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Abstracts
Workgroup: Oyster Fisheries Management and Restoration
Modeling the Effects of Climate Variability on the Prevalence and Intensity of Dermo and MSX Diseases in Eastern Oyster Populations
Principal Investigator(s):
Eileen E. Hofmann, Old Dominion University, hofmann@ccpo.odu.edu
Co-Investigator(s):
J.M. Klinck, Old Dominion University; S. Ford and E. Powell, Rutgers University; S. Jordan, Sarbanes Cooperative Oxford Laboratory; E. Burreson, Virginia Institute of Marine Science
Funding Period: 10/01/99-07/31/02
The specific research topics investigated as part of this study are: 1) the effect of climate variability on initiating and controlling epizootics of Dermo and MSX disease in oyster populations in Chesapeake and Delaware Bays; 2) the interaction of Dermo and MSX disease in Chesapeake and Delaware Bays oyster populations; 3) the factors (environmental and biological) that account for differences in prevalence and intensity in the two diseases over a latitudinal gradient within Chesapeake Bay and between Chesapeake and Delaware Bays; and 4) the value of nowcasts of oyster disease prevalence and intensity in Chesapeake Bay.
The first three objectives were addressed with a series of simulations that used output of the Hadley Center Climate Model to specify the predicted change in salinity that would be encountered in Chesapeake Bay for conditions of continued climate warming resulting from a doubling of CO2. Additional simulations considered the effect of variability in food supply and environmental conditions, such as periods of high food years followed by low food years or wet years followed by periods of dry years. The results of these simulations were compared to simulations that used mean conditions that were established using time series of temperature, salinity, chlorophyll and total suspended solids from the Chesapeake Bay EPA data set for the period 1987 to 1998 for several sites in Chesapeake Bay. The simulations were done using the Dermo and MSX disease models that are coupled to the oyster population dynamics model. The results of these simulations are now being prepared for publication.
The fourth objective was addressed with a model that was developed for the management of fished oyster populations in which disease mortality is a controlling influence. The model requires a quantitative estimate of abundance by size class, some knowledge about growth rates to establish the size range recruiting into the fisheries, and an estimate of the anticipated natural mortality rate. The model permits investigation of scenarios that include a range of allocations, timing of fishing seasons, variation in fishing efforts within seasons to establish a preferred harvest level, variation in the distribution of fishing among beds to minimize over-harvesting of disease-affected beds (area management), and rebuilding plans to increase total stock abundance after epizootic mortality or periods of over-harvesting. Another management-oriented model has been developed and calibrated using long-term oyster monitoring data from Maryland's Chesapeake Bay. Means and standard deviations of natural mortality (principally from diseases), fishing mortality and recruitment were derived from a 17-year time series (1985-2001). Population parameters can be adjusted to simulate the effects of management options on the long-term abundance of the market oyster stock.
The simulations show that conditions of doubled CO2, which results in increased precipitation in the Chesapeake Bay region and thus lower salinity, will produce a decrease in the prevalence and intensity of Dermo and MSX disease in oyster populations. Continued conditions of decreased salinity results from the high precipitation (e.g., more wet years) will further reduce prevalence and intensity of the two diseases. However, for reduced salinity conditions, there is a trade-off between reduced Dermo and MSX disease prevalence and intensity and reduced reproductive capacity of the oysters. Extensive periods of low salinity significantly reduce the reproductive output of the oysters and as a result recruitment to the population is reduced. However, additional simulations show that conditions of increased food can offset/overwhelm effects of either increased or decreased salinity on oyster reproduction. These results show clearly the need to characterize the food environment of the oyster populations in Chesapeake Bay. Another factor for further investigation is the effect of warming temperatures on Dermo and MSX disease and oyster reproduction.
The total oyster biomass changes calculated from the climate change simulations suggest that the northern Chesapeake Bay oyster populations may not be viable over the long term without external inputs of juveniles. The simulations using conditions characteristic of the Rappahannock and York Rivers show that oyster populations at these sites will either increase or have stable biomass over time for most of the climate change conditions tested with model. The implication of these simulations is that the southern Chesapeake Bay oyster populations may sustain the Bay-wide oyster fishery during periods of climate change that result in a decrease of Bay salinity. This is an important result for development of long-term management strategies for oyster populations.
