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52 results for “Fish Detection”
Fish tag data remotely detected using whole stream antennas or hand held tag readers in the Kuparuk, Itkilik, and Sagavanirktok drainages near Toolik Field Station, Alaska, from 2010 to 2017
From 2009 to 2017, the FISHSCAPE Project (grant numbers 1719267, 1417754, and 0902153), based at Toolik Field Station, has monitored physical, chemical, and biological parameters within three watersheds: The Kuparuk (including Toolik Lake and Toolik outlet stream); The Sagavanirktok (primarily Oksrukuyik Creek, but also including sections of the Ailish and Atigun Rivers and the Galbraith Lakes); and The Itkillik (primarily the I-Minus outlet stream, a tributary that that feeds into the Itkilik River). Target species were primarily Arctic grayling and Lake trout, although Arctic char, Burbot, Dolly varden, round whitefish, and slimey sculpin were also captured. This file contains the detectioned fish tags using whole stream or hand-held antennas in the three watersheds. We had no field season in 2014 and thus did not deploy antennaes. Fish were tagged with Passive Integrated Transponder (PIT) tags which can be read with a whole stream antenna to track the migration of the fish, predominately Arctic grayling, throughout the systems. Fish tags detected with a handheld readers are designated in Site ID as "XXX_capture". For "capture" fish time is arbitraily set at '7:00:00'' of the day of capture and tagging because actual time was not recorded. The individual fish data (date, tag number, length, weight, species) associated with the tag can be found in the 2009-2017_FISHSCAPE_fish_tagging file.
A deep learning dataset for underwater object detection of tropical freshwater fish species in northern Australia
<p>This dataset includes 44,112 images with 82,904 bounding box annotations for 23 tropical freshwater fish taxa from northern Australia. </p> <p>Images were derived from Remote Underwater Video (RUV) deployments in deep channel and shallow lowland billabongs, Kakadu National Park, Northern Territory Australia. RUV deployments were conducted during the <a href="https://www.dcceew.gov.au/science-research/supervising-scientist">Supervising Scientists</a> annual fish monitoring program in the 2016, 2017 and 2018 recessional flow period (dry season). More information can be found <a href="https://www.dcceew.gov.au/sites/default/files/documents/ss-atr-2020-21.pdf">here</a>.</p> <ul> <li>All images are in .jpg format and are 1920x1080 in dimension.</li> <li>Bounding box annotations are in COCO format. </li> </ul> <p>Two .zip files are included:</p> <ul> <li><a href="https://zenodo.org/api/files/990412db-e633-4f82-9b32-6990ef439ccd/202210-KakaduFishAI-CompactModel.zip">202210-KakaduFishAI-CompactModel.zip</a>: includes compact model weights in tensorflow format (.pb) trained using Azure's Custom Vision platform. This model is suitable for edge devices due to its reduced size. Code is provided to use the compact model for inferencing. </li> <li> <a href="https://zenodo.org/api/files/990412db-e633-4f82-9b32-6990ef439ccd/202210-KakaduFishAI-TrainingData.zip">202210-KakaduFishAI-TrainingData.zip</a>: includes all images and one COCO (.json) file with annotations. </li> </ul> <p>Fish taxa include: </p> <ol> <li><em>Ambassis agrammus</em></li> <li><em>Ambassis macleayi</em></li> <li><em>Amniataba percoides</em></li> <li><em>Craterocephalus stercusmuscarum</em></li> <li><em>Denariusa bandata</em></li> <li><em>Glossamia aprion</em></li> <li><em>Glossogobius</em> spp.</li> <li><em>Hephaestus fuliginosus</em></li> <li><em>Lates calcarifer</em></li> <li><em>Leiopotherapon unicolor</em></li> <li><em>Liza ordensis</em></li> <li><em>Megalops cyprinoides</em></li> <li><em>Melanotaenia nigrans</em></li> <li><em>Melanotaenia splendida inornata</em></li> <li><em>Mogurnda mogurnda</em></li> <li><em>Nemetalosa erebi</em></li> <li><em>Neoarius</em> spp.</li> <li><em>Neosilurus</em> spp.</li> <li><em>Oxyeleotris</em> spp.</li> <li><em>Scleropages jardinii</em></li> <li><em>Strongylura kreffti</em></li> <li><em>Syncomistes butleri</em></li> <li><em>Toxotes chatareus</em></li> </ol> <p>If you use this data for your own deep learning project we'd love to hear about how you used this dataset: andrew.jansen@environment.gov.au.</p>
Dataset for Multiplex-PCR detection and Nanopore-based genotyping of fish pathogens
<p>This is a revised zip file contains scripts, initial fastq files, assembled amplicon (public and from this study) as well as bioinformatics intermediate files used for this study.</p> <p>Changelog:</p> <p>1. Fixed a bug in the 02_consensus.sh to enable proper removal of amplicons with zero depth</p> <p>2. Added a script (06_unclassified_read.sh) to extract and annotate reads that previously could not align to the 4 reference gene segment. Now the previously unclassified reads will be re-align (raw fastq) back to the gene segments as well as an additional tilapia genome assembly to gauge amount of reads mapping to the host genome. Furthermore, any read that still fail to align with minimap2 was subsequently aligned using blastn (-word_size 15 -evalue 0.01) against the same sequences.