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Mortality estimate driven by population abundance field data in a stage-structured demographic model. The case of Lobesia botrana

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  • Pasquali, S.
  • Soresina, C.
  • Marchesini, E.

Abstract

Simulating the population dynamics of a stage-structured population requires the knowledge of development, mortality and fecundity rate functions characterizing the species. In general, development and fecundity can satisfactorily be estimated starting from literature data. Unfortunately, this is often not the case for the mortality function due to 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 using the confidence bands for both mortality and dynamics. The presented method allows obtaining a more flexible shape for the mortality rate functions compared with previous methods applied to the same pest. The method has been applied to the case of Lobesia botrana, the main pest in the European vineyards, with abundance data collected for five consecutive years in an experimental field in the North of Italy. Data collected over three years are used to estimate the mortality and to analyse the variability in the estimate and its effects on the population dynamics, while the other two datasets are used to validate the model simulating the dynamics using the estimated mortality.

Suggested Citation

  • Pasquali, S. & Soresina, C. & Marchesini, E., 2022. "Mortality estimate driven by population abundance field data in a stage-structured demographic model. The case of Lobesia botrana," Ecological Modelling, Elsevier, vol. 464(C).
    • Handle: RePEc:eee:ecomod:v:464:y:2022:i:c:s0304380021003823
    DOI: 10.1016/j.ecolmodel.2021.109842
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    References listed on IDEAS

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    1. Giovanni Marini & Piero Poletti & Mario Giacobini & Andrea Pugliese & Stefano Merler & Roberto Rosà, 2016. "The Role of Climatic and Density Dependent Factors in Shaping Mosquito Population Dynamics: The Case of Culex pipiens in Northwestern Italy," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-15, April.
    2. Gilioli, Gianni & Pasquali, Sara & Marchesini, Enrico, 2016. "A modelling framework for pest population dynamics and management: An application to the grape berry moth," Ecological Modelling, Elsevier, vol. 320(C), pages 348-357.
    3. Blum, Moshe & Nestel, David & Cohen, Yafit & Goldshtein, Eitan & Helman, David & Lensky, Itamar M., 2018. "Predicting Heliothis (Helicoverpa armigera) pest population dynamics with an age-structured insect population model driven by satellite data," Ecological Modelling, Elsevier, vol. 369(C), pages 1-12.
    4. Pasquali, S. & Soresina, C. & Gilioli, G., 2019. "The effects of fecundity, mortality and distribution of the initial condition in phenological models," Ecological Modelling, Elsevier, vol. 402(C), pages 45-58.
    5. Delphine Picart & Fabio Augusto Milner & Denis Thiéry, 2015. "Optimal Treatment Schedule in Insect Pest Control in Viticulture," Mathematical Population Studies, Taylor & Francis Journals, vol. 22(3), pages 172-181, September.
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    1. Aguirre-Zapata, Estefania & Alvarez, Hernan & Dagatti, Carla Vanina & di Sciascio, Fernando & Amicarelli, Adriana N., 2023. "Parametric interpretability of growth kinetics equations in a process model for the life cycle of Lobesia botrana," Ecological Modelling, Elsevier, vol. 482(C).

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