Academic literature on the topic 'Wool Prices Australia'

Time of shearing affects many aspects of wool production and sheep health but no study has examined these factors concurrently in a spring-lambing, self-replacing Merino flock in southern Australia. A 5-year field experiment compared wool production in spring-lambing Merino ewes and their progeny shorn at different times and managed under commercial conditions in south-eastern Australia. Groups of 200 adult ewes were shorn in December, March or May, and their progeny were shorn in December or October, March or June, or May or July, respectively. There was no consistent association between time of shearing and the staple strength of wool (P = 0.73). December-shorn ewes produced significantly lighter and finer fleeces (average 19.1 μm, 3.0 kg clean weight) than did March-shorn ewes (19.4 μm, 3.1 kg). Fleeces from ewes shorn in May were of similar weight to those from March-shorn ewes (3.1 kg), but they were of significantly broader diameter (19.7 μm). In young sheep, desirable changes in some wool characteristics for each shearing group were offset by undesirable changes in others. On the basis of median historical (1991–2006) wool prices, shearing ewes in March and their progeny first in June produced the greatest total value of wool over a sheep’s lifetime ($161/head). The wool values per head for other shearing times were as follows: March (weaners)–March (ewes): $158; October–December: $157; December–December: $153; July–May: $151; and May–May: $148. Thus, December and March shearing were appropriate alternatives for maximising wool value produced from a self-replacing Merino flock in south-eastern Australia, whereas May was a less preferable shearing time because it always produced wool of lesser value.

In the absence of financial information on Australian mohair enterprises we aimed to determine the gross margins (per dry sheep equivalent, DSE) and their relationships with farm inputs, productivity and mohair quality in Australian mohair enterprises. Using established Victorian Farm and Sheep Monitor Project protocols we collected data for the financial years 2004–05, 2005–06 and 2006–07 from farmers in south-eastern Australia and made comparisons with data from wool enterprises of similar farm area. Over 3 years the financial returns from mohair exceeded that from wool in terms of $/DSE ($23.0 v. 11.3) and $/ha ($132 v. $116). This result was achieved despite the mohair enterprises grazing their goats far less intensively compared with the grazing intensity of sheep (5.9 v. 10.3–11.1 DSE/ha) and by using far less phosphate fertiliser than used in the wool enterprises (2.2 v. 4.6–6.1 kg P/ha). These differences were counterbalanced by higher prices for mohair compared with fine wool ($13.15/kg v. $8.35/kg clean fibre). Gross margin for the mohair enterprise did not increase as stocking rate increased. Income from mohair sales declined as the proportion of does in the flock increased. Increasing the proportion of does in the flock was associated with a decline in the average price of mohair ($16/kg greasy at 42% does to $8/kg greasy at 83% does in the flock). This decline was closely associated with the increasing proportion of the total amount of mohair coarser than 34.0 µm (either fine hair or hair) plus stained mohair. The variation in profitability between farms indicates significant scope for many mohair enterprises to increase profit. A focus on producing finer quality mohair will increase mohair profitability.

Achieving higher lamb weaning percentages by reducing lamb mortality can improve the profitability of sheep enterprises. In this paper we estimated the financial benefits from providing shelter to reduce the mortality of twin lambs in self-replacing Merino or dual-purpose Merino flock enterprises in south-west Victoria. A whole-farm bio-economic model (MIDAS) was initially used to estimate the increase in profit from reducing mortality of twin lambs and a second analysis included the costs of using perennial grass hedges to provide the shelter during lambing. The economic value of providing shelter was tested at three rates of twinning (10, 30 and 50%), three rates of mortality without shelter (70, 50 and 30%) and two levels of reduction in lamb mortality by providing shelter (25 and 50% reduction). A sensitivity analysis to wool and lamb prices, costs of establishing the grass hedges and stocking rates in the shelter area were also tested. Overall, more than 2500 scenarios were tested. Across the range of twinning rates and levels of twin mortality tested, at standard wool and meat prices, providing shelter to the dual-purpose Merino ewe flock was always profitable ($0.05 to 11.35/ewe) and the profits from providing shelter to the self-replacing Merino ewe flock were generally lower ($0.15 to $6.35/ewe). The impacts of changing wool and lamb prices depended on enterprise type, whereas the costs of establishment of the hedges or stocking rate of ewes in the hedge area during lambing had little impact on profitability. The main factor that determined the economic return from shelter was the reduction in mortality provided by the shelter but the proportion of twin-bearing ewes in the flock and the base rate of lamb mortality without shelter was also important. Overall, based on the assumptions used, we conclude that the profitability of many sheep enterprises lambing during frequent high chill weather conditions in temperate areas of south-eastern Australia could be improved by providing low cost shelter for twin-bearing Merino ewes lambing from July to September.

