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

S. Pasquali, C. Soresina and E. Marchesini

Ecological Modelling, 2022, vol. 464, issue C

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.

Keywords: Stage-structured population; Physiologically-based demographic model; Mortality estimate; Population abundance time-series; Lobesia botrana (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380021003823
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:464:y:2022:i:c:s0304380021003823

DOI: 10.1016/j.ecolmodel.2021.109842

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().