ORCID Profile
0000-0002-9919-9376
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Marine and Estuarine Ecology (incl. Marine Ichthyology) | Natural Resource Management | Evolutionary Impacts of Climate Change | Life Histories | Ecology | Ecosystem Function | Evolutionary Biology
ANZSRC Socio-Economic Objective (SEO)
Wild Caught Fin Fish (excl. Tuna) | Ecosystem Assessment and Management of Coastal and Estuarine Environments | Ecosystem Adaptation to Climate Change | Climate Change Adaptation Measures |
Related Links
Publications
A machine learning based image classification method to estimate fish sizes from images without a specified reference object
Publisher: Cold Spring Harbor Laboratory
Date: 27-12-2022
DOI: 10.1101/2022.12.27.521854
Abstract: Most fish populations around the world are unassessed and their status is unknown. Size based methods could provide fast and transparent assessments, but they require information on fish sizes. Citizen science programs, social media and smart phone applications generate millions of georeferenced fish images globally. Machine learning based fish species and size identification could help turn these images into valuable data for population status assessments. We present a machine learning, image classification based method to identify fish size classes from photos of anglers holding fish. To train the model we group images into ten 5-10 cm size classes, similar to classes used in underwater visual fish surveys. The model was trained using 2602 images from angler citizen science platforms MyCatch and FishSizeProject. Although the number of images was limited, the model achieved an overall accuracy of ~50%. Importantly, the misidentification of size classes was consistent across 20 separate model training rounds, each conducted with an independent, random allocation of images for training and test datasets. Our method suggests that photo based fish size class identification is feasible, and that prediction uncertainty should be incorporated into subsequent analysis, as it is done with fish ageing errors in fisheries stock assessments.
Atlantis : A spatially explicit end‐to‐end marine ecosystem model with dynamically integrated physics, ecology and socio‐economic modules
Publisher: Wiley
Date: 21-08-2019
Fish body sizes change with temperature but not all species shrink with warming
Publisher: Springer Science and Business Media LLC
Date: 06-04-2020
A scalable open-source framework for machine learning based image collection, annotation and classification: a case study for automatic fish species identification
Publisher: Cold Spring Harbor Laboratory
Date: 02-07-2022
DOI: 10.1101/2022.06.29.498112
Abstract: Citizen science platforms, social media and multiple smart phone applications enable collection of large amounts of georeferenced images. This provides a huge opportunity in bio ersity 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. The majority of non-commercial inland and coastal fisheries are considered data poor and are rarely assessed, yet they provide multiple societal benefits and can have large ecological impacts. Given that large quantities of fish observations and images are being collected by fishers every day, artificial intelligence (AI) and computer vision applications offer a great opportunity to improve data collection, automate analyses and inform management. Yet, to date, many AI image analysis applications in fisheries are focused on the commercial sector and are not publicly available for community use. In this study we present an open-source 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 implementation of this framework in an ex le case study for automatic fish species identification from images taken through a recreational fishing smartphone application. The framework presented here is highly customisable for further advancement and community based image collection and annotation.
Ecological consequences of body size decline in harvested fish species: positive feedback loops in trophic interactions amplify human impact
Publisher: The Royal Society
Date: 23-04-2013
Abstract: Humans are changing marine ecosystems worldwide, both directly through fishing and indirectly through climate change. One of the little explored outcomes of human-induced change involves the decreasing body sizes of fishes. We use a marine ecosystem model to explore how a slow (less than 0.1% per year) decrease in the length of five harvested species could affect species interactions, biomasses and yields. We find that even small decreases in fish sizes are lified by positive feedback loops in the ecosystem and can lead to major changes in natural mortality. For some species, a total of 4 per cent decrease in length-at-age over 50 years resulted in 50 per cent increase in predation mortality. However, the magnitude and direction in predation mortality changes differed among species and one shrinking species even experienced reduced predation pressure. Nevertheless, 50 years of gradual decrease in body size resulted in 1–35% decrease in biomasses and catches of all shrinking species. Therefore, fisheries management practices that ignore contemporary life-history changes are likely to overestimate long-term yields and can lead to overfishing.
