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Knowledge of population structure and breed composition of a population can be advantageous for a number of reasons; these include designing optimal (cross)breeding strategies in order to maximise non-additive genetic effects, maintaining flockbook integrity by authenticating animals being registered and as a quality control measure in the genotyping process. The objectives of the present study were to 1) describe the population structure of 24 sheep breeds, 2) quantify the breed composition of both flockbook-recorded and crossbred animals using single nucleotide polymorphism BLUP (SNP-BLUP), and 3) quantify the accuracy of breed composition prediction from low-density genotype panels containing between 2000 and 6000 SNPs. In total, 9334 autosomal SNPs on 11 144 flockbook-recorded animals and 1172 crossbred animals were used. The population structure of all breeds was characterised by principal component analysis (PCA) as well as the pairwise breed fixation index (Fst). The total number of animals, all of which were purebred, included in the calibration population for SNP-BLUP was 2579 with the number of animals per breed ranging from 9 to 500. The remaining 9559 flockbook-recorded animals, composite breeds and crossbred animals represented the test population; three breeds were excluded from breed composition prediction. The breed composition predicted using SNP-BLUP with 9334 SNPs was considered the gold standard prediction. The pairwise breed Fst ranged from 0.040 (between the Irish Blackface and Scottish Blackface) to 0.282 (between the Border Leicester and Suffolk). Principal component analysis revealed that the Suffolk from Ireland and the Suffolk from New Zealand formed distinct, non-overlapping clusters. In contrast, the Texel from Ireland and that from New Zealand formed integrated, overlapping clusters. Composite animals such as the Belclare clustered close to its founder breeds (i.e., Finn, Galway, Lleyn and Texel). When all 9334 SNPs were used to predict breed composition, an animal that had a majority breed proportion predicted to be ≥0.90 was defined as purebred for the present study. As the panel density decreased, the predicted breed proportion threshold, used to identify animals as purebred, also decreased (≥0.85 with 6000 SNPs to ≥0.60 with 2000 SNPs). In all, results from the study suggest that breed composition for purebred and crossbred animals can be determined with SNP-BLUP using ≥5000 SNPs.
Poor compliance of prescription medication is an ongoing public health crisis. Nearly half of patients do not take their medication as prescribed, harming their own health while also increasing public health care costs. Despite these detrimental consequences, prior research has struggled to establish cost-effective and scalable interventions to improve adherence rates. We suggest that one reason for the limited success of prior interventions is that they make the personal health costs of non-adherence insufficiently prominent, while a higher saliency of these costs may motivate patients to adhere more. In the current research, we test whether an intervention that makes the personal health costs of non-compliance more salient for patients will increase their medication adherence. To do so, we conducted a randomized controlled trial with 16,191 patients across 278 UK pharmacies over a 9-month time period and manipulated the perceived consequences of medication non-adherence. We find that patients who received a treatment highlighting the personal health costs of non-compliance were significantly more likely to adhere to their medication than three comparison groups (odds ratio = 1.84, 95% confidence interval = 1.37–2.47). Shifting patients’ focus to the personal health costs of non-compliance may thus offer a potentially cost-effective and scalable approach to improving medication adherence.
Although food from grazed animals is increasingly sought by consumers because of perceived animal welfare advantages, grazing systems provide the farmer and the animal with unique challenges. The system is dependent almost daily on the climate for feed supply, with the importation of large amounts of feed from off farm, and associated labour and mechanisation costs, sometimes reducing economic viability. Furthermore, the cow may have to walk long distances and be able to harvest feed efficiently in a highly competitive environment because of the need for high levels of pasture utilisation. She must, also, be: (1) highly fertile, with a requirement for pregnancy within ~80 days post-calving; (2) ‘easy care’, because of the need for the management of large herds with limited labour; (3) able to walk long distances; and (4) robust to changes in feed supply and quality, so that short-term nutritional insults do not unduly influence her production and reproduction cycles. These are very different and are in addition to demands placed on cows in housed systems offered pre-made mixed rations. Furthermore, additional demands in environmental sustainability and animal welfare, in conjunction with the need for greater system-level biological efficiency (i.e. ‘sustainable intensification’), will add to the ‘robustness’ requirements of cows in the future. Increasingly, there is evidence that certain genotypes of cows perform better or worse in grazing systems, indicating a genotype×environment interaction. This has led to the development of tailored breeding objectives within countries for important heritable traits to maximise the profitability and sustainability of their production system. To date, these breeding objectives have focussed on the more easily measured traits and those of highest relative economic importance. In the future, there will be greater emphasis on more difficult to measure traits that are important to the quality of life of the animal in each production system and to reduce the system’s environmental footprint.
