GROWTH PATTERNS OF RANGE BEEF CALVES OVER DISCRETE PREWEANING INTERVALS

1989 ◽  
Vol 69 (4) ◽  
pp. 865-869 ◽  
Author(s):  
K. M. HAVSTAD ◽  
M. J. McINERNEY ◽  
S. B. CHURCH
Keyword(s):  
Key Words ◽  
Growth Rates ◽  
Seasonal Variations ◽  
Growth Patterns ◽  
Seasonal Growth ◽  
Management Performance ◽  
Beef Calves ◽  
Maximum Interval

Suckling range beef calf production demonstrates periodicity despite consistency of management. Performance of calves within 33- to 50-d intervals from birth to weaning over nine seasons demonstrated maximum interval growth of approximately 1 kg d−1, but average seasonal growth rates varied from 0.79 to 0.99 kg d−1. Maximizing available forages for the final 33 d preweaning could minimize seasonal variations in calf production. Key words: Calf production, liveweight gain, rangelands

scholarly journals Long term pasture growth patterns for Southland New Zealand: 1978 to 2012

2012 ◽  
pp. 147-151
Author(s):  
L.C. Smith
Keyword(s):  
New Zealand ◽  
Key Words ◽  
Growth Rates ◽  
Initial Period ◽  
Farm Management ◽  
Growth Patterns ◽  
Annual Growth ◽  
Management Systems ◽  
Summer Peak

Pasture growth rates for Southland were reported by several researchers in the late 1970s and early 1980s. However, pasture species and farm management systems have changed somewhat since then. This paper presents data from measurements at Woodlands, near Invercargill, that have been ongoing since 1977, and discusses some of the variability that has occurred over the years. Measurement of pasture growth was done using a standardised cutting method known as "rate of growth" or moving cages, with measurements every 3 weeks. Annual yields were calculated from 1 June to 31 May of the next year. The pasture growth at Woodlands is characterised by a spring-summer peak of growth followed by a deep winter trough where growth is minimal. Long-term average annual growth was 11.8 t DM/ha for older 'Ruanui' based pasture and 12.7 t DM/ ha for newer 'Nui'/'Supreme'/'Greenstone' ryegrass based pasture. However the newer pasture produced considerably more (ca.14.2 t DM/ha/year) for an initial period of 3 years, after which time the production dropped back to be similar to the old pasture (ca.12.0 t DM/ha/year). Key words. pasture growth; long-term; annual variability

scholarly journals StalGrowth—A Program to Estimate Speleothem Growth Rates and Seasonal Growth Variations

Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 187
Author(s):  
Rolf Vieten ◽  
Francisco Hernandez
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Environmental Parameters ◽  
Ion Concentration ◽  
Radiometric Dating ◽  
Seasonal Growth ◽  
Climate Signal ◽  
Show Evidence ◽  
Cave Monitoring ◽  
Calcium Ion Concentration

Speleothems are one of the few archives which allow us to reconstruct the terrestrial paleoclimate and help us to understand the important climate dynamics in inhabited regions of our planet. Their time of growth can be precisely dated by radiometric techniques, but unfortunately seasonal radiometric dating resolution is so far not feasible. Numerous cave environmental monitoring studies show evidence for significant seasonal variations in parameters influencing carbonate deposition (calcium-ion concentration, cave air pCO2, drip rate and temperature). Variations in speleothem deposition rates need to be known in order to correctly decipher the climate signal stored in the speleothem archive. StalGrowth is the first software to quantify growth rates based on cave monitoring results, detect growth seasonality and estimate the seasonal growth bias. It quickly plots the predicted speleothem growth rate together with the influencing cave environmental parameters to identify which parameter(s) cause changes in speleothem growth rate, and it can also identify periods of no growth. This new program has been applied to multiannual cave monitoring studies in Austria, Gibraltar, Puerto Rico and Texas, and it has identified two cases of seasonal varying speleothem growth.

scholarly journals Erratum: Corrigendum: Dinosaurian growth patterns and rapid avian growth rates

