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Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field.
Petrovskaya, Natalia B; Forbes, Emily; Petrovskii, Sergei V; Walters, Keith F A.
Afiliação
  • Petrovskaya NB; School of Mathematics, University of Birmingham, Birmingham B15 2TT, UK. n.b.petrovskaya@bham.ac.uk.
  • Forbes E; Harper Adams University, Newport, Shropshire TF10 8NB, UK. eforbes@harper-adams.ac.uk.
  • Petrovskii SV; Department of Mathematics, University of Leicester, Leicester LE1 7RH, UK. sp237@le.ac.uk.
  • Walters KFA; Harper Adams University, Newport, Shropshire TF10 8NB, UK. keith.walters@imperial.ac.uk.
Insects ; 9(1)2018 Feb 27.
Article em En | MEDLINE | ID: mdl-29495513
ABSTRACT
Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Insects Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Insects Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido