Description
Because benthic macroinvertebrates and zooplankton are susceptible to the pesticide rotenone, we surveyed freshwater macroinvertebrates in the Miller Creek Watershed, Kenai Peninsula, Alaska ahead of a rotenone treatment in fall 2021 to eradicate a population of invasive northern pike (Esox lucius Linnaeus, 1758). We collected 32 samples in 2021 and another 32 post-treatment invertebrate samples in 2022 at the same places and during the same time of year to enable comparison of pre- and post-treatment freshwater invertebrate communities.
Enregistrements de données
Les données de cette ressource occurrence ont été publiées sous forme d'une Archive Darwin Core (Darwin Core Archive ou DwC-A), le format standard pour partager des données de biodiversité en tant qu'ensemble d'un ou plusieurs tableurs de données. Le tableur de données du cœur de standard (core) contient 9 101 enregistrements.
2 tableurs de données d'extension existent également. Un enregistrement d'extension fournit des informations supplémentaires sur un enregistrement du cœur de standard (core). Le nombre d'enregistrements dans chaque tableur de données d'extension est illustré ci-dessous.
Cet IPT archive les données et sert donc de dépôt de données. Les données et métadonnées de la ressource sont disponibles pour téléchargement dans la section téléchargements. Le tableau des versions liste les autres versions de chaque ressource rendues disponibles de façon publique et permet de tracer les modifications apportées à la ressource au fil du temps.
Versions
Le tableau ci-dessous n'affiche que les versions publiées de la ressource accessibles publiquement.
Comment citer
Les chercheurs doivent citer cette ressource comme suit:
Bowser M L, Artaiz S I, Danner J M, Dent K K, Meyer B, Watts D, Wyrick W R (2022): Metabarcoding Data from an Inventory of Freshwater Invertebrates from the Miller Creek Watershed, Kenai Peninsula, Alaska, USA. v1.3. United States Geological Survey. Dataset/Occurrence. https://bison.usgs.gov/ipt/resource?r=knwr_miller_creek_2021&v=1.3
Droits
Les chercheurs doivent respecter la déclaration de droits suivante:
L’éditeur et détenteur des droits de cette ressource est United States Geological Survey. En vertu de la loi, l'éditeur a abandonné ses droits par rapport à ces données et les a dédié au Domaine Public (CC0 1.0). Les utilisateurs peuvent copier, modifier, distribuer et utiliser ces travaux, incluant des utilisations commerciales, sans aucune restriction.
Enregistrement GBIF
Cette ressource a été enregistrée sur le portail GBIF, et possède l'UUID GBIF suivante : 9d7baaac-57db-4852-9993-7f0e7f15635b. United States Geological Survey publie cette ressource, et est enregistré dans le GBIF comme éditeur de données avec l'approbation du GBIF-US.
Mots-clé
Occurrence
Données externes
Les données de la ressource sont disponibles dans d'autres formats
| Miller Creek Watershed aquatic invertebrate inventory, raw metabarcoding data from the 2021 field season | https://ecos.fws.gov/ServCat/Reference/Profile/139306 UTF-8 FASTQ |
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Contacts
- Fournisseur Des Métadonnées ●
- Créateur ●
- Personne De Contact
http://orcid.org/0000-0003-4879-3997
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Couverture géographique
The geographic coverage is part of the Miller Creek watershed including North Vogel Lake, Vogel Lake, and Miller Creek.
| Enveloppe géographique | Sud Ouest [60,984, -150,515], Nord Est [61,005, -150,41] |
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Couverture taxonomique
Annelida, Arthropoda, Mollusca
| Phylum | Annelida, Arthropoda, Mollusca |
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Couverture temporelle
| Date de début / Date de fin | 2021-07-21 / 2022-08-29 |
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Données sur le projet
Because benthic macroinvertebrates and zooplankton are susceptible to the pesticide rotenone, surveys of freshwater macroinvertebrates were conducted in the Miller Creek Watershed, Kenai Peninsula, Alaska ahead of a planned rotenone treatment in fall 2021. Currently, 32 of 32 planned samples have been collected in 2021. Another 32 post-treatment invertebrate samples are planned in 2022 to enable comparison of pre- and post-treatment freshwater invertebrate communities.
| Titre | Inventory of Freshwater Invertebrates from the Miller Creek Watershed, Kenai Peninsula, Alaska, USA |
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| Identifiant | https://ecos.fws.gov/ServCat/Reference/Profile/139305 |
| Description du domaine d'étude / de recherche | The study area included North Vogel Lake, Vogel Lake, and Miller Creek in the Miller Creek watershed, Kenai Peninsula, Alaska, USA. |
| Description du design | At each of two visits per year we planned to collect 3 D-net samples, 3 Ekman dredge samples, and 2 Wisconsin net samples in Vogel Lake; 2 D-net samples, 2 Ekman dredge samples, and 1 Wisconsin net sample in North Vogel Lake; and 3 D-net samples in Miller Creek, a total of 16 invertebrate samples per visit, 32 samples per year, and 64 samples over the two year project. At North Vogel Lake, Vogel Lake, and upper Miller Creek we sampled twice in 2021: first on July 20--23 and second on August 28. We sampled at 15 sites using three methods. We failed to make it out to the mouth of Miller Creek in July and August, collecting samples there only on September 13, 2021. |
Les personnes impliquées dans le projet:
- Auteur
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Méthodes d'échantillonnage
Field methods generally followed the methods of Massengill (2014, 2017). We took vertical plankton tows in the deepest parts of the lakes using an Aquatic Research Instruments Wisconsin net. We sampled littoral areas using with D-nets. We obtained benthic samples using either an AMS Incorporated model 445.11 Ekman dredge or an AMS Incorporated model 445.60 stainless steel dredge. Most benthic samples were sorted using a series of sieves.