Estimating maturity from size-at-age data: Are real-world fisheries datasets up to the task?
Publisher: Springer Science and Business Media LLC
Date: 18-08-2020
Calibrating process-based marine ecosystem models: An example case using Atlantis
Publisher: Elsevier BV
Date: 11-2019
Historical fish survey datasets from productive aquatic ecosystems in Lithuania
Publisher: Elsevier BV
Date: 04-2022
A cross-scale framework to support a mechanistic understanding and modelling of marine climate-driven species redistribution, from individuals to communities
Publisher: Wiley
Date: 04-08-2020
DOI: 10.1111/ECOG.04996
A Scalable Open-Source Framework for Machine Learning-Based Image Collection, Annotation and Classification: A Case Study for Automatic Fish Species Identification
Publisher: MDPI AG
Date: 02-11-2022
DOI: 10.3390/SU142114324
Abstract: Citizen science platforms, social media and smart phone applications enable the collection of large amounts of georeferenced images. This provides a huge opportunity in bio ersity 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 ex le 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.
Is oxygen limitation in warming waters a valid mechanism to explain decreased body sizes in aquatic ectotherms?
Publisher: Wiley
Date: 16-11-2019
DOI: 10.1111/GEB.12847
Deep impact of fisheries
Publisher: Springer Science and Business Media LLC
Date: 20-08-2018
Exploring trade‐offs in mixed fisheries by integrating fleet dynamics into multispecies size‐spectrum models
Publisher: Wiley
Date: 08-12-2022
Abstract: Ecosystem‐based fisheries management aims to ensure ecologically sustainable fishing while maximising socio‐economic benefits. Achieving this goal for mixed fisheries requires better understanding of the effects of competing fishing fleets on shared resources and economic performance. Proposed management strategies that promote either specialisation or ersification of catches may result in unintended consequences for ecosystem‐based management. Here, we ask the following questions: does increased or decreased competition among fleets lead to better ecological and socio‐economic fishery outcomes? How effective are currently proposed management strategies for achieving these outcomes? We integrated fleet dynamics into a multispecies size‐spectrum model and parameterised this model to represent Australian Southern and Eastern Scalefish and Shark Mixed Fishery. We compared the fishery status quo to two extreme scenarios: no competition , where each species is fished only by one fleet (specialisation) and maximal competition , where all fleets catch all species ( ersification). To answer our second question, we considered three more plausible scenarios resulting from proposed management strategies: decreased competition due to reduced bycatch, and increased competition due to increased catches of under‐utilised or valuable species. We used indicators to explore scenarios' outcomes. Our model reproduced observed trends in fishing effort and yield. Extreme scenarios showed that a fishery dependent on single species management structures is more likely to achieve ecosystem‐based management objectives if fleets do not compete, while maximal competition can lead to socio‐economic loss as management buffers the ecological impact of ersifying. The more plausible scenarios showed little improvement over the status quo , with mixed ecological and negative economic effects. Synthesis and applications . Our model can be applied to assess mixed fisheries ecosystem‐based management strategies. Our results show that, under single species management approaches, greatest outcomes can be achieved when fleets are specialised, whereas managing fleets that catch similar species is unlikely to be successful. They question the effectiveness of these management approaches in providing resilience for mixed fisheries facing changes and highlight the need to account for fleet interactions in the evaluation of management strategies to avert unintended risks.
Impacts of Recreational Angling on Fish Population Recovery after a Commercial Fishing Ban
Publisher: MDPI AG
Date: 09-2022
Abstract: It is often assumed that recreational fishing has negligible influences on fish stocks compared to commercial fishing. However, for inland water bodies in densely populated areas, this assumption may not be supported. In this study, we demonstrate variable stock recovery rates among different fish species with similar life histories in a large productive inland freshwater ecosystem (Kaunas Reservoir, Lithuania), where previously intensive commercial fishing has been banned since 2013. We conducted over 900 surveys of recreational anglers from 2016 to 2021 to document recreational fishing catches and combined these catch estimates with drone and fishfinder device-based assessments of recreational fishing effort. Fish population recovery rates were assessed using a standardized catch-per-unit-effort time series in independent scientific surveys. We show that recreational fishing is slowing the recovery of predatory species, such as pikeperch Sander lucioperca (Linnaeus, 1758) and Eurasian perch Perca fluviatilis Linnaeus, 1758. The estimated annual recreational catches for these species were 19 tons (min-max of 7–55 tons) and 9 tons (4–28), respectively, which was considerably higher than the average commercial catch before the fishery closure (10 and 1 tons, respectively). In contrast, the recovery of roach Rutilus rutilus (Linnaeus, 1758), rarely caught by anglers (annual recreational catch of ca 3 tons compared to ca 100 tons of commercial catch), has been rapid, and the species is now dominating the ecosystem. Our study demonstrates that recreational fishing can have strong and selective impacts on fish species, reduce predator abundance, alter relative species composition and potentially change ecosystem state and dynamics.
