Fish Movement Research Articles

Assessment of Morphometric Variations Among the Populations of Asian Sheat Catfish <i>Wallago attu</i> (Siluridae) from Five Indian Rivers

Morphological variations of the Asian sheat catfish, Wallago attu (Bloch and Schneider, 1801) sampled from the rivers Gomti, Ganga, Yamuna at Lucknow, Kanpur and Agra districts in Northern India, river Hooghly at Kolkata in Eastern India and river Pampa at Kerala in Southern India were analyzed in the present study. Images of 261 specimens of W. attu were taken without harming the fish to evaluate the morphometric variation using 8 digitized homologous landmarks for truss analysis and geometric morphometrics. Size corrected morphometric variables were analyzed using analysis of variance (ANOVA), multivariate analysis of variance (MANOVA), principal component analysis (PCA) and discriminant function analysis (DFA). Coefficients of all PCs were positively and negatively correlated to 31 significant (p 0.001) truss measurements due to variations in size and shape. Morphometric measurements lying in the head region such as head length (HL), eye diameter (ED), inter-orbital length (IOL) and snout length (SNL) contributed most to differentiate the populations in truss analysis. The ED, HL, SNL and IOL of Yamuna fish was significantly (p 0.001) smaller than the other fish populations. This could be attributed to the heavy pollution load in the Yamuna River and differences in the feeding regimes of fish. PCs and relative warps depicted differences in geometric analysis because of body shape variations among different river populations. The scatter plot in DFA revealed the presence of three distant and different phenotypic groups of W. attu among five wild river populations of fish with 70.5 and 83.9% of correct classification of fish into their original groups in truss and geometric analysis respectively. A single homogenous stock of fish was found to be in the rivers Gomti, Ganga and Hooghly because of a high level of intermixing (maximum misclassification) among the three river populations, whereas Yamuna and Pampa populations were two non-overlapping isolated groups due to negligible intermixing. These variations in the present study might be the effect of geographical isolation and river fragmentation due to the change in habitat that restricts fish movements. This is the first report on the morphometric assessment of W. attu that provides base line data for further confirmatory stock studies that would be useful for conservation and sustainable management of this vulnerable fish.

MAXIMUM SUSTAINABLE YIELD FOR A FISHERY WITH VARIABLE PRICE

We present a bioeconomic fishery model with variable price based on supply and demand. The model considers three variables: resource biomass, fishing effort, and market price. Rapid price changes classify the fishery system as a slow–fast system. Two main cases arise: catastrophic equilibrium (CE) with overexploitation and fish extinction, and a sustainable fishery equilibrium. We aim to determine conditions for maximum sustainable yield by optimizing cost per unit of fishing effort. Additionally, we explore conditions to prevent extinction and restore sustainable fishing. Marine protected areas (MPAs) can restore fish stocks by destabilizing the CE and maintaining a stable positive equilibrium. A model incorporating an MPA and fish movement is proposed, suggesting a small carrying capacity-to-surface area ratio in the fishing zone. Optimal total catch can be achieved by selecting the appropriate MPA surface area.

Deconstructing dams and disease: predictions for salmon disease risk following Klamath River dam removals

