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Benchmarking passive transfer of immunity and growth in dairy calves Atkinson, Dax 2016

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BENCHMARKING PASSIVE TRANSFER OF IMMUNITY                     AND GROWTH IN DAIRY CALVES  by  Dax Atkinson B.Sc., The University of British Columbia, 2014  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF                                THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE  in  The Faculty of Graduate and Postdoctoral Studies (Applied Animal Biology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  June 2016  © Dax Atkinson, 2016 ii  Abstract  Poor health and growth of young dairy calves can have lasting effects on development and future production. This study aimed to benchmark calf-rearing outcomes in a cohort of Canadian dairy farms, report these findings back to producers alongside their veterinarians, and document the results. A total of 18 Holstein dairy farms, located in the Fraser Valley region of British Columbia, were recruited and surveyed on current colostrum and feed management practices of pre-weaned calves. Blood samples were collected from 1 to 7 day old calves to estimate serum total protein levels by digital refractometry. Failure of passive transfer (FPT) was determined using a total protein threshold of 5.2 g/dL. Average daily gains (ADG) were estimated from 1 to 70 day old pre-weaned heifers using heart-girth tape measurements with early (≤ 35 days) and late (> 35 days) period growth also analysed separately. At first assessment, the average farm FPT rate was 16%. Overall ADG was 0.68 kg/day, with early and late period growth rates of 0.50 and 0.86 kg/day, respectively. Following delivery of benchmark reports, all participants volunteered to undergo a second assessment. The majority (83%) of participants elected to make at least one colostrum or feed protocol change between data collection periods, including increased colostrum at first feeding, increased initial and maximum daily milk, and reduced time to first colostrum. Farms that made such changes experienced improved outcomes; average FPT rates were reduced by 9% and ADG was increased by 0.06 kg/day for all calves, and by 0.16 kg/day for calves less than 36 days old. These results indicate that benchmarking FPT and ADG can motivate producer engagement on calf care, leading to improved production and welfare outcomes for calves on farms that apply relevant management changes.  iii  Preface  The research for this thesis was conducted on dairy farms in the Fraser Valley of BC and at the University of British Columbia Dairy Education and Research Centre in Agassiz, BC. The research project and methodology were approved by the University of British Columbia’s Animal Care Committee (application #A13-0148) and Behavioural Research Ethics Board (application #H14-03196). The material in Chapter 2 is to be submitted for publication under the title: Benchmarking passive transfer of immunity and growth in dairy calves by D.J. Atkinson, J., M.A.G. von Keyserlingk, and D.M. Weary. The manuscript was co-authored by my supervisors M.A.G. von Keyserlingk and D.M. Weary. The co-authors supervised and assisted interpreting the data and provided comments on manuscript drafts. The main ideas of the study and the methodology were developed with my co-authors and the veterinary staff at Greenbelt Veterinary Clinic, Chilliwack, BC. I was responsible for communication with veterinary collaborators and participants, data collection, statistical analysis and manuscript composition.       iv  Table of contents  Abstract .................................................................................................................................... ii Preface ..................................................................................................................................... iii Table of contents ..................................................................................................................... iv List of tables ............................................................................................................................ vi List of figures .......................................................................................................................... vii List of abbreviations ............................................................................................................. viii Glossary ................................................................................................................................... ix Acknowledgements ....................................................................................................................x Chapter 1: General introduction ..............................................................................................1 1.1 Introduction ..................................................................................................................1 1.1.1 Intervention programs ............................................................................................2 1.1.2 Communication and engagement ...........................................................................2 1.1.3 Engaging interventions...........................................................................................4 1.1.4 Benchmarking ........................................................................................................4 1.1.5 Benchmarking calf performance.............................................................................5 1.2 Passive transfer of immunity .........................................................................................6 1.2.1 General definitions .................................................................................................6 1.2.2 Failure of passive transfer ......................................................................................7 1.2.3 Colostrum quality ..................................................................................................7 1.2.4 Colostrum quantity.................................................................................................8 1.2.5 Colostrum timing ...................................................................................................9 1.2.6 Additional risks .................................................................................................... 10 1.2.7 Consequences of FPT........................................................................................... 11 1.2.8 Assessment methods ............................................................................................ 11 1.2.9 Current outcomes ................................................................................................. 13 1.3 Growth ........................................................................................................................ 14 1.3.1 Newborn physiology ............................................................................................ 14 1.3.2 Natural feeding behaviour .................................................................................... 14 1.3.3 Conventional feeding practices ............................................................................ 15 1.3.4 Rethinking conventional practices ........................................................................ 16 v  1.3.5 More milk and some forage .................................................................................. 17 1.3.6 Growth................................................................................................................. 18 1.3.7 Weaning .............................................................................................................. 19 1.3.8 Benefits of natural growth .................................................................................... 20 1.3.9 Current outcomes ................................................................................................. 20 1.4 Thesis objective and hypothesis .................................................................................. 21 Chapter 2: Benchmarking passive transfer of immunity and growth in dairy calves .......... 22 2.1 Introduction ................................................................................................................ 22 2.2 Materials and methods ................................................................................................ 24 2.2.1 Project design ...................................................................................................... 24 2.2.2 Data collection ..................................................................................................... 25 2.2.3 Benchmarking ...................................................................................................... 27 2.2.4 Statistical analysis ................................................................................................ 27 2.3 Results ........................................................................................................................ 28 2.3.1 Before benchmarking ........................................................................................... 28 2.3.2 After benchmarking ............................................................................................. 29 2.4 Discussion................................................................................................................... 31 2.4.1 Producer engagement and changed practices ........................................................ 31 2.4.2 Passive transfer of immunity ................................................................................ 31 2.4.3 Weight gains ........................................................................................................ 33 2.5 Conclusion .................................................................................................................. 35 Chapter 3: General discussion ................................................................................................ 40 3.1 Summary .................................................................................................................... 40 3.2  Strengths and limitations ............................................................................................. 41 3.3  Recommendations ....................................................................................................... 45 3.4  Conclusions ................................................................................................................ 47 Bibliography ............................................................................................................................ 49     vi  List of tables  Table 1. Summary of categorical calf management practices reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period. ............................................................................. 36  Table 2. Summary of quantitative calf management practices reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period. ............................................................................. 37  Table 3. Summary of calf management changes reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period................................................................................................... 38             vii  List of figures  Figure 1. Failure of passive transfer rates (A) and average daily gains (B) of pre-weaned Holstein calves on 18 farms before and after the benchmark intervention. ................................. 