This paper describes three case examples from a recent trial of family intervention specifically designed for people of African-Caribbean descent. These examples, told from the therapists’ perspectives, highlight key components of the intervention and issues that arose in working with this client group. Findings from the study suggest that it is possible to engage this client-group in family therapy similar to traditional evidenced-based family interventions, although as illustrated in the paper, it is important that therapists pay attention to themes that are likely to be particularly pertinent for this group, including experiences of discrimination and mistrust of services. The use of Family Support Members, consisting of members of the person's care team or volunteers recruited from the community, may also help support people to engage in therapy in the absence of biological relatives.
Body condition score (BCS) is a subjective assessment of the proportion of body fat an animal possesses and is independent of frame size. There is a growing awareness of the importance of mature animal live-weight given its contribution to the overall costs of production of a sector. Because of the known relationship between BCS and live-weight, strategies to reduce live-weight could contribute to the favouring of animals with lesser body condition. The objective of the present study was to estimate the average difference in live-weight per incremental change in BCS, measured subjectively on a scale of 1 to 5. The data used consisted of 19 033 BCS and live-weight observations recorded on the same day from 7556 ewes on commercial and research flocks; the breeds represented included purebred Belclare (540 ewes), Charollais (1484 ewes), Suffolk (885 ewes), Texel (1695 ewes), Vendeen (140 ewes), as well as, crossbreds (2812 ewes). All associations were quantified using linear mixed models with the dependent variable of live-weight; ewe parity was included as a random effect. The independent variables were BCS, breed (n=6), stage of the inter-lambing interval (n=6; pregnancy, lambing, pre-weaning, at weaning, post-weaning and mating) and parity (1, 2, 3, 4 and 5+). In addition, two-way interactions were used to investigate whether the association between BCS and live-weight differed by parity, a period of the inter-lambing interval or breed. The association between BCS and live-weight differed by parity, by a period of the inter-lambing interval and by breed. Across all data, a one-unit difference in BCS was associated with 4.82 (SE=0.08) kg live-weight, but this differed by parity from 4.23 kg in parity 1 ewes to 5.82 kg in parity 5+ ewes. The correlation between BCS and live-weight across all data was 0.48 (0.47 when adjusted for nuisance factors in the statistical model), but this varied from 0.48 to 0.53 by parity, from 0.36 to 0.63 by stage of the inter-lambing interval and from 0.41 to 0.62 by breed. Results demonstrate that consideration should be taken of differences in BCS when comparing ewes on live-weight as differences in BCS contribute quite substantially to differences in live-weight; moreover, adjustments for differences in BCS should consider the population stratum, especially breed.
