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
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
Final report
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.