39    viii  List of abbreviations   ADG = average daily gains BW = body weight  CFU = colony forming unit  DMI = dry matter intake  FPT = failure of passive transfer (of immunity) GIT = gastrointestinal tract  IgG = immunoglobulin G  RID = radial immunodiffusion TP = total protein VFA = volatile fatty acids                ix  Glossary   Agammaglobulinemic = having very low levels of immunoglobulins  Colostrum = first milk produced in mammals Colostrometer = hydrometer that measures the specific gravity of a fluid  Dystocia = obstructed or difficult birth  Enterocyte = cells lining the small intestine  Parity = number of times an animal has given birth  Refractometry = measuring a substance’s composition by its refractive index Transition milk = milk during the transition from colostrum to whole milk  Waste milk = unsaleable milk    x  Acknowledgements  I would like to express my deepest gratitude to Dan Weary and Nina von Keyserlingk, who introduced me to the amazing world of animal welfare science, graciously invited me to be a part of it, and continue to inspire me with their endless passion and energy. I also give many thanks to Ronaldo Cerri, Bruna, and Augusto for providing me with an addictive first taste of dairy science. I am truly indebted to the UBC Dairy and all of the staff and students for providing so many unforgettable and invaluable experiences, while I called it home for a summer. In particular, I have Becky and Joao to thank for throwing me to the calves, and with that the seed that would become this project.    This thesis would not have been possible without Samantha to bravely face hours of calf wrangling (and my endless yammering) on a daily basis. I would also not have had farms to work with, if not for the all of the dairy farmers, who graciously opened their farms, showed endless patience giving me their time, and made this whole endeavour worthwhile with their eager participation. Equally amazing was the above and beyond cooperation and enthusiasm from the veterinarians at Greenbelt.   Most importantly, I give endless praise to my wife, Shoko, who humbles me with the many selfless sacrifices she has made to see me pursue my dreams. Without her support and encouragement, I would have never begun this long journey that began 6 years ago back in Tokyo. Finally, from the bottom of my heart I thank all of my family, friends, and colleagues, who are amazing and always cheered me on towards the finish line. 1  Chapter 1: General introduction  1.1 Introduction   Modern dairy farmers rely on data about the health and performance of their animals to inform management decisions. Performance measures have typically focused on lactating dairy cows, including milk production and reproductive efficiency, to maximize economic gains and meet quality standards required by regulation (e.g. milk somatic cell count). Advances in technologies such as automated milking robotics (Jacobs and Siegford, 2012) and activity monitoring systems (Chanvallon et al., 2014)  provide individual animal data that is collected and reported automatically. Producers may also receive information and recommendations from a variety of industry experts, such as veterinarians, nutritionists, geneticists, reproduction specialists, and hoof trimmers (Whay et al., 2012). Increasing public interest and research on animal welfare has also led to the development of external assurance, or auditing programs to ensure best practices related to welfare (Rushen et al., 2011). Unfortunately, the majority of these various resources are either not applicable to calves or are only utilized after calves have been raised to breeding age and are producing milk.   Heifer calves represent the future of a dairy’s herd, requiring a large investment of time and a significant portion of production costs (Mohd Nor et al., 2015), with mean estimates as high as US$1800 per heifer raised to first calving  (Heinrichs et al., 2013). Calves are also highly susceptible to diseases that can have lasting effects on growth and mature performance (see Weaver et al., 2000). Current U.S. estimates for pre-weaned morbidity and mortality (excluding calves that are born alive but die within 48 hours, referred to as stillbirths) rates are 38.5% and 7.8% respectively, which means that the risk of illness and death is higher in this period than any 2  other point in the life of dairy cattle (USDA, 2010). Despite their recognized future importance, investment costs, and vulnerability, pre-weaned calves often remain a low priority for monitoring and daily management considerations (Murray and Leslie, 2013). Without access to objective and relevant data or opportunities that promote information sharing, producers may not be aware of weaknesses in their calf rearing program. Similar knowledge and engagement gaps in other areas of dairy management have been addressed by designing and implementing intervention programs, with varying degrees of success.   1.1.1 Intervention programs  Two extension studies in the UK focusing on mastitis (Green et al., 2007) and lameness (Bell et al., 2009), illustrate a similar design and highlight some common challenges inherent in these kinds of projects. In both studies, researches performed an on-farm assessment of relevant quantitative outcomes (e.g. disease incidence) and formulated detailed lists of potential risk factors. Farm specific recommendations or ‘action plans’ were then created and presented to producers by veterinarians. Although the degree of success reported by these studies differed, the authors of both studies stressed that participant compliance was a substantial challenge (Bell et al., 2009; Green et al., 2007). Effective knowledge transfer (communication) and the motivation to implement appropriate changes (engagement) are now considered some of the main obstacles to improving dairy cattle welfare on farms (Kristensen and Jakobsen, 2011; LeBlanc et al., 2006).  1.1.2 Communication and engagement   Effective communication is a necessary component for promoting active producer engagement, which cannot be replaced by the validity of information alone (Main et al., 2012; 3  Valeeva et al., 2007). A good communicator must take into consideration the farmers’ perspectives, which are complex, individual, and contextual (Jansen et al., 2010c). Relying on data alone to persuade a farmer assumes purely rational thinking, which will only be effective provided there was a pre-existing motivation to use such information (Jansen et al., 2010b). Of course, human behaviour is also influenced by many factors, including attitudes, values, social norms, and perceived control (see Ajzen, 1991; Jaccard and Blanton, 2005). Attitudes, in particular, have been recognized to have a major influence on how dairy farmers address issues, such as mastitis (Nyman et al., 2007), with one study finding up to nearly half of their observed variance explained by producer attitudes alone (Jansen et al., 2009).  It is also a mistake to assume that a farm has not adopted certain best practices due to a lack of information on the subject (Valeeva et al., 2007). This may not only overlook various internal and external motivators, but offering previously known information risks disinteresting the farmer (Jansen et al., 2009). Information must be perceived as relevant and aligning with the farmer’s values and goals (Kristensen and Jakobsen, 2011), reflecting their perceptions of risk, not the advisor’s (Hadar and Fischer, 2008). As with decisions around human health, there must be an internal belief in the legitimacy of the problem and potential solutions to inspire behavioural change (see Dernburg et al., 2007). The majority of farmers tend to assume their current knowledge and practices are appropriate and sufficient (Kuiper et al., 2005). If suddenly given a list of problems with their current management practices and changes to make, these farmers may face internal conflict with their identity as a competent and moral person, which can lead to cognitive dissonance and the rejection of the external information altogether (Kristensen and Jakobsen, 2011). This form of 4  cognitive dissonance can also occur if the problem is perceived as too complex and solutions too difficult (Jansen et al., 2010c).  1.1.3 Engaging interventions  Recognizing some of the above challenges inherent in prescriptive intervention designs, Main et al. (2012) describe a lameness intervention following the same basic structure as outlined in Bell et al. (2009), but with the addition of researcher-facilitated discussions to encourage self-generated action plans (Main et al., 2012). This facilitated approach to identifying problems and forming recommendations reduced the risk of cognitive dissonance as the farmer was guided to their own conclusions, rather than being told (Festinger, 1957; Whay et al., 2012).  In addition, facilitated discussions led to much higher engagement, with farmers generating double the number of action plans compared with previous methods (Whay et al., 2012).  Another study investigating lameness prevalence on American dairy farms incorporated elements of benchmarking into the process (von Keyserlingk et al., 2012). Farm data were collected on all participating farms before the results were presented to producers, ranked alongside their peers (von Keyserlingk et al., 2012). A follow up assessment was conducted the following year at the request of former participants, the majority of whom had spontaneously implemented management changes to address lameness, which had significantly improved (Chapinal et al., 2014). This example highlights the potential power of benchmarking tools to engage producers in intervention programs.  1.1.4 Benchmarking  Benchmarking is a management tool for improvement employed in a wide range of industries and organizations, including governments, firms, health care providers, researcher, and 5  the agriculture industry (Bogetoft, 2012; Jarrar and Zairi, 2001; Sutherland and Peel, 2011). While the concept itself is very old, benchmarking was made famous as a tool in the corporate world in 1981, when Xerox adopted such practices across all aspects of its organization (Camp, 1989). Today benchmarking consistently ranks near the top of most popular improvement tools utilized by corporate executives globally (Rigby and Bilodeau, 2015).  At its core, benchmarking is a relative performance evaluation tool that analyses outcomes, identifies areas of improvement, and adopts practices based on one’s comparative position with others (Bogetoft, 2012). Combined with facilitated intervention techniques, benchmarking has the potential to motivate engagement by encouraging the interpretation of one’s relative performance, self-reflection on potential areas of improvement, and open dialogue (Meade, 1994). In particular, comparisons with peers can help influence perceptions of social norms and best practices (Jansen et al., 2009), as well as tap into motivation stemming from pride in one’s work (Valeeva et al., 2007). The foundation of an effective benchmark program is determining an area for improvement and quantitative performance indicators that adequately represent the different outcomes of current practices (Meade, 1994). 1.1.5 Benchmarking calf performance   There are several areas of calf management needing improvement that have been identified by animal welfare experts, including calving and newborn care, colostrum management, dehorning, feed management, and housing practices (Vasseur et al., 2010; von Keyserlingk et al., 2009). Colostrum and feed management in particular, lend themselves to the benchmarking process by each having a singular well-established quantitative performance indicator; the passive transfer of immunity and average daily gains, respectively. These data are practical to obtain and scientifically validated as representative outcome measures for the 6  complex multifactorial inputs that go into calf management practices on dairy farms. A number of the influential qualitative risk factors related to these outcomes have also been studied extensively and help to facilitate a discussion around effective management practices.  