Connecting the dots
First off, am I the only one who after hearing “connect the dots” thinks, “la, la la”? I forgot that this was from Pee Wee Herman .
This week, several of the readings were about rethinking/revamping how we teach students in today’s society where everyone is connected via the internet and the job requirements are shifting, stressing the importance of producing innovators. This got me thinking about what innovation has looked like in the fields of wildlife science and ecological statistics and where they overlap. In wildlife science, innovation has been driven by technology. In the 70’s someone put a VHF beacon in a collar and attached it to an animal so they could follow it around. Then everyone started doing it. GPS technology made it’s way into the larger animal tracking collars in the late 1990’s and the size of GPS collars has been decreasing and the performance has been increasing ever since due to innovators in the smart phone industry.
In wildlife science, mark recapture models are the dominant method for estimating population sizes. You catch animals, tag them, release them, and then try to catch them again. Through this process, you can estimate the detection probability which can be combined with the number you actually caught to estimate the population size. We used to have to physically capture the animals. This is a lot of work and generally sucks for the animals involved (although with baited traps, some animals inevitably become “trap-happy”, judging the bait to be worth it). The discovery of microsatellite markers in DNA opened the door to doing mark recapture using genetic samples such as those found in hair follicles or scat samples. Instead of having to capture a bunch of bears, we now only have to capture a bunch of their hairs. How do we do this? Biologists innovated the hair snare. Put barbed wire around some trees and put a doughnut in the middle. Bears can’t resist.
What about wolverines? I bet they get really pissed off when caught in a trap. Biologists came up with this contraption and put a piece of chicken on the top.
You can also get DNA from scat samples. Animal poop. Do you just go out looking for poop? No! You train a dog to find them for you (and not eat them). There are now several scat dog services you can hire to go capture animal scats for you.
About the same time genetics was making its way into mark recapture, people started putting up motion sensitive cameras in systematic arrays. Camera traps. It turns out many animals have unique patterns on their coats which can be used to identify them when caught later. Like tigers. In order to fully identify an animal with a camera trap, you need to capture both sides simultaneously. Otherwise, you don’t know which left side photos go with each right side photo. So the smart thing to do is to put two cameras at each site pointed at each other, right? This has been the conventional wisdom for 20 years, but… no! I’m developing mark recapture models that allow you to probabilistically link left and right sides based on the spatial location where they were captured. Spatial partial identity models. It turns out that hybrid grid designs consisting of both single and double camera stations (that most biologists would tell you are stupid) can estimate the number of animals with the most precision because you can cover more ground with your cameras and catch more animals. I’m planning on expanding the same ideas to use partial genotype samples in hair snare and scat surveys that are currently being discarded.
So there are two types of innovations here, one technology driven and the other, driven by innovation in statistical models. Did those innovating biologists have any natural propensity to be innovators? I don’t really think so. It seems like technology is the limiting factor and everyone in the field knows what to do with the new technology once it arrives and it’s a race to see who can do it first. The area where the most innovation is currently getting ready to occur is in the use of drones to survey wildlife. It’s pretty obvious what to do with a drone to survey wildlife. You do the same thing you were doing with airplanes only better and safer. You put VHF antennae on them and go find the animals. You put thermal cameras on them and do transect surveys. There are probably instances of more non-straight forward innovation in wildlife, but none come to mind.
Where innovation seems less inevitable is in the development of statistical methodology to analyze data collected in new ways. But even here, there is a widespread sense of where the field is going and people are frequently “scooped” by others who beat you to publication. Although maybe statisticians are just natural innovators. I believe this is largely true. I don’t think this has to do with their background in the humanities–I think it comes from their training in how to structure reality with probabilistic abstractions. And programming. Programming is problem solving and abstract thinking and innovation is rewarded. I’d recommend programming over the humanities if the goal is to create innovators.