) stress effects on developmental processes. Alternatively, FA may not be a sensitive indicator of stress in broiler chickens due to the general absence of energy allocation constraints in ad libitum-fed organisms housed under conditions that optimize growth and feed conversion efficiency. Enlarging the difference in stress effects between stress treatment and control groups, either by decreasing background stress (in line with findings of Tuyttens et al., 2007) or by superimposing nutritional stress, may allow discrimination between both hypotheses.
It is further known that FA constitutes an exceedingly small signal (often <1% of the trait size; Palmer, 1994) and that its applicability depends on both measurement accuracy and statistical power. For all but 1 trait under study, measurement error was smaller than the level of FA. But, even if measurement accuracy was theoretically sufficient to detect between-group differences in FA, it might still not have been possible to demonstrate such differences due to insufficient statistical power and also when combining information from different traits into a single analysis, which is generally believed to increase the probability of detecting stress effects (Leung et al., 2000). Higher statistical power could have been achieved either by increasing sample size or by increasing the number of repeated measurements per individual (Van Dongen et al., 1999; Knierim et al., 2007).
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ACKNOWLEDGMENTS |
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Received for publication November 21, 2006. Accepted for publication June 9, 2007.
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