1.2   Passive transfer of immunity  1.2.1 General definitions   Passive transfer of immunity refers to components of the immune system that were externally received, such as a neonatal mammal will obtain maternally through the placenta or colostrum until its own immune system is fully functioning. As a consequence of the placenta morphology in cattle, large molecules such as immune proteins are unable to cross the placental barrier from maternal to fetal blood circulation and calves will not receive this passive transfer of immunity while in-utero (Jainudeen and Hafez, 2008). This means that calves are born agammaglobulinemic - effectively immunocompromised - and will be entirely dependant on colostrum to provide maternal protection from disease insults for the first few weeks of life (Beam et al., 2009; Godden, 2008; Vogels et al., 2013).  Colostrum is the first lactation product secreted immediately following parturition (Godhia and Patel, 2013). The composition of colostrum can vary dramatically within and between species, but for cattle in general it distinguishes itself from milk by having a much higher fat and protein content, and contains many additional components such as cytokines, growth factors, hormones, peptides, vitamins and minerals that support early developmental processes (see McGrath et al., 2016). Up to 80% of the colostral protein portion is made up of immunoglobulins (McGrath et al., 2016), of which Immunoglobulin G (IgG) is the primary constituent and major contributor to passive transfer of immunity (Larson et al., 1980; Elfstrand 7  et al., 2002). This compositional profile will shift rapidly into what is known as transition milk until reaching the stable levels found in standard milk over the next several days (Godden, 2008).  1.2.2 Failure of passive transfer    When a calf has failed to absorb a sufficient quantity of maternal immune proteins to minimize the risk of disease, it is considered a failure of passive transfer (FPT). A general consensus threshold for successful passive transfer in dairy calves is a blood serum IgG concentration of 10 mg/mL (or 1 g/dL) in neonatal calves from 1 to 7 days old (Tyler et al., 1996; Weaver et al., 2000), though some have advocated for slight adjustments to this cut-point (see Chigerwe et al., 2009). As newborn calves’ only source of IgG is colostrum, it follows that the greatest risk factors for FPT centers around colostrum and colostrum management, which can influence future health and welfare (Godden, 2008; Weaver et al., 2000).  1.2.3 Colostrum quality  Colostrum quality is typically defined in terms of IgG concentration, with a goal of >50 mg/mL (Beam et al., 2009; McGuirk and Collins, 2004). Quality can vary significantly between individual animals and farms (Morrill et al., 2012; Swan et al., 2007) due to a number of internal and external factors.  As colostrum production ceases and is replaced by more dilute transition milk immediately following calving (McGuirk and Collins, 2004), colostrum may be at risk of being leaked, diluted, or reabsorbed. Indeed, studies have observed a close negative association between the time to first milking and a decline in IgG (Moore et al., 2005). It is therefore recommended that colostrum be collected as soon as possible, and no later than 6 hours to ensure minimal degradation (Godden, 2008).  8  A number of studies have also found colostrum quality to vary with age; specifically higher parity cows tending to produce better colostrum (Chigerwe et al., 2009; Furman-Fratczak et al., 2011; Kehoe et al., 2011). This has been hypothesised to be due to the greater exposure to pathogens and subsequent production of antigens in older animals (see Godden, 2008), although not all studies have found this association (Gulliksen et al., 2008). Due to individual variation, it is recommended to test all colostrum regardless of parity (Kehoe et al., 2011) . Lower quality colostrum has also been noted in cows with particularly short dry periods (Rastani et al., 2005).    Even the highest quality colostrum can lose its effectiveness due to certain practices and environmental challenges. Pooling multiple cows’ colostrum together can end up diluting high quality colostrum with large volumes of less concentrated colostrum (Weaver et al., 2000) and increase risk of spreading pathogens and bacteria (Godden, 2008; Morrill et al., 2012). Indeed, Beam et al. (2009) found pooling colostrum associated with increased FPT.    Colostrum quality can be compromised by bacterial contamination as high bacteria levels can interfere with the calf’s ability to effectively absorb the immune proteins (Johnson et al., 2007). Bacteria are able to proliferate rapidly unless colostrum is promptly frozen, refrigerated, or fed to the calf (Cummins et al., 2016; Stewart et al., 2005). Colostrum with a total plate count of >100,000 cfu/mL is no not considered appropriate to offer a newborn calf, regardless of its IgG concentration (McGuirk and Collins, 2004).  1.2.4 Colostrum quantity   For an average sized newborn Holstein calf, a minimum of 100 to 150 g of IgG is considered necessary to ensure the greatest possibility of sufficient absorption (Besser et al., 1991; Chigerwe et al., 2008). Obviously, the volume of colostrum required to meet this condition 9  depends on the concentration of IgG; the higher the quality, the less colostrum required. As previously mentioned, quality is not consistent, which is illustrated by research that tested colostrum to find that only 36% of samples would have provided sufficient IgG if it they had assumed good quality (> 50 mg/mL) and fed 2 L (Besser et al., 1991). Other studies have observed a link between higher volumes of colostrum and lower FPT levels (Chigerwe et al., 2008; Trotz-Williams et al., 2008), illustrating that volume can compensate for some of the variation in quality. Assuming the exact IgG concentration of a sample is unknown, it is generally recommended to provide dairy (specifically Holstein) calves 4 L or 10% of body weight (BW) of colostrum at first feeding (Besser et al., 1991; Morin et al., 1997).  1.2.5 Colostrum timing   Providing sufficient volumes of high quality colostrum mean nothing if the calf is unable to absorb the immune proteins; a process that is extremely time sensitive. Newborn calves are said have an ‘open gut’, referring to fetal enterocyte cells that line the small intestine and are capable of non-selectively transporting large immune proteins from the lumen to the peripheral circulation via the lymph (Comline et al., 1951). Following birth, these fetal cells are eventually replaced by normal adult cells in a process called ‘gut closure’ (Smith, 1985). Absorption remains optimal for up to 4 hours from the time of calving, but the closure process begins to decline after 6 hours, severely reducing efficiency by 12 hours, and rapidly approaches complete closure at 24 hours (Stott et al., 1979). While there may still be some localized effects provided along the intestinal walls (Godden, 2008), any additional colostral immune proteins will simply be ingested from this point on. The difference in absorption capabilities over time is illustrated by Chigerwe et al. (2008), who calculated that feeding at 14 hours instead of 6 hours doubled the 10  risk of FPT. To ensure maximum absorption, it is recommended that calves receive their first colostrum meal within 6 hours (Godden, 2008; McGuirk and Collins, 2004).  1.2.6 Additional risks  There are a number of other factors that have received attention for their potential to reduce FPT outcomes. Studies have reported very high rates of FPT for calves that were left to nurse from the dam to receive colostrum (Beam et al., 2009; Besser et al., 1991);  nearly double for calves that had been left with their dams for 3 or more hours (Trotz-Williams et al. 2008). This may have to do with calves not suckling sufficient quantities of colostrum soon enough (Edwards and Broom, 1979), as well as increased risk of pathogen exposure (McGuirk and Collins, 2004).  Beam et al. (2009) reported increased risk of FPT for calves that experienced a difficult calving in cold weather. Cold stress has been found to delay and impair the process of open gut absorption (Olson et al., 1980). Hypoxia and resulting acidosis from prolonged calving has also been implicated in reduced absorption capacity, but results are inconclusive (see Godden, 2008). Nevertheless, dystocia has continued to be found linked to FPT, with farms that did not seek professional assistance for complicated pregnancies (Beam et al., 2009) also being at increased risk for weakened calves (Furman-Fratczak et al., 2011).   Finally, there are a number of colostrum replacer products on the market, which have had mixed results in providing similar levels of protection from FPT as fresh colostrum, and are generally recommended to be used with caution (see Smith and Foster, 2007), or not at all.   11  1.2.7 Consequences of FPT   Calves with FPT are more likely to experience respiratory or enteric disease, as well as septicaemia (Donovan et al., 1998). In addition, illness bouts may be more severe (Furman-Fratczak et al., 2011) and have a longer duration (Paré et al., 1993). Risk to other calves is also increased as FPT calves have elevated levels of pathogen shedding (Lopez et al., 1988). Calves were calculated to incur double the veterinary-related costs when provided 2 L of colostrum rather than 4 L at birth (Faber et al., 2005) As a natural consequence of this increased risk of morbidity, it is unsurprising that mortality risk also increases rapidly with FPT and can remain elevated well past weaning (Tyler et al., 1998). Wells et al. (1996) have estimated that 31% of calf mortality in the first 3 weeks of life is attributable to FPT. Calves that survive tend to show reduced growth throughout the pre-weaning period (Dewell et al., 2006; Faber et al., 2005; Robison et al., 1988).  One repercussion of difficulties in early rearing is reduced performance that continues into adulthood, with age at first calving delayed (Heinrichs et al., 2005), quality and quantity of milk at first lactation reduced (DeNise et al., 1989; Heinrichs and Heinrichs, 2011), and increased culling rates (DeNise et al., 1989). These economic consequences have been analysed in a recent meta-analysis, which estimated the total costs of FPT to be €60 / calf (Raboisson et al., 2016). 1.2.8 Assessment methods   There are a large number of different tests that can be employed to assess the blood serum IgG level and, by extension, the passive transfer status of calves. The gold standard method is radial immunodiffusion (RID; Beam et al., 2009), which measures IgG levels directly 12  (Fahey and McKelvey, 1965). The drawbacks to RID are that it is a laboratory process that requires 18 to 24 hours incubation time, appropriate facilities/equipment, and training (Deelen et al., 2014). Enzyme-linked immunosorbant assay (ELISA) is another laboratory method capable of directly quantifying IgG (Weaver et al., 2000), and this method is seeing more use (Conneely et al., 2013; Liu et al., 2009), however, most alternative indirect testing methods are validated by correlation with RID results. Some of these alternative methods include a sodium or zinc sulfite turbidity test, turbidimetric immunoassay, and a whole-blood glutaraldehyde coagulation test (see Weaver et al., 2000). These tests have shown varying levels of success and may not always be practical for on-farm use (Godden, 2008).  Of the many alternative methods of FPT testing, refractometry has received the most attention for its reasonable results and practicality.  A refractometer quantifies the refracted light passing through a sample, and is able to estimate the concentration of dissolved solids, such as the protein levels in a blood serum sample (George, 2001). As expected, studies have found that the serum total protein levels estimated by refractometry are highly correlated with actual IgG levels (Deelen et al., 2014; Morrill et al., 2013; Quigley et al., 2013; Thornhill et al., 2015). The sensitivity (detection of true positives) and specificity (detection of true negatives) of refractometers, when determining FPT in calves have also been found to be acceptable for herd level testing (Godden, 2008; McGuirk and Collins, 2004).  