The health of fish populations and the river systems they inhabit have broad ecological, cultural, recreational, and economic relevance. This is exemplified by the iconic anadromous salmonid fishes native to the West Coast of North America. Salmon populations have been constrained since the mid nineteenth century by dam construction and water reallocation. In the Klamath River (Oregon and California, USA), a series of dams built in the early-mid 20th century cut the basin in two and blocked anadromous fish access to more than 600 river kilometers. This dramatic loss of habitat, coupled with infectious diseases and resulting epizootics, have impacted the wellbeing of these salmonid populations. In 2023-2024, the Klamath River will undergo the largest river restoration project in US history. Removal of the four lowermost dams will cause profound physical changes to the river, including flow, water temperature, and channel geomorphology. The dam removals will reconnect the lower and upper portions of the basin, and provide fish passage after a century of segregation. Reestablishment of upstream and downstream fish movements will also alter the occupancy and abundance of the salmonid hosts and their pathogens. The increased habitat availability and longer migration routes will increase duration of pathogen exposure and potential impacts on juvenile survival and adult pre-spawn mortality. However, restoration of more natural flow and sediment regimes will decrease overall fish disease risk by disrupting complex parasite life cycles. To better understand these multifarious, competing factors, we review the salmonid species in the Klamath River, and provide an overview of their historical pathogen challenges and associated diseases and use this as a framework to predict the effects of dam removals on disease dynamics. Our review and predictions are a synthesis of expertise from tribal biologists, fish health specialists and fish biologists, many of whom have lived and worked on the Klamath River for decades. We conclude with recommendations for expansion of current pathogen monitoring and research efforts to measure changes in host-pathogen dynamics basin-wide.

SCIENCE PRACTICUM ACTIVITIES THROUGH WATER AND AIR POLLUTION EXPERIMENTS ON ENVIRONMENTAL POLLUTION MATERIALS IN JUNIOR HIGH SCHOOLS

Learning that is carried out using the experimental practicum method gives students the ability to think critically, actively and collaboratively in solving a problem in science material, especially environmental pollution material. This study aims to provide an alternative way for educators to convey material related to environmental pollution, especially water and air pollution. The method used is the development of practicum learning methods on the material of water pollution and air pollution which is carried out in class 7th grade students at junior high school. The results of the water pollution practicum research stated that the average fish operculum movement experienced the highest decrease in Jar 3, from 95 to 69. The results of observations on the average movement of fish that experience slow changes and die the most are in Jar 2 with an average of 60% of fish moving slowly and 80% of fish dying in the second minute. The higher the dose of detergent, the less movement of the fish operculum and the slower the movement of fish and the death. In air pollution, the highest percentage decline in normal cricket activity was in Jar 2, from 50% in the 3rd minute to 30% in the 6th minute. The longer the crickets were exposed to the smoke of the mosquito coils, the lower the displacement of the places carried out by the crickets and the higher the activity move the antenna.

FishTrack: Multi-object tracking method for fish using spatiotemporal information fusion

Tracking the fish is a key step in analyzing fish behavior, evaluating their health levels, and warning of abnormal water quality, so it is of significant importance for intelligent monitoring in fish farming. However, multi-object tracking for fish is a very challenging task due to foam occlusion in the factory tank, high individual similarity, and fast-paced motion of fish. To address the above issues, an online multi-fish tracking model called FishTrack is proposed with 3 branches of target detection, track prediction, and re-identification, which establishes the motion model and appearance model for fish simultaneously, thus achieving the online multi-fish tracking. It is a complete Encoder-Decoder structure and the Pyramid Vision Transformer (PVT) is adopted as the backbone network to extract multi-level features. Then an Encoder is specially designed to encode the historical information of the positions of fish, and automatically update its spatiotemporal information in an autoregressive fashion, to perform the fusion of the spatiotemporal information of fish targets and avoid manual selection of spatiotemporal features. Finally, a parallel dual-Decoder is used to decode the motion and appearance features of fish to reduce the interference of the two optimization directions during the joint model training. The motion cues are first used in linear assignment to reduce the interference of occlusion and deformation issues, and when the motion model fails to track, the appearance cues can recover the identity to deal with long occlusion. The experiments on the established multiple fish tracking dataset showed that the higher order tracking accuracy (HOTA) reached 71.4%, the multi-object tracking accuracy (MOTA) reached 94.8%, the most tracked ratio (MT) reached 93.3%, and the identification F1 score (IDF1) reached 82.5%. The results show that FishTrack can solve the problem of tracking accuracy decrease caused by foam occlusion and fish deformation, and save the inference time by sharing features, increasing the robustness of online multi-fish tracking in factory farming.

