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17 results for “invasive species detection”
Figure 2 in A workshop to advance invasive species early detection capacity of The Rapid Environmental DNA Assessment and Deployment Initiative & Network (READI-Net)
Figure 2. The Rapid Environmental (e)DNA Assessment and Deployment Initiative & Network (READI-Net) project components being developed to support molecular detection of invasive species. Molecular tools, like eDNA sampling, are sensitive and costeffective for early detection of invasive species and are one component of the National Early Detection Rapid Response framework.
Figure 1 in A workshop to advance invasive species early detection capacity of The Rapid Environmental DNA Assessment and Deployment Initiative & Network (READI-Net)
Figure 1. The National Early Detection Rapid Response framework developed by the U.S. Department of the Interior Invasive Species Task Force. Open circles represent the components to be enacted for effective early detection and rapid response of invasive species. The associated commentary reflects the primary questions, observations, and directives that the process from one component to the next. At the core of the process, are the informational inputs necessary for management decision-making.
Explainable few-shot learning workflow for detecting invasive and exotic tree species
<p>This is the supporting dataset of research work: <a href="Link"><strong>Explainable few-shot learning workflow for detecting</strong></a> <a href="Link"><strong>invasive and exotic tree species</strong></a>. (Link to be added after the publication) In this research, we presents a workflow that tackles both challenges by proposing an explainable few-shot learning workflow for detecting invasive and exotic tree species in the Atlantic Forest of Brazil using Unmanned Aerial Vehicle (UAV) images. By integrating a Siamese network with explainable AI (XAI), the workflow enables the classification of tree species with minimal labeled data while providing visual, case-based explanations for the predictions.</p> <p>The workflow is accessible in <a href="Link">this GitHub repository</a> (Link to be added after the publication). The required dataset of this workflow in provided in this Zenodo repository.</p> <p>This dataset repository has the following contents</p> <ul> <li> <p>uav_img.zip: the UAV orthomosaic image (.tif) of the study area used in this research, with related metadata</p> </li> <li>tree_labels.zip: the labels of trees created by expert, available in .shp and .gpkg</li> <li> <p>cutouts.zip: tree cutouts used in this study. They are two sub-directories:</p> <ul> <li>all_cutouts: all the candidated cutouts from three sources. See the README.md file insisde this folder for more information</li> <li>selected cutout: the manually selected cutouts from all cutouts used for training.</li> </ul> </li> <li> <p>training_pairs_20000.zarr.zip: training data created for base network traning. It is created by pairing the selected cutouts.</p> </li> <li>netflora.zip: Netflora workflow prediction results</li> <li>optimized_models.zip: Optimized base models (shallow and deep) and refined models with different shots/fold setup.</li> <li>n_fold_x_validation.zip: data pairs for refinement traing, with n fold and x valiation setup.</li> </ul>
Data for: Environmental DNA storage and extraction method affects detectability for multiple aquatic invasive species
<p>Environmental DNA (eDNA) refers to genetic material released by organisms into their surrounding environment. Collecting and identifying eDNA has gained popularity for monitoring and surveillance of aquatic invasive species. Invasive species management is most successful when an invasion is identified early while population size is likely to be low, highlighting the importance of eDNA detection sensitivity. Various factors influence DNA yield recovered from environmental samples. Environmental DNA storage and extraction methods, for example, can be adjusted to maximize DNA yield, thereby improving detectability. In this study, we compared the performance of two eDNA storage and extraction methods in detecting three common aquatic invasive species (<em>Bythotrephes longimanus</em>, <em>Dreissena polymorpha</em>, and <em>Faxonius rusticus</em>) across five natural ecosystems of Minnesota, United States. One method involved storing filters in 95% ethanol (EtOH) and extracting DNA using a DNeasy PowerSoil Pro Kit (Qiagen, Hilden, Germany), whereas the other method used cetyl trimethylammonium bromide (CTAB) for storage and a phenol–chloroform–isoamyl (PCI) procedure for DNA extraction. We also investigated the effect of DNA extract volume (1 μL relative to 3 μL) in qPCR reactions on eDNA detections for the commercial kit method. The CTAB‐PCI method yielded significantly more positive detections, across all three species, compared to the EtOH‐Qiagen method. Moreover, we found that using 1 μL of DNA extract in qPCR reactions was equally effective as using 3 μL. To improve detections of aquatic invasive species, we recommend that researchers store eDNA sample filters in CTAB or a similar lysis buffer such as Longmire's solution and extract with PCI when feasible, but note that lower extract volumes might be used without negative effect when either increasing technical replicates or repurposing samples for the detection of multiple species.</p>
Data from: Detecting aquatic invasive species in bait and pond stores with targeted environmental (e) DNA high-throughput sequencing metabarcode assays: angler, retailer, and manager implications
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Data for: Environmental DNA storage and extraction method affects detectability for multiple aquatic invasive species
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Ichthyoplankton metabarcoding: an efficient tool for early detection of invasive species establishment
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Data from: Using ABC and microsatellite data to detect multiple introductions of invasive species from a single source
The introduction of invasive species to new locations (that is, biological invasions) can have major impact on biodiversity, agriculture and public health. As such, determining the routes and modality of introductions with genetic data has become a fundamental goal in molecular ecology. To assist with this goal, new statistical methods and frameworks have been developed, such as approximate Bayesian computation (ABC) for inferring invasion history. Here, we present a model of invasion accounting for multiple introductions from a single source (MISS), a heretofore largely unexplored model. We simulate microsatellite data to evaluate the power of ABC to distinguish between single and multiple introductions from the same source, under a range of demographic parameters. We also apply ABC to microsatellite data from three invasions of bumblebee in New Zealand. In addition, we assess the performance of several methods of summary statistics selection. Our simulated results suggested good ability to distinguish between one- and two-wave models over much but not all of the parameter space tested, independent of summary statistics used. Globally, parameter estimation was good except for bottleneck timing. For one of the bumblebee species, we clearly rejected the MISS model, while for the other two we found inconclusive results. Since a second wave may provide genetic reinforcement to initial colonists, help relieve inbreeding among founders, or increase the hazard of the invasion, its detection may be crucial for managing invasions; we suggest that the MISS model could be considered as a potential model in future theoretical and empirical studies of invasions.