Understanding how critical sow live-weight and back-fat depth during gestation are in ensuring optimum sow productivity is important. The objective of this study was to quantify the association between sow parity, live-weight and back-fat depth during gestation with subsequent sow reproductive performance. Records of 1058 sows and 13 827 piglets from 10 trials on two research farms between the years 2005 and 2015 were analysed. Sows ranged from parity 1 to 6 with the number of sows per parity distributed as follows: 232, 277, 180, 131, 132 and 106, respectively. Variables that were analysed included total born (TB), born alive (BA), piglet birth weight (BtWT), pre-weaning mortality (PWM), piglet wean weight (WnWT), number of piglets weaned (Wn), wean to service interval (WSI), piglets born alive in subsequent farrowing and sow lactation feed intake. Calculated variables included the within-litter CV in birth weight (LtV), pre-weaning growth rate per litter (PWG), total litter gain (TLG), lactation efficiency and litter size reared after cross-fostering. Data were analysed using linear mixed models accounting for covariance among records. Third and fourth parity sows had more (P<0.05) TB, BA and heavier BtWT compared with gilts and parity 6 sow contemporaries. Parities 2 and 3 sows weaned more (P<0.05) piglets than older sows. These piglets had heavier (P<0.05) birth weights than those from gilt litters. LtV and PWM were greater (P<0.01) in litters born to parity 5 sows than those born to younger sows. Sow live-weight and back-fat depth at service, days 25 and 50 of gestation were not associated with TB, BA, BtWT, LtV, PWG, WnWT or lactation efficiency (P>0.05). Heavier sow live-weight throughout gestation was associated with an increase in PWM (P<0.01) and reduced Wn and lactation feed intake (P<0.05). Deeper back-fat in late gestation was associated with fewer (P<0.05) BA but heavier (P<0.05) BtWT, whereas deeper back-fat depth throughout gestation was associated with reduced (P<0.01) lactation feed intake. Sow back-fat depth was not associated with LtV, PWG, TLG, WSI or piglets born alive in subsequent farrowing (P>0.05). In conclusion, this study showed that sow parity, live-weight and back-fat depth can be used as indicators of reproductive performance. In addition, this study also provides validation for future development of a benchmarking tool to monitor and improve the productivity of modern sow herd.
Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 test-day records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31±0.05 (5 DIM) to 0.67±0.04 (181 DIM) for Ca, from 0.18±0.03 (60 DIM) to 0.24±0.05 (305 DIM) for K, from 0.08±0.03 (15 DIM) to 0.37±0.03 (223 DIM) for Mg, from 0.16±0.03 (30 DIM) to 0.37±0.04 (305 DIM) for Na and from 0.21±0.04 (12 DIM) to 0.57±0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38±0.21 (5 DIM) to 0.79±0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.
Most theories of government growth place nearly exclusive attention on real changes in public sector activity. Yet, much nominal post–WWII government spending growth was not in the form of the public sector doing more relative to the general economy (real growth), but in the form of government activities becoming relatively more expensive (cost growth). Baumol's (1967) “cost disease” model is our best guide to understanding cost growth, but over time, Baumol has offered conflicting hypotheses about how cost growth bears on real growth. Using 1947–2012 U.S. data, we test these hypotheses, along with a more novel expectation, by modifying Berry and Lowery's (1987b) econometric models of real growth in public purchases and transfers to consider the influence of government cost growth on real public domestic spending.
Inflammation of the mammary gland following bacterial infection, commonly known as mastitis, affects all mammalian species. Although the aetiology and epidemiology of mastitis in the dairy cow are well described, the genetic factors mediating resistance to mammary gland infection are not well known, due in part to the difficulty in obtaining robust phenotypic information from sufficiently large numbers of individuals. To address this problem, an experimental mammary gland infection experiment was undertaken, using a Friesian-Jersey cross breed F2 herd. A total of 604 animals received an intramammary infusion of Streptococcus uberis in one gland, and the clinical response over 13 milkings was used for linkage mapping and genome-wide association analysis. A quantitative trait locus (QTL) was detected on bovine chromosome 11 for clinical mastitis status using micro-satellite and Affymetrix 10 K SNP markers, and then exome and genome sequence data used from the six F1 sires of the experimental animals to examine this region in more detail. A total of 485 sequence variants were typed in the QTL interval, and association mapping using these and an additional 37 986 genome-wide markers from the Illumina SNP50 bovine SNP panel revealed association with markers encompassing the interleukin-1 gene cluster locus. This study highlights a region on bovine chromosome 11, consistent with earlier studies, as conferring resistance to experimentally induced mammary gland infection, and newly prioritises the IL1 gene cluster for further analysis in genetic resistance to mastitis.