Underwater soundscape observations and associated demersal fish movement during a seismic airgun survey in coastal Oregon

Sound is a crucial aspect of the underwater environment for fishes—various species use sound to communicate, identify predators, navigate, and many other activities needed for survival in their habitat. In the summer of 2021, a seismic survey passed nearby Southern Oregon to map the Cascadia Subduction Zone using an array of airguns. To evaluate the effect of the seismic survey on the behavior of demersal fish, acoustic pressure and particle motion measurements were collected within a marine protected area, accompanied by tagging of two rockfish species, Black Rockfish (Sebastes melanops) and China Rockfish (S. nebulosus). Acoustic measurements were obtained using a vector sensor array, deployed in 25 m deep water. It was found that while cumulative sound exposure levels were dominated by wind noise, other metrics such as peak sound pressure, kurtosis, acoustic complexity index, crest factor and acoustic entropy showed clear signals associated with the seismic survey. Animal behavior and spatial use by the two rockfish species were also evaluated. Overall, results indicate that there are slight differences in movement and spatial use during times of seismic survey noise presence, but observed differences are reduced after only a few days.

Waiting for the right time and tide: The fine‐scale migratory behavior of river herring in two coastal New England streams

AbstractObjectiveAlewife Alosa pseudoharengus and Blueback Herring A. aestivalis, collectively referred to as river herring, are anadromous clupeids inhabiting the North American Atlantic coast. Although the seasonal patterns of their spawning migration are well studied and predictable, the fine‐scale movements are still poorly resolved.MethodsThis study used high‐resolution acoustic imaging to study the fine‐scale behavior of river herring during their spring spawning migration in two coastal rivers in Massachusetts, United States.ResultObservations suggest that seasonal patterns of migration appear to be influenced by temperature, while fine‐scale patterns in migration were associated with the time of day, tidal state, and their interaction. River herring were consistently observed during both day and night, with elevated peaks of activity in the early morning and late afternoon. Daytime movement consisted of the intermittent passage of large, dense schools, while nighttime movement consisted of the frequent passage of individuals or small groups. The highest numbers of herring observations were associated with flood and high tides. Additionally, the interactions between time of day and tidal state resulted in synergistic positive effects during crepuscular incoming tides, which were favorable to movement, and synergistic negative effects during midday low tides, which inhibited fish movement.ConclusionThe changing relationship between the time of day and tidal state within the season manifested in changing periodicity in fish movement to correlate with favorable movement conditions. Since movements may be related to both time of day and tide, previous run size estimates from visual counts made only during the day may be too low. Sampling methodologies that collect information during all 24 h would likely produce the most accurate run size estimates. This study highlights the need to view river herring migration in a holistic context predicated by multiple environmental and biological factors that vary at several temporal scales (i.e., seasonally, daily, and hourly).

Evaluating the efficacy of using GPS satellite transmitters to assess movement of bigheaded carp in a riverine system

Abstract We have evaluated the feasibility of using GPS satellite transmitters on invasive bigheaded carp species, silver carp and bighead carp, that could determine patterns of movement, identify potential feeding and spawning areas, and inform a comprehensive monitoring and commercial removal program in the Illinois River Waterway system in the United States. Despite a wealth of information on bigheaded carp movement from acoustic and radio telemetry, a finer‐scale approach to understand habitat use and daily surfacing trends in movement would strengthen management efforts. Custom Fastloc™‐GPS data‐logging transmitters (with radio telemetry capability) manufactured by Sirtrack™ were tethered to adult bigheaded carp in field experiments. Sixteen field‐deployed transmitters were recovered and yielded 490 individual GPS waypoints when transmitters were attached to fish. We observed movement rates within the Dresden Island Reach of the Illinois River Waterway of approximately 16 river km, and movement in and out of backwater habitats and the warm‐water discharge of a nuclear generating station. We have demonstrated the use of this technology to monitor bigheaded carp and will use the information gained from this study to inform future work with remotely accessed, real‐time, Argos satellite linked prototypes. Fine‐scale accuracies, fast acquisition speeds and the ability to gather real‐time data make this a promising tool and is one the first uses of GPS technology to track fish movement in a riverine system. Continued exploration to improve tag retention efficiency will enhance its utility for continued invasive carp management.

