Prediction of mortality and conception rates of beef breeding cattle in northern Australia

In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.

Factors associated with calf mortality in tropically adapted beef breeds managed in extensive Australian production systems

Data from 9296 calves born to 2078 dams over 9 years across five sites were used to investigate factors associated with calf mortality for tropically adapted breeds (Brahman and Tropical Composite) recorded in extensive production systems, using multivariate logistic regression. The average calf mortality pre-weaning was 9.5% of calves born, varying from 1.5% to 41% across all sites and years. In total, 67% of calves that died did so within a week of their birth, with cause of death most frequently recorded as unknown. The major factors significantly (P < 0.05) associated with mortality for potentially large numbers of calves included the specific production environment represented by site-year, low calf birthweight (more so than high birthweight) and horn status at branding. Almost all calf deaths post-branding (assessed from n = 8348 calves) occurred in calves that were dehorned, totalling 2.1% of dehorned calves and 15.9% of all calf deaths recorded. Breed effects on calf mortality were primarily the result of breed differences in calf birthweight and, to a lesser extent, large teat size of cows; however, differences in other breed characteristics could be important. Twin births and calves assisted at birth had a very high risk of mortality, but <1% of calves were twins and few calves were assisted at birth. Conversely, it could not be established how many calves would have benefitted from assistance at birth. Cow age group and outcome from the previous season were also associated with current calf mortality; maiden or young cows (<4 years old) had increased calf losses overall. More mature cows with a previous outcome of calf loss were also more likely to have another calf loss in the subsequent year, and this should be considered for culling decisions. Closer attention to the management of younger cows is warranted to improve calf survival.

A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

This is a retrospective study of 38 cases of infection by Babesia macropus, associated with a syndrome of anaemia and debility in hand-reared or free-ranging juvenile eastern grey kangaroos (Macropus giganteus) from coastal New South Wales and south-eastern Queensland between 1995 and 2013. Infection with B. macropus is recorded for the first time in agile wallabies (Macropus agilis) from far north Queensland. Animals in which B. macropus infection was considered to be the primary cause of morbidity had marked anaemia, lethargy and neurological signs, and often died. In these cases, parasitised erythrocytes were few or undetectable in peripheral blood samples but were sequestered in large numbers within small vessels of visceral organs, particularly in the kidney and brain, associated with distinctive clusters of extraerythrocytic organisms. Initial identification of this piroplasm in peripheral blood smears and in tissue impression smears and histological sections was confirmed using transmission electron microscopy and molecular analysis. Samples of kidney, brain or blood were tested using PCR and DNA sequencing of the 18S ribosomal RNA and heat shock protein 70 gene using primers specific for piroplasms. The piroplasm detected in these samples had 100 sequence identity in the 18S rRNA region with the recently described Babesia macropus in two eastern grey kangaroos from New South Wales and Queensland, and a high degree of similarity to an unnamed Babesia sp. recently detected in three woylies (Bettongia penicillata ogilbyi) in Western Australia.

Hazard Function Models to Estimate Mortality Rates Affecting Fish Populations with Application to the Sea Mullet (Mugil cephalus) Fishery on the Queensland Coast (Australia)

Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .

Maximum likelihood estimation of natural mortality and quantification of temperature effects on catchability of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia) using logbook data

It is common to model the dynamics of fisheries using natural and fishing mortality rates estimated independently using two separate analyses. Fishing mortality is routinely estimated from widely available logbook data, whereas natural mortality estimations have often required more specific, less frequently available, data. However, in the case of the fishery for brown tiger prawn (Penaeus esculentus) in Moreton Bay, both fishing and natural mortality rates have been estimated from logbook data. The present work extended the fishing mortality model to incorporate an eco-physiological response of tiger prawn to temperature, and allowed recruitment timing to vary from year to year. These ecological characteristics of the dynamics of this fishery were ignored in the separate model that estimated natural mortality. Therefore, we propose to estimate both natural and fishing mortality rates within a single model using a consistent set of hypotheses. This approach was applied to Moreton Bay brown tiger prawn data collected between 1990 and 2010. Natural mortality was estimated by maximum likelihood to be equal to 0.032 ± 0.002 week−1, approximately 30% lower than the fixed value used in previous models of this fishery (0.045 week−1).