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Stage-specific density dependence in blowfly populations: experimental assesment of estimates from non-parametric time series modelling

Vitenskapelig artikkel
Publiseringsår
2002
Tidsskrift
Oikos
Eksterne nettsted
Cristin
NIVA-involverte
Jannicke Moe
Forfattere
Jannicke Moe, Nils Christian Stenseth, Robert H. Smith

Sammendrag

Two approaches for describing density dependence in demographic rates of stage-structured populations are compared in this study. Time-series data from laboratory blowfly populations (Lucilia sericata) have been analysed in a separate study (Lingjærde et al. 2001), with a statistical modelling approach that incorporated density dependences as unspecified (non-parametric) functions. In this study, we assessed density-dependent structures by manipulating densities of larvae and adults in cohorts of blowflies and measuring the demographic rates. We here compare the density-dependent structures revealed by the cohort experiments with those estimated by the non-parametric model. The model the demographic rates to have the following density-dependent structure: (i) larval survival was non-linearly density-dependent (a 'humped' function), (ii) adult survival was density-independent, and (iii) reproductive rate decreased with adult density. In the cohort experiments reported here, (i) juvenile survival exhibited a positive density dependence in low densities (facilitation), which became negative at higher densities (competition). Pupal and adult size decreased with initial larval density. (ii) Adult survival was reduced by high initial larval density, but it was independent of adult density. (iii) Reproductive rate was reduced by high initial larval density, and by high adult density in populations of large individuals (from low larval density). Hence, the results from these experiments support the non-parametric model estimates regarding density-dependent structures of demographic rates in the blowfly populations. The mean demographic rates, however, were apparently underestimated by the model. We conclude that non-parametric modelling is a useful first approach for exploratory analysis of ecological time-series data.