Yes, so in conservation decisions, one of the things that's important to understand is that we're not taking raw data and making decisions from raw data. There's a very rigorous modelling process, and I'd be happy to share with your analyst a few of the papers about how this works, but basically, the challenge that we have, when we're trying to deal with animal distributions, is that the things that animals are keying into differ across time and space.
For birds, it can be particularly challenging, and even if you just look at the breeding season for one species, that is going to be very different in the Okanagan Valley than it might be here in Ontario. When they migrate, they're using different habitats as well.
The modelling approach that we need to use needs to be robust enough that you can understand the difference in spatial and temporal patterns. What we're basically doing at a high level is running a series of independent models that allow us to understand those relationships. Think of it as a 100 by 100 kilometre grid. We overlay these on top of each other, and then do those for every week of the year. That allows us to understand how those spatial patterns could change across time and space.
One of the challenges you have is.... Traditionally, if you wanted to look at habitat management, you could do an intensive study in one particular place and focus on that question. Those results would probably work 50 miles away from there, maybe 100 kilometres away from there, but with distance and time, the impact would be different.
Citizen science allows us to understand that at an increasing spatial resolution, and that's some of the real power. Some of the things we've been doing right now have focused on sagebrush. Sagebrush in the inner mountain west is really being affected by non-native cheatgrass. It's sort of a merger of both of your questions.
Under various climate scenarios, the challenge that we have is where the best places are to target action on cheatgrass removal to achieve an optimal outcome. Using more traditional science, it's hard to address that, but in this case, we're able to look at that, because we have this information that's so spatially detailed. We can point to areas and say that these are the areas where you're going to see the highest number of increases in species of birds, because of the broad dataset and the fairly sophisticated analyses.