Spatial modelling of plant diversity from high-throughput environmental dna sequence data

Angelika Studeny 1, * Florence Forbes 1, * Eric Coissac 2 Alain Viari 3 Celine Mercier 2 Lucie Zinger 2 Aurélie Bonin 2 Frédéric Boyer 2 Pierre Taberlet 2
* Corresponding author
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 BAMBOO - An algorithmic view on genomes, cells, and environments
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : This paper considers a statistical modelling approach to investigate spatial cross-correlations between species in an ecosystem. A special feature is the origin of the data from high-troughput environmental DNA sequencing of soil samples. Here we use data collected at the Nourague CNRS Field Station in French Guiana. We describe bivariate spatial relationships in these data by a separable linear model of coregionalisation and estimate a cross-correlation parameter. Based on this estimate, we visualise plant taxa co-occurrence pattern in form of 'interaction graphs' which can be interpreted in terms of ecological interactions. Limitations of this approach are discussed along with possible alternatives.
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Submitted on : Monday, January 20, 2014 - 10:54:50 PM
Last modification on : Thursday, March 21, 2019 - 2:51:28 PM

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  • HAL Id : hal-00933699, version 1

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Angelika Studeny, Florence Forbes, Eric Coissac, Alain Viari, Celine Mercier, et al.. Spatial modelling of plant diversity from high-throughput environmental dna sequence data. 45èmes Journées de Statistique, Société Française de Statistique, May 2013, Toulouse, France. ⟨hal-00933699⟩

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