Social media for anglers produces climate change data for researchers


Anglers log the fish they catch with the date, time, location and species on the Fishbrain app. Researchers use the data to study how climate change affects fish. Image: Jack Armstrong

By Jack Armstrong

Users of the “Fishbrain” app each day log, photograph and post their best fish catches. It’s a bit like Instagram for anglers – and it could help researchers better understand how fish are affected by climate change.

Former Ball State University Researcher Zachary McDonald investigated the effects of climate change on fish with data pulled from Fishbrain, an app that allows users to post photos of their catches and log  the species and size of the fish they caught, the gear they used and the location, date and time of the catch.

“We’re using the catches that are logged in the app itself as our wildlife data for our project,” McDonald said.

Climate change affects ecosystems and fish directly and indirectly. It can cause harmful algal blooms, alter spawning and migration times and disrupt habitats. If rising temperatures cause warm-water fish to become more common and cold-water species to decrease, it should be reflected in the quantity and type of fish anglers catch and log on Fishbrain.

“A lot of climate change research and a lot of research about how species are and populations are changing over time delve into historical data, or case studies,” McDonald said. “With the Fishbrain application, it adds even more useful data to the mix…we’re seeing what is being presented on a day to day basis.”

Paul Venturelli, an associate professor of fisheries at Ball State and McDonald’s adviser, said using digital data to investigate the effects of climate change on fish is increasingly popular.

“The list of potential devices and types of digital data that people are interested in, is fairly long,” he said. Social media posts and cell phone locations are potential data sources.

McDonald and the Venturelli lab obtained catch data from across the United States through a data-sharing agreement with Fishbrain. Fishbrain’s 14 million users record data every day.. The company shares some of this data, which is anonymized and updated every six months. McDonald’s thesis relied on data captured between 2015 and 2020.

Nate Roman, partnerships manager at Fishbrain, said the company is committed to conservation and wants to advance work that is good for the environment, fisheries and anglers.

“There’s a lot of potential applications to look at this huge scale data set of people reporting catches, and see whether that can be leveraged, not just for the good of the anglers who want to see it, but also for the good of the fisheries and for people making decisions to protect those,” Roman said.

Processing the data takes a bit of work, Venturelli said. Sometimes, fish that are only found in the ocean are incorrectly logged in lakes, and this data needs to be purged. And of course, Fishbrain is not immune to the occasional fish tale – fish that are logged as ridiculously large or small are also flagged. Recognizing the value of the data, Fishbrain now flags users who consistently provide misleading information, Venturelli said.

Citizen science presents unique challenges. The research has to consider that anglers may prefer to fish for one species over another.

“We have to still account for the fact that people that use the app may not be fishing for all the species that we’d like them to,” McDonald said.

For the most part, the results of the research are unsurprising. As climate change warms bodies of water across the country, warm-water fish become more common, typically at the expense of cool-water species. This pattern is especially strong in the Great Lakes area, the Northeast, and parts of the West Coast. This correlation was expected, and the results come with some caveats. Fish populations are also  influenced by factors like particular species becoming more popular among anglers or changes in population due to pollution. But Fishbrain lays the groundwork for further research using similar methods.

The data “is starting to line up with what is being presented in other literature that’s tackling the same topic,” McDonald said.

Applying the method over longer periods would help researchers rule out the non-climate change explanation of  population shifts, he said.

But the consistency of the data with the expected effects of climate change is a win in itself, Venturelli said.

“The success is that it seems to have worked and warrants further research.” .

The method could be used as an early warning system to detect large changes in the abundance of a population for reasons not limited to climate change, he said.

“If it works, then you could perhaps monitor the data, and just run them through an algorithm on a regular basis and then have these flags pop up saying, hey, there’s some changes happening in this location,” he said.

McDonald hopes to publish an adapted version of his thesis in a scholarly journal specializing in fisheries in the next few months.

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