<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0034-7744</journal-id>
<journal-title><![CDATA[Revista de Biología Tropical]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. biol. trop]]></abbrev-journal-title>
<issn>0034-7744</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Costa Rica]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0034-77442016000401441</article-id>
<article-id pub-id-type="doi">10.15517/rbt.v64i4.22176</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Does Plan B work? Home range estimations from stored on board and transmitted data sets produced by GPS-telemetry in the Colombian Amazon]]></article-title>
<article-title xml:lang="es"><![CDATA[¿Funciona el plan B? Estimación de rango de hogar a partir de datos almacenados en instrumentos a bordo de animales y los obtenidos a partir de telemetría satelital de GPS en el Amazonas colombiano.]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cabrera]]></surname>
<given-names><![CDATA[Jaime A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Molina]]></surname>
<given-names><![CDATA[Eduardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González]]></surname>
<given-names><![CDATA[Tania]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Armenteras]]></surname>
<given-names><![CDATA[Dolors]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia Departamento de Biología ]]></institution>
<addr-line><![CDATA[ Bogotá]]></addr-line>
<country>CO</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<volume>64</volume>
<numero>4</numero>
<fpage>1441</fpage>
<lpage>1450</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_arttext&amp;pid=S0034-77442016000401441&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_abstract&amp;pid=S0034-77442016000401441&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_pdf&amp;pid=S0034-77442016000401441&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract:Telemetry based on Global Positioning Systems (GPS) makes possible to gather large quantities of information in a very fine scale and work with species that were impossible to study in the past. When working with GPS telemetry, the option of storing data on board could be more desirable than the sole satellite transmitted data, due to the increase in the amount of locations available for analysis. Nonetheless, the uncertainty in the retrieving of the collar unit makes satellite-transmitted technologies something to take into account. Therefore, differences between store-on-board (SoB) and satellite-transmitted (IT) data sets need to be considered. Differences between SoB and IT data collected from two lowland tapirs (Tapirus terrestris), were explored by means of the calculation of home range areas by three different methods: the Minimum Convex Polygon (MCP), the Fixed Kernel Density Estimator (KDE) and the Brownian Bridges (BB). Results showed that SoB and IT data sets for the same individual were similar, with fix ranging from 63 % to 85 % respectively, and 16 m to 17 m horizontal errors. Depending on the total number of locations available for each individual, the home ranges estimated showed differences between 2.7 % and 79.3 %, for the 50 % probability contour and between 9.9 % and 61.8 % for the 95 % probability contour. These differences imply variations in the spatial coincidence of the estimated home ranges. We concluded that the use of IT data is not a good option for the estimation of home range areas if the collar settings have not been designed specifically for this use. Nonetheless, geographical representations of the IT based estimators could be of great help to identify areas of use, besides its assistance to locate the collar for its retrieval at the end of the field season and as a proximate backup when collars disappear. Rev. Biol. Trop. 64 (4): 1441-1450. Epub 2016 December 01.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen:La telemetría basada en los sistemas de geopocisionamiento global (GPS) hace posible recopilar gran cantidad de información a escalas muy finas, y trabajar con especies imposibles de estudiar en el pasado. Al trabajar con telemetría de GPS, la opción de guardar información en la memoria interna del instrumento puede ser más deseable que sólo tener acceso a la información enviada vía satélite, debido a la mayor cantidad de localizaciones disponibles para analizar. No obstante, la incertidumbre de recuperar el collar hace que las tecnología de trasmisión vía satélite deba ser tenida en cuenta. Diferencias entre las bases de datos almacenadas en el collar (SoB) y las trasmitidas vía satélite (IT), recolectadas de dos individuos de Tapir de tierras bajas (Tapirus terrestris), son consideradas, en términos de las áreas de los rangos de hogar calculados con cada uno y mediante el uso de tres metodologías diferentes: Mínimo Polígono Convexo (MCP), Estimador de Densidad de Kernel Fijo (KDE) y los Puentes Brownianos (BB). Las bases de datos SoB e IT son similares, con tasas de acierto de localizaciones que oscilan entre 63 % to 85 % y errores horizontales de 16 m y 17 m respectivamente. Dependiendo del número total de localizaciones disponibles para cada individuo, los rangos de hogar estimados muestran diferencias entre 2.7 % y 79.3 %, para el contorno del 50 % de probabilidades, y entre 9.9 % y 61.8 % para el contorno del 95 % de probabilidades. Estas diferencias implican variaciones en la coincidencia espacial de los rangos de hogar estimados. Concluimos que el uso de la información trasmitida vía satélite no es una buena opción para la estimación de rangos de hogar, si la programción de los collares no ha sido diseñada específicamente para tal fin. Sin embargo, las representaciones geográficas de los estimados a partir de las bases de datos IT pueden ser de gran ayuda para la identificación de áreas de uso, además de su utilidad para la localización y recuperación de collares tras su liberación de los individuos monitoreados y como una base de datos de soporte en caso de pérdida del collar.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[brownian bridges]]></kwd>
<kwd lng="en"><![CDATA[Colombian Amazon]]></kwd>
<kwd lng="en"><![CDATA[gps telemetry]]></kwd>
<kwd lng="en"><![CDATA[home range]]></kwd>
<kwd lng="en"><![CDATA[kernel density estimator]]></kwd>
<kwd lng="en"><![CDATA[minimum convex polygon]]></kwd>
<kwd lng="en"><![CDATA[Tapirus terrestris.]]></kwd>
<kwd lng="es"><![CDATA[Puentes brownianos]]></kwd>
<kwd lng="es"><![CDATA[Amazonía colombiana]]></kwd>
<kwd lng="es"><![CDATA[telemetría]]></kwd>
<kwd lng="es"><![CDATA[gps]]></kwd>
<kwd lng="es"><![CDATA[rango de hogar]]></kwd>
<kwd lng="es"><![CDATA[estimador de densidad de kernel]]></kwd>
<kwd lng="es"><![CDATA[mínimo polígono convexo]]></kwd>
<kwd lng="es"><![CDATA[Tapirus terrestris.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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