Does the Ice Age legacy end in Central Europe? The shrinking distributions of glacial relict crustaceans in Lithuania

Glacial relict crustaceans are characterized by their affinity for cold and well-oxygenated waters and their limited dispersal ability. They occur in large, deep lakes of Northern and Central Europe and North America, with their distributions shaped by glaciation events. In many countries and especially along the southern distribution edge, glacial relict populations are declining as a result of eutrophication, global warming, and possible adverse interactions with invasive Ponto-Caspian crustaceans. This study assessed the status of three glacial relict malacostracan species (the amphipods Monoporeia affinis and Pallaseopsis quadrispinosa and the mysid Mysis relicta) in Lithuania and modelled their abundance across environmental variables, including the presence of Ponto-Caspian malacostracans. The results showed that M. affinis is probably extinct in the country, whereas M. relicta was found in only nine out of 16 locations from which it was previously recorded. The distribution of P. quadrispinosa also seems to be shrinking. The annual water renewal rate (P. quadrispinosa and M. relicta) and lake depth (P. quadrispinosa) were significantly and positively associated with the relative abundance of relict mysids and amphipods, but no association was found with lake size or with the presence of invasive Ponto-Caspian crustaceans. Both species were less abundant in samples collected in the 21st century compared with the 20th century. Given the biogeographical and ecological importance of glacial relict crustaceans, their widespread declines are of concern and point to the deterioration of habitat quality, essential for other species with similar requirements. Urgent action is needed to improve water conditions and safeguard these communities. In cases where water quality improves, the reintroduction of extirpated relict populations should be considered. One example is Lake Drūkšiai, where these crustaceans became extinct during the operation of the Ignalina nuclear power plant but where conditions improved following the closure of the power plant in 2009

Tolerance of Paramysis lacustris and Limnomysis benedeni (Crustacea, Mysida) to sudden salinity changes: implications for ballast water treatment

In order to draw implications for ballast water management, we tested the tolerance of two Ponto-Caspian mysid species Paramysis lacustris and Limnomysis benedeni to sudden salinity changes. The naturally stenohaline P. lacustris was more susceptible to higher salinities; its mortality rate at 19 PSU was 60%, whereas exposure to 23 PSU was 100% lethal. The euryhaline L. benedeni survived in salinities of up to 19 PSU, but experienced 100% mortality at 34 PSU. The return of both mysid species to fresh water after the 24 h exposure to higher salinities did not prevent further mortality. Considering the rather high short-term salinity tolerance of both species, a salinity of at least 30 PSU should be used as an appropriate biocide

Temperature impacts on fish physiology and resource abundance lead to faster growth but smaller fish sizes and yields under warming

Resolving the combined effect of climate warming and exploitation in a food web context is key for predicting future biomass production, size-structure and potential yields of marine fishes. Previous studies based on mechanistic size-based food web models have found that bottom-up processes are important drivers of size-structure and fisheries yield in changing climates. However, we know less about the joint effects of ‘bottom-up’ and physiological effects of temperature; how do temperature effects propagate from individual-level physiology through food webs and alter the size-structure of exploited species in a community? Here, we assess how a species-resolved size-based food web is affected by warming through both these pathways and by exploitation. We parameterize a dynamic size spectrum food web model inspired by the offshore Baltic Sea food web, and investigate how individual growth rates, size-structure, and relative abundances of species and yields are affected by warming. The magnitude of warming is based on projections by the regional coupled model system RCA4-NEMO and the RCP 8.5 emission scenario, and we evaluate different scenarios of temperature dependence on fish physiology and resource productivity. When accounting for temperature-effects on physiology in addition to on basal productivity, projected size-at-age in 2050 increases on average for all fish species, mainly for young fish, compared to scenarios without warming. In contrast, size-at-age decreases when temperature affects resource dynamics only, and the decline is largest for young fish. Faster growth rates due to warming, however, do not always translate to larger yields, as lower resource carrying capacities with increasing temperature tend to result in decline in the abundance of larger fish and hence spawning stock biomass. These results suggest that to understand how global warming affects the size structure of fish communities, both direct metabolic effects and indirect effects of temperature via basal resources must be accounted for