</p> <p>File Structure and Descriptions</p> <p>├── 01_process.sh : primer trimming, length-based filtering, read alignment, alignment filtering (unique hit) and extraction of uniquely hit reads for consensus generation<br> ├── 02_consensus.sh : [need artic conda env] Generation of consensus based on uniquely-mapped reads and minimal read depth of 20x required to call a variant (or it will be masked)<br> ├── 03_cleanup.sh: General folder and intermediate file re-organization<br> ├── 04_filter.sh: [need quast conda env] statistic of consensus generated and filtering of consensus with one or more ambiguous base (N), not suitable for haplotype<br> ├── 05_cluster.sh: clustering of consensus based on 100% identity threshold to generate putative haplotype<br> ├── 06_unclassified_read.sh: Extraction and annotation of unclassified reads using lenient criteria and with host reference genome as added reference<br> ├── Amplicon_FastQ folder: uniquely mapped fastq files for consensus generation<br> ├── BAM: alignment files generated from minimap2 used as input for the artic pipeline to identify variants<br> ├── Cluster_Rep.txt: Consensus sequences that were chosen to represent each haplotype<br> ├── Consensus folder: consensus fasta files generated for each sample containing sequences for each specific pathogen<br> ├── Coverage folder: coverage and base-level read depth for each sample and each pathogen reference genes<br> ├── Filter: individual fasta sequences (only 1 sequence per file) for each pathogen and each sample without any ambiguous base for subsequent clustering analysis<br> ├── Full_Haplotype.fasta: all possible haplotype sequences generated for each pathogen<br> ├── Gap_Analysis.tsv: Table with percentage of gap (0-100%) for each consensus sequence generated (used for filtering)<br> ├── Haplotype folder: Intermediate file and sample-level haplotype used to infer final haplotype and generate haplotype summary<br> ├── Haplotype_summary.tsv: Table with sample ID and their respectively pathogen haplotype<br> ├── Minimap2_PAF: Intermediate alignment generated from minimap2 used to generate the count table<br> ├── FailMinimap2 folder: FastQ files that didn't align using minimap2. Will be subsequently aligned using blastN (more sensitive) against the same reference sequences as minimap2<br> ├── Host_4Pathogen.fasta: Fasta file containing the tilapia genome and 4 pathogen (primer binding site included)<br> ├── Original: fastq with original naming prior to renaming based on sampleID. a script (rename.sh) was included to show renaming scheme<br> ├── primer.fasta: Primer sequences used for identifying and trimming reads with flanking primer sequence<br> ├── primer.fasta.fai: the index file for primer.fasta<br> ├── PrimerTrim folder: Primer-trimmed reads<br> ├── quast_results: consensus statistics generated by quast<br> ├── RawCount.tsv: Count table generated that can used as a input to generate figure<br> ├── RawFastq folder: Raw reads that have been renamed to reflect sample information<br> ├── readme.md: The current readme file<br> ├── ref_full_latest.fasta: Reference sequence of (gene segments) 4 pathogens e.g. TilV, ISKNV, SAG (Streptococcus agalactiae), FNO (Francisella noatunensis subsp. orientalis)<br> ├── ref_full_latest.primer.fasta: Same as above but with their primer binding sequence trimmed similar to the processed reads<br> ├── ref_full_latest.primer.fasta.fai<br> ├── RenameHaplotype: Script to perform reorganization of cdhit output<br> ├── Seq.stat.tsv: Sequencing statistics<br> ├── Uniq_PAF: Minimap2 alignment file for raw reads that initially failed quality check (no primer present and/or less than 80% query coverage / not unique alignment)<br> ├── Unmap: Raw reads that initial failed quality check (no primer on both ends / less than 80% query coverage / not unique alignment) <br> └── VCF: VCF files from medaka variant calling used to generate the final consensus</p>
Data for: Optimizing a metabarcoding marker portfolio for species detection from complex mixtures of globally diverse fishes
<p>DNA metabarcoding is used to enumerate and identify taxa in both environmental samples and tissue mixtures, but the effectiveness of particular markers depends on their sensitivity to the taxa involved. Using multiple primer sets that amplify different genes can mitigate biases in amplification efficiency, sequence resolution, and reference data availability, but few empirical studies have evaluated markers for complementary performance. Here, we assess the individual and joint performance of 22 markers for detecting species in a DNA pool of 98 species of marine and freshwater bony fishes from geographically and phylogenetically diverse origins. We find that a portfolio of four markers targeting 12S, 16S, and two regions of COI identifies 100% of reference taxa to family and nearly 60% to species. We then use these four markers to evaluate metabarcoding of heterogeneous tissue mixtures, using experimental fishmeal to test: 1) the tissue input threshold to ensure detection; 2) how read depth scales with tissue abundance; and 3) the effect of non-target material in the mixture on recovery of target taxa. We consistently detect taxa that make up >1% of fishmeal mixtures and can detect taxa at the lowest input level of 0.01%, but rare taxa (<1%) were detected inconsistently across markers and replicates. Read counts showed only a weak correlation with tissue input, suggesting they are not a reliable quantitative proxy for relative abundance. Despite the limitations arising from primer specificity and reference data availability, our results demonstrate that a modest portfolio of markers can perform well in detecting and identifying aquatic species in complex mixtures despite heterogeneity in tissue representation, phylogenetic affinities, and from a broad geographic range.</p>
