[tlocoh-info] Dealing with multiple datasets Digest, Vol 6, Issue 8
Wayne Getz
wgetz at berkeley.edu
Wed May 28 01:50:29 CEST 2014
Hi Thomas
I would suggest that you start using a fixed k method. This is more intuitive and you know how many consecutive points you will get if you select s large enough to wash out spatial distances. Thus if you are interested in diurnal patterns and have a fix frequency of one point every hour, then choosing k=7, 13 or 25 will give you hulls that correspond to a quarter, half or full 24-hour day (provide s is large enough). The a (adaptive method) is most appropriate if you are trying to build utilization distributions and want to adaptively change the number points where densities are high (in the core) verses low (at the boundaries). These distributions are best constructed with s=0 or very close to 0. In this case, I would select a value for a using our guide but compare what I get to values of a that are x% bigger or smaller where x may be something like 30%.
Good luck.
Wayne
> Anne,
>
> I appreciate the response and help. I am still confused on the methods of computing a 's' and 'a' value for all of my datasets. Do I need to merge the data into 1 CSV doc and separate them by a Freq column, or do I need to individually load the datasets and run one-by-one or at the same time?
>
> Also, I have read and practiced the tutorial, it was helpful, but still only looked at one animal's data set in that example.
>
> As far as the coordinate system, I believe I am going to have everything calculated in UTMs. I will also try and figure out the resampling protocol to work with all of my datasets.
>
> Thanks and have a good one,
>
>
> Thomas
> ________________________________________
> From: tlocoh-info-bounces at lists.r-forge.r-project.org [tlocoh-info-bounces at lists.r-forge.r-project.org] on behalf of Anna Schweiger [anna.schweiger at nationalpark.ch]
> Sent: Tuesday, May 27, 2014 12:20 PM
> To: tlocoh-info at lists.r-forge.r-project.org
> Subject: Re: [tlocoh-info] Dealing with multiple datasets Digest, Vol 6, Issue 8
>
> Hi Thomas,
>
> I was also recently thinking on how to deal with multiple
> datasets/multiple individuals.
> Thanks to Wayne´s and Andy´s responses I could get my head around it.
> The short version (at least in my case) is:
> Either use the same parameter values for all individuals or the same
> technique (the same treshold) to select the paramter values.
> You find the full responses here (see point 1):
> http://lists.r-forge.r-project.org/pipermail/tlocoh-info/2014-May/000013.html
>
> For me a good way to get started with was to follow the Tutorial on
> the TLoCoH homepage with my own data.
> In the tutorial most initial issues are covered (coordinate systems,
> data import). Have you already seen it?
> http://tlocoh.r-forge.r-project.org/tlocoh_tutorial_2013-09-22.pdf
>
> Regarding coordinate system: I think you have to decide on one. Maybe
> it´s best to use the coordinate system of your environmental data. If
> you are working with raster data, it´s nice to avoid reprojecting
> them. While reprojecting trajectories or points is quite straight
> forward, raster reprojection involves two steps 1) project the cell
> centers into the new CRS 2) resample the cell values into a regular
> grid system. So, I always choose to reproject points, lines, polygons
> and not raster.
>
> If you have differing sampling schemes, you can resample the data to a
> common frequency (using xy.thin.byfreq).
> For example:
>> ibex.4h.lxy <- lxy.thin.byfreq (ibex.lxy, trim.ends=FALSE, samp.freq=14400, status=T)
> # resamples my data on ibex, with sampling frequencies of 10 min, 2 h
> and 4 h to a common interval of 4 h (14400 seconds)
>
> As far as I understood it, differing data set sizes (e.g. 1 month
> compared to 2 years) are not problematic, because if you include time
> in your analysis (s > 0), two points have to be close in time as well
> as close in space to be considered as nearest neighbours. Of course,
> if you are comparing individuals, the times (biological seasons) have
> to be matched between individuals and you have to have enough
> locations for nearest neighbours calculations (I chose to include only
> indiv. with more than 90 fixes after resampling to a common
> frequency).