This method requires the one-time purchase of a refractometer, which could be optical or digital. Both types have been shown to give similar results (Thornhill et al., 2015), however the optical model does require the operator to judge the final score visually, while the digital eliminates this extra step. Serum has traditionally been separated with a centrifuge, however 13  Wallace et al. (2006) found that naturally separated serum yielded comparable results and could be considered as an acceptable on-farm alternative.  These same refractometers have been found to be just as reliable for assessing the IgG content of colostrum (Bartier et al., 2015; Chigerwe and Hagey, 2014), which does not require any mechanical separation prior to testing. The most commonly used tool for colostrum quality assessment however, is a hydrometer, or ‘colostrometer’, which measures the specific gravity of a sample to estimate total solids (Fleenor and Stott, 1980). Although inexpensive, colostrometers are fragile, influenced by temperature, and have received mixed results in validation studies (Morin et al., 2001; Pritchett et al., 1994). For these reasons, it is now recommended that producers monitor their colostrum quality with refractometers rather than colostrometers (Bartier et al., 2015; Morin et al., 2001). 1.2.9 Current outcomes   Survey studies suggest that very few North American farms are testing their colostrum quality or the serum total protein of calves (Beam et al., 2009; Vasseur et al., 2010). Interestingly the most recent UDSA (2016) survey indicates that although only 6.2% of all dairy farms routinely monitor serum proteins, almost 40% of large farms (over 500 cows) routinely monitored calf serum proteins as a means to evaluate their colostrum management program. When colostrum quality was tested for both IgG content and bacterial contamination, nearly 60% of samples on U.S. farms were considered inadequate (Morrill et al., 2012). Given these findings, it is unsurprising that rates of FPT remain relatively high. Canadian studies have reported FPT rates of 25% (Wallace et al., 2006), 29% (Bartier et al., 2015), and 37% (Trotz-Williams et al., 2008). Similar results are seen in the U.S., with recent national FPT rates of 19.2% (USDA, 2010) and researchers reporting 34% on Washington State farms (Wenz, 2011). Vogels et al. 14  (2013) reported 38% FPT rates on farms in Australia. As current herd assessment protocols advocate target FPT rates below 10% (McGuirk, 2010), these examples illustrate that dairy farms continue to struggle with FPT, which has both significant animal welfare and economic consequences.   1.3 Growth   How well an animal grows is a crucial indicator of the degree of success for producers, as a wide range of management factors can influence this outcome measure (Breen et al., 2012). This section will focus on the effects of nutrition management, as this is the primary and most immediate determinant of growth for pre-weaned calves.  1.3.1 Newborn physiology    Calves are born as functional monogastric digesters. The reticulorumen is initially morphologically underdeveloped (Baldwin et al., 2004) and free of any microbes. Over the first few hours of life the rumen will be colonized by bacteria from the environment (Fonty et al., 1989). The eventual establishment of a healthy anaerobic microbial population is critical to become a healthy ruminating animal capable of digesting plant matter (Jami et al., 2013). Although evidence of fermentation can be observed within 2 weeks (Beharka et al., 1998), the entire process of becoming a functional ruminant is long and complex, with the expression of hundreds of genes altered (Connor et al., 2013) that lead to developmental changes throughout the gastrointestinal tract (GIT; see Baldwin et al., 2004; Drackley, 2008). 1.3.2 Natural feeding behaviour   Holstein calves that are reared by their dam will nurse approximately 4 to 10 times per day in 7 to 10 minute bouts (de Passillé, 2001) , consuming a total of 6 kg of milk per day in the 15  first week of life (de Passillé et al., 2008). This nursing frequency will drop gradually, while volume of milk intake will quickly increase up to 12 L/day (de Passillé et al., 2008). Calves first begin to graze within a few weeks (Tedeschi and Fox, 2009), but will not be regularly grazers until 4 to 6 m of age (Key and MacIver, 1980). Natural weaning takes place gradually over several months and ends by the time the calf is roughly 10 months of age (Reinhardt and Reinhardt, 1981).  1.3.3 Conventional feeding practices    Some of the physiological developmental changes in the rumen are thought to be triggered by exposure to fermentation products, which include volatile fatty acids (VFA) (Baldwin et al., 2004). Butyrate in particular, has been associated with rumen development (Sander et al., 1959; Tamate et al., 1962). As feeding milk is more costly than solid feeds, producers have an incentive to wean animals as soon as possible (typically at 5 to 7 weeks; USDA, 2010). In addition, there is a negative relationship between the amount of milk provided to calves and the amount of solid feed consumed, or dry matter intake (DMI; de Passillé et al., 2011; Jasper and Weary, 2002). For these reasons, it has become common practice to encourage calves to transition to solid feed by limiting their milk intake to about 10% of BW, or 4 L/day (khan 2011).  To facilitate the production of VFA and hasten rumen development, grain based ‘calf starter’ feeds were developed and popularized (see Khan et al., 2016). Providing forage, such as hay is generally discouraged as early research found this led to ‘gut-fill’, decreasing grain consumption and thus, overall energy intake (Hill et al., 2008; Stobo et al., 1965). This nutrition management system is now considered ‘conventional’, with calves typically provided a restricted milk diet of roughly 4 L/d, ad libitum access to a calf starter within the first weeks of life, and no 16  access to forage until after weaning (Khan et al., 2016), which tends to be abrupt (Khan et al., 2011). Milk is typically delivered by bottle for the first several days before being transitioned to bucket feeding (USDA, 2016).  1.3.4 Rethinking conventional practices    More recently, doubts have been cast on the validity of much of this early research on calf nutrition (Khan et al., 2011a, 2016). The unnaturally low milk levels, method of delivery, and absence of forage under conventional practices are potentially confounding factors that could lead to research observations and results that are not representative of the natural biological functioning of calves.  In addition to these research concerns, whenever natural behaviour and processes are hindered, animal welfare may be compromised (Fraser et al., 1997). Indeed, calves receiving restricted milk volumes display behavioural signs of chronic hunger (De Paula Vieira et al., 2008; Jensen and Holm, 2003; Thomas et al., 2001). In contrast to nipple feeding, bucket feeding also encourages unnaturally short meals (2 L in 45 seconds; Appleby et al., 2001), that potentially hinders digestion and leads to increased non-nutritive oral behaviours, such as cross-sucking (de Passillé, 2001; De Paula Vieira et al., 2008).   Rumen development is not just dependent on exposure to VFA and resulting fermentation processes. Some have suggested that the intense production of VFAs may have deleterious effects due to the resulting decrease to rumen pH (Khan et al., 2016). The right types and levels of microbes must also be established, which can take months before reaching a composition comparable to adult animals (Minato et al. 1992). This is also true for the physiological development of other aspects of the GIT, such as the production of saliva to buffer the rumen pH, which requires up to 4 weeks for the parotid gland to mature (Kay, 1960).  17  To fuel this dramatic development, calves require a steady intake of accessible nutrients. Young calves on a restricted milk program however, are not yet physically able to utilize the energy from solid feed, resulting in reduced nutrient intake for development compared with calves fed ad-libitum (Jasper and Weary, 2002; Nielsen et al., 2008; Sweeney et al., 2010). These nutrient starved calves cannot catch up to natural growth rates, even when consuming twice the level of solid feed in this early period (Nielsen et al., 2008).   1.3.5 More milk and some forage  Holstein calves offered ad-libitum milk will consume daily volumes comparable with a natural setting; reaching up to 12 L (de Passillé and Rushen, 2012; Jasper and Weary, 2002; Sweeney et al., 2010). Calves offered milk volumes that approximate natural levels, are able to utilize twice the amount of nutrients as calves on a conventional diet (Khan et al., 2011a). Nutrients available at more natural levels facilitate both basal maintenance requirements and lead to improvements in all aspects of development, including the rumen and other GIT components (see Khan et al., 2016), as well as overall growth (Appleby et al., 2001; Jasper and Weary, 2002).   Recent studies have also found that the introduction of forage to calves fed a natural level of milk did not lead to reduced grain intake (de Passillé and Rushen, 2012; de Passillé et al., 2011; Roth et al., 2009). In fact, evidence now suggests that access to forage during pre-weaning may actually encourage solid feed intake (de Passillé and Rushen, 2012), increase early rumination (Castells et al., 2012) and consequently saliva that buffers rumen pH, contribute to rumen development (Khan et al., 2011b), and ultimately lead to improved growth (De Paula Vieira et al., 2012; Castells et al., 2012, 2013). 18  There have been some accounts that calves on higher milk diets are at higher risk of enteric disease than milk restricted calves, but studies that have investigated this question found no difference in health status (Bach et al., 2013; De Paula Vieira et al., 2008; Jasper and Weary, 2002; Khan et al., 2007). This suggests that pre-weaned health outcomes are more related to other management factors, such as sanitation, than milk volumes specifically (Hammon et al., 2002). 1.3.6 Growth   Calves left with the dam to nurse are able to gain over 3 times the weight of conventionally fed calves (e.g. milk rations equivalent to 10% of BW) over the first 2 weeks of life (Flower and Weary, 2001). This contrast in growth rates has now been found in numerous studies using higher volumes of milk or concentrations of milk replacer (Jasper and Weary, 2002; Khan et al., 2007; de Passillé et al., 2011; Davis Rincker et al., 2011). Calves fed these ‘accelerated’ feeding programs, which more closely approximate natural levels, consistently have higher pre-weaning growth rates, reaching 1.0 kg/day (Eckert et al., 2015; Sweeney et al., 2010), roughly doubling the growth rates of conventionally fed calves (Borderas et al., 2009). This disparity in growth has been reported to be most pronounced early in life, for example 0.36 vs. 0.85 kg/day at 2 weeks (Appleby et al., 2001) and 0.41 vs. 0.94 kg/day at 3 weeks (Borderas et al., 2009). de Passillé et al. (2011) reported that conventional calves could not match the growth rates of ad-libitum calves until 6 weeks, while Borderas et al. (2009) described a similar difference until 5 weeks. Similarly, calves fed 8 L of milk were observed to maintain significantly greater growth for 4 weeks (Kiezebrink et al., 2015). These results suggest that no amount of solid feed can nutritionally compensate for low milk volumes as the calf’s GIT is not physiologically capable of utilizing it in the early pre-weaned period. 