Nature ◽  
2015 ◽  
Vol 531 (7595) ◽  
pp. 538-538
Author(s):  
Gregory M. Erickson ◽  
Kristina Curry Rogers ◽  
Scott A. Yerby
Keyword(s):  
Growth Rates ◽  
Growth Patterns

Spurious Persistence and Unit Roots due to Seasonal Differencing: The Case of Inflation Rates / Künstliche Persistenz und Einheitswurzeln infolge saisonaler Differenzen: Das Beispiel Inflationsraten

2005 ◽  
Vol 225 (4) ◽  
Author(s):  
Uwe Hassler ◽  
Matei Demetrescu
Keyword(s):  
Growth Rates ◽  
Unit Root ◽  
Unit Roots ◽  
Annual Growth ◽  
Seasonal Growth ◽  
Seasonal Differences ◽  
Inflation Rates ◽  
European Economies ◽  
Seasonal Data

SummaryStudying annual growth rates (seasonal differences) in case of seasonal data produces much more persistence, autocorrelation and stronger evidence in favour of a unit root than analyzing seasonal growth rates (ordinary differences). First, this statement is quantified theoretically. Second, it is supported experimentally with simulations, and, finally, it is empirically illustrated with quarterly GDP deflators from 7 European economies.

The lambing period of mountain sheep: synthesis, hypotheses, and tests

1982 ◽  
Vol 60 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Fred L. Bunnell
Keyword(s):  
Body Weight ◽  
Thermal Stress ◽  
Weight Gain ◽  
Female Body ◽  
Extreme Environments ◽  
Growth Patterns ◽  
Central Tendency ◽  
Seasonal Growth ◽  
Early Weight Gain ◽  
Definition Of

Data on lambing periods from 30 populations of North American mountain sheep are reviewed. Among all populations lambing begins later and duration is shorter at more northern altitudes (p < 0.00006). Correlations are enhanced (p < 0.00003) when latitude is replaced by a phenological index incorporating altitude. Termination of lambing is not correlated with latitude or with phenological index. Two broad patterns are evident. Populations feeding on vegetation of less predictable growth patterns ("desert type") have lengthy lambing seasons; populations feeding on vegetation exhibiting more predictable growth patterns ("alpine type") have shorter lambing seasons, typically two oestrous cycles in length. Definition of "types" by latitude or sheep taxonomy reveals significant differences in lambing periods, but correlations are enhanced when "types" are defined on the basis of habitat.Among taxa, birth weights are correlated with female body weight (rs = 0.87). Birth weights are heavier in extreme environments, seasonal growth patterns are expressed better in the alpine type, and early weight gain is most rapid in the northernmost subspecies. All populations show a strong central tendency with regard to peak lambing (17 May ± 6.8 days). Departures from that tendency respond more to predictability of vegetation than to thermal stress or predation pressure.

Age validation and seasonal growth patterns of a subtropical marsh fish: The Gulf Killifish, Fundulus grandis

2017 ◽  
Vol 100 (10) ◽  
pp. 1315-1327 ◽  
Author(s):  
Anthony R. Vastano ◽  
Kenneth W. Able ◽  
Olaf P. Jensen ◽  
Paola C. López-Duarte ◽  
Charles W. Martin ◽  
...  
Keyword(s):  
Growth Patterns ◽  
Seasonal Growth ◽  
Age Validation ◽  
Fundulus Grandis

Concentrations of glucose, albumin, inorganic phosphate and sodium in the blood of beef calves at 2 ½ months of age and their relationships with subsequent weight gain

1980 ◽  
Vol 94 (1) ◽  
pp. 95-104 ◽  
Author(s):  
G. J. Rowlands
Keyword(s):  
Growth Rate ◽  
Blood Glucose ◽  
Growth Rates ◽  
Inorganic Phosphate ◽  
The Body ◽  
The Other ◽  
Growth Depression ◽  
Blood Samples ◽  
Beef Calves ◽  
Body Weights