Low levels of plant-available micronutrients were an inherent feature of many agricultural soils in Australia, mostly due to the prevalence of highly weathered soil parent materials. The diagnosis and correction of the widespread deficiencies of micronutrients, especially copper (Cu), molybdenum (Mo) and zinc (Zn), were prerequisites for the development of productive, legume-based pastures in southern Australia. In subtropical and tropical regions, Mo deficiency commonly limited pasture-legume production. Soil treatments involving micronutrient fertiliser incorporated in soils, or applied as additives to superphosphate, were generally effective in alleviating micronutrient deficiencies. In the low-output dryland pasture systems, the annual removal of micronutrients in wool and meat is small compared with rates added in fertiliser. Hence, in general, the residues of soil-applied micronutrient fertilisers remain effective for many years, for example, up to 30 years for Cu. By contrast, shorter residual values occur for manganese (Mn) fertiliser on highly calcareous soils, and for Zn in high-output pasture systems such as intensive dairy production. In the last two decades since the recommendations for micronutrient management of pastures were developed, there have been many changes to farming systems, with likely implications for micronutrient status in pastures. First, increased cropping intensity and low prices for wool and meat have meant lower nutrient inputs to pastures or to the pasture phase of rotations with crops. However, when pastures have been rotated with crops, ongoing small additions of Cu, Zn and Mo have been common. In cropping phases of farming systems, lime application and no-till may have altered the chemical and positional availability of micronutrients in soils to pastures. However, there has been little study of the impacts of these farming-systems changes on micronutrient status of pastures or profitability of the production system. The intensification of dairy production systems may also have altered the demand for, and removal rates of, micronutrients. Soil tests are not very reliable for Mn or Mo deficiencies, and well-calibrated soil tests for boron, Cu and Zn have been developed only for limited areas of pasture production and for a limited range of species. There is limited use of plant tests for nutrient management of pastures. In conclusion, there is limited knowledge of the current micronutrient status of pastures and their effects on animal health. Pasture production would benefit from targeted investigation of micronutrients status of pasture soils, pasture plants and micronutrient-linked animal-health issues.

The productivity of spring-lambing fine wool Merino sheep grazing pastures sown in 1977 to perennial ryegrass and subterranean clover was assessed from 1989 to 1998. The pastures were fertilised each autumn with single superphosphate at 6 levels, and were stocked at a low, medium, or high stocking rate (SR) at each level of fertiliser. The average phosphorus (P) applied annually since sowing (P ) ranged from 1.6 to 32.9 kg/ha. The SRs used varied with fertiliser level in that they were higher where more fertiliser had been applied, so that the highest SR at each level of fertiliser ensured that the pastures were well utilised. Each ewe raised 1 lamb, which was removed at weaning. The influence of fertiliser on the productivity of the sheep at 4 classes (1–4) of SR (mean SR = 7.1, 10.1, 12.6, and 18.2 ewes/ha for classes 1–4, respectively) was described by: y = A−BCP, where y represents production per sheep (kg), and A, B, and C are constants. For greasy fleece weight, estimates of B and C were 1.59 and 0.84; and for SR classes 1–4, the estimates of A were 5.06, 4.89, 4.78, and 4.46, respectively. For weaning weight of lambs, estimates of B and C were 8.4 and 0.82, and estimates of A were 23.5, 22.7, 21.5, and 20.9 for SR classes 1–4. The mean fibre diameter (µm) of the wool was described by: D = 14.18+1.48 GW, where GW is the mean greasy wool produced annually per sheep (kg) averaged over all sheep and years for each of the 18 treatments. The price (cents/kg) of wool with a fibre diameter D (P D) was given by: P D = 12197+4.94P2 + 688D−0.1945P20D − 5810√D, where 20 µm wool is P20 cents/kg. Supplements were fed if the body condition of ewes fell to a predetermined level. The supplement fed per ewe each year (S), expressed as metabolisable energy (in MJ) was described by: S = −602 − 44.1S R + 178.5P + 8.71S R P +539 √SR− 338.5√P−70.8P√SR, where S R and P represent the mean stocking rate (ewes/ha) and mean P applied annually. When a current set of costs and prices was applied to these equations, the maximum gross margin for a SR of 7.1 ewes/ha was $AU119/ha with 8.6 kg P/ha applied annually, and $AU262/ha for SR of 18.2 ewes/ha with 17.6 kg P/ha applied annually. If income derived from sheep is maintained constant, intensifying the sheep enterprise from the low to the high SR system would involve increasing sheep numbers by about 17%, but would release about 55% of the farm’s area for another purpose.

