What’s New In GIS And Biological Research: 26 May 2015

26 May

This week’s summary contains a variety of very different posts which cover topics ranging from how-to tips, to why you don’t get pineapples in the Antarctic. So, without further ado, I’ll begin.

The first post I want to highlight is a tutorial from Saara Pakarinen on creating a PostGIS database for QGIS. While not everyone who does GIS will use the database management systems, for those who do find that they need to use them, then this tutorial will help get you started.

Secondly, and while still on the subject of QGIS, there’s a really nice post from GIS Digest about qquality control, and how you can use the QGIS topology checker to help deal with any quality control problems you come across with your GIS data layers. This is something which is really important to know how to do, not only because it can help you work out why a specific data layer isn’t working properly, but also because, as with all analysis, in biological research, your results will only be as good as the quality of data which goes into your analysis in the first place.

Next, I want to consider a post from Geospatial Wanderings on extracting data layers from OpenStreetMap. For those of you who don’t know, OpenStreetMap can be a great source of spatial information, but sometimes it can be a little tricky to extract exactly the information you need. Geospatial Wanderings’ post provides instructions on how to do this in two different ways. They’re both command-based, rather than graphic user interface-based, but the flexibility that they provided in extracting just the data you want more than pays off the fact that they are a bit difficult to get to grips with the first time you use them.

Fourthly, I want to draw your attention to Volunteered Geographic Information (VGI), and how it can be used to help fill in spatial information where little is currently available. VGI (and the above mentioned OpenStreetMap is an example of this) does exactly what it says on the tin, and uses volunteered information to increase the amount of spatial data available. In ecology and conservation, this can involve things like looking for evidence of changes in forest cover from satellite images, or other similar changes in land use, but the example I’m going to point you towards today is humanitarian in nature and about how VGI is being used to help those caught up in the recent earthquakes in Nepal. It’s a nice case study of how communities of people from around the globe can come together to help others with the skills that they have.

To return to advice about using GIS, MaybeItsAMap has a great post for ArcGIS users which looks at how to select data points or features from a data layer based on their spatial locations, or the spatial locations of features in another data layer. The example they use is selecting features from a line data layer of streams based on things like polygons of management or political areas, and it provides detailed information about how to use this tool effectively to select exactly the subset of data that you want to select.

Still on the advice for using GIS, but going back to QGIS, if you’re interested in making really nice terrain maps complete with shaded elevations and contours, then check out this post by Anita Graser titled How to create illuminated contours, Tanaka-style. This isn’t something I’ve done before, but I could see it being a nice skill to have for creating really smart-looking maps for reports and presentations, especially when overlaid with biological data, such as sampling locations.

The last four posts I’m going to mention this week are brought together under the banner of things that made be stop and think. They are all loosely GIS-based (some, admittedly, more loosely than others), and all connected to various aspects of biology.

The first of these posts comes from Hamilton Ecology Lab, and is about a study of genetic diversity in an invasive species. In this case, it is European stoats in New Zealand. As invasive species often start with a small number of individuals, you’d usually expect their genetics to go through a bottleneck, but this doesn’t seem to be the case in this example. Or rather, it seems, the original source population in Britain has, for various reasons, gone through a greater bottleneck than the introduced one in New Zealand. Where’s the spatial element in all this? Well, it just goes to show that you shouldn’t make assumptions about your samples based on where the came from. Instead, you need to approach them without such preconceived spatial prejudices.

Over at Mashables, in tribute to the recent International Day for Biological Diversity, they put together a post to highlight the five greatest threats that biodiversity faces: Climate change, habitat loss, overexploitation, invasive species and pollution. This list will be nothing new to most biologists, but it strikes me how important spatial analyses are for studying, and managing, all these threats. In fact, without a decent spatial knowledge to underpin our management strategies, it’s unlikely we’d be able to control any of these impacts effectively.

HominidLikeMe has an interesting post on non-infectious epidemics, and while they are rather bizarre examples, they all have one thing in common: spatial clustering of people suffering from unusual symptoms that might, at first, appear to be caused by infections of some kind. However, further exploration results in the identification on non-infectious causes. As with one of the first ever studies that integrated spatial analysis and epidemiology, these examples show how spatial information can help us understand the causes behind human diseases, and how they are spread.

The final post comes from Scientiflix, and is aimed at kids. It’s about why certain types of plants are only found in some places and not others. In other words, it provides a kid-friendly introduction to the idea that there are spatial patterns in where different species occur, and that is a great introduction to one of the reasons why GIS is such an important tool for studying spatial patterns in ecology.  Without GIS, we wouldn’t be able to explore and test the hypothesis we generate to explain such patterns, and if we couldn’t do that, then we’re not doing science. And of course, it’s never too early to get kids interested in GIS!

So these are the GIS-related things that have caught my eye this week, but, as always, I’m sure there’s a lot of other good stuff out there as well.

Dr Colin D. MacLeod,
Founder, GIS In Ecology

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