Four-channel generative adversarial networks can predict the distribution of reef-associated fish in the South and East China Seas

Reef-associated fish (RAF) are socioeconomically and ecologically important. Herein, we used a four-channel generative adversarial network (GAN) architecture with a retrospective cycle feature to model the distribution of RAF in the East China Sea (ECS) and South China Sea (SCS). Our approach entailed the use of RAF suitability maps and key environmental layers, including sea body temperature, chlorophyll-α concentration, and salinity, as input data. These environmental factors have been demonstrated to significantly influence the distribution of RAF. Our results show that four-channel GANs performed better than one-channel GANs in predicting the distribution of RAF. Furthermore, the proposed four-channel retrospective-cycle GAN (4CRCGAN) model outperformed the commonly used four-channel convolutional GAN (4CCGAN), emphasizing the importance of considering temporal dynamics and feedback loops in predicting the distribution of species. However, it is worth noting that the predictive performance for the distribution of RAF in summer and winter was relatively poor, implying that other environmental and biological factors also exert nonnegligible influences on fish movement and abundance; this underscores the necessity of comprehensively understanding the intricate and dynamic nature of species-environment interactions within marine ecosystems. Our study also revealed that the proposed 4CRCGAN model performed well over multiple steps, which is reflective of its potential to provide valuable insights for decision-makers and stakeholders in the fisheries management sector. Overall, our findings offer critical insights for the development of effective and sustainable management strategies that balance the conservation and sustainable use of these valuable marine resources.

Kajian Sistem Pemasaran dan Hasil Tangkapan Nelayan Serta Tingkat Kesejahteraan Nelayan di Desa Lembur Barat, Kecamatan Alor Tengah Utara, Kabupaten Alor.

Fishermen are groups of individuals who carry out fishing and other aquatic biota in various types of waters, including fresh, brackish, and marine waters. Fishermen are communities that live on the coast and rely on marine catches for their livelihood. Although fraught with risks, the fishing profession is often passed down from generation to generation in Indonesia. However, their economic conditions are often affected by various factors, including climate problems such as famine seasons that occur every year. BPS 2013 data shows that fishermen and fishing communities play a large role in Indonesia's poverty rate. This study adopts a qualitative approach, by applying direct interviews with fishermen and document collection as data collection methods. Research findings show that fishermen face challenges in fishing, especially during high sea waves and lean seasons. In West Overtime Village, North Central Alor District, fishermen have difficulty finding fish because of the large rompong that affects the movement of fish in these waters. This condition encourages most fishermen to switch professions to become farmers to meet their daily needs. In small fishing communities, visible traits include the use of small-scale fishing gear, uncertain income, independent operations, and simple skills. Social and geographical isolation are also influencing factors, along with low levels of well-being. This research provides an in-depth understanding of the conditions and challenges faced by fishing communities and their impact on their welfare. Therefore, this research makes a valuable contribution in understanding the lives of fishermen in coastal Indonesia.

Evolution of schooling drives changes in neuroanatomy and motion characteristics across predation contexts in guppies

One of the most spectacular displays of social behavior is the synchronized movements that many animal groups perform to travel, forage and escape from predators. However, elucidating the neural mechanisms underlying the evolution of collective behaviors, as well as their fitness effects, remains challenging. Here, we study collective motion patterns with and without predation threat and predator inspection behavior in guppies experimentally selected for divergence in polarization, an important ecological driver of coordinated movement in fish. We find that groups from artificially selected lines remain more polarized than control groups in the presence of a threat. Neuroanatomical measurements of polarization-selected individuals indicate changes in brain regions previously suggested to be important regulators of perception, fear and attention, and motor response. Additional visual acuity and temporal resolution tests performed in polarization-selected and control individuals indicate that observed differences in predator inspection and schooling behavior should not be attributable to changes in visual perception, but rather are more likely the result of the more efficient relay of sensory input in the brain of polarization-selected fish. Our findings highlight that brain morphology may play a fundamental role in the evolution of coordinated movement and anti-predator behavior.

