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 >600 00 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. (C) 2022 The Author(s). Published by Elsevier Inc.