M
Marie-Josée Fortin
Researcher at University of Toronto
Publications - 327
Citations - 24151
Marie-Josée Fortin is an academic researcher from University of Toronto. The author has contributed to research in topics: Spatial ecology & Spatial analysis. The author has an hindex of 69, co-authored 306 publications receiving 20890 citations. Previous affiliations of Marie-Josée Fortin include State University of New York System & Université de Sherbrooke.
Papers
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Journal ArticleDOI
Spatial pattern and ecological analysis
TL;DR: In this article, the spatial heterogeneity of populations and communities plays a central role in many ecological theories, such as succession, adaptation, maintenance of species diversity, community stability, competition, predator-prey interactions, parasitism, epidemics and other natural catastrophes, ergoclines, and so on.
Book
Spatial Analysis A Guide for Ecologists
TL;DR: In this paper, the authors present a spatial analysis of complete point location data, including points, lines, and graphs, and a multiscale analysis of the data set, including spatial diversity analysis and spatial autocorrelation.
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Measuring ecological niche overlap from occurrence and spatial environmental data
Olivier Broennimann,Matthew C. Fitzpatrick,Peter B. Pearman,Blaise Petitpierre,Loïc Pellissier,Nigel G. Yoccoz,Wilfried Thuiller,Marie-Josée Fortin,Christophe F. Randin,Niklaus E. Zimmermann,Catherine H. Graham,Antoine Guisan +11 more
TL;DR: A statistical framework to describe and compare environmental niches from occurrence and spatial environmental data and shows that niche overlap can be accurately detected with the framework when variables driving the distributions are known.
Journal ArticleDOI
The consequences of spatial structure for the design and analysis of ecological field surveys
Pierre Legendre,Mark R. T. Dale,Marie-Josée Fortin,Jessica Gurevitch,Michael Hohn,Donald E. Myers +5 more
TL;DR: In this paper, the authors compared the effect of spatial autocorrelation on the statistical tests commonly used by ecologists to analyse field survey data and found that the presence of a broad-scale spatial structure present in data has the same effect on the tests as spatial auto-correlation.
Journal ArticleDOI
A balanced view of scale in spatial statistical analysis
Jennifer L. Dungan,Joe N. Perry,Mark R. T. Dale,Pierre Legendre,S. Citron-Pousty,Marie-Josée Fortin,A. Jakomulska,M. Miriti,Michael S. Rosenberg +8 more
TL;DR: In this paper, the authors identify the influence of observational scale on statistical results as a subset of what geographers call the Modifiable Area Unit Problem (MAUP), and recommend a set of considerations for sampling design to allow useful tests for specific scales of a phenomenon under study.