Journal of Applied Ichthyology 

About: Journal of Applied Ichthyology is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Sturgeon & Population. It has an ISSN identifier of 0175-8659. Over the lifetime, 4666 publications have been published receiving 78475 citations. The journal is also known as: Zeitschrift für angewandte Ichthyologie & Journal of applied ichthyology (Print).

Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations

Abstract: Summary This study presents a historical review, a meta-analysis, and recommendations for users about weight–length relationships, condition factors and relative weight equations. The historical review traces the developments of the respective concepts. The meta-analysis explores 3929 weight–length relationships of the type W ¼ aL b for 1773 species of fishes. It shows that 82% of the variance in a plot of log a over b can be explained by allometric versus isometric growth patterns and by different body shapes of the respective species. Across species median b ¼ 3.03 is significantly larger than 3.0, thus indicating a tendency towards slightly positive-allometric growth (increase in relative body thickness or plumpness) in most fishes. The expected range of 2.5 < b < 3.5 is confirmed. Mean estimates of b outside this range are often based on only one or two weight–length relationships per species. However, true cases of strong allometric growth do exist and three examples are given. Within species, a plot of log a vs b can be used to detect outliers in weight–length relationships. An equation to calculate mean condition factors from weight–length relationships is given as Kmean ¼ 100aL b)3 . Relative weight Wrm ¼ 100W/ (amL b m ) can be used for comparing the condition of individuals across populations, where am is the geometric mean of a and bm is the mean of b across all available weight–length relationships for a given species. Twelve recommendations for proper use and presentation of weight–length relationships, condition factors and relative weight are given.

To be, or not to be, a non‐native freshwater fish?

Abstract: Summary We examine the evolving concept of what constitutes a nonnative (or alien) freshwater fish. In an attempt to distinguish between biogeographical and socio-political perspectives, we review the patterns in the introduction and dispersal of nonnative fishes in Europe and North America, and especially the recent expansion of Ponto-Caspian gobies in Europe. We assess patterns in the development of national policy and legislation in response to the perceived threat of non-native fish introductions to native species and ecosystems. We review, and provide a glossary of, the terms and definitions associated with non-native species. Finally, we discuss perspectives as regards the future treatment of naturalized species.

Length-weight and length-length relationships of fish species from the Aegean Sea (Greece)

Abstract: Summary We present the relationships between total (TL), fork(FL) and standard (SL) length for 37 fish species and the relationships between TL and wet weight for 40 fish species from the Aegean Sea (Cyclades; Greece). The relationships between TL, FL and SL were all linear (for all cases: r 2 > 0.928). The values of the exponent b of the length–weight relationships ranged from 2.235 to 3.704.

A Bayesian approach for estimating length-weight relationships in fishes

Abstract: A Bayesian hierarchical approach is presented for the estimation of length-weight relationships (LWR) in fishes. In particular, estimates are provided for the LWR parameters a and b in general as well as by body shape. These priors and existing LWR studies were used to derive species-specific LWR parameters. In the cases of data-poor species, the analysis includes LWR studies of closely related species with the same body shape. This approach yielded LWR parameter estimates with measures of uncertainty for practically all known 32 000 species of fishes. Provided is a 3 large LWR data set extracted from www.fishbase.org, the source code of the respective analyses, and ready-to-use tools for practitioners. This is presented as an example of a self-learning online database where the addition of new studies improves the species-specific parameter estimates, and where these parameter estimates inform the analysis of new data.