Merino wethers aged 1.5 years grazed a saltland pasture comprising old man saltbush (Atriplex nummularia) with an inter-row of senesced grasses and medic for 6 weeks in autumn, in a cereal–livestock zone with a Mediterranean-type environment in South Australia. The experimental treatments were a control (old man saltbush, SB), supplementation with 250 g/sheep.day barley straw (SB + S), supplementation with 250 g/sheep.day barley grain (SB + G) and supplementation with 250 g/sheep.day barley straw + 250 g/sheep.day barley grain (SB + S + G). The sheep in SB + G finished the experimental period significantly heavier (53.6 kg, P < 0.001) than SB (51.0 kg), SB + S (50.5 kg) or SB + S + G (51.1 kg) animals. Feeding grain also increased length of wool grown daily by 16% and would have increased the value of the sheep by being able to sell them ‘out of season’ when prices are higher. Sheep supplemented with grain alone had a higher liveweight than those provided with grain and straw, a result that cannot be explained but may be associated with altered grazing behaviour. It appears that, while old man saltbush provides sheep with an acceptable intake of protein and minerals, the addition of a cereal grain supplement improves energy balance and optimises rumen protein capture to improve liveweight and wool growth performance.

Current use of reproductive technology in the Australian livestock industries is limited, though it increased in line with higher prices for beef and wool through the 1980s. The required techniques, many of which were developed in Australia, are available and the level of expertise is comparable to the best in the world. However, the extensive pastoral industries do not readily lend themselves to these procedures. Only in the dairy industry is artificial insemination used to a significant degree. On the other hand, application of the technology in the pastoral industries is confined largely to studs and breeding cooperatives which provide breeding animals for producer flocks and herds. Hence the impact of applied technology may be more widespread than first appears. Until recently, little regard was paid to application of the technology along sound breeding principles. Artificial insemination and multiple ovulation and embryo transfer (MOET) have not been used so much in planned breeding programmes aimed at local improvement of stock, but more to proliferate genes of reputedly superior stock, imported either from overseas or elsewhere in Australia. This is particularly true of MOET, where the incentive to use it is commonly a short term cash gain made from proliferating breeding stock of a particularly valuable and usually novel strain or breed. Recent technological improvements which render the use of reproductive technology cheaper and more effective will lead to its more widespread use in commercial practice. Techniques for embryo freezing and splitting have been greatly simplified and quickly put into practice. The novel livestock technologies of in vitro oocyte maturation and fertilization have already found commercial application overseas. Fecundity-enhancing products have also been adopted by the livestock industries. There is potential value for greater use of reproductive technology in the livestock industries provided it is implemented according to sound breeding principles and provided associated management practices are applied simultaneously.

