What’s New In GIS And Biological Research: 19 May 2015

19 May

From this week’s summary, you’ll see that there’s been little of the usual postings about the specifics of using GIS, so instead, I’ve concentrated more on selecting some nice examples of how GIS is actually used in a variety of areas of biology, including some you might not usually associated with GIS.

However, before introducing you to these examples, there are a few how-to posts which I’d like to highlight. First, there’s the usual outputs from the MapsNigeriaInititive blog who are continuing their series of tips for QGIS users. This includes a post on how to conduct a spatial join using the MMQGIS plugin and one on how to perform spatial queries on data layers. Both of these are useful things for biologists to know how to do.

For ArcGIS uses, MaybeItsAMap continues to produce some useful tips. The ones I’ve picked out this week are one on how to alter a tool’s Environmental Settings, and one on how to repeatedly run a tool with exactly the same settings as before. If you run into problems when running a GIS tool, there’s a good chance that it is because you haven’t changed one of the settings under the Environments section. This is where you usually set things like which projection/coordinate system the output of the tool will use, and what extent it will have. Sometimes in the rush to run a tool, the Environment settings can get overlooked, but, as MaybeItsAMAp points out in the above post, this is something you do at your own peril. If you do find you make a mistake, and forget to set your environmental settings correctly, then the chances are you’ll have to run your tool again. This can be tedious, especially if you have to enter all the setting again from scratch. This is where the second post from MaybeItsAMap comes in. This shows you how to use the results window in ArcGIS to re-open the tool window with all the same settings you used before. If you set these correctly, you can run the tool again right away, but if you got one of them wrong, you can change it without having to re-set every other setting at the same time. This is really useful, and can save a lot of time when you make one of those little mistakes that it is so easy to do when doing GIS.

So, that’s the GIS user tips for this week, and it’s time to move on to the examples of GIS in action in biological research. While it will be clear how GIS is used on some of these, in others it will be less so, but this is often the case with GIS. The first of these is about the accuracy of visual estimates of land cover by a given vegetation type for monitoring changes in land use over time. Such visual estimates of land cover and land use are critical in many aspects of environmental monitoring, and are widely used in GIS-based studies, so it is essential that they are correct. Thus, it is useful to have a paper which specifically examines how valid the methods are for doing this.

The second example also deals with changes in land cover, but this time caused by something much more catastrophic. As David Frantantoni points out on his blog, it’s 35 years since Mount St Helens erupted in the Pacific Northwest of the US, instantly changing vast swathes of the landscape around it. What I want to concentrate on here, from a GIS perspective, is the satellite image that accompanies David’s post. This is exactly the type of image that biologists can use in GIS analyses to both investigate the effects of such catastrophic events on the surrounding environment, but also monitor how it changes over time as the local ecosystems seek to recover. St Helens may be one of the first volcanic eruptions where we have an almost complete time-series of such images, from the immediate aftermath of the explosions to the present day, which could be used to do this, but now it should be possible for almost any catastrophic event anywhere on the planet.

Continuing the trend of looking at environmental changes over time using GIS, but this time looking into the future rather than the past, Mark Grant as an interesting post on using big data and modelling to predict where climate refuges may occur, and how bush fire hazards may change in the future as the effects of climate change really start to bite. While this type of analysis is really only possible through large-scale collaborations, and may be beyond the reach of individual researchers working in small research groups, it is still useful to see how such are put together and what they can achieve. Again, GIS will be an essential component of any such enterprise.

The final example of environmental monitoring over time which I want to highlight here is a post about Puget sound, which is in the same part of the world as Mount St Helens, and looks at how the structure of local marine ecosystems has shifted from a fish-based on to one based on jellyfish. This is something we are increasingly seeing all around the world, and it is something that GIS is being used to investigate throughout the many locations where it is occurring.

There’s a common strand running through all these examples of GIS in action: none of them would have been possible without long time series of data, and in many cases the data were initially collected either incidentally or without a clear idea of how they might be used in the future. In these days of austerity, the collection of many such long-term data sets has been sacrificed in the name of short-term governmental cost-cutting. It might not be for many years, but I suspect that at some point, we, as the scientific community, will look back with regret that we did not fight harder to stop this happening, because only then will be become clear exactly what we have lost in terms of our ability to monitor how the world around us is changing over time.

On a final note, I want to mention something that, at first, will seem completely unrelated to GIS. This is a piece of software called IPEZ which can be used to aid in the identification of fish species.  What does this have to do with GIS? Well, the program works, in part, by taking morphological measurements and using these to help map out the shape of an unknown fish, and compare it to those of different species. This type of morphological analysis uses many of the same computational tools as GIS, and indeed, you can actually use GIS software to run these exact types of morphological analyses. This means that, while they may seem like very different fields, morphological analyses and GIS share a common skill set, and ones that can be transferred between them. Who would have thought that a bit of GIS could help you identify fish species?.

So these are my pick of GIS-related posts for 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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