We’re currently in the middle of one of those awful not-warm snaps that happen in winter, where instead of snow it rains for a day and half and all the snow turns to ankle-deep slush. Except where the snow has been insufficiently plowed, instead hammered by foot and and car alike into rock-hard ice, which how has a deep and also slippery puddle on top of it. And I can’t even be hopeful it will freeze again soon, because then everything will freeze perfectly smooth and all of town will turn into a skating rink for a bit. Ah well, the joys of winter.

We wrapped up research methodologies today, and I’m still kind of baffled they built a whole course around methodologies. But I suppose I’ve never really cared very much how information got acquired, just that it was, and maybe if this estimate will skew high or low based on mumble mumble systemic error. I can’t tell if this is because I was steeped in documentaries and Science News as a kid, so I already had a grasp on what kinds of things are possible to know by what means, or if I’m just generally confident that if you can figure out to frame your question correctly, what needs to be measured and how will become apparent. It’s not that methods aren’t important, it’s that they tend to be very specific to the question, which makes it hard to make generalizations that aren’t completely useless. I don’t know. It’s counting; most of the value add to humanity is in the analysis anyway, otherwise we could publish tables of raw figures at each other and not bother with paper writing at all. It’s especially odd to me because we don’t have to do anything difficult like the chemists or physicists or astronomers who have to measure proxies of proxies because their field is too dang small or far away. You want to know what the people do? Ask them! It’s just that easy!

Anyway, we went on a tiny hike to – I really can’t call it a forest – a large stand of trees earlier this week. I measured the area on Google Earth and it is not even a 100 acre wood fit for Christopher Robin and friends, it is a 10 acre wood. You’d have to make 1/10th scale dollhouse versions of Winnie the Pooh and everyone before this wood is big enough to have adventures in.

We went out in the first place because the program director for my program, who was teaching half of the methods class, did his PhD about forests in Switzerland and wanted us to think about sampling grids in this handy dandy pocket-sized forest. So we crawled all over the woods for about an hour and then came back and chit-chatted about what kinds of questions we could answer and what would be a reasonable sampling pattern and density. At one point he looked around and was like, Okay, anybody have any other questions, and I piped up and said, Do you know if the rocks are imported? He looked deeply baffled, and not much less baffled by I described a funky red layer I’d found on one of the boulders that didn’t look like it came from around here, before saying cautiously that the boulder was almost certainly from Iceland, if not this specific mountain. I’m a little bit sorry I asked the tree guy about the one non-tree thing in the woods, but it was a very out of place boulder. oh well. It was nice to walk in the snow for a bit, though I’d forgotten how tiring going through snow drifts is (I do love my boots an unreasonable about. tall and sturdy and keep the warmth in).

The final for this class was to write a mock methods section for a project proposal based on one of the methods we discussed in class, and while every other presenter was talking about various ways of counting, one person offhandedly mentioned network analysis as a way of thinking about social networks (among other things), so I decided to go ham on that because it’s basically graph theory and it’d be fun to read some math papers. I was correct, and I had a lot of fun reading math papers about graph theory and how it gets used in a variety of fields, including GIS (rivers, rail, utility networks, shipping routes, etc.). And also how the early data presentation for networks really knee-capped doing any proper graph theory analysis until the US Census Bureau got involved and wanted better polygons? So they built a better data structure and that’s a big reason why network analysis is taking off in GIS now and not in the 1970s when the math got hammered out, which was a wildly interesting tangent I got distracted by for a while. But did I get a little stuck in the actual writing of the paper because I have no idea how much of a math background either of the people grading this have, so I don’t quite know where to pitch the paper. Is topology friendly? Do they remember what a power law distribution is? I think I actually don’t want to describe matrix manipulations, even if I am running the risk of this being too short. I think I ended up being fairly clear (hopefully).

I went to another meeting of the shipboard research people, and the meeting was part paper discussion and part nitty-gritty ironing out of purchasing orders. Let me say, there is very little quite so confusing as intense debates about purchase orders when you don’t know the field that well (lengths and thicknesses of pipe cores and liners, and debating what materials would skew what kind of analysis).

The next class is an introduction to GIS mapping software, which means more weird computer problems for me, but I think it should be fun anyway. Maps! Maps are always a good time.