[R-sig-Geo] GRTS sampling - 2-level design

[John Wilson]

Dear Thierry,

Thank you so much for your reply. Yes, the loss of the spatial balance once
the two-tiered approach is not accounted for was what was worrying me.

The incorporation of region as a random effect has two issues - 1) the
overall sampling area is a lake, and "regions" don't make sense in that
context. 2) The analysis is a mark-recapture for fish (using the MARK
software); I've never seen the incorporation of random effects in the
Jolly-Seber / Cormark-Jolly-Seber models outside of Bayesian framework and
outside of individual random effects... but even if I could do that - the
regions just don't really make sense anyway (that I can see, anyway - maybe
I'm not thinking about it the right way?)

Thank you for the grtsdb suggestion. Do you have any examples of how this
works? I couldn't find any vignettes or worked examples...

Thank you so much,
John

On Fri, Oct 8, 2021 at 10:39 AM Thierry Onkelinx <thierry.onkelinx using inbo.be>
wrote:

> Dear John,
>
> Your procedure will create a spatially balanced level 1 sample (10
> "regions") and within those regions a spatially balanced level 2 sample.
> When you ignore the structure, there is no longer a spatial balance. So
> you'll need to incorporate the two level sampling structure in your
> analysis. E.g. by using region as random effect.
>
> I presume you are catching fish along rivers and assume that the rivers
> are linear features. I'd consider drawing 10 samples using GRTS to define
> the regions. Then use that location as the center point of 5 systematic
> samples along the river (-2, -1, 0, +1 and +2 km).
>
> You might want to take a look at our grtsdb package. Available at
> https://inbo.r-universe.dev/ It generates a full grid of master samples
> and stores it in the database. So you can draw multiple samples from the
> same master sample. This is useful in case of monitoring with a changing
> population. You draw a sample and keep the lowest ranking locations that
> are part of the population. If the population changes over time, then the
> new sample will keep a proportion of the original sampling location
> relative to the proportion of the population that remained stable. This
> allows for repeated measures for stable locations while taking into account
> the changes in population.
>
> Best regards,
>
> Thierry
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be
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>
>
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> Op do 7 okt. 2021 om 15:54 schreef John Wilson <jhwilson.nb using gmail.com>:
>
>> Oh, sorry - I normally use the grts() function from the spsurvey package.
>> My hacky approach was to make 10 balanced points with grts(), followed by
>> imposing a 5 km buffer around each one, and either systematic sampling
>> within the buffer circle, or running a separate GRTS for the 5 points
>> within each 5 km buffer circle. Even writing this makes me cringe though,
>> so hoping for something legitimate... I'll contact the authors if I don't
>> get any solid leads on here.
>>
>> On Thu, Oct 7, 2021 at 10:40 AM Roger Bivand <Roger.Bivand using nhh.no> wrote:
>>
>> > On Thu, 7 Oct 2021, John Wilson wrote:
>> >
>> > > Hi everyone,
>> > >
>> > > I'm working on a sampling design using GRTS, but I'm running into a
>> > > logistics problem. The field crew can set 5 nets per day, but only
>> > within a
>> > > 5 km stretch, due to travel time constraints. With 10 sampling days,
>> > that's
>> > > a total of 50 sites. The overall sampling area is huge, so running a
>> > > regular GRTS design for 50 sites results, of course, in much larger
>> > > distances between sampling points.
>> > >
>> > > Is there a legitimate way to create a 2-level GRTS design, where in
>> step
>> > 1
>> > > we choose 10 spatially-balanced sampling points (one "core" point per
>> > > sampling day), and then for each of these "core points", we create a
>> grid
>> > > of 5 sampling points that are constrained to all be within 5 km from
>> each
>> > > other? I can make that happen code-wise, but am not sure what the
>> > > implications on spatial balance are, or if there's a built-in way to
>> do
>> > > this.
>> >
>> > Do you have a code example? Are you using BalancedSampling, SDraw or
>> > Spbsampling or packages (probably SDraw)? Have you run any simulations
>> to
>> > try to get a first assessment on the impact of constraining your sample?
>> > Might approach a package author also help?
>> >
>> > Roger
>> >
>> >
>> > >
>> > > Would appreciate any thoughts...
>> > > John
>> > >
>> > >       [[alternative HTML version deleted]]
>> > >
>> > > _______________________________________________
>> > > R-sig-Geo mailing list
>> > > R-sig-Geo using r-project.org
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>> > >
>> >
>> > --
>> > Roger Bivand
>> > Emeritus Professor
>> > Department of Economics, Norwegian School of Economics,
>> > Postboks 3490 Ytre Sandviken, 5045 Bergen, Norway.
>> > e-mail: Roger.Bivand using nhh.no
>> > https://orcid.org/0000-0003-2392-6140
>> > https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>> >
>>
>>         [[alternative HTML version deleted]]
>>
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