Eleni Matechou

TL;DR: In this article, the authors review the mathematical foundations of model averaging along with the diversity of approaches available and stress the importance of non-parametric methods such as cross-validation for a reliable uncertainty quantification of model-averaged predictions.

TL;DR: This work presents a novel Bayesian model for analysing eDNA data by proposing informative prior distributions for logistic regression coefficients that allow us to overcome parameter identifiability, while performing efficientBayesian model-selection.

TL;DR: This work introduces a new modelling approach, which borrows ideas from the ‘stopover’ capture–recapture literature, that permits the estimation of parameters of interest, such as mean arrival times and relative abundance, or in some cases, absolute abundance, and the comparison of these between sites.

TL;DR: In this paper, two sets of data were collected at the stop-over site: a capture-recapture-resighting data set and a vector of counts of unmarked birds.

TL;DR: In this article , the authors outline challenges for biodiversity monitoring using citizen science data in four partially overlapping categories: challenges that arise as a result of observer behaviour, data structures, statistical models, and communication.