The estimation of the mortality rate function for a stage-structured population is obtained starting from time-series field data on the abundance of the species. The method is based on the formulation of the mortality as a combination of cubic splines and it is applied to the  case of Lobesia botrana, the main pest in the European vineyards, with  data collected in a location in the North of Italy . Mortality estimates are based on 3 years of data and are used to obtain the dynamics for two different years. These dynamics give a satisfactory fit of the phenology of the pest. The method presented allows to obtain more flexible shape for the mortality rate functions compared with previously methods applied for the same pest .
Simulating the population dynamics of a stage-structured population requires the knowledge of the biodemographic functions characterizing the species, namely development, mortality and fecundity. In general, development and fecundity can satisfactorily be estimated starting from literature data. Unfortunately, this is often not the case of the mortality function, because of the lack of experimental data. To overcome this problem we estimate the mortality rate function from field data on the abundance of the species. The mortality is expressed as a linear combination of cubic splines and the estimation method allows to determine its coefficients taking into account the observations measurement error. Moreover, the variability in the estimate is quantified by means of the confidence bands for both mortality and dynamics. The presented method allows to obtain a more flexible shape for the mortality rate functions compared with previous methods applied to the same pest. The method is applied to the case of Lobesia botrana, the main pest in the European vineyards, with abundance data collected in a location in the North of Italy for five consecutive years. Data collected over three years are used to estimate the mortality and to analyze the variability in the estimate and its effects on the population dynamics. Other two datasets are used to validate the model simulating the dynamics using the estimated mortality .
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The estimation of the mortality rate function for
Simulating the population dynamics of
R
is obtained starting from time-series
requires the knowledge of the biodemographic functions characterizing the species, namely development, mortality and fecundity. In general, development and fecundity can satisfactorily be estimated starting from literature data. Unfortunately, this is often not the case of the mortality function, because of the lack of experimental data. To overcome this problem we estimate the mortality rate function from
R
method is based on the formulation of the mortality as a
mortality is expressed as a linear
R
it is
the estimation method allows to determine its coefficients taking into account the observations measurement error. Moreover, the variability in the estimate is quantified by means of the confidence bands for both mortality and dynamics. The presented method allows to obtain a more flexible shape for the mortality rate functions compared with previous methods
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same pest. The method is applied to the
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abundance
R
. Mortality estimates are based on 3 years of data and
for five consecutive years. Data collected over three years
R
obtain the dynamics for two different years. These dynamics give a satisfactory fit of the phenology of the pest. The method presented allows to obtain more flexible shape for the mortality rate functions compared with previously methods applied for the same pest
estimate the mortality and to analyze the variability in the estimate and its effects on the population dynamics. Other two datasets are used to validate the model simulating the dynamics using the estimated mortality