Two experiments on weaner production are reported. In experiment 1, the liveweight and wool production were measured in medium Peppin Merino sheep that grazed at 10.5 weanerstha 8 plots of a mixed Phalaris aquatica-subterranean clover pasture or 8 plots of annual pasture (Trifolium subterraneum cv. Woogenellup and volunteer annual grass species). This was repeated over 2 years using autumn-born sheep; 4 groups on each pasture type were offered no supplement, 2 groups a cereal supplement (340 goats), and 2 groups of supplement isoenergetic with the cereal group but having a high protein meal replace some of the cereal (250 g oats and 60 g protein). The feed supplement was offered over the summer (January-April). The sheep on 2 of the unsupplemented plots and 1 of the 2 plots receiving either a cereal or cereal + protein supplement were offered access to a composite mineral block formulated to meet the mineral requirements of sheep with the exception of cobalt and selenium. There were 16 sheep on each plot within each group of 16 weaners, 4 were given an intraruminal cobalt 'bullet', 4 were given 5 mg of selenium orally, 4 given cobalt plus selenium and 4 were untreated controls. Experiment 2 was in year 3 with spring-born weaners on the same plots. The mineral block treatment was discarded on the plots receiving supplement and the effect of supplementary feeding at the beginning of March was compared with feeding in early January; barley was also compared with oats and protein. The stocking rate was raised to 13.5 sheep/ha. There were no statistically significant differences in sheep liveweight due to pasture type in either of the years of experiment 1 or experiment 2. Supplementation with cereals or protein-fortified cereals resulted in a significantly ( P < 0.05) increased liveweight at the end of March (5.6 kg in year 1,2.4 kg in year 2 of experiment 1, and 2.5 kg in experiment 2), and wool production (0.49 kg clean wool in year 1 and 0.3 1 kg in year 2 in experiment 1, and 0.49 in experiment 2). There was a significant liveweight response on the perennial plots to selenium + cobalt in year 1 of experiment 1. All cobalt-treated sheep were heavier ( P < 0.001) in year 2. Neither selenium nor cobalt significantly affected liveweight in experiment 2. The proportion of Phalaris aquatica on the perennial pasture diminished from 18% to less than 9% by the end of year 2 in experiment 1. These results suggest that, if perennial pastures cannot be maintained, then their establishment in the south-west of Western Australia would not result in greater animal production than on annual pasture. Decisions on using supplements would be dependent upon feed and wool prices.

The impact of fluctuating wool prices on setting economic values (EVs) in selection indices, e.g. WOOLPLAN, are studied by modelling genetic change in a flock following index selection, Operating under different wool price regimes. Because future price changes are difficult to predict, there is no guaranteed, optimal method of determining EVs. One possibility is the use of a moving regression of the last five years' wool prices (in real terms), rather than setting the index once, or every five years, or every year, based on current prices. The ratio (R) of clean wool price to micron premium is more important than actual prices. It is suggested that the default EVs used currently in WOOLPLAN are appropriate for strong wool Merino flocks. The choice and implications of EVs in other situations are discussed.

Profitability of sheep production systems in southern Australia is optimised at a stocking rate that provides adequate nutrition for breeding ewes and enables efficient utilisation of grown pasture and supplements. In this paper we used bio-economic modelling to develop optimum liveweight1 profiles for spring-lambing Merino ewes in different environments. The modelling included the impacts of the ewe liveweight profile on the production of the ewe and the survival and lifetime wool production of her progeny. Fifteen ewe liveweight profiles were analysed for each region to determine the profitability of varying ewe liveweight at joining, varying rate of loss of liveweight after joining and the rate of gain in liveweight from the minimum to lambing. The analyses support the hypotheses that whole-farm profitability is sensitive to the liveweight profile of Merino ewe flocks and that there is a liveweight profile that maximises whole-farm profit. The variation between the most and least profitable ewe liveweight profile was $69 0002 per farm ($14.30/ewe) for south-west Victoria, $51 000 per farm ($8.70/ewe) for Great Southern Western Australia and $33 300 per farm ($9.70/ewe) for southern New South Wales. The changes in profit were due to differences in costs of feeding to achieve the ewe liveweight profile and its influence on the production of both the ewes and their progeny. Failure to include the impacts of liveweight profile on progeny survival and lifetime wool production incorrectly identifies the optimum ewe liveweight profile and provided inaccurate estimates of profitability. The optimum liveweight profiles for ewes lambing in spring were similar for all three regions and insensitive to changing commodity prices, pasture productivity and management. The optimum profile was to join ewes at ~90% of the standard reference weight of the genotype, lose a small amount of weight after joining and regain weight in late pregnancy to return to the joining weight by lambing. Regaining the liveweight lost in early pregnancy by lambing is the most important target to achieve. The cost per farm of missing this liveweight target by 1 kg was $13 000 ($2.60/ewe) for south-west Victoria, $8900 ($1.45/ewe) for Great Southern Western Australia and $5500 ($1.65/ewe) for southern New South Wales. By contrast, the cost per farm of missing the joining target by 1 kg was $5500 for south-west Victoria and less than $2000 across the other two regions. Whole-farm profit increased with increasing stocking rate up to an optimum and regardless of stocking rate there is an additional opportunity to increase whole-farm profit by up to 15% by managing ewes to achieve the optimum liveweight profile. This indicates that the optimum liveweight profile should be achieved by increasing the level of grain feeding and altering the timing of utilising the farm feed resources rather than manipulating stocking rate.

