The aim of the current study was to address length‐weight relationships (LWRs) in seven ornamental fish species from the Unini River basin—the main tributary of lower Negro River (Brazilian Amazon). Specimens were seasonally sampled by using hand nets and beach seines (mesh size < 1 mm) in five different occasions (August 2009—December 2010). Preserved specimens (initially kept in 10% formalin and transferred to 70% ethanol 10 days later) were measured and weighted in laboratory. The LWR was calculated based on a log‐transformed linear regression. The maximum standard length of each species was different from the ones previously reported at Fishbase. In addition, b values were different from the ones reported for the four species whose data were available in the literature.
Length at first maturity (L 50) is an important tool for the management and conservation of fish populations. Traditional approaches based on macroscopic and microscopic maturity staging exhibit high accuracy and precision, while alternative approaches (e.g., I g-based staging, stanza changing point) are less resource-demanding. Herein, we compare four approaches to estimate L 50 in a population of the heptapterid Rhamdioglanis transfasciatus from Atlantic Forest streams. Fish were sampled monthly during a year by using electrofishing. We measured the length (cm), mass (g), and gonad mass (g) of each specimen, then classified their maturity status macroscopically and microscopically. Alternative approaches were strongly discordant from traditional ones. Logistic curves considering mature individuals as those displaying at least 1% of the maximum I g in the sample greatly underestimated L 50 for females and overestimated L 50 for males. The stanza changing point derived from the polyphasic growth model underestimated L 50 in both cases. Despite the increasing development of less onerous approaches, it seems that they are not suitable for all fish populations and the requirements to use such approaches demand further investigation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.