Kenai National Wildlife Refuge Aquatic Invasive Plant Surveys 2023

Data Records

The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 476 records.

2 extension data tables also exist. An extension record supplies extra information about a core record. The number of records in each extension data table is illustrated below.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versions

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Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is United States Fish and Wildlife Service. To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: bb398390-d071-4e6b-aa2e-e69709d620fb.  United States Fish and Wildlife Service publishes this resource, and is itself registered in GBIF as a data publisher endorsed by GBIF-US.

Keywords

Occurrence; Observation

Contacts

Geographic Coverage

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

Taxonomic Coverage

We surveyed for non-native plants, especially Elodea.

Temporal Coverage

Project Data

No Description available

The personnel involved in the project:

Sampling Methods

We selected 23 lakes to survey for elodea in 2023, mostly basing our selections on the prioritization of 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 pike surveys, avoiding lakes that had been surveyed for pike in the last 10 years or where surveys are planned for 2024. We collaboratively planned with our partners, openly sharing our survey schedule. 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 n = mp + b, where where n was the sample size, m was 2.4 km-1, p was the perimeter in km, and b was 27. This resulted in a range of sample sizes of 30 to 63 sampling locations per lake. To select sampling points we used a Quarto document that called R, version 4.2.3 (R Core Team, 2023) and used the R packages lwgeom, version 0.2-13 (Pebesma, 2023) and sf, version 1.0-12 (Pebesma, 2018; Pebesma and Bivand, 2023). We divided the lake perimeters into segments, one segment corresponding to a target sampling location in each lake. Our rake throw survey methods were similar to the examples of Fulkerson (2022a) and Fulkerson (2022b).

Method step description:

1. 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 larger 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.
2. From the selected point the two observers threw the two 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, photographed, and the presence or absence of elodea was recorded. We also recorded depth, substrate types, and the presence of other aquatic plant species.

Bibliographic Citations

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. 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://ecos.fws.gov/ServCat/Reference/Profile/149784 https://ecos.fws.gov/ServCat/Reference/Profile/149784
3. Fulkerson JR (2022a) Aquatic Plant and Elodea Survey in Chugach National Forest: 2021 Survey Results. Anchorage, Alaska: Alaska Center for Conservation Science, University of Alaska Anchorage, pp. 26 + appendix.
4. Fulkerson JR (2022b) Aquatic Plant and Elodea Survey in Chugach National Forest: 2022 Survey Results. Anchorage, Alaska: Alaska Center for Conservation Science, University of Alaska Anchorage, pp. 21 + appendix.
5. 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
6. Pebesma E (2023) lwgeom: Bindings to selected ’liblwgeom’ functions for simple features. https://CRAN.R-project.org/package=lwgeom. https://CRAN.R-project.org/package=lwgeom
7. 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/
8. R Core Team (2023) 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/

Additional Metadata