Early detection of karyotype abnormalities, including aneuploidy, could aid producers in identifying animals which, for example, would not be suitable candidate parents. Genome-wide genetic marker data in the form of single nucleotide polymorphisms (SNPs) are now being routinely generated on animals. The objective of the present study was to describe the statistics that could be generated from the allele intensity values from such SNP data to diagnose karyotype abnormalities; of particular interest was whether detection of aneuploidy was possible with both commonly used genotyping platforms in agricultural species, namely the Applied BiosystemsTM AxiomTM and the Illumina platform. The hypothesis was tested using a case study of a set of dizygotic X-chromosome monosomy 53,X sheep twins. Genome-wide SNP data were available from the Illumina platform (11 082 autosomal and 191 X-chromosome SNPs) on 1848 male and 8954 female sheep and available from the AxiomTM platform (11 128 autosomal and 68 X-chromosome SNPs) on 383 female sheep. Genotype allele intensity values, either as their original raw values or transformed to logarithm intensity ratio (LRR), were used to accurately diagnose two dizygotic (i.e. fraternal) twin 53,X sheep, both of which received their single X chromosome from their sire. This is the first reported case of 53,X dizygotic twins in any species. Relative to the X-chromosome SNP genotype mean allele intensity values of normal females, the mean allele intensity value of SNP genotypes on the X chromosome of the two females monosomic for the X chromosome was 7.45 to 12.4 standard deviations less, and were easily detectable using either the AxiomTM or Illumina genotype platform; the next lowest mean allele intensity value of a female was 4.71 or 3.3 standard deviations less than the population mean depending on the platform used. Both 53,X females could also be detected based on the genotype LRR although this was more easily detectable when comparing the mean LRR of the X chromosome of each female to the mean LRR of their respective autosomes. On autopsy, the ovaries of the two sheep were small for their age and evidence of prior ovulation was not appreciated. In both sheep, the density of primordial follicles in the ovarian cortex was lower than normally found in ovine ovaries and primary follicle development was not observed. Mammary gland development was very limited. Results substantiate previous studies in other species that aneuploidy can be readily detected using SNP genotype allele intensity values generally already available, and the approach proposed in the present study was agnostic to genotype platform.
The overall objective of a series of experiments to investigate ‘metabolic stress’ was to examine the relationships between ‘metabolic load’, disease and other parameters associated with the welfare of the dairy cow. In the main, these used several well controlled herd based studies complimented with more basic and strategic investigations. In this paper we compare and contrast practical aspects of health and welfare in two high genetic merit herds managed at the extremes of inputs and outputs for dairy farming in south-west Scotland. The hypothesis was that high output herds would have more health and welfare problems than low input herds. Two herds (70 Holstein-Friesian cows each) at SAC Acrehead Dumfries of a similar genetic background (overall in the top 5% of UK cows by PIN and ITEM), were housed in identical buildings and tended by the same herdsman. Both herds had autumn- and spring-calving cattle. The ‘low input’ herd (LI) was given a minimum of concentrate (approx. 0.5 t per cow per year) and milked twice a day and had a restricted quota of 385 000 l. The ‘high output’ herd (HO) was managed for high yields (unrestricted quota) and was given concentrates (2 t per cow per year) and forage ad libitum and milked three times daily. In 1995-96 the sole source of winter forage was grass/clover silage (LI) or grass silage (HO) but in 1996-1998 ensiled cereal and fodder beet were included in both diets. ‘Metabolic load’ could only be inferred from overall inputs, milk outputs, weight loss, body condition score and behaviour. There were significant differences in 305-day lactation yields between herds, and season of calving especially in 1995-96 (LI autumn; 5952 l at 30 g/kg protein (P); LI spring; 5741 l, 32.5 g/kg P; HO autumn; 9541 l at 32.8 g/kg P; HO spring; 8402 l, 32.6 g/kg P). LI weight and body condition-score losses were greatest in this year and behavioural studies showed substantial differences in feeding time (HO < LI, P < 0.05) and total lying time (LI < HO; P < 0.05). However these differences were much less marked in subsequent years. There was a significant difference in the prevalence and incidence of clinical lameness between herds (HO > LI; P < 0.05) and season (autumn > spring P < 0.05) but not for mastitis or metabolic disease. An in-depth study of subclinical claw horn lesion development in first calving heifers showed significant differences between herds in 1996-97 (LI > HO, P < 0.05) but none in 1995-96. There was a significant difference for season in both years (autumn > spring, P < 0.05). Analysis of blood biochemistry parameters of samples taken at approximately 1 month after calving showed some significant differences between LI and HO generally indicating a greater ‘metabolic load’ for LI. Although the full effects of ‘metabolic load’ on immune function and reproduction are dealt with elsewhere our preliminary data showed no significant differences between herds for the former but some significant differences for the latter, in particular there were differences in aspects of the progesterone profiles between herds and more importantly between seasons. However these latter differences were not clearly reflected in conception rates. It was concluded that the hypothesis was not fully sustained and that both systems had pitfalls in terms of welfare. The three major areas causing difficulties for both systems were the need first to ensure adequate intake of forage; secondly to limit the environmental challenge to the feet and udder and finally to marry these systems to the factors limiting reproduction, primarily calving season and ability of reproduction management.
