Using an age-structured model to simulate the recovery of the Australian pilchard (Sardinops sagax) population following epidemic mass mortality

Murray, Alexander G.; Gaughan, D.J.

doi:10.1016/s0165-7836(02)00136-4

Cited by 13 publications

(14 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As noted earlier the value of maximizing short-term harvest and the final surviving population P 3 depends upon how long it takes for the population to recover, and hence for how long future harvests are reduced. Recruitment may occur relatively rapidly due to factors such as juvenile reserves or enhanced recruitment per individual adult (Murray and Gaughan [2003]) or increased individual growth (Tibbo and Graham [1963]) at low population densities. However, in other cases recovery of depleted populations may be slow (Hutchings [2000]).…”

Section: Resultsmentioning

confidence: 99%

Managing Harvesting to Minimize the Impact of Epidemics on Wild Fish Stocks

Murray

2004

Natural Resource Modeling

Self Cite

View full text Add to dashboard Cite

Epidemic diseases inflict substantial damage to stocks of harvested species. Epidemic waves can be predictable away from their origin. I use a classical epidemiology model to investigate the interaction of harvesting strategy with an epidemic. The effect of reducing populations by harvesting before the epidemic depends upon the nature of the epidemic's survivors. If these have recovered following infection, then pre-epidemic fishing optimizes the harvest, but reduces long-term survival. However, if these survivors avoided infection, then increased pre-epidemic fishing effort can increase post-epidemic populations; survival is maximized by reducing the pre-epidemic population to the threshold required to propagate infection. Post-epidemic harvesting provides poor returns and damages stocks. Optimal stock management strategy in the face of a predicted epidemic depends upon balancing harvesting and conservation of stocks complimentary or antagonistic goals, depending on the nature of the epidemic.

show abstract

Section: Resultsmentioning

confidence: 99%

Managing Harvesting to Minimize the Impact of Epidemics on Wild Fish Stocks

Murray

2004

Natural Resource Modeling

Self Cite

View full text Add to dashboard Cite

show abstract

“…In spite of the lack of sensitivity of wave speed to this parameter, it may have varied by orders of magnitude, and so could have changed wave velocity between epidemics. A major reduction in lesion frequency in (Murray & Gaughan 2003) and so differences in population sizes did not play a significant role in the differences between epidemics.…”

Section: Wave Velocities' Parameter Sensitivitymentioning

confidence: 87%

“…non-linear transmission (Murray et al 2000). A model of the population's post-epidemic recovery has also been developed (Murray & Gaughan 2003). In other words, we do not seek to design an all inclusive model, but rather our models are designed to be appropriate to our various tasks and the available data.…”

Section: The Modelmentioning

confidence: 99%

See 1 more Smart Citation

A model of spatially evolving herpesvirus epidemics causing mass mortality in Australian pilchard Sardinops sagax

Murray

O’Callaghan²,

Jones³

2003

Dis. Aquat. Org.