Simulations with the fisheries model show that appropriate timing of the fishing season with respect to the timing of disease mortality can more than double the yearly allocation to the fishery. Besides disease, the other model parameter that most affects the simulation outcomes is the abundance of submarket-size oysters that can be expected to recruit to the fishery in the simulated year. Population stability is strongly determined by the number of recruits available to replace the deaths that decimate the market-size population each year. The model points to the critical need to understand population dynamics and survival of size classes below market size that are not often the targets of investigation. Simulations with the Maryland model also have highlighted the importance of recruitment and the need to develop an age-structured model that includes a growth component, as well as a better understanding of the stock-recruitment relationship. Baseline simulations indicate that the average rates of disease mortality, fishing mortality and recruitment that have been observed in Maryland since 1985 are not sustainable. The market oyster stock will continue an exponential decline unless mortality is reduced, recruitment increased, or both. Reducing fishing mortality from F=0.6 to F=0.4, or doubling of recent hatchery-based stock enhancement efforts could reverse the downward trend over the next decade.
We undertook a new modeling approach that is based on basic metabolic processes, as part of our continuing effort of development of models for shellfish populations. This consisted of development of a biochemically-based model for simulating the growth, development, and metamorphosis of larvae of the Pacific oyster, Crassostrea gigas. This model, which is the first of its type, defines larvae in terms of their gross biochemical composition: protein, neutral lipid, polar lipid, carbohydrate, and ash content. The model includes parameterizations for larval filtration, ingestion, and respiration, which determine growth rate, and processes controlling larval mortality and metamorphosis. The initial biochemical content of the larva is determined by the composition of the egg. Changes in the initial ratios of protein, carbohydrate, neutral lipid and polar lipid occur as the larva grows and in response to the biochemical composition of available food.
The larval growth model was developed for a single individual. Thus, we also developed an approach for extending the model results to an entire population through use of probability distributions that are applied to metabolic processes, such as respiration or assimilation. This approach allows genetic variability within a population to a factor in determining larval survival.
IMPACTS and/or BENEFITS:
The results of the simulation models from this effort show the importance of including climate change effects in development of long-term management strategies for oyster populations in Chesapeake Bay.
The biochemically-based model developed for C. gigas larvae provides a mechanistic structure for models of shellfish populations. This approach is already being incorporated into the development of models for other shellfish, such as the hard clam and the butter clam.
The fisheries management models provide quantitative tools for setting harvesting times, quotas and evaluating other management options for diseased oyster fisheries. These models are now being applied to oyster populations in Delaware and Chesapeake Bays.
The primary benefit of this research is the development and availability of models for oyster-disease interactions and a fisheries model for managing an oyster fishery that is impacted by disease. These models are potentially of use to managers. The fisheries model is now being used to guide management decisions for oyster populations in Chesapeake and Delaware Bays.
PROJECT PUBLICATIONS:
Bochenek, E.A., J.M. Klinck, E.N. Powell, E.E. Hofmann, A biochemically based model for the growth and development of Crassostrea gigas larvae, Journal of Shellfish Research, 20, 243-265, 2001.
Hofmann, E.E., S.E. Ford, E.N. Powell, J.M. Klinck, Modeling studies of the effect of climate change on MSX disease in eastern Oyster (Crassostrea virginica) populations, In: The Ecology and Etiology of Newly Emerging Marine Diseases, J.W. Porter, ed., Hydrobiologia, 460, 195-212, 2001.
Hofmann, E.E., J.M. Klinck, E.N. Powell, S.E. Ford, S. Jordan, E. Burreson, Modeling studies of climate variability and disease interactions in eastern oyster populations, manuscript in preparation.
Hofmann, E.E., E.N. Powell, E.A. Bochenek, J.M. Klinck, Critical conditions for larval success: influence of environmental food supply on survival of Crassostrea gigas larvae: a modeling study, Marine Ecology Progress Series, submitted.
Jordan, S.J., K.N. Greenhawk, C.B. McCollough, J. Vanisko, M.L. Homer, Oyster biomass and abundance in northern Chesapeake Bay: trends and forecasts, Journal of Shellfish Research, submitted.
Klinck, J.M., E.N. Powell, J.N. Kraeuter, S.E. Ford, K.A. Ashton-Alcox, A fisheries model for managing the oyster fishery during times of disease, Journal of Shellfish Research, 20, 977-989, 2001.
Powell, E.N., E.A. Bochenek, J.M. Klinck, E.E. Hofmann, Influence of food quality and quantity on the growth and development of Crassostrea gigas larvae: a modeling study, Aquaculture, 210, 89-117, 2002.
Powell, E.N., E.A. Bochenek, J.M. Klinck, E.E. Hofmann, Critical conditions for larval success: influence of short-term variations in food supply on survival of Crassostrea gigas larvae: a modeling study, Marine Ecology Progress Series, submitted.
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