Scaling up population dynamics: integrating theory and data

How to scale up from local-scale interactions to regional-scale dynamics is a critical issue in field ecology. We show how to implement a systematic approach to the problem of scaling up, using scale transition theory. Scale transition theory shows that dynamics on larger spatial scales differ from predictions based on the local dynamics alone because of an interaction between local-scale nonlinear dynamics and spatial variation in density or the environment. Based on this theory, a systematic approach to scaling up has four steps: (1) derive a model to translate the effects of local dynamics to the regional scale, and to identify key interactions between nonlinearity and spatial variation, (2) measure local-scale model parameters to determine nonlinearities at local scales, (3) measure spatial variation, and (4) combine nonlinearity and variation measures to obtain the scale transition. We illustrate the approach, with an example from benthic stream ecology of caddisflies living in riffles. By sampling from a simulated system, we show how collecting the appropriate data at local (riffle) scales to measure nonlinearities, combined with measures of spatial variation, leads to the correct inference for dynamics at the larger scale of the stream. The approach provides a way to investigate the mechanisms and consequences of changes in population dynamics with spatial scale using a relatively small amount of field data.

[1]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1951 .

[2]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[3]  G. Jong The Influence of the Distribution of Juveniles Over Patches of Food On the Dynamics of a Population , 1978 .

[4]  Peter Chesson,et al.  Predator-Prey Theory and Variability , 1978 .

[5]  M. Lloyd,et al.  On Reconciling Patchy Microspatial Distributions with Competition Models , 1980, The American Naturalist.

[6]  Yang Lo A General Criterion , 1984 .

[7]  A. Ives Covariance, coexistence and the population dynamics of two competitors using a patchy resource , 1988 .

[8]  L. R. Taylor,et al.  Specificity of the spatial power-law exponent in ecology and agriculture , 1988, Nature.

[9]  A. Townsend Peterson,et al.  The Fallacy of Averages , 1988, The American Naturalist.

[10]  Peter Chesson,et al.  The Persistence of Host-Parasitoid Associations in Patchy Environments. I. A General Criterion , 1991, The American Naturalist.

[11]  S. Kohler Competition and the Structure of a Benthic Stream Community , 1992 .

[12]  D. Ruppert,et al.  Measurement Error in Nonlinear Models , 1995 .

[13]  J. Perry,et al.  Estimating Taylor's power law parameters for weeds and the effect of spatial scale , 1996 .

[14]  Andy W. Sheppard,et al.  Frontiers of population ecology , 1997 .

[15]  Simon A. Levin,et al.  Biologically generated spatial pattern and the coexistence of competing species , 1997 .

[16]  R. Hilborn,et al.  The Ecological Detective: Confronting Models with Data , 1997 .

[17]  Ilkka Hanski,et al.  The Metapopulation Approach, Its History, Conceptual Domain, and Application to Conservation , 1997 .

[18]  M. Wiley,et al.  PATHOGEN OUTBREAKS REVEAL LARGE‐SCALE EFFECTS OF COMPETITION IN STREAM COMMUNITIES , 1997 .

[19]  B. Bolker,et al.  Using Moment Equations to Understand Stochastically Driven Spatial Pattern Formation in Ecological Systems , 1997, Theoretical population biology.

[20]  M. Gilpin,et al.  Metapopulation Biology: Ecology, Genetics, and Evolution , 1997 .

[21]  Peter Kareiva,et al.  Spatial ecology : the role of space in population dynamics and interspecific interactions , 1998 .

[22]  Stuart E. Bunn,et al.  Dispersal and recruitment ofTasiagma ciliata(Trichoptera: Tasimiidae) in rainforest streams, south-eastern Australia , 1998 .

[23]  Ricard V. Solé,et al.  Modeling spatiotemporal dynamics in ecology , 1998 .

[24]  P. Chesson Spatial scales in the study of reef fishes: A theoretical perspective , 1998 .

[25]  J. Webb,et al.  Scales and frequencies of disturbances: rock size, bed packing and variation among upland streams , 1998 .

[26]  R. Freckleton,et al.  The Ecological Detective: Confronting Models with Data , 1999 .

[27]  M. Ayres,et al.  Jensen's inequality predicts effects of environmental variation. , 1999, Trends in ecology & evolution.

[28]  R. Marchant,et al.  Growth, production and mortality of two species of Agapetus (Trichoptera : Glossosomatidae) in the Acheron River, south-east Australia , 1999 .

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

[30]  V. Resh,et al.  Long-term movements of self-marked caddisfly larvae (Trichoptera: Sericostomatidae) in a California coastal mountain stream , 1999 .

[31]  P. Chesson General theory of competitive coexistence in spatially-varying environments. , 2000, Theoretical population biology.

[32]  P. Chesson,et al.  Chapter 14 : Applying scale transition theory to metacommunities in the field , 2003 .

[33]  S. D. Cooper,et al.  Scale effects and extrapolation in ecological experiments , 2003 .

[34]  Peter Chesson,et al.  Local dispersal can facilitate coexistence in the presence of permanent spatial heterogeneity , 2003 .

[35]  Mathew A. Leibold,et al.  Metacommunities: Spatial Dynamics and Ecological Communities , 2005 .