# The effects of fecundity, mortality and distribution of the initial condition in phenological models

## TL;DR

This study enhances pest phenological models by incorporating age distribution, fecundity, and mortality factors, demonstrating their impact through simulations and a case study on codling moth to improve pest control strategies.

## Contribution

It introduces a more realistic phenological model framework by including age, fecundity, and mortality, extending beyond traditional development rate-based models.

## Key findings

- Inclusion of age distribution affects model predictions.
- Fecundity and mortality rates significantly influence pest development timing.
- Model comparisons highlight improved accuracy for pest management decisions.

## Abstract

Pest phenological models describe the cumulative flux of the individuals into each stage of the life cycle of a stage-structured population. Phenological models are widely used tools in pest control decision making. Despite the fact that these models do not provide information on population abundance, they share some advantages with respect to the more sophisticated and complex demographic models. The main advantage is that they do not require data collection to define the initial conditions of model simulation, reducing the effort for field sampling and the high uncertainty affecting sample estimates. Phenological models are often built considering the developmental rate function only. To the aim of adding more realism to phenological models, in this paper we explore the consequences of improving these models taking into consideration three additional elements: the age distribution of individuals which exit from the overwintering phase, the age- and temperature-dependent profile of the fecundity rate function and the consideration of a temperature-dependent mortality rate function. Numerical simulations are performed to investigate the effect of these elements with respect to phenological models considering development rate functions only. To further test the implications of different models formulation, we compare results obtained from different phenological models to the case study of the codling moth (Cydia pomonella) a primary pest of the apple orchard. The results obtained from model comparison are discussed in view of their potential application in pest control decision support.