Specific Fish Species Research Articles

Assessing the potential ecological and human health risks of trace metal pollution in surface water, sediment, and commercially valuable fish species in the Pashur River, Bangladesh.

This research examines the contamination levels in the Pashur River in Bangladesh stemming from trace metal discharge originating from the Mongla seaport and various industrial outlets. It delves into both ecological risks and potential health hazards for humans consuming fish carrying accumulated trace metals. The research employed atomic absorption spectrometry to measure the concentrations of chromium (Cr), arsenic (As), manganese (Mn), copper (Cu), zinc (Zn), nickel (Ni), lead (Pb), and cadmium (Cd) in surface water, sediment, and fish samples. Target hazard quotient (THQ) and carcinogenic risks were calculated to determine the human health risk caused by the consumption of these targeted fish species. An RI value of 42.89 indicates that the collective presence of trace metals in sediment poses significant ecological risks to the study area. Although the majority of trace metals present in sediment are categorized under class 1 (ranging from unpolluted to moderately polluted) based on the Igeo values, Cd is classified under class 2, signifying a moderate level of pollution. Significantly, THQ values surpass the threshold of 1 for Cr and As, indicating potential health risks associated with the consumption of specific fish species. Among the trace metals analyzed, Ni demonstrates the highest cancer risk (CR) value, at 5.78 × 103, indicating a notable cancer risk associated with the consumption of targeted fish. Recommendations include the strict enforcement of waste disposal policies to mitigate anthropogenic discharge and safeguard the river from further pollution.

Comparative of Hepatocytes and Intestinal Villi in Zebra Fish (Danio rerio) and Guppy Fish (Poecilia reticulata): Novel Insights into Species-Specific Fish for Animal Model

Comparative of Hepatocytes and Intestinal Villi in Zebra Fish (Danio rerio) and Guppy Fish (Poecilia reticulata): Novel Insights into Species-Specific Fish for Animal Model

Investigation of the pangas (Pangasianodon hypophthalmus) cultivation sustainability in cages at the Ratargul Freshwater Swamp Forest of Bangladesh

AbstractDetermining the most appropriate stocking density for a specific fish species in an ambient condition is essential for successful cage aquaculture in terms of profitability which is mainly governed by growth. The current study was conducted to ascertain which stocking density gives the best result of widely cultured species in cage aquaculture, pangas (Pangasianodon hypophthalmus), at swamp forest environment of Ratargul Freshwater Swamp Forest, Bangladesh in terms of growth, production and economic return. Fish were reared for 93 days at three stocking densities, namely 30, 40 and 50 fish/m3 which were denoted as FSD30, FSD40 and FSD50, respectively, containing three replications of each. Growth and yield comparisons indicated that the stocking density of fish had significant (p < 0.05) effects on growth rate and productivity. Fish cultivated at the maximum density (FSD50) had lower mean weights than fish reared at lower densities. The significantly highest mean weights (376.58 ± 14.65 g) and benefit–cost ratio (BCR) (1.617 ± 0.035) obtained from FSD30 show the suitability of this density in terms of fish growth and profitability of pangas in swamp forest environment.

A New Workflow for Instance Segmentation of Fish with YOLO

The application of deep-learning technology for marine fishery resource investigation is still in its infancy stage. In this study, we applied YOLOv5 and YOLOv8 methods to identify and segment fish in the seabed. Our results show that both methods could achieve superior performance in the segmentation task of the DeepFish dataset. We also expanded the labeling of specific fish species classification tags on the basis of the original semantic segmentation dataset of DeepFish and completed the multi-class instance segmentation task of fish based on the newly labeled tags. Based on the above two achievements, we propose a general and flexible self-iterative fish identification and segmentation standard workflow that can effectively improve the efficiency of fish surveys.