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.
Supplementary material 1 from: Erdélyi A, Hartdégen J, Malatinszky Á, Vadász C (2023) Historical reconstruction of the invasions of four non-native tree species at local scale: a detective work on Ailanthus altissima, Celtis occidentalis, Prunus serotina and Acer negundo. One Ecosystem 8: e108683. https://doi.org/10.3897/oneeco.8.e108683
Derived data of Ailanthus altissima, Celtis occidentalis, Prunus serotina and Acer negundo from the National Forestry Database and its archives.
Data from: Environmental DNA surveillance for invertebrate species: advantages and technical limitations to detect invasive crayfish Procambarus clarkii in freshwater ponds
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Data from: Using ABC and microsatellite data to detect multiple introductions of invasive species from a single source
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Data from: Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries
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Data from: An examination of the accuracy of a sequential PCR and sequencing test used to detect the incursion of an invasive species: the case of the red fox in Tasmania
1. Polymerase Chain Reaction (PCR) diagnostic tests are increasingly applied to the identification of wildlife. Yet rigorous verification is rare and the estimation of test accuracy (the probability that true positive and true negative samples are correctly identified – test sensitivity and specificity, respectively), particularly in combination with sequencing, is uncommon. This is important because PCR-based tests are prone to contamination in sampling and the laboratory. 2. Here, we use an experimental case–control approach to estimate the sensitivity and specificity of a sequential PCR-based wildlife detection test used to identify incursions of red foxes into Tasmania from predator faeces (scats). 3. Our results show that the sensitivity of the fox test is high (~94%) for the PCR-based test on its own, but this decreases to ~84% when combined with the DNA sequencing step. In contrast, the specificity increases from ~96% in the PCR only test to ~99.6% after inclusion of the DNA sequencing step. 4. The intense public scrutiny of the fox eradication program in Tasmania, has undoubtedly influenced the application of a sequential PCR test that maximises specificity at the expense of sensitivity and so increases the risk that scats containing fox DNA would not be detected. This could lead to the establishment of foxes in Tasmania as a consequence. 5. Synthesis and applications. Importantly, the estimation of the sensitivity and specificity of sequential tests enables decisions about the risk associated with mistaken identification (i.e. false negatives vs false positives) to be quantified for decision makers. The cost of false negative errors should be balanced against the costs of false positive errors, which could include the expenditure incurred in the application of unnecessary management actions were foxes not in fact present. Understanding the risks and costs associated with both false negative and false positive errors is therefore a key component to the decision making process for the management of the Tasmanian fox incursion.
Supplementary material 1 from: Roques A, Ren L, Rassati D, Shi J, Akulov E, Audsley N, Auger-Rozenberg M-A, Avtzis D, Battisti A, Bellanger R, Bernard A, Bernadinelli I, Branco M, Cavaletto G, Cocquempot C, Contarini M, Courtial B, Courtin C, Denux O, Dvořák M, Fan J-t, Feddern N, Francese J, Franzen EKL, Garcia A, Georgiev G, Georgieva M, Giarruzzo F, Gossner M, Gross L, Guarneri D, Hoch G, Hölling D, Jonsell M, Kirichenko N, Loomans A, Luo Y-q, McCullough D, Maddox C, Magnoux E, Marchioro M, Martinek P, Mas H, Mériguet B, Pan Y-z, Phélut R, Pineau P, Ray AM, Roques O, Ruiz M-C, Sarto i Monteys V, Speranza S, Sun J-h, Sweeney JD, Touroult J, Valladares L, Veillat L, Yuan Y, Zalucki MP, Zou Y, Žunič-Kosi A, Hanks LM, Millar JG (2023) Worldwide tests of generic attractants, a promising tool for early detection of non-native cerambycid species. In: Jactel H, Orazio C, Robinet C, Douma JC, Santini A, Battisti A, Branco M, Seehausen L, Kenis M (Eds) Conceptual and technical innovations to better manage invasions of alien pests and pathogens in forests. NeoBiota 84: 169-209. https://doi.org/10.3897/neobiota.84.91096
Total trapping network
Data from: An examination of the accuracy of a sequential PCR and sequencing test used to detect the incursion of an invasive species: the case of the red fox in Tasmania
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Data from: Detecting an elusive invasive species: a diagnostic PCR to detect Burmese python in Florida waters and an assessment of persistence of environmental DNA
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.