| Etendue de l'étude | The study extent included 3 D-net samples, 3 Ekman dredge samples, and 2 Wisconsin net samples in Vogel Lake; 2 D-net samples, 2 Ekman dredge samples, and 1 Wisconsin net sample in North Vogel Lake; and 3 D-net samples in Miller Creek, a total of 16 invertebrate samples per visit, sampled twice per year for a total of 32 samples per year. |
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Description des étapes de la méthode:
- Metabarcoding samples were stored in a -23 °C freezer exept when samples were being processed. Invertebrates were separated from debris by hand under a dissecting microscope. Care was taken to reduce possible crosscontamination of DNA among samples. Samples were shipped out on ice on September 29, 2021, arriving the next day at MR DNA (Shallowater, Texas, http://www. mrdnalab.com). We chose to use the mlCOIintF/jgHCO2198 primer set of Leray et al. (2013) for PCR, targeting a 313 bp region of the COI DNA barcoding region. The mlCOIintF/jgHCO2198 primer pair was used with barcode on the forward primer in a 30–35 PCR using the HotStarTaq Plus Master Mix Kit (Qiagen, USA) under the following conditions: 94 °C for 3 minutes, followed by 30– 35 cycles of 94 °C for 30 s, 53 °C for 40 seconds and 72 °C for 1 minute, after which a final elongation step at 72 °C for 5 minutes was performed. After amplification, PCR products were checked in 2% agarose gel to determine the success of amplification and the relative intensity of bands. Multiple samples were pooled together in equal proportions based on their molecular weight and DNA concentrations. Pooled samples were purified using calibrated Ampure XP beads. The pooled and purified PCR product was used to prepare an illumina DNA library. Sequencing was performed at MR DNA on a MiSeq following the manufacturer’s guidelines. We processed the raw sequence data on the USGS Yeti supercomputer (USGS Advanced Research Computing, 2021) using R, version 4.1.1 for manipulating data and Je, version 2.0.RC (Girardot et al., 2016) for demultiplexing. The raw data included reads in alternating directions with the sample barcodes only on one read. Accordingly, we exectued the je demultiplex command, accepting the defaults that only require one of the two reads to contain a sample barcode. Raw read data were processed using MetaWorks, version 1.9.5 (Porter and Hajibabaei, 2020), running the default analysis options for metazoan COI DNA barcode sequences. Sequences were identified using the RDP classifier, version 2.13 (Wang et al., 2007) and the CO1 Classifier, version 4.0.1 reference library (Porter, 2017; Porter and Hajibabaei, 2018). Finally, we also compared the sequences to libraries we had obtained in previous metabarcoding projects on the Kenai Peninsula.
Citations bibliographiques
- Massengill R (2014) Control Efforts for Invasive Northern Pike on the Kenai Peninsula, 2009. Special Publication 14-11. URL http://www.adfg.alaska.gov/FedAidPDFs/SP14-11.pdf http://www.adfg.alaska.gov/FedAidPDFs/SP14-11.pdf
- Massengill R (2017) Stormy Lake Restoration: Invasive Northern Pike Eradication, 2012. Special Publication 17-18, Alaska Department of Fish and Game, Divisions of Sport Fish and Commercial Fisheries. http://www.adfg.alaska.gov/FedAidPDFs/SP17-18.pdf http://www.adfg.alaska.gov/FedAidPDFs/SP17-18.pdf
- Leray M, Yang Y J, Meyer C P, Mills S C, Agudelo N, Ranwez V, Boehm J T, Machida R J (2013) A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Frontiers in Zoology https://doi.org/10.1186/1742-9994-10-34 https://doi.org/10.1186/1742-9994-10-34
- USGS Advanced Research Computing (2021) USGS Yeti Supercomputer. U.S. Geological Survey. https://doi.org/10.5066/F7D798MJ https://doi.org/10.5066/F7D798MJ
- Girardot C, Scholtalbers J, Sauer S, Su S-Y, Furlong E E (2016) Je, a versatile suite to handle multiplexed NGS libraries with unique molecular identifiers. BMC Bioinformatics 17:419. https://doi.org/10.1186/s12859-016-1284-2 https://doi.org/10.1186/s12859-016-1284-2
- Porter T M, Hajibabaei M (2020). METAWORKS: A flexible, scalable bioinformatic pipeline for multi-marker biodiversity assessments. BioRxiv, 2020.07.14.202960. https://doi.org/10.1101/2020.07.14.202960 https://doi.org/10.1101/2020.07.14.202960
- Wang Q,Garrity G M, Tiedje J M, Cole J R (2007) Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology 73:5261. https://doi.org/10.1128/AEM.00062-07 https://doi.org/10.1128/AEM.00062-07
- Porter T M (2017) Eukaryote CO1 Reference Set For The RDP Classifier. https://doi.org/10.5281/zenodo.4741447 https://doi.org/10.5281/zenodo.4741447
- Porter T M, Hajibabaei M (2018) Automated high throughput animal CO1 metabarcode classification. Scientific Reports 8:4226. https://doi.org/10.1038/s41598-018-22505-4 https://doi.org/10.1038/s41598-018-22505-4
Métadonnées additionnelles
| Identifiants alternatifs | 9d7baaac-57db-4852-9993-7f0e7f15635b |
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| https://doi.org/10.15468/49v6yh | |
| https://ipt.gbif.us/resource?r=knwr_miller_creek_2021 |