AI is making the impossible possible, and it is rewriting how we protect these elusive birds.
Ground nesting birds have never made life easy for the people trying to protect them. These birds do not build tidy little nests up in the trees where anyone can check on them. They tuck their eggs in grass, in gravel, on beaches, and in vast open landscapes where spotting a single clutch of eggs is like finding a needle in a hayfield. Now throw in the fact that most of these birds are already dealing with shrinking habitat, more predators, and climate stress, and the need to monitor them quickly becomes urgent. But until recently, the tech just wasn’t there.
That is changing fast. Artificial intelligence is giving researchers new ways to spot nests, track threats, and figure out what these birds need to survive—all without disturbing them or spending months sorting through data by hand. In other words, we are finally getting ahead of the curve. And for many species already in decline, that shift could be the difference between holding on and disappearing for good.
1. Drones with AI are helping researchers find nests no one could before.
Eurasian Curlews have been one of Europe’s most frustrating birds to monitor. These long legged shorebirds nest right in the middle of dense grasslands, and their eggs blend perfectly into the ground. Even seasoned researchers with years of field work struggle to find the nests in time to protect them. Now, drones equipped with AI powered thermal imaging are flipping the script, according to Nature.com. The system can detect the tiny heat signature of a nest even when the eggs are hidden under layers of grass.
What is even better is that this tech works fast. Instead of spending days or weeks walking transects, teams can now cover entire landscapes in a fraction of the time. That means they can get out in front of threats before predators or human disturbance wipes out a season’s worth of nesting. For birds like the curlew, which are declining across much of their range, it is exactly the kind of head start that might give them a fighting chance.
2. AI is helping researchers track predators before the birds ever get hit.
Predator management used to be a reactive game. Take Piping Plovers, for example. These tiny shorebirds nest on open beaches where predators like foxes and raccoons have an easy time finding eggs. Researchers would set up trail cameras to monitor the nests, but going through all that footage took weeks. By the time they spotted an uptick in predator activity, it was usually too late. Now AI trained on camera data can scan thousands of images in hours and detect when predators are moving into nesting zones, as reported by National Geographic.
This is giving managers a critical window to act. Instead of responding after nests are lost, they can implement targeted fencing or adjust predator control based on real time movement patterns. It is not about removing every predator, but about knowing when and where the birds are most vulnerable. For plovers, which only lay a few eggs per season, protecting even one extra clutch can make a real difference in keeping populations stable.
3. Image recognition is turning Sage Grouse monitoring from a slog into a science.
Anyone who has ever worked with Greater Sage Grouse knows how physically exhausting it is. The birds nest across huge expanses of sagebrush, and getting data meant days of hiking and driving rough terrain to check cameras by hand. Then came the even more tedious part—sorting thousands of grainy images to figure out which nests were still active and which predators had passed through. Now with AI image recognition, researchers are skipping the slog, as stated by MDPI.
The system can automatically identify active nests, log key behaviors like incubation and chick hatching, and flag any predator visits—all in a matter of hours. That lets managers focus their energy where it counts, whether that means reinforcing protection zones or addressing habitat quality in specific areas. For species like the Sage Grouse, which depend on huge, interconnected landscapes to thrive, getting this level of insight without burning out field crews is a game changer.
4. Acoustic AI is finally letting researchers hear birds they used to miss entirely.
Some ground nesting birds are so secretive that traditional monitoring barely scratched the surface of what they were doing. Take Eastern Whip Poor Wills. These nocturnal birds nest on the forest floor and call at night, but unless a researcher happened to be in the right place at the right time, entire breeding seasons could go by with little solid data. Now AI trained on whip poor will calls is changing that.
By running acoustic recorders across large areas, and letting AI sort through the recordings, researchers can track when and where these birds are active, how many territories are occupied, and even detect patterns in how vocal activity shifts during the breeding season, according to Unite.ai. Suddenly, behaviors that were once invisible are being mapped in detail. For a bird that faces mounting habitat loss and changing insect availability, that kind of knowledge comes just in time.