Origins of hatchery-reared lake trout Salvelinus namaycush to Lake Michigan’s sport fishery reflect trends in regional relative survival

Fisheries management depends on understanding fish movements, especially in large systems. In Lake Michigan, lake trout are stocked for rehabilitation and to support a diverse, multi-million dollar sport fishery. We described the contributions of lake trout stocked at offshore and onshore locations to Lake Michigan’s sport fishery at multiple spatial scales. We also assessed lake trout relative survival and age-related seasonal movements. Offshore reefs, which historically were important sources of lake trout recruitment and are currently fishery refuges, served as source-populations for nearshore fisheries, as offshore-stocked lake trout comprised 58% of recoveries lakewide and were predominant in fisheries from 9 of 13 management units. By contrast, lake trout stocked onshore primarily had local importance, consistent with the management aim to directly benefit nearshore fisheries. Lake trout relative survival significantly differed among stocking regions but not between the two genetic strains compared. Lake trout stocked at two of the three offshore regions, Julian’s Reef and Southern Refuge, had higher relative survival (0.022–0.038 fish/sampling day/100,000 fish stocked) compared to the three onshore stocking regions (0.001–0.013) and the offshore Northern Refuge (0.011), which helps explain the predominance of offshore-stocked fish in fisheries at most locations. In addition, offshore-stocked fish were most available to sport fisheries in multiple regions during summer, while mature fish generally returned to their stocking region in fall, presumably to spawn. This study demonstrated that stocking at offshore locations in Lake Michigan supported both lake trout rehabilitation efforts and sport fisheries, and illustrates how spatial ecology can help inform fisheries management.

MSGNet: multi-source guidance network for fish segmentation in underwater videos

Fish segmentation in underwater videos provides basic data for fish measurements, which is vital information that supports fish habitat monitoring and fishery resources survey. However, because of water turbidity and insufficient lighting, fish segmentation in underwater videos has low accuracy and poor robustness. Most previous work has utilized static fish appearance information while ignoring fish motion in underwater videos. Considering that motion contains more detail, this paper proposes a method that simultaneously combines appearance and motion information to guide fish segmentation in underwater videos. First, underwater videos are preprocessed to highlight fish in motion, and obtain high-quality underwater optical flow. Then, a multi-source guidance network (MSGNet) is presented to segment fish in complex underwater videos with degraded visual features. To enhance both fish appearance and motion information, a non-local-based multiple co-attention guidance module (M-CAGM) is applied in the encoder stage, in which the appearance and motion features from the intra-frame salient fish and the moving fish in video sequences are reciprocally enhanced. In addition, a feature adaptive fusion module (FAFM) is introduced in the decoder stage to avoid errors accumulated in the video sequences due to blurred fish or inaccurate optical flow. Experiments based on three publicly available datasets were designed to test the performance of the proposed model. The mean pixel accuracy (mPA) and mean intersection over union (mIoU) of MSGNet were 91.89% and 88.91% respectively with the mixed dataset. Compared with those of the advanced underwater fish segmentation and video object segmentation models, the mPA and mIoU of the proposed model significantly improved. The results showed that MSGNet achieves excellent segmentation performance in complex underwater videos and can provide an effective segmentation solution for fisheries resource assessment and ocean observation. The proposed model and code are exposed via Github1.

