Quantitative Analysis of Ecological Networks

‘Recommended.’ M. P. Gustafson, Choice Magazine
‘The foundations of the analysis of ecological graphs are provided in an almost encyclopedic format by two experts in graph theory. Their presentation emphasizes definitions, simple line graph illustrations, quantitative formulations, and references necessary for employing graph-theory concepts to analyze ecological communities … The comprehensive review of graph-theoretic analysis by the authors is an invaluable reference for those who wish to focus on how the topology of ecosystems provides clues concerning system structure and function.’ Robert E. Ulanowicz, The Quarterly Review of Biology

Mark R. T. Dale is a Professor in Environmental Science at the University of Northern British Columbia. His research interests include the spatial structure of plant communities and the development and evaluation of numerical methods to answer ecological questions, including graph theory and network complexity. His graduate students have worked in a diverse set of systems from prairie to alpine and at a range of spatial scales from plant neighbour competition to landscape disturbance patterns. He wrote Spatial Pattern Analysis in Plant Ecology (Cambridge 1999), and Applying Graph Theory in Ecological Research (Cambridge 2017) and was co-author, with Marie-Josée Fortin, of Spatial Analysis: A Guide for Ecologists (Cambridge 2005, 2nd ed. 2014).

Marie-Josée Fortin is a University Professor in Ecology and Evolutionary Biology at the University of Toronto. She is a Fellow of the Royal Society of Canada and holds a Tier 1 Canada Research Chair in Spatial Ecology. Her research endeavors focus on conservation biology issues. She investigates how ecological processes and environmental factors affect species persistence, species dispersal, and species range dynamics. Her research is at the interface of several disciplines (spatial ecology, conservation, forest ecology, disturbance ecology, community ecology, landscape genetics, spatial epidemiology, spatial statistics, spatially explicit modeling, and network theory) where the most important challenging problems lie.

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