View full text Add to dashboard Cite

In 1995 mass mortality of pilchards Sardinops sagax occurred along > 5000 km of Australian coast; similar events occurred in 1998/99. This mortality was closely associated with a herpesvirus. The pilchard is an important food source for larger animals and supports commercial fisheries. Both epidemics originated in South Australian waters and spread as waves with velocities of 10 to 40 km d -1. Velocity was constant for a single wave, but varied between the epidemics and between the east-and west-bound waves in each epidemic. The pattern of mortality evolved from recurrent episodes to a single peak with distance from the origin. A 1-dimensional model of these epidemics has been developed. The host population is divided into susceptible, infected and latent, infected and infectious, and removed (recovered and dead) phases; the latent and infectious periods are of fixed duration. This model produces the mortality patterns observed locally and during the spread and evolution of the epidemic. It is consistent with evidence from pathology. The wave velocity is sensitive to diffusion coefficients, viral transmission rates and latent period. These parameters are constrained using the local and large-scale patterns of epidemic spread. The relative roles of these parameters in explaining differences between epidemics and between east-and west-bound waves within epidemics are discussed. The model predicts very high levels of infection, indicating that many surviving pilchards recovered following infection. Control appears impracticable once epidemics are initiated, but impact can be minimised by protecting juvenile stocks. KEY WORDS: Epidemic · Model · Herpesvirus · Mass mortality · Pilchard · Australia Resale or republication not permitted without written consent of the publisherDis Aquat Org 54: [1][2][3][4][5][6][7][8][9][10][11][12][13][14] 2003 this species. The mortality occurred as a locally shortlived outbreak, forming waves that travelled at very high and near-constant velocities. Mortality also occurred from June in New Zealand (Smith 1995). The outbreak was unprecedented in scale for an observed epidemic (Gaut 2001), although Californian sedimentary records imply collapses have occurred over the centuries (Baumgartner et al. 1992). The scale of mortality provided a generally clear picture of the spread of the epidemic.In November 1998 a second occurrence of such mass mortality events began (Gaughan et al. 2000). Mortality spread over the same area, again starting in South Australia, but at about half the velocity of 1995. Hence this epidemic lasted for over 6 mo, although again the duration at most localities was brief. On this occasion New Zealand was not affected. Mortality, however, was probably even greater than during the 1995 epidemic.No features of the physical environment (Griffin et al. 1997) or unusual or toxic algae were associated with the 1995 mass mortality events. There is also no evidence of any environmental linkage in 1998/99. The only common feature of the mortality events was he...

show abstract

“…In the case of a short‐lived epidemic, host populations do not have time to respond to losses; however, host population dynamics will still control the recovery of populations following mass mortality. This situation has been modelled for an epidemic in the marine environment (an outbreak of pilchard herpes virus that caused mass mortality of marine Australian pilchards ( Sardinops sagax , Jenyns 1842) (Murray & Gaughan, 2003)), but there are no equivalent studies for freshwater ecosystems.…”

Section: Population Modelsmentioning

confidence: 99%

The application of risk and disease modelling to emerging freshwater diseases in wild aquatic animals

et al. 2011

Self Cite

View full text Add to dashboard Cite

Summary 1. Emerging diseases pose significant ecological and economic threats in fresh waters. Both risk assessment and mathematical modelling have potential to improve our understanding of the uncertainties associated with emerging disease events and make informed predictions about their likely impact. 2. We review the different methodologies that may be used to estimate the likely geographic spread and potential impact of new and emerging diseases in fresh waters. We also highlight the limitations of the currently available methods and requirements for future development. 3. In the realm of aquatic animal health, risk assessment has been used mainly to examine the risks of disease spread through international trade import risk analysis (IRA). Import risk analysis of newly emerged diseases underpins the development of appropriate risk mitigation measures to minimise further spread. This is best illustrated by assessments of the spread of Gyrodactylus salaris and also illustrates how risk assessment can examine disease interaction between wild and farmed fish. 4. Various approaches have been employed to study disease transmission within freshwater fish populations at a range of spatial scales. There is scope for the application of these techniques to predict the impact of economically and environmentally important emerging freshwater diseases that arise from new pathogens, known diseases spreading to new locations or changes in pathogenicity owing to changing environmental conditions (e.g. because of climate change). 5. Population models are widely used in freshwater fishery management. The integration of disease processes within freshwater aquatic animal population models is required to provide tools to assess the likely impact of newly emerged diseases and allow mitigation measures to be assessed. 6. Compared with their use in other areas of animal health, modelling has been relatively little used for aquatic animal disease studies. The wide range of modelling methods used to study disease in human and terrestrial animals can usefully be applied to inform the development of policies to protect the health of wild stocks from emerging diseases.

show abstract

Using an age-structured model to simulate the recovery of the Australian pilchard (Sardinops sagax) population following epidemic mass mortality

Cited by 13 publications

References 23 publications

Managing Harvesting to Minimize the Impact of Epidemics on Wild Fish Stocks

Managing Harvesting to Minimize the Impact of Epidemics on Wild Fish Stocks

A model of spatially evolving herpesvirus epidemics causing mass mortality in Australian pilchard Sardinops sagax

The application of risk and disease modelling to emerging freshwater diseases in wild aquatic animals

Contact Info

Product

Resources

About