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<p>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 <tt>lxy.anv.add()</tt> and <tt>lxy.gridanv.add()</tt>.
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.<br>
<br>
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 <tt>lhs.filter.anv()</tt>,
to create subsets of points from a locoh-xy object see <tt>lxy.subset()</tt>
(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. <br>
<br>
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., <a
href="http://jmammal.oxfordjournals.org/content/93/4/890">Fieberg
and Börger 2012</a>). <br>
<br>
To sort hulls based on an ancillary variable, you would pass <tt>sort.metric="anv"</tt>
to the function <tt>lhs.iso.add()</tt>, with an additional
argument called <tt>anv</tt> that passes the name of the
ancillary variable column name of interest (e.g., <tt>anv="temp"</tt>).
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.<br>
<br>
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., <a
href="https://static-content.springer.com/image/art%3A10.1186%2F2051-3933-1-2/MediaObjects/40462_2012_Article_2_Fig10_HTML.jpg">Fig
10</a> in <a href="http://dx.doi.org/10.1186/2051-3933-1-2">Lyons
et al 2013</a>). <br>
<br>
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.<br>
<br>
Cheers,<br>
Andy <br>
<br>
<br>
<br>
</p>
<br>
<div class="moz-cite-prefix">On 10/19/2016 6:54 AM,
<a class="moz-txt-link-abbreviated" href="mailto:maja.bradaric92@gmail.com">maja.bradaric92@gmail.com</a> wrote:<br>
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<p class="MsoNormal">Hello everyone,</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">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. </p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">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.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Also, is it possible to include only one
ancillary variable, or it can be more of them?</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Thanks in advance.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Cheers,</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Maja</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<br>
<div class="moz-signature">-- <br>
<font face="Times New Roman, Times, serif">
<strong>T-LoCoH</strong>: A hull-based method for home range
construction and spatiotemporal analysis of movement data.<br>
Lyons, A., Turner, W.C., and WM Getz. 2013. Home Range Plus: A
Space-Time Characterization of Movement Over Real Landscapes. <a
href="http://www.movementecologyjournal.com/content/1/1/2">BMC
Movement Ecology 1:2</a>.<br>
<a href="http://tlocoh.r-forge.r-project.org">http://tlocoh.r-forge.r-project.org</a><br>
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