IoT ENBALED SMART AQUARIUM FOR MONITORING THROUGH SENSORS

The development of an IoT-enabled smart aquarium system offering real-time monitoring and automated control of crucial environmental parameters. The core of the system lies in the ESP8266 microcontroller, facilitating seamless internet connectivity and data processing. Water quality assessment is achieved through a turbidity sensor, detecting suspended particles indicative of potential pollution. Environmental conditions are monitored using a DHT11 sensor, providing data on both temperature and humidity – essential factors for maintaining a healthy habitat for specific fish species. For automated lighting control mimicking natural day/night cycles and preventing excessive algae growth, a Light-Dependent Resistor (LDR) is implemented. The LDR adjusts aquarium lighting based on ambient light levels. Finally, a relay module controls the operation of a water pump, ensuring optimal water circulation and distribution of nutrients throughout the aquarium. While an I2C LCD connected to an Arduino Nano provides local data visualization within the aquarium setup, the ESP8266 transmits sensor readings to a user-friendly platform accessible remotely through a mobile application or web interface. This allows for convenient real-time monitoring of water quality, temperature, humidity, and lighting conditions. The system can be further programmed to generate alerts when critical parameters deviate from the ideal range, enabling proactive user intervention to maintain a healthy environment. This project demonstrates the potential of IoT technology to create a more automated, efficient, and user-friendly system for maintaining a thriving aquatic ecosystem. KEYWORDS: IoT (Internet of Things), Smart Aquarium, ESP8266, Turbidity Sensor, DHT11 Sensor, LDR(Light-Dependent Resistor), Relay Module, Water Pump, I2C LCD, Arduino Nano, Real-Time Monitoring, Automated Control, Remote Access, Mobile Application, Web Interface, Water Quality, Temperature, Humidity, Light Control, Aquatic Environment.

Variability and influence of fisheries acoustic echogram annotations on machine learning applications

High-frequency echosounders are the workhorse in fisheries and marine ecological surveys. Due to the inherent complexity of biological aggregations and ambiguity in interpreting echoes from species of similar size and anatomical compositions, echogram annotation typically requires combining spectral information referencing scattering physics, biological ground-truth from nearby net-trawls, and empirical school morphology of specific fish species. Here, we investigate the variability of echogram annotations and its influence on machine learning applications using data from the biennial Pacific hake acoustic-trawl survey. Compared to many other fish species, hake tend to possess less defined school boundaries with variable acoustic features and often form mixed-species aggregations in the mesopelagic. Nonnegative matrix factorization and hierarchical clustering of volume backscattering strength (Sv) distributions across the 18, 38, and 120 kHz channels revealed a spectrum of annotation region types that reflect differences in morphological and acoustic features as well as differences in annotator style. This variability likely contributes to the observed variable segmentation behavior of deep learning models trained using this dataset. These results highlight the importance of considering the diversity of echogram annotation, its connection to scattering physics and the underlying aggregation composition, and the incorporation of such information in developing machine learning models.

Integrating fish swimming abilities into rapid road crossing barrier assessment: Case studies in the southeastern United States.

Many aquatic networks are fragmented by road crossing structures; remediating these barriers to allow fish passage is critical to restoring connectivity. Maximizing connectivity requires effective barrier identification and prioritization, but many barrier prioritization efforts do not consider swimming capabilities of target species. Given the many potential barriers within watersheds, inventory efforts integrating species-specific swimming speeds into rapid assessment protocols may allow for more accurate barrier removal prioritization. In this study, we demonstrate an approach for integrating fish swimming speeds into rapid barrier assessment and illustrate its utility via two case studies. We measured critical swimming speeds (Ucrit) of two stream-resident fish species with very different swimming modes: Yoknapatawpha Darter (Etheostoma faulkneri), an at-risk species whose current distribution is restricted to highly degraded habitat, and Bluehead Chub (Nocomis leptocephalus), an important host species for the federally endangered Carolina Heelsplitter mussel (Lasmigona decorata). We assessed potential barriers for Yoknapatawpha Darters in the Mississippi-Yocona River watershed, and Bluehead Chubs in the Stevens Creek watershed, South Carolina, USA. We integrated Ucrit into the Southeast Aquatic Resources Partnership (SARP) barrier assessment protocol by estimating the proportion of individuals per species swimming at least as fast as the current through the assessed structures. Integrating Ucrit estimates into the SARP protocol considerably increased barrier severity estimates and rankings only for Yoknapatawpha Darters in the Yocona River watershed. These results indicate the importance of including species-specific swimming abilities in rapid barrier assessments and the importance of species-watershed contexts in estimating where swimming speed information might be most important. Our method has broad application for those working to identify barriers more realistically to improve species-specific fish passage. This work represents a next step in improving rapid barrier assessments and could be improved by investigating how results change with different measurements of swimming abilities and structure characteristics.