19  1.3.7 Weaning   Calves fed higher milk volumes tend to have lower DMI through the pre-weaning period (Bach et al., 2013; Cowles et al., 2006; de Passillé et al., 2011; Raeth-Knight et al., 2009), which can lead to a delay in solid feed digestion efficiency and result in reduced growth and potential weight loss during and after weaning (Chapman et al., 2016; Hill et al., 2010; Sweeney et al., 2010). These negative influences on weaning performance tend to be observed when traditional abrupt weaning practices (immediate switch from milk to solid feed) are used (Jasper and Weary 2002). The method of weaning can have a profound effect on the outcomes of calves on accelerated programs (Khan et al., 2011a). Gradual weaning (reducing the daily milk volume incrementally) has been found to reduce both the stress and severity of weight loss compared to abrupt methods (Roth et al., 2008; Sweeney et al., 2010; Weary et al., 2008). Other work has found that delaying the age of weaning by even a couple of weeks can lead to much higher DMI just before weaning and an easier transition off milk (de Passillé and Rushen, 2012; Eckert et al., 2015). When calves are gradually weaned based on their individual daily grain intake levels with automatic feeders, de Passillé and Rushen (2012) found weaning occurred sooner and with no weight loss. Another practical method of weaning introduces a gradual ‘step-down’ in milk levels midway through the milk-feeding period to encourage DMI before eventual weaning, which is also done gradually (Khan et al., 2007). Calves fed 20% BW equivalent in daily milk using this program were able to sustain their growth and maintain a size advantage over conventionally (10% BW) fed calves (Khan et al., 2007).  Social housing has also been shown to facilitate increased DMI through social facilitation (Costa et al., 2015; Jensen et al., 2015), leading to increased gains and subsequently, an easier 20  transition to solid feed. Social housing have also been found to provide a social buffering effect to the calves during stressful experiences, such as weaning (De Paula Vieira et al., 2010).  1.3.8 Benefits of natural growth    The contributions to early physiological development and growth in the early pre-weaned period appear to have lasting benefits that extend beyond weaning. Some of the reported advantages of increased growth include an earlier breeding and conception age (Davis Rincker et al., 2011; Raeth-Knight et al., 2009), earlier age at first calving (Heinrichs et al., 2005), and increased survivability to the second lactation (Bach, 2011). Most interestingly, a number of studies have found a positive association between early growth and milk production (Heinrichs and Heinrichs, 2011; Soberon et al., 2012). Two meta-analyses incorporating all of the current studies have estimated that every 100 g/day of additional growth in the pre-weaning period will translate into 155 to 225 kg of milk production at the first lactation (Bach, 2012; Soberon and Van Amburgh, 2013).  1.3.9 Current outcomes   Unlike assessing for passive transfer of immunity, tracking growth rates can be accomplished very simply by obtaining multiple weights on individual calves (Faber et al., 2005).  While a pressure scale is the gold standard, it is also possible to estimate weights with reasonable accuracy by measuring calves’ heart-girth with a tape (Heinrichs et al., 1992). This method is practical, requiring only basic training to operate and almost no cost. Despite these accessible tools and recommendations that producers perform at least monthly assessments (Breen et al.,  2012), there is little evidence of pre-weaned calf growth being tracked (Murray and Leslie, 2013).  21   Calf management surveys reveal a wide range of dairy farming practices, however the majority of farms appear to feed restricted milk volumes. A Canadian survey found the median daily milk volume to be 5.5 L for the majority of the pre-weaning period, with nearly a fifth weaning abruptly at a median age of 7 weeks (Vasseur et al., 2010). Similarly, recent data from the U.S. reveal 53% of farms offering 3.8 to 4.7 L (4 to 5 qt) of milk per day, but weaning a little later at 9 weeks (USDA, 2016). An earlier national survey of calf growth reported gains of 0.53 kg/day over the first 6 weeks and 0.26 kg/day at 2 and 3 weeks (USDA, 2010). These results suggest there are unrealized opportunities for dairy farmers to improve the welfare, health and growth of their calves.  1.4 Thesis objective and hypothesis   The primary aim of this study was to investigate the effects of a peer-based benchmarking intervention program on dairy farms using the outcome measures of FPT and average daily gains of pre-weaned calves. We hypothesised that participation in this program would motivate some farmers to adopt specific management changes intended to improve their calf outcomes, and that those farms making changes would experience improved outcomes in comparison with farms that made no such changes.   22  Chapter 2: Benchmarking passive transfer of immunity and growth in dairy calves  2.1  Introduction   Colostrum management is one of the most critical areas of calf care (Beam et al., 2009; Vogels et al., 2013). Calves are born agammaglobulinemic and are reliant upon early consumption of sufficient quantities of good quality colostrum to acquire immunoglobulins (Ig; McGrath et al., 2016). Colostrum quality is dependent on several factors including the volume produced, time of collection, concentration of immunoglobulins, and bacteria levels (see Godden, 2008; McGuirk and Collins, 2004). In addition for successful passive transfer of immunoglobulins, of which 90% is Immunoglobulin G (IgG; Larson et al., 1980), the colostrum must be ingested by the calf soon after birth (see Weaver et al., 2000). Failure of passive transfer (FPT) is currently defined as a serum IgG concentration below 10 mg/ml (Beam et al., 2009; Faber et al., 2005). Documented negative outcomes associated with FPT include: increased pre-weaning morbidity (Donovan et al., 1998) and mortality (Robison et al., 1988), increased duration of illness (Paré et al., 1993), increased contagiousness or pathogen shedding (Lopez et al., 1988), reduced growth (Dewell et al., 2006), reduced milk production in the first lactation, and increased culling rates (DeNise et al., 1989). Although the importance of colostrum and recommended protocols for achieving successful passive transfer have been studied extensively, dairy farms continue to struggle with FPT and the associated economic and welfare costs. For example, surveys have found FPT rates of 25 to 37% in Canada (Trotz-Williams et al., 2008; Wallace et al., 2006), 19% in the U.S. (USDA, 2010), and 38% in Australia (Vogels et al., 2013). A survey of calf management 23  practices in Quebec, Canada found that no farms evaluated colostrum quality or newborn passive transfer status (Vasseur et al., 2010). Recent survey data in the U.S. found that 15% of farms tested colostrum quality and only 6% routinely screened for FPT (USDA, 2016).  Another important measure for assessing calf management success is average daily gains (ADG; Breen, et al., 2012), but to our knowledge few dairy farmers routinely track calf weights (Murray and Leslie, 2013) or set specific targets during the milk-feeding period. Moreover, there has been considerable change in thinking about milk feeding practices; a developing literature indicates that providing more milk, earlier in life, can improve calf growth rates, reduce disease incidence, and facilitate greater solid feed intake when combined with an appropriate weaning strategy (see Khan et al., 2011). Calves provided free choice access to milk will often drink 10 L/day or more (de Passillé et al., 2011; Jasper and Weary, 2002) and are capable of gaining 1 kg/day (Eckert et al., 2015; Sweeney et al., 2010). Recent U.S. data, however, shows that 56% of farms continue to provide milk volumes of 5 L/day or less, and only 22% feed 8 L/day or more (USDA, 2016). Data from 2007 report ADG from birth to 69 days of 0.6 kg/day (USDA, 2010). Benchmarking is an improvement tool used in many fields including health care and agriculture (Sutherland and Peel, 2011). Comparing one’s own performance with others provides context to reflect on current practices and identify areas for improvement (Anand and Kodali, 2008; Meade, 1994). This approach may be especially useful for addressing complex multifactorial problems that cannot be solved with simple one-size-fits-all solutions.   The aim of the current study was to assess the effects of benchmarking FPT and ADG of pre-weaned calves on dairy farms. We hypothesized that after receiving benchmark reports some farmers would make management changes intended to improve these outcome measures, and 24  that those farms making changes would experience improved outcomes in comparison with farms that made no such changes. 2.2 Materials and methods  2.2.1 Project design  Dairy farms were recruited from the client roster of the Greenbelt Veterinary Clinic (Chilliwack, BC). All farms were located in the lower Fraser Valley region of British Columbia, Canada. Inclusion criteria were: 1) a Holstein herd, and 2) more than 100 milking cows. Exclusion criteria were: 1) the farm was currently or had recently (within the past year) been included in another University of British Columbia study, and 2) that the farm routinely used a colostrum replacer. Out of a total of 19 farms approached, 18 agreed to participate. The average (± SD) size of these farms was 264 ± 110 lactating cows, with a range of 113 to 450.   To facilitate logistics and control for the effects of time, participants were divided into two staggered groups consisting of 8 and 10 farms, respectively. Each group underwent an initial 7 weeks of data collection. During this period blood was collected weekly from all calves less than 7 days of age. At 2-week intervals every milk-fed calf on the farm was measured using a heart-girth tape. One to 4 weeks after the end of the data collection period benchmark reports were presented to the farms. Following discussion, producers were recommended to consult with their veterinarian and others before deciding on any management changes that they would like to implement before the second round of data collection. Farms were then offered the opportunity to participate in a second assessment period, regardless of whether changes were made or not. All of the 18 farms agreed to participate in the second round of assessment. Farms were provided 24 ± 5 days (mean 25  ± SD) between the initial benchmark report and the resumption of calf measures to consider and implement any protocol or infrastructure changes. The specific interval for each farm was dependent on receiving confirmation that the farm had implemented any intended changes.  The animal care aspects of this study were approved by the University of British Columbia’s (UBC) Animal Care Committee (application A14-0245). Survey methods were approved by UBC’s Behavioural Research Ethics Board (application H14-03196).  2.2.2 Data collection  A management practices survey was conducted in person during the initial farm visit, interviewing the primary calf caretaker(s) on that farm. Survey items included general pre-weaned calf practices, with a focus on colostrum and feed protocols. Follow-up surveys were conducted at the beginning and end of the second round of data collection to identify any changes made over the trial.  Following recommended protocols for herd assessment of FPT of immunity (McGuirk and Collins, 2004), blood samples were collected weekly from all calves (heifers and bulls) aged between 1 to 7 days of age at the time of collection. A minimum of 12 calves was required per report for each farm. On average (± SD), 22 ± 7 calves were tested per farm during each round, with 380 calves tested in Round 1 and 402 calves in Round 2.  