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Harvard Forest Data Archive

HF152

Detection Histories for Hemlock Woolly Adelgid Infestations at Cadwell Forest in Pelham MA 2008

Related Publications

Data

Overview

  • Lead: Matt Fitzpatrick, Aaron Ellison, Evan Preisser
  • Investigators: Joseph Elkinton, Adam Porter
  • Contact: Information Manager
  • Start date: 2008
  • End date: 2008
  • Status: complete
  • Location: Cadwell Memorial Forest (Pelham MA)
  • Latitude: +42.62 degrees
  • Longitude: -72.70 degrees
  • Elevation: 260 meter
  • Datum: WGS84
  • Taxa: Adelges tsugae (hemlock woolly adelgid), Tsuga canadensis (eastern hemlock)
  • Release date: 2023
  • Language: English
  • EML file: knb-lter-hfr.152.11
  • DOI: digital object identifier
  • EDI: data package
  • DataONE: data package
  • Related links:
  • Study type: short-term measurement
  • Research topic: invasive plants, pests and pathogens; regional studies
  • LTER core area: population studies
  • Keywords: hemlock, hemlock woolly adelgid, invasive species, surveys
  • Abstract:

    Monitoring programs increasingly are used to document the spread of invasive species in the hope of detecting and eradicating low-density infestations before they become established. However, interobserver variation in the detection and correct identification of low-density populations of invasive species remains largely unexplored. In this study, we compare the abilities of volunteer and experienced individuals to detect low-density populations of an actively spreading invasive species and we explore how interobserver variation can bias estimates of the proportion of sites infested derived from occupancy models that allow for both false negative and false positive (misclassification) errors. We found that experienced individuals detected small infestations at sites where volunteers failed to find infestations. However, occupancy models erroneously suggested that experienced observers had a higher probability of falsely detecting the species as present than did volunteers. This unexpected finding is an artifact of the modeling framework and results from a failure of volunteers to detect low-density infestations rather than from false positive errors by experienced observers. Our findings reveal a potential issue with site occupancy models that can arise when volunteer and experienced observers are used together in surveys.

  • Methods:

    We selected five hemlock stands (~ 1×104 m2 each) for sampling that were primarily (more than 50%) comprised of hemlock trees less than or equal to10 m in height such that a portion of each tree could be sampled from the ground. All stands were bordered by hardwood forests, allowing the natural boundaries of each stand to be readily identified. Within each stand, all hemlock trees greater than 0.5 m in height were numbered using aluminum tags and marked with flagging tape to improve visibility. We marked a total of 420 hemlock trees in the five stands (mean number of trees per stand = 80, range = 31 to 146).

    Twelve observers participated in the sampling effort: three experienced individuals who perform field research on HWA and nine volunteers who had no prior experience sampling for HWA. Prior to the sampling, the volunteers were trained for fifteen minutes on the sampling methodology and on identifying HWA infestations, including objects that could be confused with HWA. Each person was then assigned to one of four groups (n=3 persons per group). Two of the groups entirely were comprised of volunteers. The remaining two groups contained one experienced and two volunteer individuals and two experienced and one volunteer individual. Each group was provided a numbered list of trees to sample that could be located in the field by the corresponding numbered tag on each tree. To control for possible heterogeneity in infestation and detection rates between stands, each group was randomly assigned trees to sample in multiple stands.

    Three observers from the same group visited each tree independently. Observers searched all accessible branches for evidence of white woolly masses characteristic of the HWA sistens generation. Each search continued until either HWA was detected or a two-minute sampling period had expired. To ensure that sampling was independent, no two observers sampled a tree at the same time and observers were instructed not to communicate the infestation status of trees to the other observers in their group.

  • Organization: Harvard Forest. 324 North Main Street, Petersham, MA 01366, USA. Phone (978) 724-3302. Fax (978) 724-3595.

  • Project: The Harvard Forest Long-Term Ecological Research (LTER) program examines ecological dynamics in the New England region resulting from natural disturbances, environmental change, and human impacts. (ROR).

  • Funding: National Science Foundation LTER grants: DEB-8811764, DEB-9411975, DEB-0080592, DEB-0620443, DEB-1237491, DEB-1832210.

  • Use: This dataset is released to the public under Creative Commons CC0 1.0 (No Rights Reserved). Please keep the dataset creators informed of any plans to use the dataset. Consultation with the original investigators is strongly encouraged. Publications and data products that make use of the dataset should include proper acknowledgement.

  • License: Creative Commons Zero v1.0 Universal (CC0-1.0)

  • Citation: Fitzpatrick M, Ellison A, Preisser E. 2023. Detection Histories for Hemlock Woolly Adelgid Infestations at Cadwell Forest in Pelham MA 2008. Harvard Forest Data Archive: HF152 (v.11). Environmental Data Initiative: https://doi.org/10.6073/pasta/cc300bf8486be18fcb7ea692e61e5664.

Detailed Metadata

hf152-01: observations

  1. group: group number
  2. obs1: observer 1 type
    • V: volunteer
    • E: experienced
  3. hwa1: HWA detection by observer 1
    • 0: not detected
    • 1: detected
  4. obs2: observer 2 type
    • V: volunteer
    • E: experienced
  5. hwa2: HWA detection by observer 2
    • 0: not detected
    • 1: detected
  6. obs3: observer 3 type
    • V: volunteer
    • E: experienced
  7. hwa3: HWA detection by observer 3
    • 0: not detected
    • 1: detected

hf152-02: R code to run occupancy model

  • Compression: none
  • Format: R script
  • Type: script