The relative influence of temperature and ontogeny on groundfish distribution varies across life stages

AbstractDistributional changes for fish populations may be difficult to interpret since temperature responses are often confounded with ontogenetic shifts. However, the relative importance of these two types of fish movement (temperature responses and ontogenetic shifts) to population distribution remains largely unstudied. This study presents the first attempt to compare the two types of movement in depth, latitude and longitude for 10 abundant groundfish species across size class and subregion. We utilized large, quality‐controlled datasets from random depth‐stratified, bottom trawl surveys consistently conducted during the summer along NE Pacific shelf from 1996 to 2015. We show that the size structure of each species varied across years and subregions with dramatically strong or poor recruitments for some species in 2015 during a marine heatwave. Principal component analysis (PCA) demonstrated that ontogenetic shifts in depth represented the primary movement pattern while temperature responses in latitude and longitude constituted a major, but a secondary pattern. Re‐run by size class, PCA results further showed that the influence of temperature and ontogeny on population distribution varied by size classes with greater ontogenetic shifts in smaller fish and elevated temperature responses in larger fish. We further show substantial ontogeny‐induced movements by depth, latitude and longitude with high variability among species and subregions. Our analyses suggest that failing to account for size structure can lead to serious misinterpretation of population distributional changes in all three dimensions: depth, latitude and longitude for populations with or without episodic recruitments.

Estimating SVCV waterborne transmission and predicting experimental epidemic development: A modeling study using a machine learning approach

Viral infectious diseases significantly threaten the sustainability of freshwater fish aquaculture. The lack of studies on epidemic transmission patterns and mechanisms inhibits the development of containment strategies from the viewpoint of veterinary public health. This study raises an epidemic mathematical model considering water transmission with the aim of analyzing the transmission process more accurately. The basic reproduction number R0 was derived by the model parameter including the water transmission coefficient and was used for the analysis of the virus transmission. Spring viremia of carp virus (SVCV) and zebrafish were used as model viruses and animals, respectively, to conduct the transmission experiment. Transmission through water was achieved by connecting two aquarium tanks with a water channel but blocking the fish movement between the tanks. With the collected experimental data, we determined the optimal hybrid machine learning algorithm to analyze the transmission process using an established mathematical model. In addition, future transmission was predicted and validated using the epidemic model and an optimal algorithm. Finally, the sensitivity of model parameters and the simulations of R0 variation were performed based on the modified complex epidemic model. This study is of significance in providing theoretical guidance for minimizing R0 by manipulating model parameters with containment measures. More importantly, since the modified model and algorithm demonstrated better performance in handling freshwater fish transmission problems, this study advances the future application of transmissible disease modeling with larger datasets in freshwater fish aquaculture.

Pattern detection and prediction using deep learning for intelligent decision support to identify fish behaviour in aquaculture

The United Nations’ Sustainable Development Goals (SDGs) underscore aquaculture as a sustainable practice. However, many countries rely on ineffective conventional methods to monitor the aquaculture. Fish behaviour monitoring systems lack an integrated strategy, often focusing on underwater footage analysis or water quality data. Additionally, limited research exists on using learning algorithms to identify sensor data anomalies, limiting the effectiveness of such systems. This study proposes a comprehensive and effective aquaculture monitoring system to address these issues. The work introduces a novel method integrating fish motion analysis with water quality metrics. The study also presents a learning system that anticipates potential water quality parameters. The proposed model has the potential to significantly enhance aquaculture management procedures and contribute to the UN’s SDGs through its ability to forecast water quality parameters and detect abnormal behaviour without requiring training detection and tracking algorithms.The study employs a large aquarium to capture water quality parameters and fish movement patterns. The study develops an FPGA-based water quality monitoring system and a prediction model to forecast potential water quality metrics. Among multiple LSTM models, the bi-directional LSTM performs well, achieving an RMSE score of 1.01 for water quality prediction. Subsequently, an outlier detection system is applied to identify unusual water quality parameters, triggering the behaviour analysis model. The behaviour analysis model uses an auto-encoder-based reconstruction approach to detect the frantic patterns in fish. The suggested behaviour analysis model has a f1-score of 0.68, demonstrating its reliability in contrast to conventional methods. The developed system is also tested on aquaculture site videos and includes a novel dataset of Sillago sihama with annotations for frantic behaviour patterns. The system works effectively as a decision support system for aquaculture.