The largest wool exporter in the world is Australia, where wool being a major export is worth over AUD $2 billion per year and constitutes about 17 per cent of all agricultural exports. Most Australian wool is sold by auctions in three regional centres. The prices paid in these auction markets are used by the Australian production and service sectors to identify the quality preferences of the international retail markets and the intermediate processors. One ongoing problem faced by wool growers has been the lack of clear market signals on the relative importance of wool attributes with respect to the price they receive at auction. The goal of our research is to model the structure of Australian wool auction prices. We aim to optimise the information that can be extracted and used by the production and service sectors in producing and distributing the raw wool clip.Most of the previous methods of modelling and predicting wool auction prices employed by the industry have involved multiple-linear regressions. These methods have proven to be inadequate because they have too many assumptions and deficiencies. This has prompted alternative approaches such as neural networks and tree-based regression methods. In this thesis we discuss these alternative approaches. We observe that neural network methods offer good prediction accuracy of price but give minimal understanding of the price driving variables. On the other hand, tree-based regression methods offer good interpretability of the price driving characteristics but do not give good prediction accuracy of price. This motivates a hybrid approach that combines the best of the tree-based methods and neural networks, offering both prediction accuracy and interpretability.Additionally, there also exists a wool specifications problem. Industrial sorting of wool during harvest, and at the start of processing, assembles wool in bins according to the required wool specifications. At present this assembly is done by constraining the range of all specifications in each bin, and having either a very large number of bins, or a large variance of characteristics within each bin. Multiple-linear regression on price does not provide additional useful information that would streamline this process, nor does it assist in delineating the specifications of individual bins.In this thesis we will present a hybrid modular approach combining the interpretability of a regression tree with the prediction accuracy of neural networks. Our procedure was inspired by Breiman and Shang’s idea of a “representer tree” (also known as a “born again tree”) but with two main modifications: 1) we use a much more accurate Neural Network in place of a multiple tree method, and 2) we use our own modified smearing method which involves adding Gaussian noise. Our methodology has not previously been used for wool auction data and the accompanying price prediction problem. The numeric predictions from our method are highly competitive with other methods. Our method also provides an unprecedented level of clarity and interpretability of the price driving variables in the form of tree diagrams, and the tabular form of these trees developed in our research. These are extremely useful for wool growers and other casual observers who may not have a higher level understanding of modelling and mathematics. This method is also highly modular and can be continually extended and improved. We will detail this approach and illustrate it with real data.The more accurate modelling and analysis helps wool growers to better understand the market behaviour. If the important factors are identified, then effective strategies can be developed to maximise return to the growers.In Chapter 1 of this thesis, we present a brief overview of the Australian wool auction market. We then discuss the problems faced by the wool growers and their significance, which motivate our research.In Chapter 2, we define the predictive aspect of the modelling problem and present the data that is available to us for our research. We introduce the assumptions that must be made in order to model the auction data and predict the wool prices.Chapter 3 discusses neural networks and their potential in our wool auction problem. Neural networks are known to give good results in many modern applications resolving industrial problems. As a result of the popularity of such methods and the ongoing development of them, our research partner, the Department of Agriculture and Food, Government of Western Australia, performed a preliminary investigation into neural networks and found them to give satisfactory predictions of wool auction prices. In our Chapter 3, we perform an analysis and assessment of neural networks, specifically, the generalised regression neural networks (GRNN). We look at the strengths and weaknesses of GRNN, and apply them to the wool auction problem and comment on their relevance and usability in our wool problem. We detail the problems we face, and why neural networks alone may not be the best approach for the wool auction problem, thus laying the foundation for the development of our hybrid modular approach in Chapter 5. We also use the numerical prediction results from GRNN as the benchmark in our comparisons of different modelling methods in the rest of this thesis.Chapter 4 details the tree-based regression methods, as an alternate approach to neural networks. In analysing the tree-based methods with our wool auction data, we illustrate the tree methods’ advantages over neural networks, as well as the trade-offs, with our auction data. We also demonstrate how powerful and useful a tree diagram can be to the wool auction problem. And in this Chapter, we improve a typical tree diagram further by introducing our own tabular form of the tree, which can be of immerse use to wool growers. In particular, we can use our tabular form to solve the wool specification problem mentioned earlier, and we incorporate this tabular form as part of a new hybrid methodology in Chapter 5. In Chapter 4 we also consider the ensemble methods such as bootstrap aggregating (bagging) and random forests, and discuss their results. We demonstrate that, the ensemble methods provide higher prediction accuracies than ordinary regression trees by introducing many trees into the model. But this is at the expense of losing the simplicity and clarity of having only a single tree. However, the study of assemble methods do end up providing an excellent idea for our hybrid approach in Chapter 5.Chapter 5 details the new hybrid approach we developed as a result of our work in Chapters 3 and 4 using neural networks and tree-based regression methods. Our hybrid approach combines the two methods with their respective strengths. We apply our new approach to the data, compare the results with our earlier work in neural networks and tree-based regression methods, then discuss the results.Finally, we conclude our thesis with Chapter 6, discussing the potential of our new hybrid approach and the directions of possible future works.