Data for: Optimizing a metabarcoding marker portfolio for species detection from complex mixtures of globally diverse fishes
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Data from: Fluid preservation causes minimal reduction of parasite detectability in fish specimens: a new approach for reconstructing parasite communities of the past?
<ol> <li>Long-term datasets are needed to evaluate temporal patterns in wildlife disease burdens, but historical data on parasite abundance are extremely rare. For more than a century, natural history collections have been accumulating fluid-preserved specimens, which should contain the parasites infecting the host at the time of its preservation. However, before this unique data source can be exploited, we must identify the artefacts that are introduced by the preservation process. Here, we experimentally address whether the preservation process alters the degree to which metazoan parasites are detectable in fluid-preserved fish specimens when using visual parasite detection techniques.</li> <li>We randomly assigned fish of three species (<i>Gadus chalcogrammus, Thaleichthys pacificus, Parophrys vetulus</i>) to two treatments. In the first treatment, fish were preserved according to the standard procedures used in ichthyological collections. Immediately after the fluid-preservation process was complete, we performed parasitological dissection on those specimens. The second treatment was a control, in which fish were dissected without being subjected to the fluid-preservation process. We compared parasite abundance between the two treatments.</li> <li>Across 298 fish individuals and 59 host–parasite pairs, we found few differences between treatments, with 24 of 27 host–parasite pairs equally abundant between the two treatments. Of these, one pair was significantly more abundant in the preservation treatment than in the control group, and two pairs were significantly less abundant in the preservation treatment than in the control group.</li> <li>Our data suggest that the fluid-preservation process does not have a substantial effect on the detectability of metazoan parasites. This study addresses only the effects of the fixation and preservation process; long-term experiments are needed to address whether parasite detectability remains unchanged in the months, years, and decades of storage following preservation. If so, ecologists will be able to reconstruct novel, long-term datasets on parasite diversity and abundance over the past century or more using fluid-preserved specimens from natural history collections.</li> </ol>
Data from: Development and validation of targeted environmental DNA (eDNA) metabarcoding for early detection of 69 invasive fishes and aquatic invertebrates
<p>Invasive species are of concern due to their impacts on ecosystems and economies, but they pose significant control challenges. Environmental DNA (eDNA) is a powerful tool in the detection of aquatic organisms at low densities due to high sensitivity and ease of collection. Aquatic eDNA analyses have increased worldwide and are generally either applied to a few target species (quantitative PCR) or for broad taxonomic applications (metabarcoding). Here we describe the development and testing of a hybrid approach that utilized high sensitivity PCR primer sets and high-throughput sequencing (HTS), referred to as <em>targeted metabarcoding</em>, to detect 69 fishes and invertebrates. We identified target species based on reports of globally important invasive species and developed two independent PCR primers for each species (CO1 and a second mtDNA region). We assessed sensitivity and eDNA interference for all 138 primers (2 per species, 69 species) using standard end-point PCR and tested them on 10 eDNA samples spiked with various amounts of one or more of the target species' DNA. The sensitivity of the 138 primer sets ranged between 1.5×10<sup>-5</sup> and 2.64 ng template DNA (mean = 0.069 ng). Primers were also tested for interference effects using plankton eDNA to simulate field conditions. The inclusion of interfering plankton DNA reduced the sensitivity for most primer sets by one or more orders of magnitude (range 0 to 3). Overall, our targeted metabarcoding resulted in the detection of ~ 98% of species in the DNA spiked samples, and, perhaps more importantly, the HTS read count was positively related to the quantity of spiked DNA (P < 0.002). We envision this technique being particularly useful for the early detection of species at low population densities; however, there are diverse applications of targeted metabarcoding for monitoring aquatic community composition and quantifying ecosystem change and health.</p>
Genomics-enabled mixed-stock analysis uncovers intraspecific migratory complexity and detects unsampled populations in a harvested fish
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Data from: Development and validation of targeted environmental DNA (eDNA) metabarcoding for early detection of 69 invasive fishes and aquatic invertebrates
Open the record for dataset details and reuse information.