Samples were collected by jugular venipuncture with red top vacutainer tubes (10.0 mL BD Vacutainer glass serum tube, silicone coated, Becton Dickinson and Co., Franklin Lakes, NJ) and refrigerated for up to 24 hours before the serum was separated by centrifuge (Legend RT, Sorvall, Thermo Fisher Scientific Inc., Waltham, MA) at 2700 rpm for 15 minutes then stored at -20⁰C until analysis. Measuring serum total protein (TP) via refractometry is considered a valid 26  proxy measure for IgG and practical method of assessing passive transfer of immunity in calves (Deelen et al., 2014; Morrill et al., 2013; Thornhill et al., 2015). Serum TP was measured twice with a temperature-compensating digital refractometer (AR200, Reichert Analytical Instruments, Reichert Inc., Depew, NY) to assess the state of passive transfer in each calf. FPT was defined as a serum TP score below 5.2 g/dL (Calloway et al., 2002; Tyler et al., 1996). Every second week, heart-girth tape measurements were taken from all pre-weaned calves ≤ 70 days of age, to a maximum of 25 animals per visit. On average (± SD), 53 ± 10 measurements were taken per farm for each report, with a total of 866 calves taped in Round 1 and 1047 calves in Round 2. No individual calves were included in both Rounds.  To obtain a consistent measurement, calves were required to conform to a neutral standing posture, with all 4 legs straight and on even ground, head upright and forward, with the neck relaxed and not stretched or curved to the sides or back. A standard 150 cm measuring tape was passed under the chest behind the front legs and over the back just behind the calves’ withers (see Heinrichs and Lammers, 1998).  To ensure reliability within and between the two assessors who performed all of the on-farm taping, scoring sessions were carried out before the study began and during the interval between groups using a total of 66 pre-weaned Holstein calves at the University of British Columbia’s Dairy Education and Research Centre in Agassiz, British Columbia. Assessors alternated taping each calf twice and were blind to the other’s score. These calves were also weighed using a pressure scale (355 I.S., GSE Avery Weight-Tronix, Fairmont, MN).    27  2.2.3 Benchmarking   Benchmark reports summarized each farm’s passive transfer rates and average daily gains together with the results from other farms de-identified (as a means to maintain confidentiality) before group comparisons were presented. Each farm also received their individual calf data on a separate sheet as part of the report.  The herd veterinarian presented the report and the data sheets to the farm owner, manager, and the primary calf caretaker. At least one of the authors of this paper also attended each meeting. After the content of the report was explained, the farm owner and staff were encouraged to ask questions. The veterinarian, supported by the research staff, provided information in response to the questions and facilitated discussion around calf care.  2.2.4 Statistical analysis   All statistical analyses were performed in RStudio, using R version 3.2.4 (R Core Team, 2016; RStudio Team, 2015). The effects of benchmarking on passive transfer and weight gain outcomes were analysed by multilevel mixed regression modeling with the lme4 package (Bates et al., 2015). Significance was tested using Satterthwaite approximations with the lmerTest package (Kuznetsova et al., 2016). Passive transfer rates were analysed as %FPT in relation to the benchmark intervention. To account for variability at the farm level, farms were included in the model as a random effect with random intercepts and random slopes, where appropriate. ADG was estimated by regressing continuous weight data as the outcome measure with age. In addition, ADG was estimated separately for younger (≤ 35 days) and older calves (> 35 days) using the same method. These age classes were considered separately to reflect differences in management and development, including differences in milk volumes offered and rumen anatomy and physiology. Calves were also included as a random effect nested within the farm 28  level to control for individual animal variability that arose from repeat heart-girth tape measurements. Heart-girth measurements and repeat measurements obtained by the two different assessors during reliability testing sessions were analysed for inter- and intra- observer agreement using Pearson correlation. The appropriateness of heart-girth estimations for this study was evaluated by comparing the mean estimated BW with scale weights using linear regression. 2.3 Results  2.3.1 Before benchmarking  Participating farms reported a variety of calf management practices relevant to the outcome measures being assessed (Table 1). Prior to the study none of the farms regularly tested colostrum quality or monitored for FPT. The maximum time to collect colostrum was 9.9 ± 3.4 hours (mean ± SD). Eight farms maintained a frozen colostrum bank, 5 refrigerated colostrum, and 5 did not store colostrum. The maximum time until first colostrum feeding was 9.3 ± 3.9 hours, with 12 farms primarily feeding via bottle and teat, 5 via endotracheal tube, and 1 varying methods depending on who was on staff at the time the calf was born. The minimum amount of colostrum fed at the first feeding was 2.6 ± 0.8 L.  Nine of the 18 farms milked twice daily, 7 milked 3 times daily, and 2 used automated free-choice milking stations. Milk was fed twice daily on 16 farms, 1 farm fed 3 times and 1 only fed once per day. All farms offered milk by bottle and teat for the first 1 to 2 weeks, but many transitioned to bucket for the remainder of the milk-feeding period. Fresh waste milk was the primary liquid feed offered on half of the farms; pasteurized waste milk, milk replacer, and a 29  blend of replacer and waste milk were fed on the remaining farms. Nearly all farms offered increased volumes of milk to older and larger calves. Initial and maximum daily milk offered averaged (± SD) 5.1 ± 2.0 and 7.5 ± 1.5 L respectively, with maximum milk volume reached at 23.6 ± 16.8 d. Calves were weaned over an average (± SD) of 7.6 ± 7.1 days and were fully weaned from milk by 72.8 ± 11.1 days of age. The mean (± SD) serum TP level on farms at first assessment was 5.8 ± 0.2 g/dL, with a range of 5.5 to 6.3 g/dL. The average (± SD) FPT rate was 16 ± 10%, and ranged from 3 to 39% (Figure 1A). Calf age when blood sampled was not associated with FPT.  Pearson correlations and interclass correlation comparisons of heart-girth measurements for intra and inter-reliability were at least 0.99 within and between all combinations of assessors. Regressing the mean estimated weights from the taping of 66 calves 1 - 70 days against true BW (as measured by the scale) yielded an R2 = 0.97.  The ADG (± SD) for farms at the first assessment were 0.68 ± 0.01 kg/day and ranged from 0.54 to 0.88 kg/day (Figure 1B). When calves were divided into early (≤ 35 days) or late pre-weaning periods (> 35 days), average gains were 0.50 ± 0.01 kg/day and 0.86 ± 0.02 kg/day, respectively.  2.3.2 After benchmarking  Fifteen of the 18 participating farms elected to make at least 1 specific change related to either colostrum or milk-feeding practices (Table 2). Of these 15 farms, 6 made changes to both management areas, 5 made colostrum-specific changes only, and 4 made milk-feeding management changes only. One farm reported attempting a change, then reverting to original 30  operating procedures before the second assessment, and 2 farms made no changes due to inconvenient timing.  The most common change was to increase the amount of colostrum or milk fed. Of farms that made such a change, the average (± SD) increase in minimum first colostrum fed was 1.0 ± 0.1 L, and the increase in initial milk offered was 2.1 ± 1.7 L/day and 2.2 ± 1.5 L in maximum milk offered. Maximum milk was offered 17.8 ± 8.9 days earlier on the 4 farms that made such a change. Additional changes ranged from altering standard colostrum feeding procedures (quicker first feeding, additional feedings, recording time of feedings) to purchasing new equipment for testing (colostrometer or refractometer) and storing (freezer, refrigerator) colostrum.  As predicted, farms that implemented specific changes in their colostrum management protocols experienced improved FPT rates after the benchmark intervention; the 11 farms that made specific colostrum-related changes had an average (± SD) FPT of 11 ± 10% and reduced their mean FPT by 9 ± 3% (p < 0.01; range = -31 to 5%), following the benchmark report (Figure 1 A). In contrast, the 7 farms that did not make changes in their colostrum management trended towards higher FPT, with rates increasing by an average of 7 ± 4 % (p < 0.1; range = -8 to 26%), relative to their pre-benchmark performance.  Ten farms reported making specific protocol changes intended to improve calf weight gains after the first assessment. Average daily gains on these farms increased at the second assessment by 0.06 ± 0.02 kg/day (p < 0.01; Figure 1 B). This difference was greatest for calves early in the milk-feeding period (≤35 d; 0.16 ± 0.03 kg/day; p < 0.01). In contrast, for those 8 farms that did not make any specific management changes, a decline was observed after the benchmark report considering all calves (-0.05 ± 0.02 kg/day; p < 0.01), and no significant change for calves ≤ 35 days. 31  2.4 Discussion  2.4.1 Producer engagement and changed practices  To our knowledge this study is the first to experimentally assess the effects of participating in a benchmarking program relevant to dairy management. Our earlier work benchmarking lameness and skin injuries in adult cows was initially based upon a single report (von Keyserlingk et al., 2012; Chapinal et al., 2013; Barrientos et al., 2013). Our only data to assess the effectiveness of this approach in changing practices was from a convenience sample using farms that invited us to return for a second assessment approximately 1 year after the first report. This sample of producers appeared to be highly motivated to change practices, and showed improvements in lameness and hock injuries (Chapinal et al., 2014). In contrast, the current study followed all farms before and after receiving a benchmark report. Our results show a high level of producer motivation to have data from their farm on FPT and calf ADG, as demonstrated by the very high participation rate in this study (18 of 19 farms invited), and the 100% retention rate from Round 1 to Round 2 of assessments. By design, the participating farms were not required or asked to perform any specific changes by the research team. However, most farms (15 of 18) chose to make colostrum or feed protocol changes in consultation with their veterinarian.  2.4.2 Passive transfer of immunity  Recommended best practices to prevent FPT include feeding a minimum of 4 L of high quality colostrum within 6 hours of calving (Godden, 2008). Increasing the volume of colostrum fed was the most common change producers made; fewer farms introduced changes aimed at improving the quality and timing of the first colostrum feeding, likely because these changes 32  required more effort and planning. Of the 16 farms that milked manually, 11 collected colostrum exclusively during regular milking times, imposing a delay in feeding without access to a colostrum bank. Counter-intuitively, the longest delays to feed were on farms that milked three times daily, as on these farms the evening milking staff were not trained to care for newborn calves.  