Modeling oyster populations: IV. Rates of mortality, population crashes, and management
347-373 A time-dependent energy-flow model was used to examine how mortality affects oyster populations over the latitudinal gradient from Galveston Bay, Texas, to Chesapeake Bay, Virginia. Simulations using different mortality rates showed that mortality is required for market-site oysters to be a...
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fttexasamunigalv:oai:tamug-ir.tdl.org:1969.3/22869 2023-11-12T04:22:54+01:00 Modeling oyster populations: IV. Rates of mortality, population crashes, and management Powell EN Klinck JM Hofmann EE Ray SM U S National Marine Fisheries Service Fishery Bulletin 1994 http://hdl.handle.net/1969.3/22869 unknown 50299.00 http://hdl.handle.net/1969.3/22869 ADULT CHESAPEAKE BAY DISEASE AGENTS ENERGY-FLOW GALVESTON BAY JUVENILE NORTH ATLANTIC OCEAN SEASONALITY USA GULF OF MEXICO;Climatology: Environmental Sciences Conservation Development Marine Ecology: Ecology,Environmental Sciences Mathematical Biology: Computational Biology Metabolism Models and Simulations: Computational Biology Pathology Physiology Wildlife Manage;Pelecypoda [Pelecypoda];Pelecypoda: Animals,Invertebrates,Mollusks;[00512] General biology - Conservation and resource management;[04500] Mathematical biology and statistical methods;[07504] Ecology: environmental biology - Bioclimatology and biometeorology;[07512] Ecology: environmental biology - Oceanography;[07516] Ecology: environmental biology - Wildlife management: aquatic;[10515] Biophysics - Biocybernetics;[12502] Pathology - General;[12510] Pathology - Necrosis;[13003] Metabolism - Energy and respiratory metabolism;[25508] Development and Embryology - Morphogenesis;[61500] Pelecypoda;[61500] Pelecypoda,Mollusca,Invertebrata,Animalia;[64026] Invertebrata: comparative,experimental morphology,physiology and pathology - Mollusca Journal 1994 fttexasamunigalv 2023-10-30T16:17:26Z 347-373 A time-dependent energy-flow model was used to examine how mortality affects oyster populations over the latitudinal gradient from Galveston Bay, Texas, to Chesapeake Bay, Virginia. Simulations using different mortality rates showed that mortality is required for market-site oysters to be a component of the population's size-frequency distribution; otherwise a population of stunted individuals results. As mortality extends into the juvenile sizes, the population's size frequency shifts toward the larger sizes. In many cases adults increase despite a decrease in overall population abundance. Simulations, in which the timing of mortality varied, showed that oyster populations are more susceptible to population declines when mortality is restricted to the summer months. Much higher rates of winter mortality can be sustained. Comparison of simulations of Galveston Bay and Chesapeake Bay showed that oyster populations are more susceptible to intense population declines at higher latitudes. The association of population declines with disease agents causing summer mortality and the increased frequency of long-term declines at high latitudes result from the basic physiology of the oyster and its population dynamics cycle. Accordingly, management decisions on size limits, seasons and densities triggering early closure must differ across the latitudinal gradient and in populations experiencing different degrees of summer and winter mortality relative to their recruitment rate. More flexible size limits might be an important management tool. When fishing is the primary cause of mortality, populations should be managed more conservatively in the summer. The latitudinal gradient in resistance to mortality requires more conservative management at higher latitudes and different management philosophies from those used in the Gulf of Mexico http://gbic.tamug.edu/request.htm Journal/Newspaper North Atlantic Texas A&M University Galveston Campus: DSpace Repository |
institution |
Open Polar |
collection |
Texas A&M University Galveston Campus: DSpace Repository |
op_collection_id |
fttexasamunigalv |
language |
unknown |
topic |
ADULT CHESAPEAKE BAY DISEASE AGENTS ENERGY-FLOW GALVESTON BAY JUVENILE NORTH ATLANTIC OCEAN SEASONALITY USA GULF OF MEXICO;Climatology: Environmental Sciences Conservation Development Marine Ecology: Ecology,Environmental Sciences Mathematical Biology: Computational Biology Metabolism Models and Simulations: Computational Biology Pathology Physiology Wildlife Manage;Pelecypoda [Pelecypoda];Pelecypoda: Animals,Invertebrates,Mollusks;[00512] General biology - Conservation and resource management;[04500] Mathematical biology and statistical methods;[07504] Ecology: environmental biology - Bioclimatology and biometeorology;[07512] Ecology: environmental biology - Oceanography;[07516] Ecology: environmental biology - Wildlife management: aquatic;[10515] Biophysics - Biocybernetics;[12502] Pathology - General;[12510] Pathology - Necrosis;[13003] Metabolism - Energy and respiratory metabolism;[25508] Development and Embryology - Morphogenesis;[61500] Pelecypoda;[61500] Pelecypoda,Mollusca,Invertebrata,Animalia;[64026] Invertebrata: comparative,experimental morphology,physiology and pathology - Mollusca |
