11 results

Bursary to attend the 2022 Microplastics and Seafood: Human Health Symposium in the United Kingdom - Nina Wootton

Project number: 2022-055
Project Status:
Completed
Budget expenditure: $9,400.00
Principal Investigator: Nina Wootton
Organisation: University of Adelaide
Project start/end date: 30 Aug 2022 - 30 Jan 2023
Contact:
FRDC
TAGS
Symposium
Marine Plastics
Capacity Building

Need

[Produce a ‘Critical Review Paper’ to provide a potential roadmap for additional research, as well as help identify communication strategies for the seafood industry. This is a development and networking opportunity to create future relationships and collaborations]

This bursary will allow Nina Wootton to attend the microplastics and seafood symposium in Edinburgh, Scotland. The focus of the symposium will be human health aspects of microplastics in seafood. The aim is to produce a critical review paper to provide a potential roadmap for additional research, as well as help identify communication strategies for the seafood industry. This is part of an international partnership between FRDC, Seafish (UK) and Seafood Industry Research Fund (USA) that will have 11 scientific experts attending along with industry. The symposium provides Australians with a unique opportunity to engage with experts and industry from around the world.

We will also visit several UK based research groups as part of our travel - we have already engaged with researchers from Plymouth Marine Laboratories, University of Plymouth and Exeter University including Professor Richard Thompson, the first researcher to identify microplastics as an issue.

Objectives

1. Attend the 'Microplastics and Seafood
Human Health Symposium' in the United Kingdom
2. To produce a ‘Critical Review Paper’ addressing microplastics in seafood and impact on human health to provide a potential roadmap for additional research and identify communication strategies for the seafood industry

Bursary to attend the 2022 Microplastics and Seafood: Human Health Symposium in the United Kingdom - Bronwyn Gillanders

Project number: 2022-054
Project Status:
Completed
Budget expenditure: $8,885.00
Principal Investigator: Bronwyn M. Gillanders
Organisation: University of Adelaide
Project start/end date: 30 Aug 2022 - 29 Nov 2022
Contact:
FRDC
TAGS
Symposium
Marine Plastics
Capacity Building

Need

[Produce a ‘Critical Review Paper’ to provide a potential roadmap for additional research, as well as help identify communication strategies for the seafood industry. This is a development and networking opportunity to create future relationships and collaborations]

This bursary will allow Professor Gillanders to attend the microplastics and seafood symposium in Edinburgh, Scotland. The focus of the symposium will be human health aspects of microplastics in seafood. The aim is to produce a critical review paper to provide a potential roadmap for additional research, as well as help identify communication strategies for the seafood industry. This is part of an international partnership between FRDC, Seafish (UK) and Seafood Industry Research Fund (USA) that will have 11 scientific experts attending along with industry. The symposium provides Australians with a unique opportunity to engage with experts and industry from around the world.

We will also visit several UK based research groups as part of our travel - we have already engaged with researchers from Plymouth Marine Laboratories, University of Plymouth and Exeter University including Professor Richard Thompson, the first researcher to identify microplastics as an issue.

Objectives

1. Attend the 'Microplastics and Seafood
Human Health Symposium' in the United Kingdom
2. To produce a ‘Critical Review Paper’ addressing microplastics in seafood and impact on human health to provide a potential roadmap for additional research and identify communication strategies for the seafood industry
Industry

A global review on implications of plastic in seafood

Project number: 2021-117
Project Status:
Completed
Budget expenditure: $60,513.00
Principal Investigator: Bronwyn M. Gillanders
Organisation: University of Adelaide
Project start/end date: 31 May 2022 - 30 Jul 2023
Contact:
FRDC
TAGS
Pollution
Marine Plastics
Consumer Health
Animal Health

Need

The project will review and synthesise available global data on the potential effects and implications that plastic is causing in seafood species in the context of the impacts they generate to fishing and aquaculture sectors. Concurrently, using published literature on sources of marine pollution, the abundance of plastic entering aquatic systems from seafood related sources will be quantified, with particular focus to the Australian context. Ultimately, this will give the fisheries sector, particularly in an Australian setting, the knowledge to evaluate where appropriate mitigation strategies are necessary and reduce the presence and impacts of microplastics in seafood.