How fast is fisheries‐induced evolution? Quantitative analysis of modelling and empirical studies
Publisher: Wiley
Date: 24-01-2013
DOI: 10.1111/EVA.12044
Trends and management implications of human‐influenced life‐history changes in marine ectotherms
Publisher: Wiley
Date: 12-09-2016
DOI: 10.1111/FAF.12156
Multigenerational exposure to warming and fishing causes recruitment collapse, but size diversity and periodic cooling can aid recovery
Publisher: Proceedings of the National Academy of Sciences
Date: 26-04-2021
Abstract: The synergistic impacts of rapid climatic warming and fisheries harvest are threatening the sustainability of wild fisheries. Their collective impact on fish recruitment—a key process underpinning stock abundance—remains poorly understood. We experimentally exposed fish populations to realistic warming and fishing-selection regimes over multiple generations and found that warmed populations experienced a severe decline in recruitment rate. This warming-induced decline was exacerbated by size-selective fishery harvest. Once warming and size-selective fishing were relaxed, recruitment rates rapidly recovered. Our results suggest that synergistic impacts of fishing and warming can have delayed effects on stock resilience and that preserving fish body size ersity will help to increase their resilience to global warming.
Interacting forces of predation and fishing affect species’ maturation size
Publisher: Wiley
Date: 12-2020
DOI: 10.1002/ECE3.6995
Abstract: Fishing is a strong selective force and is supposed to select for earlier maturation at smaller body size. However, the extent to which fishing‐induced evolution is shaping ecosystems remains debated. This is in part because it is challenging to disentangle fishing from other selective forces (e.g., size‐structured predation and cannibalism) in complex ecosystems undergoing rapid change. Changes in maturation size from fishing and predation have previously been explored with multi‐species physiologically structured models but assumed separation of ecological and evolutionary timescales. To assess the eco‐evolutionary impact of fishing and predation at the same timescale, we developed a stochastic physiologically size‐structured food‐web model, where new phenotypes are introduced randomly through time enabling dynamic simulation of species' relative maturation sizes under different types of selection pressures. Using the model, we carried out a fully factorial in silico experiment to assess how maturation size would change in the absence and presence of both fishing and predation (including cannibalism). We carried out ten replicate stochastic simulations exposed to all combinations of fishing and predation in a model community of nine interacting fish species ranging in their maximum sizes from 10 g to 100 kg. We visualized and statistically analyzed the results using linear models. The effects of fishing on maturation size depended on whether or not predation was enabled and differed substantially across species. Fishing consistently reduced the maturation sizes of two largest species whether or not predation was enabled and this decrease was seen even at low fishing intensities ( F = 0.2 per year). In contrast, the maturation sizes of the three smallest species evolved to become smaller through time but this happened regardless of the levels of predation or fishing. For the four medium‐size species, the effect of fishing was highly variable with more species showing significant and larger fishing effects in the presence of predation. Ultimately our results suggest that the interactive effects of predation and fishing can have marked effects on species' maturation sizes, but that, at least for the largest species, predation does not counterbalance the evolutionary effect of fishing. Our model also produced relative maturation sizes that are broadly consistent with empirical estimates for many fish species.