The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.
Interest is accruing in indicator traits as predictors of fertility which: 1) can be more easily recorded; 2) can be measured early in life; and, 3) possess a co-heritability that is larger than the heritability of the fertility traits. Potentially interesting indicator traits include body condition score (BCS) and body weight (BW). The objective of this study was to estimate genetic (co) variances between BCS, BCS change, BW, BW change, and fertility traits in dairy cattle.
Veerkamp et al. (1998) make the case for including somatic cell count (SCC) in the index of total economic merit (ITEM, Veerkamp et al., 1995) used to rank dairy bulls and cows in the UK for breeding purposes. They go on to describe an empirical method to obtain a suitable economic value for SCC, reflecting the milk quality payment scheme. Since this work was carried out, the milk price has fallen while price penalties against SCC have risen. Bulk-tank SCC (BTSCC) has fallen in response. Some of this improvement may be due to culling cows with high cell counts. The objective of this work was therefore to establish an economic value for somatic cell counts which reflected the milk quality payment scheme and took into account culling strategy.
Attenuated positive symptom syndrome (APSS), characterized by ‘putatively prodromal’ attenuated psychotic-like pathology, indicates increased risk for psychosis. Poor premorbid social adjustment predicts severity of APSS symptoms and predicts subsequent psychosis in APSS-diagnosed individuals, suggesting application for improving detection of ‘true’ prodromal youth who will transition to psychosis. However, these predictive associations have not been tested in controls and therefore may be independent of the APSS diagnosis, negating utility for improving prediction in APSS-diagnosed individuals.
Association between premorbid social maladjustment and severity of positive, negative, disorganized, and general APSS symptoms was tested in 156 individuals diagnosed with APSS and 76 help-seeking (non-APSS) controls enrolled in the Enhancing the Prospective Prediction of Psychosis (PREDICT) study using prediction analysis.
Premorbid social maladjustment was associated with social anhedonia, reduced expression of emotion, restricted ideational richness, and deficits in occupational functioning, independent of the APSS diagnosis. Associations between social maladjustment and suspiciousness, unusual thought content, avolition, dysphoric mood, and impaired tolerance to normal stress were uniquely present in participants meeting APSS criteria. Social maladjustment was associated with odd behavior/appearance and diminished experience of emotions and self only in participants who did not meet APSS criteria.
Predictive associations between poor premorbid social adjustment and attenuated psychotic-like pathology were identified, a subset of which were indicative of high risk for psychosis. This study offers a method for improving risk identification while ruling out low-risk individuals.