THE DIVERSITY AND ABUNDANCE OF CHAETODONTIDAE FAMILY AND ITS RELATIONSHIP WITH LIVE CORAL COVER IN SPERMONDE ISLANDS, MAKASSAR

Coral fish are one of the marine biotas that are highly sensitive to changes in coral reef ecosystems. Therefore, the presence or absence of specific reef fish species can describe the condition of coral reefs. The objective of the current study is to investigate the relationship between the biodiversity and abundance of Chaetodontidae fish and the live coral cover at 13 locations in the Spermonde area, Makassar City. Reef fish were counted using the Underwater Visual Census method. Coral cover percentages were determined using the Underwater Photo transects method. The results found 348 individuals of the Chaetodontidae family, comprising 21 species from four genera. The mean live coral cover categories in Spermonde were in pretty good condition (27.83%). Chaetodontidae in Spermonde Island was not diverse (mean H = 1.74) and not abundant (mean abundant = 721 ind./ha). There was a weak correlation between the diversity of Chaetodontidae and live coral cover, and also weak correlation between the abundance of Chaetodontidae and live coral cover in Spermonde Island, with R2 determination coefficient linear regression were 0.1697 and 0.0471, respectively.

Duet of ViT and CNN: multi-scale dual-branch network for fine-grained image classification of marine organisms

Fine-grained image classification of marine organisms involves dividing subcategories within a larger category. For instance, this could mean distinguishing specific species of fish or types of algae. This type of classification is more intricate than regular image classification, as the minor feature differences between subcategories are often concentrated in one or a few specific areas. Therefore, accurately identifying these critical regions and effectively using local features are crucial in improving the accuracy of fine-grained image classification. Existing methods for fine-grained image classification primarily rely on single-branch models based on convolutional neural networks (CNNs) or vision transformers (ViTs). Consequently, merging them allows for a more comprehensive understanding of marine organism images. In addition, marine organism images are affected by the distance and angle of the shot, making it challenging to capture detailed local nuances at a single scale. To address these challenges, we propose a multi-scale dual-branch network (MSDBN) that combines the strengths of ViT and CNN for fine-grained image classification of marine organisms. Our model uses a novel two-stage selection module to select discriminative regions from the ViT branch. Following this, the CNN branch executes a more detailed feature extraction on the local regions. To effectively utilise the multi-scale information of marine organisms, we introduce our designed multi-scale shift-window self-attention, specifically for the ViT branch. MSDBN demonstrates improved performance compared to existing classical methods and the best-performing dual-branch methods on three marine datasets. Our code is released publicly at https://github.com/Xiaosigz/MSDBN.

A large-scale passage evaluation for multiple fish species: Lessons from 82 fishways in lowland rivers and brooks

River networks worldwide are highly fragmented and this is particularly prevalent in the human-dominated lowland landscape of the Netherlands. Fishways function as measures to facilitate passage alongside barriers for fish communities and have been evaluated mostly in single case studies. We compared fish monitoring data of 82 fishways with data of fish observed in adjacent water stretches, conducting the first nationwide study on passage for the full spectrum of fish species present. In total, 35 out of 38 (92%) native species recorded in fishways' surroundings used fishways, while per fishway the median was 59% related to a variety of factors (fish behaviour, fishway type, monitoring design). The species using fishways most frequently were perch Perca fluviatilis (71/78 of fishways present), roach Rutilus rutilus (70/79) and gudgeon Gobio gobio (68/77). Logistic regression models showed the effect of monitoring duration and timing in detecting specific fish species ascending fishways. This large-scale analysis highlights the need to consider all native fish species during the design and monitoring of fishways. The obtained information from this study can be used by water managers for improving monitoring schemes and river connectivity which is an essential component for achieving the European Water Framework Directive goals.