>
> Hope it helps a bit.
> Good luck with your analysis!
>
> Cheers, Anna
>
>
> On Tue, 27 May 2014 12:00:11 +0200
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>> Today's Topics:
>>
>> 1. Dealing w/ multiple datasets (Thomas Janke)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Mon, 26 May 2014 21:18:12 +0000
>> From: Thomas Janke <tjanke at sulross.edu>
>> To: "tlocoh-info at lists.r-forge.r-project.org"
>> <tlocoh-info at lists.r-forge.r-project.org>
>> Subject: [tlocoh-info] Dealing w/ multiple datasets
>> Message-ID:
>> <58862834A696BF4CA83ABDD585FD1C130C672450 at mailstoreEx2010.srsu.edu>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> Andy,
>>
>>
>>
>> My name is Thomas Janke. I am a graduate student at Sul Ross State
>> University in west Texas working for the Borderlands Research
>> Institute. Over the past 3 years, I have been monitoring the
>> movements and survival of reintroduced desert bighorn sheep to part
>> of their historic range. Now comes time for the analysis and writing.
>>
>>
>>
>> After diving into past research and methodology, I knew I wanted to
>> do more than just create and compare MCPs or KDEs to begin describing
>> my research. Which brings me to you and your T_LoCoH software. I
>> believe it is great y'all were able to create a software package that
>> incorporates time into the analysis.
>>
>>
>>
>> I am new to this software, but am willing to do what it takes to
>> become more familiarized with it and be able to incorporate it into
>> my data analysis. I have read your dissertation, your Home Range Plus
>> publication, and the overview of the T_LoCoH program, along with
>> following through with the example sets. Now its time for me to start
>> analyzing my data.
>>
>>
>>
>> We conducted 2 consecutive releases (2010 & 2011) for this
>> restoration effort. I currently have data from 54 GPS collars, with
>> data collection ranging from <1wk to >2yrs. Over the course of the
>> study, we used 3 different types of collars (all of which have
>> differing data formats). The 2010 released collars collected data in
>> Lat/Long and were programmed to obtain a location every 3 hours. The
>> 2011 released collars collected data in UTMs and were programmed to
>> collect a location every 5 hours.
>>
>>
>>
>> I would ultimately like to compare the movements and UDs by release
>> year, sex, and time of year (ecological seasons). I would also like
>> to use the GPS data to see if there are any preferred habitats (e.g.
>> slope, aspect, terrain ruggedness, etc.) for the previously mentioned
>> comparisons. It would also be great to be able to delineate 'travel
>> corridor(s)' from the GPS data (esp. the sheep that were documented
>> crossing international borders).
>>
>>
>>
>> How do I need to go about entering and analyzing all of my data? Is
>> there a way to compute an 's', and an 'a or k' value that can be used
>> on all of the sheep, or will I have to determine individual values?
>> If I am able to combine the data sets, how to I need to go about the
>> different coordinate systems? How do I deal with differing data set
>> sizes (e.g. 1 month compared to 2 years) or collars that had
>> different acquisition rates?
>>
>>
>>
>> Any help you're able to give would be most appreciated.
>>
>>
>>
>> Thanks and have a good one,
>>
>>
>>
>>
>>
>> Thomas
>>
>>
>>
>>
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___________________________________________________________
___________________________________________________________
Professor Wayne M. Getz
A. Starker Leopold Professor of Wildlife Ecology
Department Environmental Science Policy & Management
130 Mulford Hall
University of California at Berkeley
CA 94720-3112, USA
Campus Visitors: My office is in 5052 VLSB
Fax: ( (1-510) 666-2352
Office: (1-510) 642-8745
Lab: (1-510) 643-1227
email: wgetz at berkeley.edu
lab: http://www.CNR.Berkeley.EDU/~getz/
T-LoCoH: http://tlocoh.r-forge.r-project.org/
NOVA: http://www.novamodeler.com/
___________________________________________________________
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