Canadian contributions to environmetrics

Abstract

This article focuses on the importance of collaboration in statistics by Canadian researchers and highlights the contributions that Canadian statisticians have made to many research areas in environmetrics. We provide a discussion about different vehicles that have been developed for collaboration by Canadians in the environmetrics context as well as specific scientific areas that are focused on environmetrics research in Canada including climate science, forestry, and fisheries, which are areas of importance for natural resources in Canada.Résumé: Cet article souligne l'ampleur de la collaboration entre les scientifiques canadiens dans le domaine de la statistique et présente un survol des travaux réalisés par des spécialistes du sujet sur un ensemble de thèmes liés aux sciences de l'environnement. Les auteurs relatent différents moyens par lesquels cette collaboration s'est incarnée et a permis aux Canadiennes et Canadiens de contribuer à l'environnemétrie et à divers domaines connexes, notamment les sciences du climat, la foresterie et les pêches, dont l'importance est capitale pour la gestion des ressources naturelles du pays.

How to perform modeling with independent and preferential data jointly?

“…Geostatistical models refer to models applied over point referenced data (Diggle et al, 1998), while preferential models refer to models that account for the dependence between the process under study and the sampling locations (Diggle et al, 2010). Different studies have demonstrated the importance of accounting for the sampling process to infer good abundance estimates (Pennino et al, 2019;Watson et al, 2019;Dean et al, 2022). But, what if we have both randomly and preferentially sampled data?…”