More than 5,500 volunteers classified Florida wildlife photos; over 1 million classifications recorded 43 species across 14 management areas

We see thousands of photographs a day: selfies, brunch plates and the odd picture of a strange person and their tiny raincoat-clad dog. However, what if we were looking at images from the Greater Everglades Region? Raccoons, herons and the odd ill-mannered alligator. This is where you come in. Zooniverse’s results page for Everglades Wildlife Watch, which is a project run with the Florida Fish and Wildlife Conservation Commission (FWC), notes that over 5,500 people participated in this, contributing to over 100,000 images being classified. Because each image was typically checked by several volunteers to confirm what it showed, that work added up to over 1 million classifications and helped identify 43 species of wildlife across 14 Wildlife Management Areas.

Why do biologists need extra help?

Trail cameras can take plenty of images, but they’re not very good at classifying them. According to Zooniverse, the FWC started a large wildlife survey at the Dinner Island Ranch Wildlife Management Area in 2023. The team didn’t have enough capacity to classify them all, so they asked online volunteers to help. This saved them at least 100 hours of work. The results uncovered 16 species of mammals and 27 species in total.

The team set up eight cameras in the Everglades and Francis S. Taylor area, hoping to find Everglades minks. Baited with chicken wings and a squeaky rodent sound, the cameras captured over 26,000 images in two months. While no minks turned up, the survey still found 32 species, including alligators trying to eat the bait, pigs digging, and a night heron caught with an amphiuma, an eel-like salamander. The effort added valuable entries to the area’s wildlife list.

Can strangers really be trusted with science?

A 2016 study titled “A generalized approach for producing, quantifying, and validating citizen science data from wildlife images,” by Swanson and others, published in the journal Conservation Biology, looked at how well volunteers could classify images. Over 28,000 volunteers classified 1.51 million images taken from camera traps in Tanzania's Serengeti National Park. They found that the collective responses from the volunteers matched expert-verified data in 98% of images. They also found that 90% of images were correctly classified by just 5 volunteers. This was a different project, so we cannot guarantee the same results in Florida. Also, rare species had increased false positives and negatives. Experts are still needed.

From photos to real decisions

The images can help make decisions about managing animals. During a high water event in the Fall of 2024, deer were forced to move to the levees and tree islands. Volunteers looked at weekly images from the cameras to help the team decide when it would be safe to open these areas back up to the public. The cameras are also used for a much larger concern.

According to a Fish & Wildlife Foundation of Florida publication, a neuromuscular disease called feline leukomyelopathy was first identified near Corkscrew Swamp in Collier County in 2018. In 2020, the Fish & Wildlife Foundation of Florida gave a $150,000 grant to the FWC to investigate the cause of the disease, and data collected from trail cameras has been part of that effort. Any videos of panthers or bobcats are sent to the FWC’s panther biologists and vets to look for potential symptoms. No new cases have turned up in the footage reviewed so far, but the data is still helping biologists track the animals’ range expansion, breeding, and overall health.

The fine print

This isn’t perfect. There is a clear limitation to this project: once there are no more images to look at, the project stops. Currently, Zooniverse says there is no data available, though more is expected at the start of December 2026. Overall, it’s clear that a large number of everyday people with phones and a little spare time helped a state agency get through images it may not have had time to classify on its own. It doesn’t take a biology degree or a flight to Florida, just a willingness to look carefully at a blurry image and decide whether it’s a raccoon.