King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

The King George Whiting Simulator (WhitSim) is a simulation version of the Whiting Estimator (WhitEst) encased inside a graphical user interface (GUI) that includes geographical information systems (GIS). WhitSim provides the ability to simulate various management strategies and parameter scenarios and interrogate results of the simulation via in-built statistical, curve fitting and indicator analysis modules.

King George whiting (Sillaginodes punctata) remains a prime target species of the marine scalefish fishery of South Australia. Levels of fishing mortality are high on inshore populations throughout the fishery which has caused concern about the level of egg production. This prompted the need for a comprehensive stock assessment for this fishery. However, complicating this task is the fact that the life-history incorporates an obligate migratory step where fish move from shallow, inshore areas where they are heavily targeted, to deeper, more exposed places where the spawning populations occur.

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

Abalone stocks exist as a large number of metapopulations or sub-stocks each with peculiar growth and mortality characteristics. Hence different populations respond differently to exploitation through fishing. The sustainability of this fishery is linked to effective management of these meta-populations. For this reason, abalone catch and effort data should be collected on as fine a spatial scale as possible.

South Australia's catch and effort data is collected on the finest spatial scale of any abalone fishery in Australia. However, to date, analysis of the fine scale components of the data has been superficial simply as a result of the lack of tools to rapidly summarize and present data visually. Spatial and temporal analyses of these data will assist in the assessment of how individual sub-stocks have responded to fishing.

Across South Australia there are 35 abalone fishers fishing 7 different Total Allowable Catches (TAC's) on two species across 196 reporting areas. While the complexity of the data has to date precluded comprehensive analysis it also offers the potential for powerful insights into the dynamics of the fishery after more than 10 years of quota management.

In all fisheries, levels of catch and catch rates are two indicators used to attempt to evaluate and assess the response of stocks to exploitation through fishing. Declines in catches or catch rates are often interpreted as indicators of recruitment or growth overfishing and similarly increases in catches and catch rates may be interpreted as providing evidence that stocks are being sustained in the face of fishing or may even be under-exploited. 

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.

This project was initiated in response to a rapid increase in the demand for pilchards and other baitfish species and the subsequent expansion of purse-seine fisheries throughout southeastern Australia. During the course of the proj ect, the need for research on pilchard stocks was further increased by the mass mortality of adult pilchards that occurred between Noosa Heads (Queensland) and Red Bluff (Western Australia) in autumn 1 995 and the decrease in the 1 997 Total Allowable Catch for the Western Australian pilchard fishery which lead to a shortage of pilchards on Australian markets.