9/04/2019

The Minnesota invasion

Data from USGS Nonindigenous Aquatic Species Information Resource

Impacts of the mussel invasion


image: Mussel Prevention Program, San Luis Obispo County

  • Changes in water chemistry, water clarity
  • Decreases in native mussel populations
  • Decreases in plankton densities
    • Food web effects
  • Economic impacts

Objectives

image: Naomi Blinick

image: Naomi Blinick

Develop recommendations for underwater survey methods for monitoring zebra mussels in recently infested lakes:

  • Estimate density (number/area)
  • Spatial distribution
  • Quantify effects of treatments and environmental impacts that depend on density
  • \(\Rightarrow\) compare density estimates over time and space
  • \(\Rightarrow\) want accurate estimates
  • \(\Rightarrow\) minimize uncertainty for a given level of sampling effort

Outline

  • Challenges associated with developing a survey approach
  • Year 1: Distance sampling to estimate densities
  • Year 2: Comparing distance sampling and quadrat sampling
  • Products and knowledge transfer

Important Considerations

  • We can’t sample entire lakes!

    • must infer density after sampling only part of a lake
    • use (stratified) random or systematic sampling

  • We may not detect all mussels in the area we sample

    • use methods that can correct for imperfect detection

Important Considerations

.

Our ability to detect mussels may depend on

  • water clarity, presence of plants, …
  • the diver

Year 1: Surveys Using Distance Sampling

Year 1 field crew

image: Naomi Blinick

image: Naomi Blinick

Transect sampling

Transect Sampling + Distance Sampling

Allows us to and account for imperfect detection.

Assumptions of conventional distance sampling

  • We detection all individuals that are on or near the transect line
  • We detect fewer individuals as we move away from the transect line

Distance Sampling

Lake Sylvia

Lake Burgan

Estimating detection with two observers

  • First observer marks each detected cluster
  • Second observer looks for new clusters
  • New detections inform our estimate of detection probability

Importance of Accounting for Detection

image: Naomi Blinick

image: Naomi Blinick

Estimated density without detection \(0.08\) mussels/m\(^2\).

Estimated density without detection \(0.25\) \((0.07)\) mussels/m\(^2\) .


Correcting for imperfect detection lead to a 3-fold increase in our estimate of density!

Year 2: Comparing Distance and Quadrat Sampling

Dive team

How do distance surveys compare to quadrat surveys?

By surveying smaller quadrats, we may be able to detect all mussels in the surveyed area.

When might quadrat designs be preferable?

image: Jake Ferguson

image: Jake Ferguson

Given a fixed amount of time, which method performs best?

We compared designs across densities


Results

Results

Lessons from Year 2

  • Distance sampling is more cost-effective (less uncertainty for same level of sampling effort) at low to moderate densities

  • Quadrat sampling may be more cost effective at high densities (when?)

image: Aislyn Keyes

image: Aislyn Keyes

Generalizing these results

Ongoing Work

  • Using simulations (work with Dr. Katie St. Clair at Carleton College)



  • Analytic approach that shares similarities with models used to determine optimal foraging behaviors (Dr. Jake Ferguson, University of Hawaii)

Additional Products

Training video

Resources

Acknowledgements

Jake Ferguson

Michael McCartney

Naomi Blinick

Leslie Schroeder

Sarah Baker

Aislyn Keyes

Austin Hilding

Kylie Cattoor

Keegan Lund

Quadrat sampling error