Historical fish survey datasets from productive aquatic ecosystems in Lithuania

Many inland ecosystems (lakes, rivers, reservoirs, lagoons) around the world undergo regular biological monitoring surveys, including monitoring the abundance, biomass and size structure of fish communities. Yet, the majority of fish monitoring datasets for inland ecosystems remain inaccessible. This is especially true for historical datasets from the early and middle 20^th century, despite their immense importance for establishing baselines of ecosystem status (e.g., prior to manifestations of climate change and intensive fisheries impacts), assessing the current status of fish stocks, and more generally determining temporal changes in fish populations. Here we present a newly digitized fish monitoring dataset for two major Lithuanian inland ecosystems - Curonian Lagoon and Kaunas Water Reservoir. The data comprises >60000 records from >800 fish surveys conducted during 1950s to 1980s, using a range of fishing gears and sampling methods. We introduce three different definitions for survey methods to describe the level of detail for each fish community study. Method 1 surveys include individual fish sizes and weights, Method 2 surveys record frequencies of fish in length or weight groups, whereas Method 3 only records the total catch biomass of a given species. The majority of historical and currently collected fish survey data can be attributed to one of these three methods and we present R codes to convert data from higher resolution methods into aggregated data formats, to facilitate data sharing. In addition, commercial fisheries catch data for years that were surveyed are also provided. The data presented here can facilitate ecological and fisheries analyses of baseline ecosystem status before the onsets of rapid warming and eutrophication, exploration of fish size structure, evaluation of different catch per unit effort standardization methods, and assessment of population responses to commercial fishing.

Cormorant catch concerns for fishers: estimating the size-selectivity of a piscivorous bird

Conflict arises in fisheries worldwide when piscivorous birds target fish species of commercial value. This paper presents a method for estimating size selectivity functions for piscivores and uses it to compare predation selectivities of Great Cormorants (Phalacrocorax carbo sinensis L. 1758) with that of gill-net fishing on a European perch (Perca fluviatilis L. 1758) population in the Curonian Lagoon, Lithuania. Fishers often regard cormorants as an unwanted “satellite species”, but the degree of direct competition and overlap in size-specific selectivity between fishers and cormorants is unknown. This study showed negligible overlap in selectivity between Great Cormorants and legal-sized commercial nets. The selectivity estimation method has general application potential for use in conjunction with population dynamics models to assess fish population responses to size-selective fishing from a wide range of piscivorous predators.

Parameterization of European perch Perca fluviatilis length-at-age data using stochastic Gompertz growth models

Three stochastic versions of the Gompertz growth model were used to parameterize total length (L(T) )-at-age data for perch Perca fluviatilis, an important target species for commercial and recreational fishers and a food species for predatory fishes and aquatic birds. Each model addresses growth heterogeneity by incorporating random parameters from a specific positive distribution: Weibull, gamma or log-normal. The modelling outputs for each version of the model provide L(T) distributions for selected ages and percentiles of L(T) at age for both males and females. The results highlight the importance of using a stochastic approach and the logistic-like growth pattern for analysing growth data for P. fluviatilis in Curonian Lagoon (Lithuania). Outputs from this modelling can be extended to a stochastic analysis of fish cohort dynamics, incorporating all length-based biological relationships, and the selectivity-related interactions between fish cohorts and fishing gear.