Environmental DNA biomonitoring reveals the human impacts on native and non-native fish communities in subtropical river systems

Subtropical rivers are one of the hotspots of global biodiversity, facing increased risks of fish diversity changes and species extinction. However, until now, human impacts on native and non-native fish communities in subtropical rivers still lack sufficient effort. Here, we used the environmental DNA (eDNA) approach to investigate fish communities in the Dongjiang River of southeast China, a typical subtropical river, and explored the effects of regional land use and local water pollution on fish taxonomic and functional diversity. Our data showed that 90 species or genera of native fish and 15 species or genera of non-native fish were detected by the eDNA approach, and there was over 85% overlap between eDNA datasets and historical records. The taxonomic and functional diversity of all, native and non-native fish communities showed consistent spatial patterns, that is, the upstream of the tributary was significantly higher than that of the mainstream and downstream. Land use and water pollution such as COD and TP were the determinants in shaping the spatial structure of fish communities, and water pollution explained 31.56%, 29.88%, and 27.80% of the structural variation in all, native and non-native fish communities, respectively. The Shannon diversity and functional richness of native fish showed a significant downward trend driven by COD (pShannon = 0.0374; pfunctional = 0.0215) and land use (pShannon = 0.0159; pfunctional = 0.0441), but they did not have significant impacts on non-native fish communities. Overall, this study emphasizes the inconsistent response of native and non-native fish communities to human impacts in subtropical rivers, and managers need to develop strategies tailored to specific fish species to effectively protect water security and rivers.

Microscopic Analysis of Cell Fate Alteration Induced by Cell Fusion.

In mammals, differentiated cells generally do not de-differentiate nor undergo cell fate alterations. However, they can be experimentally guided toward a different lineage. Cell fusion involving two different cell types has long been used to study this process, as this method induces cell fate alterations within hours to days in a subpopulation of fused cells, as evidenced by changes in gene-expression profiles. Despite the robustness of this system, its use has been restricted by low fusion rates and difficulty in eliminating unfused populations, thereby compromising resolution. In this study, we address these limitations by isolating fused cells using antibody-conjugated beads. This approach enables the microscopic tracking of fused cells starting as early as 5 hours after fusion. By taking advantage of species-specific FISH probes, we show that a small population of fused cells resulting from the fusion of mouse ES and human B cells, expresses OCT4 from human nuclei at levels comparable to human induced pluripotent stem cells (iPSCs) as early as 25 hours after fusion. We also show that this response can vary depending on the fusion partner. Our study broadens the usage of the cell fusion system for comprehending the mechanisms underlying cell fate alterations. These findings hold promise for diverse fields, including regenerative medicine and cancer.

Nutritional Fish Diseases in Aquaculture: A Human Health Hazard or Mythical Theory: An Overview

To consume or not to consume farmed fish diagnosed with nutritional disorders within an aquaculture culture system is a question that resonates with fisheries and aquaculture experts worldwide. Proper fish health management in aquaculture should be a critical area of concern for all fish farmers. It has become a fundamental requirement for achieving sustainable aquaculture production. However, many fish farmers, particularly in developing countries lack knowledge about nutritional fish diseases and how to effectively manage them on the farm. Like human health, farmed fish’s health in aquaculture systems should be a daily priority for fish farmers. Nutritional fish diseases are often overlooked by the majority of fish farmers, even at the commercial level. Most Fish farmers may not realize that nutritional disease prevention can be achieved through the use of well-formulated fish feeds that meet all the nutritional requirements for fish growth. Additionally, maintaining good water quality and implementing best management practices are essential to ensure that the fish stock remains healthy in the culture system. Since different fish species have varying nutritional dietary requirements, it is important to formulate the right nutritional diet based on the specific fish species being cultured. Fish feeds should contain the necessary nutrients to ensure opportunistic disease resistance. Furthermore, fish farmers should be familiar with early diagnosis techniques for nutritional fish disease disorders. This ensures that the harvested fish reaching the market does not raise concerns about the quality and safety of farmed fish products. Failure to diagnose nutritional disorders associated with poor feeds and diets can create doubts in the rapidly growing aquaculture industry. Therefore, this review aims to explore the nutritional requirements of farmed fish species, the impact of nutritional deficiencies on human and public health, the causes of nutritional disorders, and viable therapies for managing these diseases in farmed fish. The data for this review article were collected from various secondary sources, including internationally reputable peer-reviewed articles, conference proceedings reports, internet searches, and more. The findings highlight the importance of providing aquaculture farmers with essential information on fish nutrition-related disease control, as nutritional diseases have been found to be detrimental to fish health and public health. Moreover, many farmed fish affected by nutritional disorders have entered the global fish market, raising questions about their impact on human health. Therefore, it is crucial for fish farmers to prioritize early diagnosis of nutritional fish diseases to ensure the safety of farmed fish in the market and maintain consumer confidence in farmed fish globally. The study recommends further research into the potentially lethal effects of different nutritional fish diseases, particularly when consumed in large quantities and to the environment especially when dead fish is discarded in the backwaters of an aquatic ecosystem.

