title: Complex population dynamics and complex causation: devils, details and demography.
abstract: Population dynamics result from the interplay of density-independent and density-dependent processes. Understanding this interplay is important, especially for being able to predict near-term population trajectories for management. In recent years, the study of model systems-experimental, observational and theoretical-has shed considerable light on the way that the both density-dependent and -independent aspects of the environment affect population dynamics via impacting on the organism's life history and therefore demography. These model-based approaches suggest that (i) individuals in different states differ in their demographic performance, (ii) these differences generate structure that can fluctuate independently of current total population size and so can influence the dynamics in important ways, (iii) individuals are strongly affected by both current and past environments, even when the past environments may be in previous generations and (iv) dynamics are typically complex and transient due to environmental noise perturbing complex population structures. For understanding population dynamics of any given system, we suggest that 'the devil is in the detail'. Experimental dissection of empirical systems is providing important insights into the details of the drivers of demographic responses and therefore dynamics and should also stimulate theory that incorporates relevant biological mechanism.
authors.affiliation: University of Leeds Institute of Integrative and Comparative Biology Leeds LS2 9JT, UK. t.g.benton@leeds.ac.uk
authors.forename: Tim G
authors.initials: TG
authors.lastname: Benton
authors.forename: Stewart J
authors.initials: SJ
authors.lastname: Plaistow
authors.forename: Tim N
authors.initials: TN
authors.lastname: Coulson
mesh_terms: D000222:Adaptation, Physiological; D000818:Animals; D003710:Demography; D017753:Ecosystem; D008954:Models, Biological; D010641:Phenotype; D011157:Population Dynamics; D013997:Time Factors