Length- and age-based demographics of exploited populations of stout whiting,Sillago robustaStead, 1908

Abstract

Summary This study assessed variability in the length and age compositions, longevity, length‐at‐age and rates of growth and mortality of the east Australian stout whiting Sillago robusta Stead, 1908 population harvested by demersal trawl fisheries. Sampling was done over 2 years and was spatially stratified across three depth strata between 11 and 90 m at two locations approximately 400 km apart. There were no consistent depth‐related differences in length and age compositions, but the mean and median length and age of the population was greater at the lower latitude location. Age classes 2 and 3 years dominated samples in the north, and 1 and 2 years in the south. Observed longevity was 10 years in the north, and 6 years in the south. Mean length‐at‐age was not consistently different between sexes, years or locations, nor did the von Bertalanffy growth function differ significantly between sexes, even though females had a greater estimated L∞ (23.45 cm FL) compared to males (22.36 cm FL). Estimated natural mortality (M) ranged between 0.42 and 0.77, using age‐ and length‐based methods. Age‐based catch‐curve analyses identified the instantaneous rate of total mortality (Z) to range between 1.48 and 2.70, with subsequent estimates of fishing mortality (F) ranging between 1.15 and 2.00, being greater than M. Exploitation rates (E) were greater than 0.7, indicating that S. robusta at the study locations was heavily fished. The data provided here can be used as a basis to evaluate future fishery‐ and climate‐related changes in the population demographics of east Australian S. robusta.

Age determination, growth and mortality ofGerres subfasciatusCuvier, 1830 in southeast Australia

“…The austral spring-summer timing of opaque zone formation/ completion is in general agreement with a diversity of teleost species in regional southeast Australia (Gray, 2015;Gray et al, 2017;Hughes et al, 2008;Kendall & Gray, 2009). This seasonal timing also corresponds to Japanese G. oyena (Kanak & Tachihara, 2006a), which also occurred immediately prior to that species spawning period.…”

Age, growth, and mortality rate of the yellow goosefish Lophius litulon (Jordan, 1902) in the Yellow Sea

“…We used four natural mortality estimation methods to derive a relatively certain range for the real value of M (Gray et al, 2017). The optimum exploitation level of fi sh population is 0.5, a value of E greater than 0.5 may be indicative of a heavily fi shed population (Patterson, 1992;Sun et al, 2013;Gray et al, 2017). The current exploitation rate has been around 0.5, suggesting that the population of L .…”

“…M =4.22/ t m (Hewitt and Hoenig, 2005); 3. M =-ln(0.01)/ t m (Quinn II and Deriso, 1999), where t m is the observed maximum age in year (Gray et al, 2017). The observed maximum age of 14 years old for total samples, 14 years old for NYS stock and 13 years old for SYS stock were used in this study respectively.…”

“…No.2 SUN et al: Age, growth, mortality rate of L . litulon in the Yellow Sea species inhabits (Gray et al, 2017). The values for T used were 17.02 °C and 18.15 °C for NYS and SYS stock respectively.…”

“…The instantaneous rate of fi shing mortality F (/a) was estimated using the equation Z = M+F . The lowest and highest values of M (among the four methods) were subtracted from the corresponding values of Z (Gray et al, 2017) to obtain estimates of F . Then two estimates of exploitation ratio ( E ) were obtained by dividing F by Z.…”