Evaluation of Threatened, Endangered, and Rare Fish Species and Communities of the St. Lawrence River and Its Tributaries in the United States

Biodiversity is responsible for important ecological processes like productivity and ecosystem stability, and rare species are a major component of biodiversity. Rarity increases a species' vulnerability to disturbances and also makes them difficult to study. Globally, species of freshwater systems are some of the most threatened, and evaluation of rare freshwater species and their habitats is needed to help preserve natural flexibility and ecological function. We conducted an analysis of full fish communities of the upper St. Lawrence River and its major US tributaries, with the goals of determining species locations and abundances, associated environmental conditions, the distribution of distinct fish assemblages across the landscape (with emphasis on communities supporting rare species), and potential threats. From 2009 to 2015, the US Geological Survey (USGS) and Saint Regis Mohawk Tribe (SRMT) worked together using standardized methods to collect community samples within 4 different aquatic realms (shallow and deep lentic, and small and large lotic systems) and determine species-specific fish abundances, frequencies of occurrence, and associated habitat signatures and spatial distributions. Distinct fish assemblages and associated habitat conditions were objectively identified by multivariate and hypothesis-testing methods. We used a geographic information system (GIS) to spatially associate habitat, biotic, and landscape attributes within each stream reach throughout the study area, facilitating quantification of distribution patterns. Comparisons with historical data provided estimates of loss or gain of threatened and endangered species (T&E) colonies. We developed a disturbance index to highlight potential threats to aquatic species. More than 140,000 fishes of 87 species were collected from a total of 1140 sample sites, covering 278 stream reaches, including the endangered Notropis anogenus (Pugnose Shiner), and threatened Hiodon tergisus (Mooneye), Etheostoma pellucidum (Eastern Sand Darter), and Acipenser fulvescens (Lake Sturgeon). We identified 50 distinct fish assemblages differing in species composition, abundance, and/or diversity, but only 13 of those assemblages included a T&E species. The rareness, extent, and patchiness of fish assemblages created a mosaic of fish communities across the landscape, from headwaters to the mainstem of the St. Lawrence River. Comparisons with historic surveys (1978–2008) showed a stable number of T&E species colonies or an increase for some species. The geographic distribution of multimetric disturbance index values showed where combinations of disturbances to fish habitats might affect rare fish species and aquatic communities in the region. The species–habitat associations and fish assemblage distributions can be used for evaluation of species, communities, or habitats that may need protection or restoration.

Robust features extraction from shape signature for fish images classification

Recently, the process of fish species classification has become one of the most challenging problems addressed by researchers. In this work, a robust scheme to classify fish images based on robust feature extraction from shape signatures is proposed. First, the image contour is fitted using one of the common approaches named radial basis function neural network (RBFNN) fitting to obtain image centroid. Afterward, prominent features from the shape signature are extracted. These features are representative of fish shapes because they can distinguish the characteristics of each class as well as being relatively robust to scale and rotation changes. Finally, for the classification process purpose, RBFNN is used again for image classification against one of the most commonly used classification techniques called support vector machine (SVM). The proposed paradigm has been applied to a standard fish dataset acquired from a live video dataset grouped into twenty-three clusters representing specific fish species. The resulting accuracy based on SVM and RBFNN was 90.41% and 98.04%, respectively.

Three-Dimensional-Printed Coral-like Structures as a Habitat for Reef Fish

Coral reefs are three-dimensional biogenic structures that provide habitat for plenty of marine organisms; yet, coral reefs are deteriorating worldwide. Hence, it is essential to identify suitable substitutes for such coral services. This study examines reef fishes’ behavior and reactions to three-dimensional-printed (3DP) corals based on scanned Stylophora pistillata, as well as modified 3DP models. In particular, fishes’ unresponsiveness to the color, shape, morphology, and material of 3DP models both in vitro and in situ experiments was investigated. Coral reef fishes responded to the 3DP corals and demonstrated their usage in a range of services. Moreover, a greater number of fish species interacted more with 3DP models than they did with live corals. Furthermore, specific reef fish species, such as Sea Goldies (Pseudanthias squamipinnis), showed a preference for specific 3DP coral color, and other species demonstrated preferences for specific 3DP model shapes. The current study results show that three-dimensional-printed coral models can substitute for live corals for certain types of reef fish services.