5. AI is helping land managers know which hayfields to protect for Bobolinks.
Bobolinks are one of those species that get caught between two worlds. They love nesting in grasslands, but much of their remaining habitat is working hayfields, where an early mowing can wipe out an entire generation of chicks. The challenge has always been predicting which fields the birds will use in any given year so that farmers and conservationists can time mowing to avoid the most sensitive spots. AI habitat modeling is starting to solve this.
By combining satellite imagery, on the ground surveys, and weather data, AI can predict which fields will have the right conditions for nesting. This gives land managers a head start, letting them negotiate delayed mowing where it will do the most good. And it means that instead of trying to guess after nests are already underway, they can act proactively. For a species that has been declining steadily across North America, those extra protected fields can really add up.
6. Kirtland’s Warbler nests are now getting real time protection thanks to AI.
For decades, protecting Kirtland’s Warbler meant intense, hands on field work. These rare songbirds nest on the ground in young Jack Pine forests and are magnets for predators. Even with careful management, it was hard to know when nests were being hit or when predators were ramping up activity. Now, AI connected cameras and sensors are changing the game.
The system monitors key signs at each nest site and sends instant alerts if predator visits increase or if something about the nest’s status changes. That lets managers act in real time, whether that means adjusting predator control or simply focusing their efforts where the risk is highest. In the past, such events would have been noticed days or weeks too late. Now they can intervene while it still matters. For one of the most recovery dependent birds in North America, that is huge.
7. Shorebird managers are learning exactly when beach traffic is hitting hardest.
American Oystercatchers have a tough deal. They nest right on popular beaches where human traffic can spike dramatically with tides, holidays, and weather. For years, managers relied on static beach closures and hoped for the best. AI driven analysis of camera footage and visitor movement is now giving them something better.
The data showed that in some areas, oystercatcher nests were getting hit hardest not during mid day peaks, but early mornings and late afternoons when people and off leash dogs moved closer to dunes. That insight let managers shift patrol schedules and public outreach to those specific windows. It sounds simple, but that timing adjustment gave some of the most vulnerable nests a much better shot at surviving. It is the kind of fine tuned management that was not possible before AI started revealing these hidden patterns.
8. Climate shifts in Arctic sandpipers are being mapped with AI speed.
Semipalmated Sandpipers are facing a new problem as the Arctic warms. Their chicks need to hatch when insect prey is at its peak, but climate shifts are making that timing unpredictable. Long term data hinted at mismatches, but it was too complex for researchers to sort through manually. Now AI is pulling those patterns into focus.
By analyzing weather records, nesting data, and insect emergence trends, AI models are showing where and when mismatches are happening most. That is letting scientists prioritize which breeding areas may need more focused management and giving them a preview of how future climate scenarios could play out. For birds that already face pressures along their migration routes, getting this early warning is critical.
9. Northern Harrier nest preferences are getting an unexpected update.
Conservationists long assumed that Northern Harriers picked nest sites mainly based on grass height, so that was the focus of many habitat management plans. But when AI was used to analyze a much larger set of variables, the results surprised everyone. Moisture levels and subtle differences in vegetation density turned out to matter more than grass height alone.
That is now shaping how land managers restore grasslands and wetlands for this species. Instead of just managing for a certain visual target, they are adjusting for hydrology and plant composition in ways that better match what successful nests actually need. It is a reminder that even experienced biologists sometimes miss the fine details—and that AI, used well, can help close that gap.
10. Snowy Plover teams are adjusting in real time instead of post season.
Snowy Plovers nesting on Pacific Coast beaches face a gauntlet of challenges. Storm surges, predator shifts, beach grooming, and unpredictable human traffic can all wipe out nests in a flash. In the past, managers had to wait until the season ended to analyze what worked and what did not. Now, AI powered monitoring systems are letting them adjust while the season is still unfolding.
When predator activity spikes or new nests are laid in vulnerable spots, managers get that information fast enough to move fencing, change patrol focus, or adjust signage in real time. That dynamic approach is already boosting fledging success in some California sites. It is the kind of nimble management that more species are going to need as pressures on ground nesters keep growing.