Accurate genomic analyses are predicated on access to a large quantity of accurately genotyped and phenotyped animals. Because the cost of genotyping is often less than the cost of phenotyping, interest is increasing in generating genotypes for phenotyped animals. In some instances this may imply the requirement to genotype older animals with greater phenotypic information content. Biological material for these older informative animals may, however, no longer exist. The objective of the present study was to quantify the ability to impute 11 129 single nucleotide polymorphism (SNP) genotypes of non-genotyped animals (in this instance sires) from the genotypes of their progeny with or without including the genotypes of the progenys’ dams (i.e. mates of the sire to be imputed). The impact on the accuracy of genotype imputation by including more progeny (and their dams’) genotypes in the imputation reference population was also quantified. When genotypes of the dams were not available, genotypes of 41 sires with at least 15 genotyped progeny were used for the imputation; when genotypes of the dams were available, genotypes of 21 sires with at least 10 genotyped progeny were used for the imputation. Imputation was undertaken exploiting family and population level information. The mean and variability in the proportion of genotypes per individual that could not be imputed reduced as the number of progeny genotypes used per individual increased. Little improvement in the proportion of genotypes that could not be imputed was achieved once genotypes of seven progeny and their dams were used or genotypes of 11 progeny without their respective dam’s genotypes were used. Mean imputation accuracy per individual (depicted by both concordance rates and correlation between true and imputed) increased with increasing progeny group size. Moreover, the range in mean imputation accuracy per individual reduced as more progeny genotypes were used in the imputation. If the genotype of the mate of the sire was also used, high accuracy of imputation (mean genotype concordance rate per individual of 0.988), with little additional benefit thereafter, was achieved with seven genotyped progeny. In the absence of genotypes on the dam, similar imputation accuracy could not be achieved even using genotypes on up to 15 progeny. Results therefore suggest, at least for the SNP density used in the present study, that it is possible to accurately impute the genotypes of a non-genotyped parent from the genotypes of its progeny and there is a benefit of also including the genotype of the sire’s mate (i.e. dam of the progeny).
We propose a format for presenting experimental results that combines a graph’s strength in facilitating general-pattern recognition with a table’s strength in displaying numerical results. The format supplements a conventional bar graph with additional text labels and graphics but also can be based on a dot plot. The resulting enhanced bar graph conveys general patterns about treatment effects; displays point estimates and confidence intervals for all key quantities of interest relevant to testing hypotheses (e.g., first differences in the mean of the dependent variable); and clarifies the interpretation of these quantities as treatment effects. Presenting information in a single figure avoids the need to devote scarce journal space to both a graph and a table. Moreover, an enhanced bar graph prevents readers from having to move back and forth between a graph and a table of numerical results—thereby reducing their cognitive load and facilitating their understanding of the findings.
A range of precision farming technologies are used commercially for variable rate applications of nitrogen (N) for cereals, yet these usually adjust N rates from a pre-set value, rather than predicting economically optimal N requirements on an absolute basis. This paper reports chessboard experiments set up to examine variation in N requirements, and to develop and test systems for its prediction, and to assess its predictability. Results showed very substantial variability in fertiliser N requirements within fields, typically >150 kg ha−1, and large variation in optimal yields, typically >2 t ha−1. Despite this, calculated increases in yield and gross margin with N requirements perfectly matched across fields were surprisingly modest (compared to the uniform average rate). Implications are discussed, including the causes of the large remaining variation in grain yield, after N limitations were removed.
The surface waters of the Southern Ocean play a key role in the global climate and carbon cycles by promoting growth of some of the world’s largest phytoplankton blooms. Several studies have emphasized the importance of glacial and sediment inputs of Fe that fuel the primary production of the Fe-limited Southern Ocean. Although the fertile surface waters along the shelf of the western Antarctic Peninsula (WAP) are influenced by large inputs of freshwater, this freshwater may take multiple pathways (e.g. calving, streams, groundwater discharge) with different degrees of water-rock interactions leading to variable Fe flux to coastal waters. During the summers of 2012–13 and 2013–14, seawater samples were collected along the WAP, near Anvers Island, to observe water column dynamics in nearshore and offshore waters. Tracers (223,224Ra, 222Rn, 18O, 2H) were used to evaluate the source and transport of water and nutrients in coastal fjords and across the shelf. Coastal waters are compared across two field seasons, with increased freshwater observed during 2014. Horizontal mixing rates of water masses along the WAP ranged from 110–3600 m2 s-1. These mixing rates suggest a rapid transport mechanism for moving meltwater offshore.
As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal’s capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal’s ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.