Research Interests

My research focuses on pure and applied problems in evolutionary ecology and fisheries.  Broadly speaking, I am interested in how predators, prey, and seasonality interact to shape life histories; and conversely, in how life history variation influences predation rates and ultimately population dynamics.  Because continuous feedback between theory and data is fundamental to the understanding of the complex problems in ecology and evolution, my approach is based on a combination of field studies, laboratory experiments, and mathematical modeling. 

Evolutionary ecology of growth

Recently, physiological costs of growth, such as decreased locomotive performance and decreased allocation to defensive structures have been demonstrated in a variety of taxa.  My interests in this area include empirical demonstration of growth costs, laboratory experiments to elucidate their physiological bases, and synthesis of these data in mathematical models to predict the evolution of growth trajectories.  Closely related to this is my work on compensatory growth.  Many organisms exhibit a period of supernormal growth following a period of food limitation.  In some cases, these compensating individuals actually surpass normally growing controls, while in others, little compensation occurs.  In collaboration with M. Mangel (UC Santa Cruz, Ca.), I have been developing a theoretical framework for evaluating the circumstances under which compensatory growth would be selectively advantageous. 

Evolution in harvested populations

Size-selective harvest regimes, which are the regulatory norm in many fisheries – may cause rapid evolution of growth with concomitant practical implications. Size and age at maturity have decreased in many heavily exploited stocks.  With D. Conover (Stony Brook University, NY) I conducted a multigenerational harvest experiment designed to evaluate the evolutionary effects of fishing.  We found that typical harvest practices led to decreased yield as populations evolved and that the greatest long term yields may be obtained by selecting small individuals.  My continuing work in this area includes the development of mathematical models to predict evolutionary changes in response to harvest selection and ultimately construct evolutionarily stable harvest strategies.

Applications of Bayesian nonparametrics in population dynamics modeling.

Understanding population dynamics is the Holy Grail of applied ecology; whether we seek to protect species from extinction or manage exploited populations, we can not do so without understanding the that factors cause populations to grow or decline.  There are two paths from which we can approach the study of population dynamics.  The first involves the derivation of theoretical models while the second involves statistical analysis of population time series.  Ideally, each approach should inform developments in the other.  To this end, I am developing flexible Bayesian methods for reconstructing the functional relationships underlying multispecies interactions and density dependent population regulation.

Recent Publications

Walsh, M.R., S.B. Munch, S. Chiba, and D.O. Conover. 2006. Maladaptive changes in multiple traits caused by fishing: impediments to population recovery. Ecol. Lett. 9:142-148. (pdf version)

Munch, S.B., T. Kottas and M. Mangel. 2005. Bayesian non-parametric analysis of stock-recruitment relationships. Can. J. Fish. Aquat. Sci., 62:1808-1821. (pdf version)

Mangel, M. and S.B. Munch 2005. A life-history perspective on short- and long-term consequences of growth compensation. Am. Nat. 166 (6): E155-E176. (pdf version)

Munch, S.B., M.L. Snover, G. Watters, M. Mangel. 2005. A unified treatment of top-down and bottom-up control of reproduction in populations. Ecol. Lett. 8: 691-695. (pdf version)

Munch, S.B., M. Walsh, and D.O. Conover. 2005. Harvest selection, genetic correlations, and recruitment: one less thing to worry about? Can. J. Fish. Aquat. Sci. 62:802-810. (pdf version)

Conover, D.O., S.A. Arnott, M.R. Walsh, and S.B. Munch. 2005. Darwinian Fishery Science: lessons from the Atlantic silverside. Can. J. Fish. Aquat. Sci., 62:730-737. (pdf version)

Munch, S.B. and D.O. Conover. 2004. Non-linear growth cost in Menidia menidia: theory and empirical evidence.  Evolution 58:661-664. (pdf version)

Munch, S.B. and D.O. Conover. 2003.  Rapid growth results in increased susceptibility to predation in Menidia menidia.  Evolution 57: 2119-2127. (pdf version)

Munch, S.B., Mangel, M., Conover, D.O. 2003.  Quantifying natural selection on body size from field data with an application to winter mortality in Menidia menidia. Ecology 84: 2168-2177. (pdf version)

Conover, D.O. and S.B. Munch. 2002.  Sustaining fisheries yields over evolutionary time scales.  Science. 297:94-96. (pdf version)

Munch, S.B. and D.O. Conover.  2002. Accounting for local physiological adaptation in bioenergetic models: testing hypotheses for growth rate evolution by virtual transplant experiments.  Can. J. Fish. Aquat. Sci. 59:393-403. (pdf version)

Dunning, D., Q. Ross, S.B. Munch, and L.R. Ginzburg. 2002.  Measurement error affects risk estimates for recruitment to the Hudson River stock of striped bass.  The Scientific World 2(S1):238-253. (pdf version)

Book Chapter