This project aligns with FRDC R&D Plan Outcome 1: Growth and Enduring prosperity; In particular, it targets the priorities of:
- Improving the understanding of the cause and extent of impacts to aquatic systems and what is needed to improve them
- Promote a circular economy to remove waste from the processing system, keep products and materials in use and promote the repair of natural systems

Providing information on how marine pollution may affect the seafood industry and seafood species fished will guide the urgency of future research and allow management and mitigation strategies that support the seafood sector to be developed. Ultimately, quantifying the amount of plastic contributed by the seafood sector to marine plastics will allow us to advance with solutions and uncover where plastic alternatives are most needed.

Objectives

1. Undertake a systematic review, collating, synthesising and analysing global data on the effects and implications of plastic pollution in seafood species and the seafood industry
2. Identify potential sources of plastic in marine environments, including the percentage coming through fishing and aquaculture
3. Highlight key knowledge gaps, opportunities and threats of plastic in the seafood sector
4. Disseminate findings and information on effects and implications of plastic pollution on seafood species to fishers and managers

Final report

Authors: Nina Wootton Patrick Reis-Santos and Bronwyn M Gillanders
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.
Final Report • 2023-09-27 • 3.65 MB
2021-117-DLD.pdf

Summary

Microplastics are commonly consumed by seafood species however, there is still limited understanding of the effects and implications that microplastics may have on the fishing and aquaculture industry. This project summarises research on the effects that microplastic may be having on seafood species and the contribution that the seafood industry is having to marine plastic pollution. Global literature on microplastic effects in seafood species revealed 1) that 93% of all species were negatively affected by plastics, although many studies used increased levels of microplastic contamination that are not environmentally relevant (i.e., generally do not reflect environmental conditions); and 2) 23% of plastic pollution in the marine and coastal environment originates from fishing and aquaculture sources. This
report provides clear-sighted recommendations on the threats and opportunities that plastics hold for the seafood sector, as well as avenues for potential mitigation and reduction.

Evaluation of a smart-phone application to collect recreational fishing catch estimates, including an assessment against an independent probability based survey, using South Australia as a case study

Project number: 2020-056
Project Status:
Current
Budget expenditure: $1,000,000.00
Principal Investigator: Crystal Beckmann
Organisation: University of Adelaide
Project start/end date: 4 Oct 2020 - 30 Sep 2023
Contact:
FRDC
TAGS
Sustainability
Survey
Recreational Fishing
Rac Sa
Modelling

Need

There is need to collect accurate and robust information on recreational fishing levels to inform fisheries management. Recreational fishing estimates are critical to ensure sustainable harvest of community owned fisheries resources. In South Australia, established Fishery Management Plans are in place and recreational catch must be monitored to ensure that the sector is operating within its allocated shares of the resource. Recent changes to the availability of traditional sampling frames and shifts in the way the people communicate mean that it is becoming increasingly cost-prohibitive to undertake surveys using the established methodology. There is a need to re-evaluate how recreational fishing catch and effort is assessed and to develop revised survey methodologies using the latest survey tools and techniques.

Smartphone applications may provide a cost-effective method to collect information on recreational catch. However, as most apps are self-selected, sampling is non-probability based and it is not possible to calculate confidence intervals or margins of error. There is a need to compare app-based data with traditional phone-diary surveys to compare estimates and evaluate the accuracy of the results measured relative to independent population benchmarks. The outputs from this project will provide valuable information to other jurisdictions who have existing apps or are looking to implement an app.- based survey

Objectives

1. To design and implement a survey of South Australian recreational fishers to determine participation and catch and effort levels for key species.
2. To evaluate the differences and in recreational catch estimates from smart-phone applications and traditional phone diary surveys.
3. To explore whether smart-phone applications can be feasibility integrated into future recreational fishing surveys.
4. To measure the accuracy of catch estimates from smart-phone applications relative to independent population benchmarks.
5. To outline the policy and regulatory needs and implications of implementing a smart phone based reporting app.