The current study was not designed to test the effects of specific interventions, and our sample size is inadequate to evaluate the types of changes that were most effective. However, our results do indicate that those farms that made some change were able to improve their performance relative to those farms that did not make relevant changes. It was also the case that farms showing relatively high rates of FPT were most likely to adopt changes. That farms with the lowest performance before benchmarking were the once most motivated to change practices is not surprising, but this also introduces a bias in the study; by chance alone farms at the low end of the distribution might be expected to improve and vice-versa reflecting a simple regression towards the mean (Barnett et al., 2005). Indeed, 7 of the 8 top farms in terms of low FPT during the first assessment chose to make no changes relative to colostrum management, and these farms showed somewhat poorer performance in the second round of testing; maybe because they were now focusing on other aspects identified in the discussion surrounding gains. The current study was designed to allow farmers to adopt the changes that they saw fit, but future studies could avoid this issue by experimentally assigning farms to specific interventions.  Past surveys using a similar serum TP threshold for FPT have found rates varying from 21 to 38% (USDA, 2010; Vogels et al., 2013); far above current assessment standards that recommend a threshold of 10% FPT to be considered of minimum concern (McGuirk, 2010). The FPT rates observed on farms in this study were relatively low, with 16% of calves failing at 33  the first assessment, and 11% at the second assessment following colostrum protocol changes. These results indicate that sufficiently motivated and informed producers can reach FPT rates far below industry averages, to levels approaching current best practice recommendations in a short period of time.  2.4.3 Weight gains  Calf weights were estimated from tape measurements, which is a practical method for this type of on-farm study where scales are either unavailable or impractical for use. Previous work has shown that heart-girth taping can provide reliable estimates of actual BW in young calves (Heinrichs et al., 1992). Some authors have expressed concerns of reduced accuracy of such measures for calves under 3 months (Dingwell et al., 2006; Heinrichs et al., 2007), but the results of our validation work suggest that this method can also be considered sufficiently accurate for use in these younger animals (see also Bond et al., 2015). In preliminary work we found that inconsistencies in calf posture added considerable error to the estimates. Thus we recommend training for any scientific or practical use of weight tapes on farm, with specific attention to consistency in calf posture and tape positioning.  Traditional ‘restricted’ milk feeding programs have typically provided approximately 4 L/day, compared with more recent ‘accelerated’ programs that advocate 8 L/day or more in the pre-weaning period (Khan et al., 2011), especially in the first few weeks of life when calves are unable to digest solid feeds (Baldwin et al., 2004). Recent work has shown that improved weight gains early in life translate into production improvements, including age at first calving (Heinrichs and Heinrichs, 2011), survivability to second lactation (Bach, 2011), and increased milk production (Soberon et al., 2012). Meta-analyses have estimated that every 100 g/day of 34  additional growth during the pre-weaned period equates to 155 to 225 kg of milk produced at first lactation (Bach, 2012; Soberon and Van Amburgh, 2013).  At first assessment almost every participating farm employed a dynamic ‘step-up’ milk-feeding protocol, increasing volume incrementally with age, as was similarly observed by Vasseur et al. (2010). Most participants employed this step-up system due to concerns that feeding more milk to young calves would increase the incidence of enteric disease, despite a number of studies finding no positive link between milk ration and morbidity (Borderas et al., 2009; Jasper and Weary, 2002; Khan et al., 2007). Of the farms that increased volumes for the duration of the second assessment, none reported an increase in illness over this time. Indeed, farm staff spontaneously reported to assessors a noticeable improvement in calf health and body condition. Following the benchmark report, some producers focused on milk volume increases within the first few weeks of life, which may explain why daily gains were observed to substantially improve for calves ≤ 35 days.  Four participants introduced a ‘step-down’ in milk volume at 35 to 45 days to encourage solid feed intake before weaning and minimize weaning stress (Khan et al., 2007). Although this study did not follow calves through weaning, research has shown that increased gains in accelerated programs pre-weaning are not guaranteed to carry through to breeding age, particularly when early or abrupt weaning methods are utilized (Eckert et al., 2015; Sweeney et al., 2010). We recommend that future studies follow calves through weaning, to better identify the effects of weaning practices on calf growth and health. As with FPT results, farms that made feed management changes tended to show greater ADG improvements compared with farms that did not. In this case however, initial ranking and 35  the decision to make changes were not closely linked, suggesting that the improvements in ADG were due to changes implemented rather than regression to the mean.  2.5 Conclusion    Producers were motivated to participate in a benchmarking program providing them their own data and relevant comparators for FPT and ADG in milk fed calves. Participation in the program appeared to also motivate specific management changes intended to improve performance. Farms applying relevant management changes experienced improved performance in both FPT and ADG.   36  Table 1. Summary of categorical calf management practices reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period. Management Variable Method Farms (n) Colostrum storage None 5  Refrigerated 5  Frozen 8 Colostrum quality testing  Usually 0  Rarely 1  Never 17 Colostrum feeding method Endotracheal tube 6  Bottle 13 Milk delivery frequency Once a day / free choice 1  Twice a day 16  3 times a day 1 Milk feeding apparatus  Bucket 10  Teat 7  Multi-teat mob Feeder 2 Milk type provided calves Unpasteurized 9  Pasteurized 3  Replacer 5  Replacer blend 2 Milk volume ramp-up steps  None  2  One 9  Two or more 7 Weaning process Gradual 11  Abrupt 6  Semi-abrupt  1 Calf housing Hutch 5  Hutch & run 7  Stall 6  Pair/group pen 5   37  Table 2. Summary of quantitative calf management practices reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period. Management Variable Measure Mean ± SD Range Colostrum management Maximum collection time (h) 9.9 ± 3.4 1 - 14.5 Maximum time to first feeding (h) 9.3 ± 3.9 3 - 16  Minimum amount first feeding (L) 2.6 ± 0.8 1.9 - 4.4 Feed management Initial daily milk offered (L) 5.1 ± 2 3.8 - 12.5 Maximum daily milk offered (L) 7.5 ± 1.5 5.7 - 12.5  Age at maximum daily milk (d) 23.6 ± 16.8 1 - 60  Age ad-libitum water offered (d) 16.5 ± 23.8 1 - 90  Age ad-libitum grain offered (d) 6.2 ± 4.7 1 - 17.5  Age ad-libitum forage offered (d) 66.8 ± 14.5 42 - 90  Duration of weaning period (d) 7.6 ± 7.1 0 - 21  Age weaned by (d) 72.8 ± 11.1 58 - 91 Calf housing Age pair or group housed by (d) 57.9 ± 25.6 7 - 90    38  Table 3. Summary of calf management changes reported by participating farms (n=18) at first assessment of the benchmarking study focused on colostrum feeding practices and growth rates during the milk feeding period.  Management variable Description of changes  Farms (n) Colostrum management Increase amount of first feeding 8 Additional feedings 3  Quality testing1 3  Record time of initial feeding 2  Reduce time before initial feeding 2  Acquire storage equipment2 2  Increase endotracheal tube use  2  Train additional staff to feed newborn calves 1  Install calving pen milk line for first milking 1  No changes 7 Feed management Increase initial milk volume 7 Increase maximum milk volume 7  Reduce days until maximum milk volume 4  Introduce early stepdown in milk volume 4   Provide water sooner 2  Additional daily feeding 1  Provide hay  1  Additional teats for group housed calves 1  No changes 8 1Via colostrometer, refractometer, or veterinary clinic 2Refrigerator or freezer           39  Figure 1. Failure of passive transfer rates (A) and average daily gains (B) of pre-weaned Holstein calves on 18 farms before and after the benchmark intervention.   Open circles (○) denote Round 1 results and solid shapes Round 2 results; solid triangles (▲) indicate farms made relevant protocol changes between rounds and solid circles (●) indicate no such changes were made. Farms arranged by Round 1 results in descending order for failure of passive transfer and ascending order for average daily gains.  40  Chapter 3: General discussion  3.1   Summary   Calves continue to experience high levels of morbidity and mortality (USDA, 2010), despite the considerable investment of time and money to raise them to breeding age (Heinrichs et al., 2013; Mohd Nor et al., 2015). Although the importance of successful passive transfer of immunity (Godden, 2008; Weaver et al., 2000) and vigorous growth (Bach, 2011; Soberon et al., 2012) in the pre-weaning period are well established, neither of these outcomes are typically measured on farms (Beam et al., 2009; Breen et al., 2012). Without quantitative outcome data that can be compared to a standard, producers cannot assess the effectiveness of their current practices or any future changes. As motivating producer participation remains a major barrier to successful intervention strategies (Kristensen and Jakobsen, 2011), there is a need to explore alternative methods of information dissemination that foster meaningful engagement.   The objective of my thesis was to investigate whether benchmarking failure of passive transfer (FPT) of immunity rates and average daily gains (ADG) would motivate producers to engage in issues around calf care, leading to relevant management changes and improved calf outcomes. Benchmarking is an improvement tool used across industries and organizations that contextualize one’s own performance alongside peers (Bogetoft, 2012), which has the potential to resonate more with producers than individual farm surveys and expert recommendations alone.   Participating farms demonstrated a high level of engagement and participation during the benchmark intervention, with all farms volunteering to undergo a second assessment period following the first benchmark report and 15 of 18 farms making at least one management change 41  intended to improve either FPT or ADG outcomes. The rates of FPT decreased for farms that made changes in their colostrum management program. Similarly, farms that made feed protocol changes experienced improved ADG, especially for younger calves that are fully dependent upon milk as a source of nutrients. These results provide the first experimental evidence that benchmarking FPT and ADG can motivate engagement on issues around calf care, improving the welfare and performance of pre-weaned dairy calves.  3.2  Strengths and limitations    The nature of this study, as a practical on-farm extension project in collaboration with local veterinarians and producers, led to several aspects of the experimental design that were advantageous. The outcome measures chosen for benchmarking needed to have scientific validity and be easily understood and accessible to participants. Serum total protein (TP) measured via refractometry was used for determining FPT as it is a well-established proxy measure of immunity (Godden, 2008; McGuirk and Collins, 2004) that is simple to explain, affordable, and readily available to producers as a service through their veterinarian. Similarly, ADG derived from heart-girth measurements is a valid (Heinrichs et al., 1992) low-tech method commonly used on older animals when a scale is unavailable, that could be easily adopted directly on-farm (Heinrichs and Lammers, 1998). In summary, outcome data chosen for this study could be collected, communicated, and continued relatively easily. The facilitated discussion format of our benchmark report avoided making specific recommendations for producers. There were ample opportunities for discussion and producer reflection, as both FPT and ADG are outcomes sensitive to a wide range management inputs. Meetings focused on addressing producer questions or concerns around different practices, explaining potential risk factors and alternative management options supported by current 42  research. Effort was made to frame all potential strategies as options dependant on each farm’s goals and circumstances, allowing producers to select actions they felt were most appropriate and feasible for their farm. Previous work has shown that producer motivation and compliance can be compromised if the information being received is not perceived as useful or reflective of one’s values and goals (Kristensen and Jakobsen, 2011; Jansen et al., 2009).  