By Sydney Zapf. “Wildlife Survey Automation”
I walked into work on Monday morning and was greeted by a nearly empty office. Confused, I asked my deskmate, “Where is everyone this morning?”
“They’re out in the field,” he replied. “There’s a patrol today.”
I nodded, sitting down at my desk. “Ah, I forgot,” I said. “This is still weird to me.” The office had only recently started sending out patrols to monitor the cameras.
I had just started my career as a conservation systems engineer when the ecology community started to get really nervous. Every other day, our inboxes were flooded with emails and messages about the wildlife disappearing. People were beginning to get nervous. With every acre absorbed into the suburbs, another species was decimated and another shockwave rippled throughout the ecosystem. We tried everything, from manual tagging to helicopter tracking, but we simply didn’t have the manpower to monitor location and movement data. The state decided to switch tactics, and turned its efforts to technology.
To say that work was hectic would be an understatement. I suddenly went from one of two engineers on the conservation team to heading the charge against the habitat destruction ravaging the local ecosystem. It took the collaboration of nearly all sectors of industry and government to come up with the new infrastructure. We were launching a full fleet of silent drones to monitor the protected areas of forest around the city, along with thousands of camera traps to be deployed in backyards and backwoods alike. The new data team hired would be responsible for maintaining and updating the database while keeping on high alert for anomalies. The sheer scale of the system that was deployed was unheard of, allowing us to see far beyond the reach of the city limits. In that time it had taken to design and test, we had witnessed the complete loss of dozens of species within the local ecosystem. We needed this data.
For a while, it seemed to work. With the help of specific and real time ecology data, we were able to work with policymakers and city zoners to stay out of habitats that still had significant life within them. Lumber companies avoided these areas as well, and it felt like the community came together for a common cause. Protected areas were established, and everyone involved began to relax as the wildlife populations started to stabilize. A lot of other areas across the world began deploying similar systems, and it seemed like we had finally struck a balance between nature and humanity.
I was broken out of my reverie by the sound of a phone ringing. My coworker cautiously picked it up and his eyes widened as he replied to whoever was on the other line. “Yeah, we’ll be right there.” He looked up and turned to me quickly. “We need to go. They found prints.”
…
On my way to the patrol site, I found myself staring at the app I had open on my phone. I could see where the rest of my team was, about three miles out, represented by a red blip on my screen in the middle of miles of green forest. For all of the good that this system brought, I constantly asked myself if it was worth it. A few years ago, it all went wrong. No one had anticipated this system being exploited for profit. We had assumed that poachers had left, driven off by the decrease in wildlife. They quickly returned to these protected areas once they got their hands on the same tracking technology used to preserve the habitats. Only this time, they were much more coordinated. They began to organize in the same way that we did, only instead of tagging animals, they killed them. We knew what was happening when we began showing up to camera sites expecting to find a newly formed bear family, or a lone fox that had wandered into the area, and instead found animal carcasses stripped of their fur.
…
I hopped out of the truck and walked up to the rest of the team. “So what’s up?” I asked.
One of them replied, “We found a bunch of tire tracks — not ours, obviously. I think they’re on the move today. We should try to work fast.” We had been working on tracking down some of the poaching groups in the area. It’s not something I thought I’d ever do, but I knew it was necessary.
“Alright,” I replied. “Let’s try to intercept them.”
…
We knew where they were likely to head next. My phone was pinging constantly with new alerts of wolf movement — red wolves specifically. The park only had two known red wolves left at this point. We quickly made our way to the camera sight, one of the drones scouting ahead of us. On the drone’s camera feed, we could see one of the wolves fleeing in the opposite direction, and that’s when I knew we had a problem. They always stayed together. Where was the other?
We rushed into the clearing and I could barely make out the shape of the other wolf limping away from us. I let out a rush of relief when I saw it — and then a shot rang out. I jolted my gaze up from animal that had abruptly fallen from the ground, and locked eyes with a pair of people across the small clearing. One of them had a gun in hand, and the other had a phone — a phone with the exact same application that was running on mine.
…
Technology Background: New techniques for wildlife data collection often include drones, automatic camera traps, and sound sensors to capture surrounding wildlife information. Machine learning techniques are then applied to the data sets to properly identify and map different species in order to aid conservation efforts. Many wildlife and environmental groups are using this technology instead of manual surveys.
