Christopher M. Moore (Chris)

Assistant Professor of Biology

Office: Olin Science Center 216 [ campus map ]
Phone: 207-859-5746
Fax: 207-859-5705
Moore, Christopher M.


Doctor of Philosophy, 2014, University of Nevada, Reno
Bachelor of Science in Biology, 2005, California State Polytechnic University, Pomona

Areas of Expertise

  • Ecology
  • Population ecolgogy
  • Community ecology
  • Species interactions
  • Mutualism
  • Experimental design
  • Theoretical ecology
  • Spatial ecology
  • Natural history

Current Research

I am an ecologist concerned with the distribution and abundance of organisms. My specific area of study is how the distributions and abundances of organisms are affected by positive species interactions known as mutualism. Mutualism, sometimes referred to as cooperation, is where 2 or more species directly benefit from each other (in currencies such as survival or reproduction), in cases such as plants and pollinators, coral and zooxanthellae, and plants and seed-dispersing animals. I use both empirical and theoretical approaches to my work, and I am always eager to work with interested and motivated students.


Selected publications
Dittel J.W., Moore C.M., and S.B. Vander Wall., 2019. The mismatch in distributions of vertebrates and the plants that they disperse. Ecography, 42(4), pp.621-31.

Moore, C.M., Catella, S.A. and Abbott, K.C., 2018. Population dynamics of mutualism and intraspecific density dependence: How θ-logistic density dependence affects mutualistic positive feedback. Ecological Modelling, 368, pp.191-197.

Moore, C.M. and Vander Wall, S.B., 2015. Scatter-hoarding rodents disperse seeds to safe sites in a fire-prone ecosystem. Plant ecology, 216(8), pp.1137-1153.

Vander Wall, S.B. and Moore, C.M., 2016. Interaction diversity of North American seed‐dispersal mutualisms. Global Ecology and Biogeography, 25(11), pp.1377-1386.

Moore, C.M., Stieha, C.R., Nolting, B.C., Cameron, M.K. and Abbott, K.C., 2015. QPot: An R Package for Stochastic Differential Equation Quasi-Potential Analysis. The R Journal, 8(2), pp.19-38.



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