The Energetic Cost of Reproduction and Its Effect on Optimal Life-History Strategies
Publisher: University of Chicago Press
Date: 10-2018
DOI: 10.1086/698655
Abstract: Trade-offs in energy allocation between growth, reproduction, and survival are at the core of life-history theory. While age-specific mortality is considered to be the main determinant of the optimal allocation, some life-history strategies, such as delayed or skipped reproduction, may be better understood when also accounting for reproduction costs. Here, we present a two-pool indeterminate grower model that includes survival and energetic costs of reproduction. The energetic cost sets a minimum reserve required for reproduction, while the survival cost reflects increased mortality from low postreproductive body condition. Three life-history parameters determining age-dependent energy allocation to soma, reserve, and reproduction are optimized, and we show that the optimal strategies can reproduce realistic emergent growth trajectories, maturation ages, and reproductive outputs for fish. The model predicts maturation phase shifts along the gradient of condition-related mortality and shows that increased harvesting will select for earlier maturation and higher energy allocation to reproduction. However, since the energetic reproduction cost sets limits on how early an in idual can mature, an increase in fitness at high harvesting can only be achieved by erting most reserves into reproduction. The model presented here can improve predictions of life-history responses to environmental change and human impacts because key life-history traits such as maturation age and size, maximum body size, and size-specific fecundity emerge dynamically.
Community size structure varies with predator–prey size relationships and temperature across Australian reefs
Publisher: Wiley
Date: 04-2022
DOI: 10.1002/ECE3.8789
Abstract: Climate change and fisheries exploitation are dramatically changing the abundances, species composition, and size spectra of fish communities. We explore whether variation in ‘abundance size spectra’, a widely studied ecosystem feature, is influenced by a parameter theorized to govern the shape of size‐structured ecosystems—the relationship between the sizes of predators and their prey (predator–prey mass ratios, or PPMRs). PPMR estimates are lacking for avast number of fish species, including at the scale of trophic guilds. Using measurements of 8128 prey items in gut contents of 97 reef fish species, we established predator–prey mass ratios (PPMRs) for four major trophic guilds (piscivores, invertivores, planktivores, and herbivores) using linear mixed effects models. To assess the theoretical predictions that higher community‐level PPMRs leads to shallower size spectrum slopes, we compared observations of both ecosystem metrics for ~15,000 coastal reef sites distributed around Australia. PPMRs of in idual fishes were remarkably high (median ~71,000), with significant variation between different trophic guilds (~890 for piscivores ~83,000 for planktivores), and ~8700 for whole communities. Community‐level PPMRs were positively related to size spectrum slopes, broadly consistent with theory, however, this pattern was also influenced by the latitudinal temperature gradient. Tropical reefs showed a stronger relationship between community‐level PPMRs and community size spectrum slopes than temperate reefs. The extent that these patterns apply outside Australia and consequences for community structure and dynamics are key areas for future investigation.
Smaller adult fish size in warmer water is not explained by elevated metabolism.
Publisher: Wiley
Date: 09-03-2022
DOI: 10.1111/ELE.13989
Abstract: Fish and other ectotherms living in warmer waters often grow faster as juveniles, mature earlier, but become smaller adults. Known as the temperature-size rule (TSR), this pattern is commonly attributed to higher metabolism in warmer waters, leaving fewer resources for growth. An alternative explanation focuses on growth and reproduction trade-offs across temperatures. We tested these hypotheses by measuring growth, maturation, metabolism and reproductive allocation from zebrafish populations kept at 26 and 30°C across six generations. Zebrafish growth and maturation followed TSR expectations but were not explained by baseline metabolic rate, which converged between temperature treatments after a few generations. Rather, we found that females at 30°C allocated more to reproduction, especially when maturing at the smallest sizes. We show that elevated temperatures do not necessarily increase baseline metabolism if sufficient acclimation is allowed and call for an urgent revision of modelling assumptions used to predict population and ecosystem responses to warming.
Related Organisations
No related organisations have been discovered for Asta Audzijonyte.
Related Funding Activities
Discovery Projects - Grant ID: DP220102446
Start Date: 12-2022
End Date: 11-2025
Amount: $456,000.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP190101627
Start Date: 06-2019
End Date: 12-2022
Amount: $343,000.00
Funder: Australian Research Council
View Funded Activity