The U.S. wool industry has long received lower prices for comparable wool types than those of Australia. In order to better understand such price differences, economic evaluations of both the U.S. and Australian wool markets were conducted. This research focused on two primary objectives. The first objective was to determine what price differences existed between the Australian and U.S. wool markets and measure that difference. The second objective was to calculate price differences attributable to wool characteristics, as well as those resulting from regional, seasonal, and yearly differences. In order to accomplish the objectives, the study was set up into three different hedonic pricing models: U.S., Australian, and combined. In the U.S. model, there were significant price differences in season, year, region, level of preparation, and wool description. In addition, average fiber diameter (AFD) had a negative nonlinear relationship with price and lot weight had a positive linear relationship with price. The Australian model was notably different than the U.S. model in that there were only three variables. The yearly variable follows the same general pattern as the U.S. data but with a smaller span of difference. The seasonal price differences were distinctly different than the U.S. because of the difference in seasonal patterns. In addition, the AFD had a similar negative nonlinear relationship with price. The final model combines both the U.S. data and the Australian data. The combined model had only three variables: season, year, AFD and country. As in the case of the previous two models, AFD had the same negative nonlinear relationship and similar price elasticity. Overall, there was a -30.5 percent discount for U.S. wool when compared to Australian wool. This can be attributed to several different factors. One of which is that the Australian wool industry has a more extensive marketing scheme when compared to the U.S wool market as a whole. However, this is only a beginning to future research that needs to be conducted. Continuing this study for future years, having more descriptive categories, and additional countries would further add explanation to wool prices.

An Australian by birth, Florence Melian Stawell, who was educated as a classicist at both Trinity College (Melbourne) and Newnham College (Cambridge) was a civilian living in London during the Great War. She shared this experience with Virginia Woolf, Roger Fry, and many of their Bloomsbury friends. But unlike Woolf, whose life during the war has been the subject of some attention (my own Virginia Woolf and the Great War, for example), the home-front experience of Stawell and her literary output, including her anthology of poetry (The Price of Freedom) and her writings on a range of topics (patriotism, education, and the League of Nations among them), has been overlooked. This paper suggests that we may well find the Great War as a way into the life and work of this underappreciated woman, a contemporary of Virginia Woolf.

Chapter 4 turns to colonial New Zealand where questions about the relationship of type to place played out on an imperial scale. As the global price of wool plummeted in the 1860s, pastoralists in New Zealand reconfigured their predominantly merino flocks to serve a new refrigerated trade between Great Britain and her Australasian colonies. Where New Zealand breeders had predominantly focused on wool production, with the advent of refrigerated shipping in the early 1880s, they began to breed for meat as well as wool. Colonial producers throughout Australasia discovered that British diners preferred the meat of British breeds: merino mutton from the colonies did not find a ready market in London. To satisfy the contradictory demands of colonial climate and topography, which varied from Britain’s, and metropolitan demand, New Zealand breeders constructed novel colonial breeds, like the Corriedale, forged out of a cross between British longwool stock and merino sheep. They touted these types as “native” colonial breeds, thereby adding another layer of complexity to the concept, and making a rhetorical claim as settlers of a distant land only recently wrested from the indigenous Maori people.