Chances of triggering cognitive dissonance and rejection of the process may also have been reduced by allowing participants to first interpret their results alongside those of peers rather than against a pre-defined standard. This allowed farmers to identify potential problems on their farm and see that better results were attainable (Festinger, 1957). At the conclusion of each report, continued participation and the decision to make any changes was entirely voluntary, which provided an opportunity to assess engagement with the process, and increased the likelihood that changes would be meaningful to the farmer and sustainable. The inclusion of the farms’ veterinarians in the entire benchmarking process was advantageous on several fronts. My initial recruitment of farms was made smoother by having the veterinarians involved, as they already had well-established relationships of trust with their clients. In addition, farmers may have taken the study and information presented with more gravity, as veterinarians are generally well respected sources of knowledge for producers (Jansen et al., 2010c). Having a researcher involved in the facilitated discussions may have also been more effective than the veterinarian alone (Bell et al., 2009), as was the case for the mastitis intervention study by Main et al. (2012).  The collaborative, field-study design also introduced a number of challenges. For example, some selection bias may have been introduced by recruiting all of the participating farms through one veterinary clinic. The veterinarians may have avoided approaching some of 43  the harder to reach or potentially ‘difficult’ farmers. The inclusion criteria for the study also required farms above a certain size, resulting in smaller farms not being represented.  The recruitment process involved transparency with producers in explaining my on-farm activities, and these activities could also be observed during my repeated data collection visits.  Producers were thus aware of the nature of the study at first assessment, which may have influenced their calf management practices during Round 1. To the extent that this was the case all farms may have performed somewhat better than otherwise would be expected. Thus the Hawthorne effect (i.e. improving when knowing one is being observed; Adair, 1984), may help explain why the farms in this study performed well relative to industry averages in both outcomes even during Round 1. However, this cannot explain the improvement between Rounds 1 and 2. As with most other intervention studies, neither the producers nor the researchers were blind to the specific changes made on farms following the benchmark reports (Bell et al., 2009; Green et al., 2007; Main et al., 2012). Blindness was not possible for the producers, who were required to implement changes on their own farm, or for the primary researcher who collected biological and management data directly on-farm. This study compared farms before and after the report, as well as farms that made relevant changes with those that did not. It would be possible to draw stronger inferences regarding the effects of these management changes if farms could have been randomly allocated to specific management interventions (and control conditions). However, this approach would have not allowed for producers to develop their own solutions based upon their own understanding of the issue and the constraints on their own farm. In addition, the close geographical proximity of participants would have made it impossible to prevent cross-talk between control and treatment farms (Main et al., 2012), a concern that was 44  validated over the course of the study as several producers revealed knowledge of other participants obtained through community networks. In the current study, the initial assessment period provided a type of internal control and baseline with which to compare results after benchmarking (Jansen et al., 2010b).  Due to logistical constraints, it was not possible to collect data simultaneously from all 18 participating farms, resulting in two temporally staggered groups. This aspect of my experimental design risked introducing seasonal effects as a confounding factor between groups as FPT and ADG may be affected by climate (Gulliksen et al., 2008; Place et al., 1998). We did not observe any of the differences one would expect had season been influencing outcomes, as the second round calves experienced on average warmer temperatures that would be expected to depress results. However, there remains a possibility that seasonal differences across rounds influenced the final results.  The relatively short period of time between the benchmark reports and second assessments may have dampened the effects of the intervention. Two of the three farms that made no protocol changes cited timing as the reason. Furthermore, some of the management changes made on farms may not have been fully established or sensitive to re-assessment, particularly changes to milk feeding protocols in the early pre-weaning period (which would not be measureable in older calves that had not experienced the revised program). I attempted to minimize this issue by confirming with producers that all changes had been satisfactorily implemented before commencing the second round of data collection, and by the exclusion of any animals measured in Round 1. A final limitation in design that may have affected my results was the simultaneous benchmarking of two distinct management considerations. Farms that chose to focus solely on 45  either colostrum or feed management may have improved in one area at the neglect of the other, and attempts to make changes in both areas may have diluted their efforts. Comparisons between farms that made changes in one area or in both revealed no clear disadvantage to farms that focused on both, however the possibility remains that changes could have been more extensive and results more pronounced had all farms focused on a single outcome. That said, the inclusion of both FPT and ADG may also have been an advantage, as this increased the likelihood of identifying areas of improvement that aligned with particular farmers’ values and goals. 3.3  Recommendations    The current thesis provides the first evidence that benchmark interventions can motivate producer engagement on issues around calf care, but it is not clear if the observed management changes and resulting improvements in FPT and ADG are sustainable. Longer-term research is needed to assess both the lasting interest around calf care of producers who participated in benchmarking and the sustainability of the changes they implemented. Other important related areas of investigation include determining the optimal frequency of regular benchmark feedback and whether recruitment and continued participation would be reduced by imposing some financial cost for the service (e.g. a service fee by the veterinary clinic).    I also recommend future work to extend the data collection period of calf weights through the weaning period. I found high variability in the weaning methods employed on farms, and previous research has shown that pre-weaning management will influence calves’ response to the weaning process (Khan et al., 2007), and conversely, poorly integrated weaning strategies can bottleneck calf performance, undoing earlier gains (Kiezebrink et al., 2015). This negative effect on performance is also true of regrouping, which often takes place at the same time as weaning and may be especially stressful for calves that had been individually reared (De Paula Vieira et 46  al., 2010). A greater understanding of the management practices employed around weaning, variability in calf performance, and strategies used to improve outcomes would further the goals of improving calf welfare and performance, and could be easily integrated into the benchmarking process described in this study.    While this study allowed producers to make any management changes they felt could improve their calf outcomes, there are most likely certain types of changes that tend to be more easily adopted and effective depending on the characteristics of individual farms. Some of the potential factors to consider include the current performance level of the farm (and their relative ranking with peers), farm infrastructure and resources, and current practices. If the circumstances that determined the most appropriate types of changes could be elucidated, more effective and focused suggestions could be made to producers regarding changes they should consider. There may also be beneficial synergies, where certain combinations of changes made simultaneously would be more beneficial than if adopted alone (Green et al., 2007).  Finally, future research should investigate the link between producer attitudes and responsiveness to the benchmark intervention process. As farmer attitudes and values will determine receptivity to different types of information (Jansen et al., 2009; Valeeva et al., 2007), intervention programs could benefit if the candidate participants most likely to respond positively could be identified beforehand.   Engaging and motivating dairy producers is often the greatest challenge to successful information dissemination and practices adoption (LeBlanc et al., 2006). The benchmarking methods described here could be just as effective in a context outside academic research, such as veterinary medicine or assurance programs. For example, the success of this study illustrates a 47  way for veterinarians to engage with their clients on issues around calf care, potentially creating demand and the opportunity for new types of on-farm involvement for their practices.  Dairy cow performance outcome data is already collected and interpreted on a regular basis in areas such as reproduction and milk production. Additional assurance programs are also beginning to address other health and welfare outcomes, such as lameness and the body condition of animals (see Pro-Action, Canada; FARM Program, USA). As public demand for stricter welfare standards and oversight in agriculture continues to grow, I encourage the dairy industry to consider the pro-active incorporation of standardized calf benchmark assessments into a more holistic herd-auditing program. This would help reassure the public and enable producers to better gauge their own calf rearing success, as well as facilitate greater engagement with their peers and other stakeholders.  3.4  Conclusions     This study was born from the need for intervention methods to motivate engagement around some of the challenges related to calf care in the dairy industry today. This was accomplished by implementing a benchmarking program based upon the well-understood calf-based outcome measures of FPT and ADG. My objective was to investigate the effects such an intervention program would have on the participating farms.  I found that producers valued receiving this assessment data on their calves, and remained engaged throughout the process, as all farms requested a second assessment and report. As expected, participation in the benchmark program motivated the majority of farms to make at least one protocol change to improve their performance for the second report. 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