Final report

ISBN: 978-1-876007-57-7
Authors: C.L. Beckmann L.M. Durante K. Stark and S. Tracey
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Final Report • 2024-08-01 • 14.49 MB
2020-056-DLD.pdf

Summary

Information on recreational catch and effort is becoming increasingly important to inform fishery stock assessment and the sustainable management of fisheries resources. As smartphone applications ('apps') become more sophisticated and widely available, they are increasingly being used to record recreational fishing activity, presenting an opportunity to collect non-probability data. However, the self-selected nature of data collection through apps introduces potential biases, necessitating comparative studies with traditional probability-based surveys to assess these biases as well as the accuracy and precision of app-based data. This study aims to compare a traditional probability-based survey with app-based data collection to compare estimates, assess bias and utility, and provide guidance for the future development of app-based data collection methods. 
 
The lack of regularly collected data that can provide a precise estimate of catch and effort for a range of species caught by recreational fishing presents significant challenges for fishery stock assessment and management. Traditional probability-based methods, for example stratified phone surveys, are regarded as providing the most robust estimates of catch and effort for recreational fisheries. However, these surveys are often expensive, conducted infrequently, and may not provide the species-specific information at the spatial and temporal scales required to inform stock assessment and effective management. Smartphone apps offer a promising complementary option for data collection due to their ability to gather large volumes of information in real-time. However, challenges arise regarding representativeness of the data, low participation due to technological barriers, engagement issues, quality control, and privacy and security concerns. This study aims to explore the effectiveness and suitability of a smartphone application for collecting data on recreational catch and effort, offering an innovative approach while considering the associated advantages and disadvantages.

 

The review of existing technologies and knowledge assets highlighted some of the challenges faced by probability-based surveys due to changing communication practices and sampling limitations. Although smartphone apps are acknowledged for their potential to engage users and collect recreational fishing data, they have limitations such as participant non-response and possible unknown biases that may affect reported catch rates and data quality. It was acknowledged that recruiting participants without a license frame is challenging, requires substantial communication investment, and that private companies may be able to advance app technology for broader user appeal. While app-based data collection is likely to complement probability-based methods, successful implementation requires validation, bias control, user-friendly design, transparency, and measures to ensure adequate recruitment and retention. Key to this is addressing concerns around privacy, security, and representativeness to encourage app adoption, which has the potential to promote the collection of near real-time data to inform fisheries assessment and management.

 
The study's findings have several implications for fisheries managers, scientists, and policymakers:
- Firstly, the study highlights the potential for using a combination of app-based data and probability-based survey data to obtain reliable and comprehensive information about the recreational fishing community.
- Secondly, stakeholders should view app-based data collection as a complementary approach to probability-based surveys.
- Thirdly, there is a need to increase the number of participants in app-based data collection to improve the accuracy of results.
 
In conclusion, this study provides recommendations for further work to improve recreational fishing data collection methods. It emphasises the importance of ongoing collaboration between stakeholders and scientists to improve the tools and techniques used to collect data. By implementing these recommendations, stakeholders can strive for more accurate, representative, and reliable data, leading to better-informed decisions concerning the sustainable management of recreational fisheries resources.
Environment
Communities
Environment
PROJECT NUMBER • 2019-012
PROJECT STATUS:
COMPLETED

Postgraduate funding - Stock structure and connectivity of Black Bream including implications for management

The research in this report was undertaken as part of Koster Sarakinis’s PhD project at the University of Adelaide supervised by Professor Bronwyn Gillanders (University of Adelaide), Dr Patrick Reis Santos (University of Adelaide), Dr Qifeng Ye (SARDI Aquatic Sciences), and Dr Jason...
ORGANISATION:
University of Adelaide
TAGS
Training
Stock Assessment
Rac Sa
Fisheries Management
Estuarine
SPECIES
Black Bream
People
PROJECT NUMBER • 2018-055
PROJECT STATUS:
CURRENT

Developing a positive cultural attitude towards the capture and release of sharks and rays

This report summarises the outcomes of the Workshop on; prioritisation of species, identification of best-practice capture and handling, design of post-release survival studies, and development of effective communication campaigns, for developing positive behavioural change in recreational fishing...
ORGANISATION:
University of Adelaide
TAGS
Recreational Fishing
Rac Sa
Mortality
Behaviour
Audit
SPECIES
Rays
Communities
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