The numerical response: rate of increase and food limitation in herbivores and predators

Two types of numerical response function have evolved since Solomon first introduced the term to generalize features of Lotka-Volterra predator-prey models: (i) the demographic numerical response, which links change in consumer demographic rates to food availability; and (ii) the isocline numerical...

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Published inPhilosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 357; no. 1425; pp. 1233 - 1248
Main Authors Bayliss, Peter, Choquenot, David
Format Journal Article
LanguageEnglish
Published England The Royal Society 29.09.2002
Subjects
Animals
Artiodactyla - physiology
Biomass
Carnivora - physiology
Demography
Diet, Vegetarian - statistics & numerical data
Environment
Food availability
Food Chain
Herbivores
Kangaroos
Logistic Models
Macropodidae
New Zealand
Non-Equilibrium
Numerical Analysis, Computer-Assisted
Numerical Response
Opossums
Pastures
Population Density
Population dynamics
Population Growth
Population Growth Rate
Predators
Regulation
Vegetation
Wolves
New Zealand
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Summary:Two types of numerical response function have evolved since Solomon first introduced the term to generalize features of Lotka-Volterra predator-prey models: (i) the demographic numerical response, which links change in consumer demographic rates to food availability; and (ii) the isocline numerical response, which links consumer abundance per se to food availability. These numerical responses are interchangeable because both recognize negative feedback loops between consumer and food abundance resulting in population regulation. We review how demographic and isocline numerical responses have been used to enhance our understanding of population regulation of kangaroos and possums, and argue that their utility may be increased by explicitly accounting for non-equilibrium dynamics (due to environmental variability and/or biological interactions) and the existence of multiple limiting factors. Interferential numerical response functions may help bridge three major historical dichotomies in population ecology (equilibrium versus non-equilibrium dynamics, extrinsic versus intrinsic regulation and demographic versus isocline numerical responses).
Bibliography:istex:DD4F56DDE9E7536B50393A9E66273B5141AE157F
ark:/67375/V84-7N0STPFB-P
Discussion Meeting Issue 'Population growth rate: determining factors and role in population regulation' organized by R. M. Sibly, J. Hone and T. H. Clutton-Brock
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ISSN:0962-8436
1471-2970
DOI:10.1098/rstb.2002.1124