Author Identifier

Brett Crisafulli: http://orcid.org/0000-0002-0027-9940

Date of Award

2025

Document Type

Thesis

Publisher

Edith Cowan University

Degree Name

Doctor of Philosophy

School

School of Science

First Supervisor

Johnny Lo

Second Supervisor

Eben Afrifa-Yamoah

Third Supervisor

Ute Mueller

Fourth Supervisor

Karina Ryan

Fifth Supervisor

David Fairclough

Abstract

Recreational fisheries often lack sufficient data for robust stock assessments, and post-release mortality (PRM) of discarded fish, particularly demersal species, poses a significant threat to sustainability. Because demersal fish often experience higher PRM (often due to barotrauma and stress), the substantial global interest in their recreational fisheries (e.g., Australia, Gulf of Mexico, Western Baltic Sea) raises conservation concerns. This study employs three distinct modelling approaches, applied to four reef-dwelling demersal species, to support effective recreational fisheries management by addressing data uncertainty, unintended consequences of management changes, and PRM effects. Specifically, this thesis (1) evaluates variability in average weights of recreationally-caught finfish, (2) assesses the impact of management changes on charter fisher release rates using time series analysis, and (3) applies a data-limited assessment approach incorporating PRM.

Accurate harvest estimates are crucial for stock assessments. This study examined the impact of length and weight data uncertainty from various sources (on-site surveys, charter logbooks, and voluntary donations) on average weight and harvest estimates for the four demersal species across different management zones. Generalized linear models (GLMs) yielded more precise average weights compared to traditional methods. The data source had a substantial impact on average weight and harvest estimates, with charter-boat logbooks and biological samples typically yielding higher harvest estimates. Estimating harvest at the management zone level, due to biological differences, provides greater precision and is more applicable to management.

Following a suite of management changes in 2009/10 aimed at recovering demersal scalefish stocks (including stricter bag and size limits), intervention time series analysis (ARIMA and ARIMAX models) was applied to an 18-year charter fishery dataset to assess its potential impact on release rates. The analysis revealed significant increases and trend shifts in release rates for all species and management zones. The Metropolitan zone exhibited the greatest impact of regulatory changes on release rates. Responses to the intervention varied across species and zones, ranging from short-term to sustained. Intervention time series modelling offers valuable support for evaluating policy impacts on management decisions, especially considering further management changes top this resource implemented in 2023/24.

Ignoring PRM in stock assessments can lead to biased stock status evaluations, incorrect management advice, and unsustainable harvest levels. This study quantified the impact of PRM in data-limited assessments. Simulations assessed the reliability of a length-based catch curve (LBCC) method for estimating fishing mortality and selectivity, and explored PRM’s influence on biomass estimates using length-based equilibrium analysis (LBEA). The LBCC method was applied to real datasets to estimate selectivity, and per-recruit models quantified PRM impacts. Findings demonstrated that PRM significantly affects stock status evaluations, particularly for species with high PRM rates, highlighting the critical need to incorporate PRM effects into data-limited assessments. These results emphasise the importance of considering data uncertainty, increased release rates, and PRM for sustainable recreational fisheries management globally, offering tools to inform management strategies and guide future research.

DOI

10.25958/6q1d-pd76

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