Reinterpreting space, time lags, and functional responses in ecological models.

Natural enemy-victim interactions are of major applied importance and of fundamental interest to ecologists. A key question is what stabilizes these interactions, allowing the long-term coexistence of the two species. Three main theoretical explanations have been proposed: behavioral responses, time-dependent factors such as delayed density dependence, and spatial heterogeneity. Here, using the powerful moment-closure technique, we show a fundamental equivalence between these three elements. Limited movement by organisms is a ubiquitous feature of ecological systems, allowing spatial structure to develop; we show that the effects of this can be naturally described in terms of time lags or within-generation functional responses.

[1]  V. Volterra Fluctuations in the Abundance of a Species considered Mathematically , 1926 .

[2]  W. Wilson,et al.  Dynamics of Age-Structured and Spatially Structured Predator-Prey Interactions: Individual-Based Models and Population-Level Formulations , 1993, The American Naturalist.

[3]  Eric Renshaw Modelling biological populations in space and time , 1990 .

[4]  Rodriguez Time delays in density dependence are often not destabilizing , 1998, Journal of theoretical biology.

[5]  G. P. King,et al.  Extracting qualitative dynamics from experimental data , 1986 .

[6]  B. Hörnfeldt,et al.  Delayed Density Dependence as a Determinant of Vole Cycles , 1994 .

[7]  M. Hassell,et al.  The Persistence of Host-Parasitoid Associations in Patchy Environments. II. Evaluation of Field Data , 1991, The American Naturalist.

[8]  Michael P. Hassell,et al.  Spatial structure and chaos in insect population dynamics , 1991, Nature.

[9]  B. Bolker,et al.  Spatial Moment Equations for Plant Competition: Understanding Spatial Strategies and the Advantages of Short Dispersal , 1999, The American Naturalist.

[10]  Elizabeth E. Crone,et al.  Delayed Density Dependence and the Stability of Interacting Populations and Subpopulations , 1997 .

[11]  P. Kareiva Population dynamics in spatially complex environments: theory and data , 1990 .

[12]  Ilkka Hanski,et al.  Coexistence of Competitors in Patchy Environment , 1983 .

[13]  Peter Turchin,et al.  Rarity of density dependence or population regulation with lags? , 1990, Nature.

[14]  Nils Chr. Stenseth,et al.  Population dynamics of the Indian meal moth:Demographic stochasticity and delayed regulatory mechanisms. , 1998 .

[15]  R. Durrett,et al.  The Importance of Being Discrete (and Spatial) , 1994 .

[16]  Robert M. May,et al.  HOST-PARASITOID SYSTEMS IN PATCHY ENVIRONMENTS: A PHENOMENOLOGICAL MODEL , 1978 .

[17]  R. May,et al.  Aggregation of Predators and Insect Parasites and its Effect on Stability , 1974 .

[18]  S. Pacala,et al.  Forest models defined by field measurements : Estimation, error analysis and dynamics , 1996 .

[19]  C. Huffaker Experimental studies on predation : dispersion factors and predator-prey oscillations , 1958 .

[20]  A Hastings,et al.  Spatial heterogeneity and the stability of predator-prey systems. , 1977, Theoretical population biology.

[21]  David A. Rand,et al.  Reconstructing the dynamics of unobserved variables in spatially extended systems , 1997, Proceedings of the Royal Society of London. Series B: Biological Sciences.