Kenai National Wildlife Refuge Aquatic Invasive Plant Surveys 2023

出現紀錄
最新版本 published by United States Fish and Wildlife Service on 12月 6, 2023 United States Fish and Wildlife Service

下載最新版本的 Darwin Core Archive (DwC-A) 資源,或資源詮釋資料的 EML 或 RTF 文字檔。

DwC-A資料集 下載 476 紀錄 在 English 中 (104 KB) - 更新頻率: 每年一次
元數據EML檔 下載 在 English 中 (28 KB)
元數據RTF文字檔 下載 在 English 中 (16 KB)

說明

To maintain biological integrity, biological diversity, and native fish resources in Kenai Peninsula freshwater systems, we surveyed for invasive elodea in Kenai Peninsula lakes using rakethrow surveys.

資料紀錄

此資源出現紀錄的資料已發佈為達爾文核心集檔案(DwC-A),其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 476 筆紀錄。

亦存在 2 筆延伸集的資料表。延伸集中的紀錄補充核心集中紀錄的額外資訊。 每個延伸集資料表中資料筆數顯示如下。

Occurrence (核心)
476
MeasurementOrFacts 
1428
Multimedia 
970

此 IPT 存放資料以提供資料儲存庫服務。資料與資源的詮釋資料可由「下載」單元下載。「版本」表格列出此資源的其它公開版本,以便利追蹤其隨時間的變更。

版本

以下的表格只顯示可公開存取資源的已發布版本。

權利

研究者應尊重以下權利聲明。:

此資料的發布者及權利單位為 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 註冊

此資源已向GBIF註冊,並指定以下之GBIF UUID: bb398390-d071-4e6b-aa2e-e69709d620fb。  United States Fish and Wildlife Service 發佈此資源,並經由GBIF-US同意向GBIF註冊成為資料發佈者。

關鍵字

Occurrence; Observation

聯絡資訊

Matthew Bowser
  • 元數據提供者
  • 出處
  • 連絡人
Fish and Wildlife Biologist
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Kristine Inman
  • AssociatedParty
  • 出處
  • 連絡人
Supervisory Biologist
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Nathan Davis
  • 出處
Biological Technician
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Kristian Merrell
  • 出處
Biological Technician
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Beth Sullivan
  • 出處
Volunteer
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
Dom Watts
  • 出處
Wildlife Biologist/Pilot
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Chris Snyder
  • 出處
Student Conservation Association Crew
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Sean Wise
  • 出處
Biological Intern
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Ethan Bowser
  • 出處
Volunteer
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US
Shealyn Imgarten
  • 出處
Youth Conservation Corp Crew Leader
USFWS Kenai National Wildlife Refuge
PO Box 2139
99669 Soldotna
Alaska
US

地理涵蓋範圍

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

界定座標範圍 緯度南界 經度西界 [59.131, -151.611], 緯度北界 經度東界 [61.09, -149.348]

分類群涵蓋範圍

We surveyed for non-native plants, especially Elodea.

Kingdom Plantae (plants)

時間涵蓋範圍

起始日期 / 結束日期 2023-06-27 / 2023-09-22

計畫資料

無相關描述

計畫名稱 Kenai National Wildlife Refuge Aquatic Invasive Species Surveys
辨識碼 https://ecos.fws.gov/ServCat/Reference/Profile/149924
經費來源 This work was funded by National Wildlife Refuge System Strike Team Funds.
研究區域描述 The Study area was much of the northwestern Kenai Peninsula where most of the Kenai National Wildlife Refuge is situated, bounded by Tustumena Lake to the south, Cook Inlet to the west, Turnagain Arm to the north, and the Kenai Mountains to the east. This area is characterized by mixed boreal forest, wetlands, lakes, and streams. This region was described in detail by Kenai National Wildlife Refuge and US Fish & Wildlife Service, Alaska Regional Office, Division of Conservation Planning & Policy (2010).

參與計畫的人員:

Kristine Inman
Nathan Davis
Kristian Merrell
Sean Wise
Dominique Watts
  • 作者
Beth Sullivan
  • 作者
Chris Snyder
  • 作者
Ethan Bowser
  • 作者
Shealyn Imgarten
  • 作者

取樣方法

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).

研究範圍 Our target universe was the set of all waterbodies in the study area susceptible to invasion by non-native plants, particularly elodea. Our initial sample frame was the set of lakes in the vicinity of the Kenai National Wildlife Refuge. We considered individual lakes to be the sampling units.

方法步驟描述:

  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.

引用文獻

  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/

額外的詮釋資料