4 results
Communities
PROJECT NUMBER • 2017-131
PROJECT STATUS:
COMPLETED

Media messages about sustainable seafood: how do media influencers affect consumer attitudes?

We have conducted a comprehensive media survey of key media texts across all major genres and platforms for the past 3 years (2015-2018) to identify: the major reported issues affecting seafood sustainability; the role of celebrity chefs and media influencers in this media coverage; and the effects...
ORGANISATION:
University of Adelaide
TAGS
Sustainability
Media
Human Dimensions Research
Consumer
Community
Industry
PROJECT NUMBER • 2018-059
PROJECT STATUS:
COMPLETED

World Fisheries Congress 2020 - Sharing our Oceans and Rivers: a 2020 vision for the world’s fisheries

The World Fisheries Congress is the premier international fisheries congress, bringing together research, industry and management to discuss the latest advances in fisheries world-wide. The 8th World Fisheries Congress, hosted from Adelaide, Australia from 20 to 24 September 2021, was...
ORGANISATION:
University of Adelaide
TAGS
Wild Catch
Sustainability
Stakeholder
Responsible Fishing
Marketing
Environment

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.
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