Kenai National Wildlife Refuge Aquatic Invasive Plant Surveys - 2024 Survey Data

Enregistrements de données

Les données de cette ressource occurrence ont été publiées sous forme dune Archive Darwin Core (Darwin Core Archive ou DwC-A), le format standard pour partager des données de biodiversité en tant quensemble dun ou plusieurs tableurs de données. Le tableur de données du cœur de standard (core) contient 478 enregistrements.

1 tableurs de données dextension existent également. Un enregistrement dextension fournit des informations supplémentaires sur un enregistrement du cœur de standard (core). Le nombre denregistrements dans chaque tableur de données dextension 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 naffiche que les versions publiées de la ressource accessibles publiquement.

Comment citer

Les chercheurs doivent citer cette ressource comme suit:

Bowser M, Artaiz S, Davis N, Farmer K, Magee J, Morassutti M, Stone M, Umholtz A, Watts D (2025). Kenai National Wildlife Refuge Aquatic Invasive Plant Surveys - 2024 Survey Data. Version 1.7. United States Fish and Wildlife Service. Occurrence dataset. https://ipt.gbif.us/resource?r=kenai-national-wildlife-refuge-aquatic-invasive-plant-surveys-2024-survey-data&v=1.7

Droits

Les chercheurs doivent respecter la déclaration de droits suivante:

L’éditeur et détenteur des droits de cette ressource est United States Fish and Wildlife Service. En vertu de la loi, léditeur 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 lUUID GBIF suivante : a3030de7-23da-4767-86ed-544bfe43bd31.  United States Fish and Wildlife Service publie cette ressource, et est enregistré dans le GBIF comme éditeur de données avec lapprobation du GBIF-US.

Mots-clé

Occurrence; Observation

Données externes

Les données de la ressource sont disponibles dans dautres formats

Contacts

Couverture géographique

The geographic extent included freshwater lakes in the vicinity of the Kenai National Wildlife Refuge, Kenai Peninsula, Alaska, USA.

Couverture taxonomique

We surveyed for all non-native freshwater plants that could occur in this area, but with a particular focus on northern elodea.

Couverture temporelle

Données sur le projet

To maintain biological integrity, biological diversity, and native fish resources in Kenai Peninsula freshwater systems through detection and then eradication of potential populations of northern pike and elodea, we initiated a survey for northern pike and elodea in Kenai Peninsula lakes.

Les personnes impliquées dans le projet:

Méthodes déchantillonnage

Our methods for this project were documented by Bowser and Davis (2024). We selected 16 lakes to survey for elodea in 2024, basing our selections on the Alaska Department of Fish and Game’s Invasive Species Lake Prioritization (Alaska Department of Fish and Game, 2022). We also took into account recent elodea surveys, avoiding lakes that had been surveyed for pike in the last 10 years. We collaboratively planned our survey schedule with our partners. We sought to keep the number of sites sampled per lake to between 30 and 60 sampling locations per lake. We related the range of lake perimeters in our study area to this range of sample sizes with the linear formula , where where was the sample size, was 2.4 km-1, was the perimeter in km, and was 27. This resulted in a range of sample sizes of 30 to 63 sampling locations per lake. We divided the lake perimeters into segments, one segment corresponding to a target sampling location in each lake. To generate sampling segments we used a Quarto script (Bowser, 2024b) that ran R, version 4.3.3 (R Core Team, 2024) and loaded the packages gt, version 0.11.0 (Iannone et al., 2024); lwgeom, version 0.2-14 (Pebesma, 2024); and sf, version 1.0-16 (Pebesma, 2018; Pebesma and Bivand, 2023). The resulting table of coordinates was converted to GPS exchange format (GPX) using DNRGPS version 6.1.0.6 (https://gisdata.mn.gov/dataset/dnrgps, https://maps1.dnr.state.mn.us/dnrgps/index.html)

Description des étapes de la méthode:

1. Our rake throw survey methods mostly follow Sethi et al. (2017). Within each pre-determined lake segment, we selected a location where elodea would be most likely to occur based on our previous experience surveying for elodea on the Kenai Peninsula. Within the segments we selected protected bays and avoided exposed points. We positioned our boat off of shore, usually a little farther from shore than the limit of dense emergent vegetation, often in about 1–2 m water depth. From the selected point the two observers threw the two throw rakes perpendicular to the shoreline: one rake thrown toward shore and the other out toward the center of the lake. After allowing the rakes to contact the bottom, both observers slowly and simultaneously pulled in the rakes, dragging them over the substrate. The rakes were carefully brought onto the boat and the presence or absence of elodea was recorded. We also recorded depth, substrate types, and the presence of other aquatic plant species. Data were entered into a Survey123 form (Bowser, 2024a).
2. Elodea survey data were reformatted for publication to GBIF using a Quarto document (Bowser, 2025) that ran R, version 4.4.2 (R Core Team, 2024) and using the package sf, version 1.0-20 (Pebesma, 2018; Pebesma and Bivand, 2023).