Simulating individual movement in fish

Accurately quantifying an animal’s movement is crucial for developing a greater empirical and theoretical understanding of its behaviour, and for simulating biologically plausible movement patterns. However, we have a relatively poor understanding of how animals move at fine temporal scales and in three-dimensional environments. Here, we collected high temporal resolution data on the three-dimensional spatial positions of individual three-spined sticklebacks (Gasterosteus aculeatus), allowing us to derive statistics describing key geometric characteristics of their movement and to quantify the extent to which this varies between individuals. We then used these statistics to develop a simple model of fish movement and evaluated the biological plausibility of simulated movement paths using a Turing-type test, which quantified the association preferences of live fish towards animated conspecifics following either ‘real’ (i.e., based on empirical measurements) or simulated movements. Live fish showed no difference in their response to ‘real’ movement compared to movement simulated by the model, although significantly preferred modelled movement over putatively unnatural movement patterns. The model therefore has the potential to facilitate a greater understanding of the causes and consequences of individual variation in movement, as well as enabling the construction of agent-based models or real-time computer animations in which individual fish move in biologically feasible ways.

FishPass sortable attribute database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Laurentian Great Lakes fishes

In-stream barriers pose threats to fishes, including habitat loss, constraints on migration, and reduced connectivity between populations. Despite many negative consequences, barriers can serve to protect native species by limiting the spread of invasive species. For example, in the Laurentian Great Lakes, physical barriers have long been used to control invasive sea lamprey (Petromyzon marinus) populations by limiting access to potential upstream spawning and rearing habitat. Selective fish passage systems could solve this management trade-off, termed the “connectivity conundrum”, but must efficiently pass multiple native or desirable species while blocking invasive species. Designing such fish passage systems requires an understanding of the attribute dimensions of the fish community, specifically, the phenology, morphology, physiology, and behaviour of each species. Here, we describe the first comprehensive collection of sortable attributes associated with fish passage. The integrated database consists of 21 biological attributes that influence the movement and passage of 220 species in the Great Lakes, including native species, established non-native species, and unestablished but potentially invasive fishes. Data coverage varies with species, taxonomic orders, and attribute dimensions. Behavioural attributes were typically underrepresented in the literature, and the ecology of potential invaders was not well understood. The synthesis described herein is a critical step towards a holistic approach to fish passage design and may help to inform management actions related to population connectivity. The database is openly accessible online and is expected to be updated periodically.

Simultaneous Measurement of Turbulent Surface Velocities and Fish Movement in an Open Channel Flow with Implications for Agent-Based Models

Simultaneous Measurement of Turbulent Surface Velocities and Fish Movement in an Open Channel Flow with Implications for Agent-Based Models

Lipid Correction for Carbon Stable Isotope Analysis of Yellowfin Tuna

Carbon stable isotopes (δ13C) are widely used in ecological studies to understand diet, food web dynamics, and movements of marine fishes. Still, δ13C is influenced by lipid content and often requires chemical extraction or mathematical correction. Here, we developed a species-specific mathematical lipid correction for white muscle tissue of yellowfin tuna (Thunnus albacares), a highly migratory finfish of considerable economic and ecological value. Lipid extraction was conducted on yellowfin tuna white muscle tissue (C:N range: 2.96–6.49), and both linear and non-linear lipid correction models for δ13C were fitted and assessed. Lipid extraction increased δ13C, and to a lesser extent, δ15N values in yellowfin tuna white muscle tissue, but had no effect on δ34S. Both non-linear models provided better fits to the data than the linear model, suggesting an asymptotic relationship between C:N and ∆δ13C. Results support the growing body of evidence that C:N ratios can be used to predict lipid corrected δ13C and highlight the value of mathematical correction approaches. We provide species-specific parameter estimates that can be used for lipid correction of white muscle tissue for δ13C analysis in yellowfin tuna and similar species for which species-specific models have yet to be developed.