ESTIMATING CHAOS AND COMPLEX DYNAMICS IN AN INSECT POPULATION

By Brian Dennis, R. Desharnais, J. Cushing, Shandelle M. Henson, R. Costantino. 2001

201 citations recorded by the source corpus.

Subfields: Ecology, Ecology, Evolution, Behavior and Systematics, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/92ecea44bf567d4b6cc03b7b70d43b68132b6eba

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Ecology, Evolution, Behavior and Systematics

In Public Health, Environmental and Occupational Health

Citations in the corpus

Monte Carlo State-Space Likelihoods by Weighted Posterior Kernel Density Estimation (2004, background): “…incorporate relevant biological processes, with a handful of exceptions that are in various ways specialized (e.g., Dennis, Desharnais, Cushing, and Costantino 1995; Dennis et al. 2001; Ives et al. 1999; Gibson, Gilligan, and Kleczkowski 1999; Bjørnstad, Sait, Stenseth, Thompson, and Begon 2001).”
Can noise induce chaos (2003, methodology): “Our current working hypothesis is that the bulk of departures of data from model are explained by stochastic fluctuations of the ''demographic'' type: the independent random contributions of births and deaths by individual population members (Dennis et al. 2001).”
Boom or bust? A comparative analysis of transient population dynamics in plants (2010, background): “…simple model predictions, and current explanations for fluctuations in dynamics of populations range from deterministic chaos (Hastings et al. 1993) to environmental stochasticity (Dennis & Costantino 1988) and various combinations of these (Dennis et al. 1997, 2001; Bjørnstad & Grenfell 2001).”
Efficacy of simple viability models in ecological risk assessment: Does density dependence matter? (2004, methodology): “In each case we added environmental variability—or process error—as a lognormal variate (following Dennis et al. 2001) and assumed no observation error.”
Transition to spatiotemporal chaos can resolve the paradox of enrichment (2004, background): “It should be mentioned here that, although conclusive evidence of ecological chaos is still to be found, there is a growing number of indications of chaos in real ecosystems(Scheffer, 1991; Hanski et al., 1993; Ellner and Turchin, 1995; Dennis et al., 2001).”
ESTIMATING COMMUNITY STABILITY AND ECOLOGICAL INTERACTIONS FROM TIME‐SERIES DATA (2003, methodology): “The first uses bootstrapping (Efron and Tibshirani 1993, Dennis et al. 2001).”
Integral projection models for populations in temporally varying environments (2009, unknown): “…in which the mean field model is perturbed by random variables whose mean and variance approximate the net effect of manyindividuals-level random events; a well-known example is the ‘‘LPA model’’ for experimental Tribolium populations with demographic stochasticity (e.g., Dennis et al. 2001: Eqs.”
POPULATION TIME SERIES: PROCESS VARIABILITY, OBSERVATION ERRORS, MISSING VALUES, LAGS, AND HIDDEN STATES (2004, background): “An integrated framework for analysis is needed, because process variability is part of population growth, whereas observation errors are not (Turchin 1995, Bjørnstad et al. 2001, Dennis et al. 2001, de Valpine 2002, de Valpine and Hastings 2002, Calder et al. 2003).”