[tlocoh-info] Ancillary variables

Andy Lyons lyons.andy at gmail.com
Mon Oct 24 19:22:26 CEST 2016

Hi Maja. Good questions. You are correct that there are not many 
guidelines for using ancillary variables in the documentation, but your 
instincts on how they could be useful in an analysis seem spot on. As a 
reminder to others, 'ancillary variable' is the T-LoCoH term for  
additional columns or attributes associated with each location. They can 
be either measured values from a GPS sensor (e.g., temperature), or 
derived during post-processing from other data (e.g., NDVI values). See 
lxy.anv.add() and lxy.gridanv.add(). Internally, ancillary variables are 
saved in columns in the data frame attached to the 
SpatialPointsDataFrame which contains the locations. All the original 
points are saved in both locoh-xy and locoh-hullset objects.

One way you can use ancillary variables is for subsetting data, as you 
suggested. This could be useful for example if you wanted to look at 
space use patterns for different sets of locations based on an attribute 
field. To create subsets of hulls, see lhs.filter.anv(), to create 
subsets of points from a locoh-xy object see lxy.subset() (I can send a 
code sample if it isn't clear how to use). Subsetting location data 
could also of course be done prior to turning the locations into a 
locoh-xy object.

Ancillary variables can also be used to sort hulls when constructing 
isopleths. This is one option for differentiating internal space within 
the 'home range' along a gradient other than density. If your GPS sensor 
recorded temperature, for example, you could create a utilization 
distribution that highlights how the individual used the space based on 
a temperature gradient. IMHO, the ability to create UDs that 
differentiate space use along behavioral or environmental gradients is 
one of T-LoCoH's most interesting and underutilized features which has a 
lot of promise for connecting the concept of a home range to a much 
broader range of behavioral and ecological questions (e.g., Fieberg and 
Börger 2012 <http://jmammal.oxfordjournals.org/content/93/4/890>).

To sort hulls based on an ancillary variable, you would pass 
sort.metric="anv" to the function lhs.iso.add(), with an additional 
argument called anv that passes the name of the ancillary variable 
column name of interest (e.g., anv="temp"). The 'anv' hull metric is 
defined to be the ancillary variable value of the hull parent point. You 
may ask why the hull parent point, and not the mean value of all points 
used to construct the hull, or all points enclosed by the hull? That was 
just the easiest to implement, but if you were going to sort hulls for 
isopleths it might be better to define a hull metric for the mean 
ancillary value for all enclosed points (depends on the pattern you're 
seeking). Defining new hull metrics is not terribly hard but takes some 
coding knowledge, contact me for details.

You can also use ancillary variables of the hull parent point as you 
would any other hull metric - for plotting symbology, in scatter plots, 
etc. If you see an interesting pattern in a two-dimensional scatterplot 
of an ancillary variable and another hull metric, you can use that as a 
legend in a map (e.g., Fig 10 
in Lyons et al 2013 <http://dx.doi.org/10.1186/2051-3933-1-2>).

Hope this helps you think about possible ways for using ancillary 
variables in an analysis. A lot of this is new territory, but T-LoCoH is 
all about giving you a flexible set of tools to explore and visualize 
your data. Let me know if you have any questions or need help with any 
of the functions.


On 10/19/2016 6:54 AM, maja.bradaric92 at gmail.com wrote:
> Hello everyone,
> I’ve started to use T-LoCoH just recently and I am still investigating 
> can this package help me answer all the questions I have in my 
> research. I guess this is very basic question, but, there is no so 
> much explained about ancillary variables and what can be done if we 
> have them in our data.
> If I include ancillary variables in my lxy object (temperature, for 
> example), does that mean space use maps will later be created 
> according to the ancillary variable? Or I can use them just to make 
> subsets of the hulls according to certain temperature values? Can I 
> produce behavioural maps according to temperature and possible 
> temperature changes? I don`t really understand how this works, so I 
> would be very grateful for any clarification, in order to be able to 
> continue with my data analysis.
> Also, is it possible to include only one ancillary variable, or it can 
> be more of them?
> Thanks in advance.
> Cheers,
> Maja
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*T-LoCoH*: A hull-based method for home range construction and 
spatiotemporal analysis of movement data.
Lyons, A., Turner, W.C., and WM Getz. 2013. Home Range Plus: A 
Space-Time Characterization of Movement Over Real Landscapes. BMC 
Movement Ecology 1:2 <http://www.movementecologyjournal.com/content/1/1/2>.

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