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Factsheet – Using Data From a Popular Fishing App to Predict the Spread of Aquatic Invasives and Identify Characteristics of Resistant/Resilient Lakes in the Upper Mississippi River Basin

A research project funded by the Indiana Water Resources Research Center through the U.S. Geological Survey’s 104g National Competitive Aquatic Invasive Species (AIS) Grants Program (section 104 of the Water Resources Research Act of 1984, as amended).
Start Date: 2020-01-01

End Date: 2023-03-23

Total Federal Funds: $79,195

Total Non-Federal Funds: $84,490

Recreational anglers and boaters can be a major vector of the spread of aquatic invasive species (AIS) in the Upper Mississippi Basin (UMRB), but their movement patterns are poorly understood because our ability to collect movement data by traditional means is limited in both time and space. Recreational fishing apps are a potentially innovative and economical means of obtaining movement data. The few angler movement studies that have been conducted are limited to local or regional waterbodies collecting data over a few weeks or months. This has resulted in an incomplete picture of an inherently broad problem, one that limits the ability of agencies and organizations within the UMRB to prioritize efforts to detect, monitor and contain AIS.

This project used big data from Fishbrain, the most popular fishing app in the United States, and the U.S. Geological Survey to identify roadways, lake characteristics, and timing that contribute the most to the spread of AIS within the UMRB. Agencies and Non-government organizations can use this information to inform policy, and more efficiently allocate and coordinate AIS management efforts such as detection, inspection, enforcement, and targeted education and outreach campaigns.

Research Objectives

Big data from Fishbrain fishing app and the U.S. Geological Survey were used to develop a large database to answer the following questions:

1. Is it possible to predict which lakes in the Upper Mississippi River Basin contain aquatic invasive species?

2. Do these predictions improve if lakes that are not checked for invasive species are ignored?

3. Are some anglers more likely to spread aquatic invasive species than others?

map of angler path density along major US highways
Figure 1. A map of angler path density (per km2) along major highways in the United States (US) and parts of southern Canada. The UMRB is represented by the grey polygon. I-35 marks the division of eastern and western US. These divisions require separate scales because of differences in surface water and population density.

Researcher Profile

Dr. Paul Venturelli

Principal Investigator Dr. Paul Venturelli is an Associate Professor of Fisheries and Director of PhD in Environmental Sciences at Ball State University.

Major Conclusions & Significance

We analyzed data from 30,475 lakes and developed the following conclusions:

  • Aquatic invasions are more likely when a lake is large, close to a city, easy to get to, and visited by many anglers.
  • Our first analysis assumed all lakes were checked for aquatic invasive species, but it is possible that some lakes that were labeled as “uninvaded” had not been physically monitored and actually contain aquatic invaders. Therefore, our ability to predict invasions changed when we only considered lakes that had been checked. We can improve predictions by checking lakes randomly.
  • Anglers who like to fish a lot are most likely to spread invasive species. The species of fish anglers targeted for fishing did not affect this result.

What Does This Mean For Indiana?

Our analysis showed that invasions of non-native plants, mussels, snails, and crayfish are more likely to occur in lakes that are large, in close proximity to a city, have easy access via roadways/highways, and are visited by many anglers. We also found that aquatic invaders may be more widespread that first assumed. Scientists and resource managers are able to use this information to more efficiently identify lakes with high potential of aquatic invaders and help slow the spread of species.

We also found that the anglers that fish most frequently are the most likely to spread invasive species. Therefore, resource managers can target this group for AIS education and can perform checks on these specific anglers.

Publications from this research

Weir, J.L., Vacura, K., Bagga, J., Berland, A., Hyder, K., Skov, C., Attby, J. and Venturelli, P.A. (2022). Big data from a popular app reveals that fishing creates superhighways for aquatic invaders. PNAS nexus 1(3), pgac075. https://doi.org/10.1093/pnasnexus/pgac075

Weir, J.L., Daniel, W., Hyder, K., Skov, C., and Venturelli, P.A. (2024). Artificial intelligence applied to big data reveals that lake invasions are predicted by human traffic and co-occurring invasions. Biological Invasions 26, pp. 3163-3178. https://doi.org/10.1007/s10530-024-03367-6

Training The Next Generation

One of the missions of the Indiana Water Resources Research Center, and all Water Centers, is to train the next generation of water scientists. This project successfully funded research for one Ph.D., one Masters, and three undergraduate students within Dr. Venturelli’s lab.

 

Contact Laura Esman, Managing Director, to request a printed copy of this factsheet.

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