Citations bibliographiques

1. Alaska Department of Fish and Game (2022) Alaska invasive species lake prioritization. Alaska Department of Fish and Game. https://experience.arcgis.com/experience/41a6f3a3f35f4e0fae52f9c5a0c2fbd2/ https://experience.arcgis.com/experience/41a6f3a3f35f4e0fae52f9c5a0c2fbd2/
2. Bowser ML (2024a) Kenai National Wildlife Refuge aquatic invasive plant survey 2024 Survey123 XLSForm. Soldotna, Alaska: United States Fish and Wildlife Service, Kenai National Wildlife Refuge. https://iris.fws.gov/APPS/ServCat/Reference/Profile/168311 https://iris.fws.gov/APPS/ServCat/Reference/Profile/168311
3. Bowser ML (2024b) Quarto Script for Generating Elodea Sampling Segments. Soldotna, Alaska: United States Fish and Wildlife Service, Kenai National Wildlife Refuge. https://iris.fws.gov/APPS/ServCat/Reference/Profile/168206 https://iris.fws.gov/APPS/ServCat/Reference/Profile/168206
4. Bowser ML (2025) Preparing data from Kenai National Wildlife Refuge’s 2024 elodea surveys for publication to GBIF. Soldotna, Alaska: United States Fish and Wildlife Service Kenai National Wildlife Refuge. https://iris.fws.gov/APPS/ServCat/Reference/Profile/186394 https://iris.fws.gov/APPS/ServCat/Reference/Profile/186394
5. Bowser ML & Davis N (2024) Site-specific protocol for aquatic invasive species management. Kenai National Wildlife Refuge. Soldotna, Alaska: United States Fish and Wildlife Service, Kenai National Wildlife Refuge. https://iris.fws.gov/APPS/ServCat/Reference/Profile/171396 https://iris.fws.gov/APPS/ServCat/Reference/Profile/171396
6. Iannone R, Cheng J, Schloerke B, Hughes E, Lauer A, Seo J, Brevoort K & Roy O (2024) gt: Easily create presentation-ready display tables. https://CRAN.R-project.org/package=gt https://CRAN.R-project.org/package=gt
7. Kenai National Wildlife Refuge & US Fish & Wildlife Service, Alaska Regional Office, Division of Conservation Planning & Policy (2010) Comprehensive Conservation Plan: Kenai National Wildlife Refuge. Anchorage, Alaska: U.S. Fish & Wildlife Service. https://iris.fws.gov/APPS/ServCat/Reference/Profile/149784 https://iris.fws.gov/APPS/ServCat/Reference/Profile/149784
8. Pebesma E (2018) Simple features for R: Standardized support for spatial vector data, The R Journal, 10(1), pp. 439–446. https://doi.org/10.32614/RJ-2018-009 https://doi.org/10.32614/RJ-2018-009
9. Pebesma E (2024) lwgeom: Bindings to selected ’liblwgeom’ functions for simple features. https://CRAN.R-project.org/package=lwgeom https://CRAN.R-project.org/package=lwgeom
10. Pebesma E & Bivand R (2023) Spatial data science: With applications in R. Chapman and Hall/CRC, p. 352. https://r-spatial.org/book/ https://r-spatial.org/book/
11. R Core Team (2024) R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/ https://www.R-project.org/
12. Sethi SA, Carey MP, Morton JM, Edgar Guerron-Orejuela, Decino R, Willette M, Boersma J, Jablonski J & Anderson C (2017) Rapid response for invasive waterweeds at the arctic invasion front: Assessment of collateral impacts from herbicide treatments, Biological Conservation, 212, Part A, pp. 300–309. https://doi.org/10.1016/j.biocon.2017.06.015 https://doi.org/10.1016/j.biocon.2017.06.015

Métadonnées additionnelles