The electronic grizzly bear

Maybe one of my favourite parts is just trying to figure out the best place to put a camera to get as much wildlife action as possible. It makes my imagination go in to overdrive.

Maybe one of my favourite parts is just trying to figure out the best place to put a camera to get as much wildlife action as possible. It makes my imagination go in to overdrive.

As a bear biologist, I’ll admit that I love the field work the most. Working in the woods all day, setting up remote cameras, looking for bear sign, and talking to visitors. Even when I don’t see a bear, which is most of the time, it’s just fantastic to be out there. But as the bears go in to their dens, I have a mountain of information to sort through and examine and make sense of – that’s my electronic grizzly bear and it’s what a winter in front of the computer is for. Before getting in to the nitty gritty, it’s important to take stock of what I have.

A Mountain of Data

One of things that makes grizzly bears so awesome is that they are all different, and they have personalities and can react to the same situation differently on different days. That’s also what makes them a big time pain in the butt when it comes to stats. Knowing this would happen, I’ve designed a study that will have data coming from multiple sources; this helps me cover my bases if one data source doesn’t give me enough information to conduct robust statistical analyses.

Not always bears are captured by the remote cameras. This last camera of the season captured this little critter for a walk in the snow.

Not always bears are captured by the remote cameras. This last camera of the season captured this little critter for a walk in the snow.

So here’s what I’ve got:

  1. Remote Camera Pictures
    Over the summer, my volunteers and I set up 36 different remote cameras on 12 different hiking trails between Banff and Lake Louise. This effort is measured in camera trap days, which is every 24 hour period that a camera was set up on a trail. In total, I have data generated from 1,066 camera trap days. This gave me a total of 96,307 images to classify and analyse.
  2. Visitor Survey
    Visitor surveys were disseminated at 25 different trailheads from Banff to Lake Louise. A total of 317 groups were asked to participate in the survey and only 53 parties refused, giving me a response rate of 83.2%. That’s really high for any kind of social science survey, which is great.
  3. Tracksticks
    The tracksticks were a bit of an experiment this year and were less of a priority than the surveys and the cameras. In total, we distributed 15 tracksticks on 4 different trails. I still have to look at that data and see how many human hiking routes were generated with those tracks station… coming to a trail near you next year too!
  4. GPS collars
    Parks Canada had collars on at least 9 bears throughout the summer. Most of these collars were set to generate a location every 4 hours, which has generated literally thousands of points across Banff National Park of grizzly bear locations.

Managing the Mountain

Getting a handle on this volume of data is a bit of a mind-bender in and of itself. I started small and am working my way through chunks so as to avoid getting overwhelmed. The data from the visitor surveys has already been entered and is just waiting for me to dig in and start analysis. I’ve got a couple of volunteers working on classifying the remote camera images and I’ll be recruiting a few more at my University to get all that done by January. The trackstick data will just have to be imported in to ArcGIS, which I’m sure sounds easier than it will actually turn out to be. Parks Canada staff will clean up the grizzly bear GPS data and email that to me later this year, then I’ll import that in to ArcGIS and start analyzing it.

My plan of attack right now is to chip away at all this data until it’s done. The analysis of the visitor survey will be the least complex, mostly because I am familiar with the program I’ll be using and the data itself is independent from the other data sources. Even though the results of the visitor survey will influence final recommendations, that data can be analysed on its own. The remote camera data will end up being a massive spreadsheet that in and of itself will be analysed in the same program as the visitor survey data.

It’s the GPS data that will get confusing, so I’ll save that for a little later… when I’m already well on my way to genius. The GPS data from the grizzly bear collars will have to be analysed on its own, as will the data from the tracksticks. Then I’ll have do an analysis that looks at the data from the tracksticks combined with the data from the GPS collars. Finally, I’ll also need to do an analysis that compares the results from the remote cameras to the actual grizzly bear locations from the GPS collars. Part of the challenge will actually be determining what kinds of analyses to do and what tests to run. I do have some ideas, but these things hardly ever work out the way you think they will the first time.

It all sounds a little intense, and I’m sure it will be. But I figure breaking it up in to smaller pieces will make the pain less intense and maybe reduce my chances of breaking in to tears… although I’m sure there will be tears (no PhD students can come out of analysis without crying a few times).

A very special THANK YOU

My volunteers helped with all aspects of data collection: cameras, surveys, tracksticks, and now even data entry. Without them, I wouldn't have a project at all!

My volunteers helped with all aspects of data collection: cameras, surveys, tracksticks, and now even data entry. Without them, I wouldn’t have a project at all!

This summer, 22 volunteers helped me to collect this mountain of data and I  am truly grateful. It was amazing to work with each of them and I am stoked to think that this is only the beginning. Several volunteers have stated interest in coming back next year, and I hope to recruit more. Working with volunteers was such a success that the experience has become an integral part of my thesis, and believe it or not is going to be the case study in an upcoming book chapter that I will be co-authoring with my supervisors. Funny how I just thought it would help me collect more data and get the community involved, but the lessons learned through this process will end up being shared across my field with many other researchers interested in engaging volunteers in their work.

Back Down Under

So I’m now back in Australia to do all of this, and why? I work at home, so why not just keep doing that? Well to work through all of that mess of data, I’m going to need help. Don’t tell anyone, but I don’t really know what I’m doing. I need to have some face to face time with my supervisors to figure it all out. Fortunately, my supervisors in Australia are good at stats and at GPS analysis (no coincidence that they’re on my supervisory team)! I’ll work through the madness with them to help guide me, which will hopefully reduce the tears (I hope they read this and get the hint). Hmm…

Besides, when you have an opportunity in life to spend a big chunk of the Canadian winter on the East Coast of Australia, you take it! I arrived in Gladstone yesterday and have been enjoying getting reacquainted with my flip flops and shorts. I look forward to exploring the data and seeing what I can see. I’ll be posting some of what I learn on this blog, so stay tuned throughout the winter as I get deeper in the data and closer to answering my research questions. I may also get deeper in to the ocean and closer to answering the questions I have about the Great Barrier Reef… so maybe I’ll post some of that too.IMG_1412[2]

 

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