Data from: Fluid preservation causes minimal reduction of parasite detectability in fish specimens: a new approach for reconstructing parasite communities of the past?
Open the record for dataset details and reuse information.
Data from: Redirection of ambient light improves predator detection in a diurnal fish
Cases where animals use controlled illumination to improve vision are rare and thus far limited to chemiluminescence, which only functions in darkness. This constraint was recently relaxed by studies on Tripterygion delaisi, a small triplefin that redirects sunlight instead. By reflecting light sideways with its iris, it has been suggested to induce and detect eyeshine in nearby microprey. Here, we test whether "diurnal active photolocation" also improves T. delaisi's ability to detect a cryptobenthic sit-and-wait predator Scorpaena porcus, a scorpionfish with strong daytime retroreflective eyeshine. Three independent experiments revealed that triplefins in which light redirection was artificially suppressed approached scorpionfish significantly closer than two control treatments before moving away to a safer distance. Visual modelling confirmed that ocular light redirection by a triplefin is sufficiently strong to generate a luminance increase in scorpionfish eyeshine that can be perceived by the triplefin over 6-8 cm under average conditions. These distances coincide well with the closest approaches observed. We conclude that light redirection by small, diurnal fish significantly contributes to their ability to visually detect cryptic predators, strongly widening the conditions under which active sensing with light is feasible. We discuss the consequences for fish eye evolution.
Underwater caustics disrupt prey detection by a reef fish
Natural habitats contain dynamic elements, such as varying local illumination: can such features mitigate the salience of organism movement? Dynamic illumination is particularly prevalent in coral reefs, where reticulate patterns known as 'water caustics' play chaotically in the shallows. In behavioural experiments with a wild-caught reef fish, the Picasso triggerfish (Rhinecanthus aculeatus), we demonstrate that the presence of dynamic water caustics negatively affects the detection of moving prey items, as measured by attack latency. Manipulating two features of water caustic form (sharpness and scale) implies that the masking effect should be most effective in shallow water. Due to the direct impact upon foraging efficiency, we expect the presence of water caustics to influence decisions about habitat choice and foraging by wild prey and predators.
Data from: Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries
The extraction and characterization of DNA from aquatic environmental samples offers an alternative, non-invasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next-generation sequencing ("metabarcoding"), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom designed group-specific primer set and next-generation sequencing for the detection of three species at risk; (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada; the Grand River and the Sydenham River. Out of 82 fish species detected in both rivers using capture-based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co-occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture-based methods, for improved mapping of species distribution patterns.
