Message-ID: <CABkCotRdfNF9q2RqUn37p1ksY=AtJkkUHrUo7wvvtKBGY3wysw@mail.gmail.com>
Date: 2021-03-03T21:56:17Z
From: Manuel Spínola
Subject: [EXTERNAL] Time to Independence in R
In-Reply-To: <SA9PR09MB5967E50282C59FF9E022B9F4F3989@SA9PR09MB5967.namprd09.prod.outlook.com>
Thank you very much Tom.
Manuel
El mi?, 3 mar 2021 a las 15:35, Philippi, Tom (<Tom_Philippi at nps.gov>)
escribi?:
> Manuel--
> I apologize in advance for not answering the exact question you ask about
> packages. [It is included in some geostatistics packages in terms of
> semivariance, nugget, sill, etc.]
>
> In ecological data, time to independence is very scale dependent. There's
> autocorrelation at scales of seconds due to instrument
> temperature-dependence if that hasn't been calibrated for, or the same
> individuals in the camera trap frame. That component of dependence may
> have a half-life of minutes. There's often autocorrelation based on time
> of day & temperature, with cycles of 24 hours. There may be pulse events
> from storms that persist a few days. There's seasonality driving
> temperatures, day lengths, and plant & animal behavior, with cycles of 1
> year. Then where I live there are ENSO-driven temporal dependence at
> scales of 1.5 - 3 years, PDO at about a decade, and ENSO-La Nina dominated
> periods of 4-6 decades that drive not just ocean ecology, but rainfall &
> thus terrestrial ecology. Then there's tends up to climate change.
>
> So, in my experience in optimizing sampling designs for monitoring for
> trends, the majority of the temporal dependence is driven by cycles or
> pulses of characteristic duration, and that is more useful for determining
> the sampling frequency than empirical estimation form a "continuous"
> datastream of limited duration. That approach also helps me think about
> the spatial concordance of the correlated errors: which are site-specific,
> which are concordant across all of the sites.
>
> Tom
>
> -----Original Message-----
> From: R-sig-ecology <r-sig-ecology-bounces at r-project.org> On Behalf Of
> Manuel Sp?nola
> Sent: Wednesday, March 3, 2021 1:06 PM
> To: r-sig-ecology at r-project.org
> Subject: [EXTERNAL] [R-sig-eco] Time to Independence in R
>
>
>
> This email has been received from outside of DOI - Use caution before
> clicking on links, opening attachments, or responding.
>
>
>
> Dear list members,
>
> It is common in ecology to sampling in almost a continuous manner when
> using data loggers, camera traps, sound recorders, gps radio-collars. etc.
>
> Is there any R package to assess time to independence for the data to
> avoid temporal autocorrelation?
>
> I know that there are models to take into account the temporal
> autocorrelation of the data, but I am asking to optimize the data
> collection, before modeling.
>
> Thank you very much in advance.
>
> Manuel
>
> --
> *Manuel Sp?nola, Ph.D.*
> Instituto Internacional en Conservaci?n y Manejo de Vida Silvestre
> Universidad Nacional Apartado 1350-3000 Heredia COSTA RICA mspinola at una.cr
> <mspinola at una.ac.cr> mspinola10 at gmail.com
> Tel?fono: (506) 8706 - 4662
> Personal website: Lobito de r?o <
> https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.google.com%2Fsite%2Flobitoderio%2F&data=04%7C01%7Ctom_philippi%40nps.gov%7C7c92bae61c0d458d045908d8de8881b0%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C637504025171590082%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=qTaPgnDdCNuCtww7koY%2F7StrjYRczIa2YNZiNveJo%2FQ%3D&reserved=0
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--
*Manuel Sp?nola, Ph.D.*
Instituto Internacional en Conservaci?n y Manejo de Vida Silvestre
Universidad Nacional
Apartado 1350-3000
Heredia
COSTA RICA
mspinola at una.cr <mspinola at una.ac.cr>
mspinola10 at gmail.com
Tel?fono: (506) 8706 - 4662
Personal website: Lobito de r?o <https://sites.google.com/site/lobitoderio/>
Institutional website: ICOMVIS <http://www.icomvis.una.ac.cr/>
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