Using eDNA sampling for species-specific fish detection in tropical oceanic samples: limitations and recommendations for future use.

Over the past decade, environmental DNA (eDNA) has become a resourceful tool in conservation and biomonitoring. Environmental DNA has been applied in a variety of environments, but the application to studies of marine fish, particularly at tropical latitudes, are limited. Since many commercially important Caribbean fishes are overexploited, these species are optimal candidates to explore the use of this method as a biomonitoring tool. Specifically, for many of these species, the formation of fish spawning aggregations (FSAs) marks a critical life history event where fishes will gather in large numbers for reproduction. These FSAs are ephemeral in nature, lasting only a few days, but are predictable in time and space which makes them susceptible to overfishing. In this study, we test the feasibility of using an eDNA sampling approach (water and sediment collection) to detect the presence of known FSAs off the west coast of Puerto Rico, with cytochrome c oxidase subunit 1 (CO1) and 12S rRNA (12S) primers designed to target specific species. A total of 290 eDNA samples were collected and, of those, 206 eDNA samples were processed. All eDNA samples varied in DNA concentration, both between replicates and collection methods. A total of 12 primer sets were developed and tested using traditional PCR and qPCR. Despite validation of primer accuracy and sample collection during known peak spawning times, the use of traditional PCR and qPCR with both molecular markers failed to produce species-specific amplification. Thus, a trial test was conducted using the CO1 primers in which target fish DNA was 'spiked' at various concentrations into the respective eDNA samples to determine the target species DNA concentration limit of detection. Upon successful amplification of the trial, results indicated that eDNA samples were below the detection threshold of our methods, suggesting that the number of fish present at the spawning aggregations was inadequate for single-species detection methods. In addition, elements such as the unavoidable presence of non-target DNA, oceanic environmental conditions, shedding rates of target fish, among other biotic and abiotic factors could have affected DNA persistence and degradation rates at the sites. We provide recommendations for species-specific fish detection in lower latitudes, and suggestions for studies aiming to monitor or detect fish spawning aggregations using eDNA sampling.

FishAI: The Lodestar fishing platform


 
 
 Lodestar is a web app for fishers to improve their efficiency at sea, by giving valuable input to the decision making on where to fish and which route to take. It combines historical catch data with environmental data to predict the most likely location of 10 different species across the Nordic seas, and shows it in an interactive map. It is both time sensitive and allows the user to plug in preferences to best show where specific fish species have historically been in the current conditions and suggest a route for the coming week.
 
 

Susceptibility of three indigenous Indonesian fish species: mahseer (Tor soro), snakehead (Channa striata), and bagrid catfish (Hemibagrus nemurus) against parasites infection

Abstract Mahseer "dewa" (Tor soro), snakehead "gabus" (Channa striata), and bagrid catfish "baung" (Hemibagrus nemurus) are local specific fish species that are promising to be developed as freshwater aquaculture commodities in Indonesia. Disease cases/outbreaks in those fish farming have often been reported, however, there is not much information on the epizootiology and disease status of those fish species. The susceptibility of those fish to parasitic infection was evaluated by natural and artificial infection. Natural infection was conducted by randomly sampling 20 fish at 5-day intervals and lasting for 30 days. In artificial infection, 150 tested fish cohabited with 40 parasite-carrying fish that were known to be definitely infected by the parasite. The observation was carried out by sampling 20 fish at 5-day intervals and lasting for 30 days. The results showed that the three fish species were susceptible to infection with Trichodina spp, Epistylis spp, Tetrahymena spp, Ichtyophthirius multifiliis, Dactylogyrus spp, and Gyrodactylus spp, while the helminth parasite Pallisentis nagpurensis (Acanthocephala) was only identified in snakehead. A number of parasites such as I. multifiliis, Dactylogyrus spp., and Gyrodactylus spp. are likely to be potential obstacles in the cultivation of those fish species, especially in hatcheries and nurseries. Keywords: mahseer, snakehead, bagrid catfish, parasites

Pipeline, Pathway, Burrow

Pipeline, Pathway, Burrow