Effects of fishing on tropical reef associated shark populations on the Great Barrier Reef

Three data sets were examined to define the level of interaction of reef associated sharks with the commercial Coral Reef Fin Fish Fishery within the Great Barrier Reef (GBR). Data were examined from fishery logbooks, an observer program within the fishery and a fishery-independent survey conducted as part of the Effects of Line Fishing (ELF) Experiment. The majority of the identified catch was comprised of grey reef (62-72%), whitetip reef (16-29%) and blacktip reef (6-13%) sharks. Logbook data revealed spatially and temporally variable landings of shark from the GBR. Catch per unit effort (CPUE) through time was stable for the period from 1989 to 2006 with no evidence of increase or decline. Data from observer and ELF data sets indicated no differences in CPUE among regions. The ELF data set demonstrated that CPUE was higher in Marine National Park zones (no fishing) when compared to General Use zones (open to fishing). The ongoing and consistent catches of reef sharks in the fishery and effectiveness of no-fishing zones suggest that management zones within the GBR Marine Park are effective at protecting a portion of the reef shark population from exploitation.

Fishing power and standardised catch rates: Implications of missing vessel-characteristic data from the Australian eastern king prawn fishery

Standardised time series of fishery catch rates require collations of fishing power data on vessel characteristics. Linear mixed models were used to quantify fishing power trends and study the effect of missing data encountered when relying on commercial logbooks. For this, Australian eastern king prawn (Melicertus plebejus) harvests were analysed with historical (from vessel surveys) and current (from commercial logbooks) vessel data. Between 1989 and 2010, fishing power increased up to 76%. To date, both forward-filling and, alternatively, omitting records with missing vessel information from commercial logbooks produce broadly similar fishing power increases and standardised catch rates, due to the strong influence of years with complete vessel data (16 out of 23 years of data). However, if gaps in vessel information had not originated randomly and skippers from the most efficient vessels were the most diligent at filling in logbooks, considerable errors would be introduced. Also, the buffering effect of complete years would be short lived as years with missing data accumulate. Given ongoing changes in fleet profile with high-catching vessels fishing proportionately more of the fleet’s effort, compliance with logbook completion, or alternatively ongoing vessel gear surveys, is required for generating accurate estimates of fishing power and standardised catch rates.

Abundance indices for long-lived tropical snappers: estimating standardized catch rates from spatially and temporally coarse logbook data

The Northern Demersal Scalefish Fishery has historically comprised a small fleet (≤10 vessels year−1) operating over a relatively large area off the northwest coast of Australia. This multispecies fishery primarily harvests two species of snapper: goldband snapper, Pristipomoides multidens and red emperor, Lutjanus sebae. A key input to age-structured assessments of these stocks has been the annual time-series of the catch rate. We used an approach that combined Generalized Linear Models, spatio-temporal imputation, and computer-intensive methods to standardize the fishery catch rates and report uncertainty in the indices. These analyses, which represent one of the first attempts to standardize fish trap catch rates, were also augmented to gain additional insights into the effects of targeting, historical effort creep, and spatio-temporal resolution of catch and effort data on trap fishery dynamics. Results from monthly reported catches (i.e. 1993 on) were compared with those reported daily from more recently (i.e. 2008 on) enhanced catch and effort logbooks. Model effects of catches of one species on the catch rates of another became more conspicuous when the daily data were analysed and produced estimates with greater precision. The rate of putative effort creep estimated for standardized catch rates was much lower than estimated for nominal catch rates. These results therefore demonstrate how important additional insights into fishery and fish population dynamics can be elucidated from such “pre-assessment” analyses.