spellingShingle |
ADULT CHESAPEAKE BAY DISEASE AGENTS ENERGY-FLOW GALVESTON BAY JUVENILE NORTH ATLANTIC OCEAN SEASONALITY USA GULF OF MEXICO;Climatology: Environmental Sciences Conservation Development Marine Ecology: Ecology,Environmental Sciences Mathematical Biology: Computational Biology Metabolism Models and Simulations: Computational Biology Pathology Physiology Wildlife Manage;Pelecypoda [Pelecypoda];Pelecypoda: Animals,Invertebrates,Mollusks;[00512] General biology - Conservation and resource management;[04500] Mathematical biology and statistical methods;[07504] Ecology: environmental biology - Bioclimatology and biometeorology;[07512] Ecology: environmental biology - Oceanography;[07516] Ecology: environmental biology - Wildlife management: aquatic;[10515] Biophysics - Biocybernetics;[12502] Pathology - General;[12510] Pathology - Necrosis;[13003] Metabolism - Energy and respiratory metabolism;[25508] Development and Embryology - Morphogenesis;[61500] Pelecypoda;[61500] Pelecypoda,Mollusca,Invertebrata,Animalia;[64026] Invertebrata: comparative,experimental morphology,physiology and pathology - Mollusca Powell EN Klinck JM Hofmann EE Ray SM Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
topic_facet |
ADULT CHESAPEAKE BAY DISEASE AGENTS ENERGY-FLOW GALVESTON BAY JUVENILE NORTH ATLANTIC OCEAN SEASONALITY USA GULF OF MEXICO;Climatology: Environmental Sciences Conservation Development Marine Ecology: Ecology,Environmental Sciences Mathematical Biology: Computational Biology Metabolism Models and Simulations: Computational Biology Pathology Physiology Wildlife Manage;Pelecypoda [Pelecypoda];Pelecypoda: Animals,Invertebrates,Mollusks;[00512] General biology - Conservation and resource management;[04500] Mathematical biology and statistical methods;[07504] Ecology: environmental biology - Bioclimatology and biometeorology;[07512] Ecology: environmental biology - Oceanography;[07516] Ecology: environmental biology - Wildlife management: aquatic;[10515] Biophysics - Biocybernetics;[12502] Pathology - General;[12510] Pathology - Necrosis;[13003] Metabolism - Energy and respiratory metabolism;[25508] Development and Embryology - Morphogenesis;[61500] Pelecypoda;[61500] Pelecypoda,Mollusca,Invertebrata,Animalia;[64026] Invertebrata: comparative,experimental morphology,physiology and pathology - Mollusca |
description |
347-373 A time-dependent energy-flow model was used to examine how mortality affects oyster populations over the latitudinal gradient from Galveston Bay, Texas, to Chesapeake Bay, Virginia. Simulations using different mortality rates showed that mortality is required for market-site oysters to be a component of the population's size-frequency distribution; otherwise a population of stunted individuals results. As mortality extends into the juvenile sizes, the population's size frequency shifts toward the larger sizes. In many cases adults increase despite a decrease in overall population abundance. Simulations, in which the timing of mortality varied, showed that oyster populations are more susceptible to population declines when mortality is restricted to the summer months. Much higher rates of winter mortality can be sustained. Comparison of simulations of Galveston Bay and Chesapeake Bay showed that oyster populations are more susceptible to intense population declines at higher latitudes. The association of population declines with disease agents causing summer mortality and the increased frequency of long-term declines at high latitudes result from the basic physiology of the oyster and its population dynamics cycle. Accordingly, management decisions on size limits, seasons and densities triggering early closure must differ across the latitudinal gradient and in populations experiencing different degrees of summer and winter mortality relative to their recruitment rate. More flexible size limits might be an important management tool. When fishing is the primary cause of mortality, populations should be managed more conservatively in the summer. The latitudinal gradient in resistance to mortality requires more conservative management at higher latitudes and different management philosophies from those used in the Gulf of Mexico http://gbic.tamug.edu/request.htm |
author2 |
U S National Marine Fisheries Service Fishery Bulletin |
format |
Journal/Newspaper |
author |
Powell EN Klinck JM Hofmann EE Ray SM |
author_facet |
Powell EN Klinck JM Hofmann EE Ray SM |
author_sort |
Powell EN |
title |
Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
title_short |
Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
title_full |
Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
title_fullStr |
Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
title_full_unstemmed |
Modeling oyster populations: IV. Rates of mortality, population crashes, and management |
title_sort |
modeling oyster populations: iv. rates of mortality, population crashes, and management |
publishDate |
1994 |
url |
http://hdl.handle.net/1969.3/22869 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
50299.00 http://hdl.handle.net/1969.3/22869 |
_version_ |
1782337831899758592 |