Data from: A new composite abundance metric detects stream fish declines and community homogenization during six decades of invasions
<p><b>Aim</b>:<b> </b>We developed a new technique, utilizing species-specific counts of individuals from historical fish community samples, to examine landscape-level, spatiotemporal trends in relative abundance distributions. Abundance-based historical distribution analyses are often plagued by data comparability issues, but provide critical information about community composition trends inaccessible to those using analyses based only on species presence-absence. We established trends in native and non-native fish abundance and community homogenization, uniqueness, and diversity to help local conservation managers prioritize targets and motivate similar studies globally to support fish conservation.</p> <p><b>Location</b>: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA.</p> <p><b>Methods</b>: We compiled catch data from 61 years of fish community surveys (1958-2019) and tested for community homogenization by comparing data from repeatedly sampled sites (1900s versus 2000s samples) using dispersion analyses. We measured community uniqueness (site contributions to beta diversity) and species diversity (Shannon index) at sampled streams to identify potential conservation hotspots. We then used regression analyses and Wilcoxon signed-rank tests to examine species-specific basin-wide and local abundance trends and identify species of potential conservation concern.</p> <p><b>Results</b>: Dispersion of sites in species-abundance space was significantly greater in the 1900s compared to the 2000s, indicating homogenization had occurred. Of 36 native species analyzed, 44.4% (16) showed basin-wide declines. Non-native species exhibited mixed patterns; site-level abundance increased in 2 of 15 species analyzed (13%).</p> <p><b>Main conclusions</b>: Our results indicate basin-wide community homogenization has occurred within the UMNR, but many unique and diverse communities persist. If conserved, these could help maintain regional fish diversity. We found basin-wide declines in four endemic species, as well as spread patterns of non-native and native species that were not detected by a presence-absence analysis applied within the same study area. This finding illustrates the importance of considering both species' abundance and occurrence patterns as separate dimensions of biodiversity to inform conservation planning.</p>
Data from: Comparison of fish detections, community diversity, and relative abundance using environmental DNA metabarcoding and traditional gears
Background <p>Detecting species at low abundance, including aquatic invasive species (AIS), is critical for making informed management decisions. Environmental DNA (eDNA) methods have become a powerful tool for rare or cryptic species detection; however, many eDNA assays offer limited utility for community‐level analyses due to their use of species‐specific (presence/absence) 'barcodes'. Metabarcoding methods provide information on entire communities based on sequencing of all taxon‐specific barcodes within an eDNA sample.</p> Aims <p>Evaluate measures of fish species detections, community diversity, and estimates of relative abundance based on eDNA metabarcoding and traditional fisheries sampling approaches in the context of fish community characterization and AIS survellience.</p> Materials and Methods <p>In 2016, eight limnologically diverse lakes (surface area range: 13 – 1,728 ha) in Michigan, USA were sampled using a variety of traditional fisheries gears to characterize fish community composition. Environmental DNAs from surface (33 ± 6, mean ± 1 SD) and benthic (14 ± 2) water samples from each lake were isolated and amplified for two metabarcoding markers (mitochondrial 12S and 16S rDNA loci) using fish‐specific primers. Fish species detected within each lake were determined by comparing the sequencing data to a database of sequences from native Michigan fish species and 19 AIS on the Michigan's Watch List.</p> Results <p>Analysis of species accumulation curves indicated multi‐locus eDNA metabarcoding assays can enhance species detection capacities and characterize 95% of a fish community in fewer sampling efforts than traditional gear (range: 2 – 62, median: 14). In addition, all AIS detected in traditional gear samples were also detected by eDNA, while some AIS detected by eDNA assays were absent from traditional gear samples.</p> Discussion <p>Results reported here are, in part, driven by the lack of species‐selectivity during eDNA sampling events. Given the efficacy of eDNA assays, we suggest multi‐locus eDNA metabarcoding assays be implemented in early detection efforts.</p>
Fish eDNA detections in ports mirror fishing fleet activities and highlight the spread of non-indigenous species in the Mediterranean Sea. Environmental DNA Metabarcoding DATASET
<p>Environmental DNA metabarcoding data set. Environmental samples were collected in 2018 (one sample replicate of 2L surface water) and 2019 (four replicates of 1 L surface water) from several Mediterranean ports and data were generated using 12S rRNA and mitochondrial COI. For each sampling campaign (2018 and 2019) and marker two sheets are presented (with the same numeration): the first one represents all the ASV/MOTUs after the bioinformatics pipelines; the second one shows the curated assignment. The last two sheets are the OTU tables (presence-absence).</p>
Multicenter Validation of the Sensitivity of Theranostic ALK Rearrangement Detection by FISH Analysis and Prevalence of Escaping Mutations in Circulating Tumor Cells for the Non-invasive Management of
ClinicalTrials.gov study NCT02372448. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PNA FISH, PCR and Gram Staining for Detection of Bacterial Vaginosis - a Comparative Clinical Study in a Danish IVF Setting
ClinicalTrials.gov study NCT02042352. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Comparison of fish detections, community diversity, and relative abundance using environmental DNA metabarcoding and traditional gears
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Data from: A new composite abundance metric detects stream fish declines and community homogenization during six decades of invasions
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