Angling counts: Harnessing the power of technological advances for recreational fishing surveys

As the popularity of recreational fishing gathers global momentum, so does the importance of knowing the number of active anglers and their spatial behaviour. Conventional counting methods, however, can be inaccurate and time-consuming. Here we present two novel methods to monitor recreational fishing applied in Kaunas water reservoir (ca 65 km2), Lithuania, comparing their performance to a conventional visual count. First, we employed a remotely piloted fixed wing drone which conducted 39 missions distributed over one year and compared its accuracy to conventional visual land or boat-based counts. With these data we developed a linear model to predict the annual number of anglers depending on weekday and ice conditions. Second, we used anonymous data from a popular GPS-enabled sonar device Deeper®, used by anglers to explore underwater landscapes and to find fish. The sonar usage probability was calibrated with angler observations from drones using Bayesian methods, demonstrating that at any given time ~2 % of anglers are using the sonar device during the open water season and ~15 % during the ice fishing season. The calibrated values were then used to estimate the total number of anglers, given the daily records of sonar usage in Kaunas water reservoir. The predicted annual number of anglers from both linear drone-based and Bayesian sonar-based methods gave similar results of 25 and 27 thousand anglers within the area during the period of day surveyed, which corresponded to nearly 110 thousand angling trips in the total reservoir area annually. Our study shows high potential of both drone and fish finder digital devices for assessing recreational fishing activities through space and time

Scalable open-source framework for machine learning-based image collection, annotation and classification: A case study for automatic fish species identification

Citizen science platforms, social media and smart phone applications enable the collection of large amounts of georeferenced images. This provides a huge opportunity in biodiversity and ecological research, but also creates challenges for efficient data handling and processing. Recreational and small-scale fisheries is one of the fields that could be revolutionised by efficient, widely accessible and machine learning-based processing of georeferenced images. Most non-commercial inland and coastal fisheries are considered data poor and are rarely assessed, yet they provide multiple societal benefits and can have substantial ecological impacts. Given that large quantities of georeferenced fish images are being collected by fishers every day, artificial intelligence (AI) and computer vision applications offer a great opportunity to automate their analyses by providing species identification, and potentially also fish size estimation. This would deliver data needed for fisheries management and fisher engagement. To date, however, many AI image analysis applications in fisheries are focused on the commercial sector, limited to specific species or settings, and are not publicly available. In addition, using AI and computer vision tools often requires a strong background in programming. In this study, we aim to facilitate broader use of computer vision tools in fisheries and ecological research by compiling an open-source user friendly and modular framework for large-scale image storage, handling, annotation and automatic classification, using cost- and labour-efficient methodologies. The tool is based on TensorFlow Lite Model Maker library, and includes data augmentation and transfer learning techniques applied to different convolutional neural network models. We demonstrate the potential application of this framework using a small example dataset of fish images taken through a recreational fishing smartphone application. The framework presented here can be used to develop region-specific species identification models, which could potentially be combined into a larger hierarchical model

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 20th 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

Impacts of recreational angling on fish population recovery after a commercial fishing ban

It is often assumed that recreational fishing has negligible impact on fish stocks compared to commercial fishing. Yet, for inland water bodies in densely populated areas, this is unlikely to be true. In this study we demonstrate remarkably variable stock recovery rates among different fish species with similar life histories in a large productive inland freshwater ecosystem (Kaunas Reservoir, Lithuania), where all commercial fishing has been banned since 2013. We conducted over 900 surveys of recreational anglers during a period of four years (2016 to 2021) to assess recreational fishing catches. These surveys are combined with drone and fishfinder device-based assessment of recreational fishing effort. Fish population recovery rates were assessed using standardised catch per unit effort time series. We show that recreational fishing is having a major impact in retarding the recovery of predatory species, such as pikeperch and perch. In contrast, recovery of roach, rarely caught by anglers, has been remarkably rapid and the species is now dominating the ecosystem. Our study demonstrates that recreational fishing can have strong impacts on some fish species, alter relative species composition and potentially change ecosystem state and dynamics