0000000001077809
AUTHOR
Nathalie Peyrard
showing 5 related works from this author
A modeling approach to evaluate the influence of spatial and temporal structure of an epidemiological surveillance network on the intensity of phytos…
2017
National audience
Weeds sampling for map reconstruction: a Markov random field approach
2012
In the past 15 years, there has been a growing interest for the study of the spatial repartition of weeds in crops, mainly because this is a prerequisite to herbicides use reduction. There has been a large variety of statistical methods developped for this problem ([5], [7], [10]). However, one common point of all of these methods is that they are based on in situ collection of data about weeds spatial repartition. A crucial problem is then to choose where, in the eld, data should be collected. Since exhaustive sampling of a eld is too costly, a lot of attention has been paid to the development of spatial sampling methods ([12], [4], [6] [9]). Classical spatial stochastic model of weeds cou…
Using coupled hidden markov chains to estimate colonization and seed bank survival in a metapopulation of annual plants
2022
The study of ecological systems is often impeded by components that escape perfect observation, such as the trajectories of moving animals or the status of plant seed banks. These hidden components can be efficiently handled with statistical modeling by using hidden variables, which are often called latent variables.Notably, the hidden variables framework enables us to model an underlying interaction structure between variables (including random effects in regression models) and perform data clustering, which are useful tools in the analysis of ecological data.This book provides an introduction to hidden variables in ecology, through recent works on statistical modeling as well as on estima…
Des HMM pour estimer la dynamique de la banque de graines chez les plantes
2022
La persistance des populations de plantes à fleur repose sur la colonisation et la dormance, cette dernière étant difficile à estimer car la banque de graines est rarement observée. Nous présentons une modélisation par chaînes de Markov cachées couplées qui représente explicitement ces deux processus. Nous l’illustrons sur l’estimation des paramètres clés de la dynamique des plantes adventices.
The importance of long-term monitoring for inferring populations dynamics: the example of the Biovigilance French network on weeds
2014
National audience