SummaryBlood samples were taken at 9, 10 and 11 weeks of age from 230 male Hereford × Friesian calves, the progeny of 12 Hereford bulls. Concentrations of blood glucose, serum albumin, inorganic phosphate and sodium were measured and correlated with body weights and growth rates until slaughter at 19½ months of age.Correlations between growth rates and glucose concentrations (0·44) and between growth rates and albumin concentrations (0·38) were observed until 4 months of age. Similar correlations between body weights and blood glucose or albumin concentrations persisted until 6 months of age. By 10 months, however, the correlations had begun to decline, and by slaughter they had become insignificant.Correlations between growth rates and inorganic phosphate or sodium concentrations were smaller, and also decreased with age.The effect of hypoglycaemia on growth rate was compared with the effect of enzootic pneumonia. Although the 10% of calves with the lowest glucose concentrations were growing 24% more slowly than the other calves at the time of sampling, this growth depression was not related to pneumonia, and they subsequently made up for most of the early loss of growth.Three blood samples were also taken from 22 Hereford bulls. No significant correlations were observed between the blood composition of the bulls and the body weights or weight gains of their progeny.

scholarly journals Growth and body weight of free-range reindeer in western Alaska

Rangifer ◽  
2000 ◽  
Vol 20 (2-3) ◽  
pp. 221 ◽  
Author(s):  
Greg L. Finstad ◽  
Alexander K. Prichard
Keyword(s):  
Body Weight ◽  
Growth Rates ◽  
Total Body Weight ◽  
Growth Patterns ◽  
Spatial And Temporal Variation ◽  
Adult Males ◽  
Body Weights ◽  
Total Body ◽  
Reproductive Females ◽  
Average Body

Total body weight of 9749 reindeer calves and 4798 adult reindeer were measured from 1984 to 1999 on the Seward Peninsula, western Alaska, USA. Growth rates of male and female calves, and annual growth patterns of adults were determined. Male calves grew faster than female calves. Reproductive females were lighter than non-reproductive females during summer but there was no effect of reproduction on average body weights the following winter. Adult males age 3-5 were heavier during summer than winter. Castrated males weighed the same as uncastrated males in summer, but were significantly heavier in winter, and did not display the large annual fluctuations in weight typical of reproductive males and females. Growth rates were higher and body weights greater in this herd than many other cir-cumpolar reindeer populations. We suggest these kinds of physiological indices should be used to monitor the possible effects of spatial and temporal variation in population density and to evaluate changes in herding practices.

scholarly journals Epidemic Growth Rates and Host Movement Patterns Shape Management Performance for Pathogen Spillover at The Wildlife-livestock Interface

2019 ◽  
Author(s):  
Kezia R. Manlove ◽  
Laura M. Sampson ◽  
Benny Borremans ◽  
E. Frances Cassirer ◽  
Ryan S. Miller ◽  
...  
Keyword(s):  
Growth Rates ◽  
Life Histories ◽  
Animal Health ◽  
Movement Patterns ◽  
Health Food ◽  
Management Options ◽  
Management Performance ◽  
Fast Growing ◽  
Management Actions ◽  
Host Movement

ABSTRACTManaging pathogen spillover at the wildlife-livestock interface is a key step toward improving global animal health, food security, and wildlife conservation. However, predicting the effectiveness of management actions across host-pathogen systems with different life histories is an on-going challenge since data on intervention effectiveness are expensive to collect and results are system-specific. We developed a simulation model to explore how the efficacies of different management strategies vary according to host movement patterns and epidemic growth rates. The model suggested that fast-growing, fast-moving epidemics like avian influenza were best-managed with actions like biosecurity or containment, which limited and localized overall spillover risk. For fast-growing, slower-moving diseases like foot-and-mouth disease, depopulation or prophylactic vaccination were competitive management options. Many actions performed competitively when epidemics grew slowly and host movements were limited, and how management efficacy related to epidemic growth rate or host movement propensity depended on what objective was used to evaluate management performance. This framework may be a useful step in advancing how we classify and prioritise responses to novel pathogen spillover threats, and evaluate current management actions for pathogens emerging at the wildlife-livestock interface.

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