A Bayesian estimation approach for the mortality in a stage-structured demographic model

Abstract

Control interventions in sustainable pest management schemes are set according to the phenology and the population abundance of the pests. This information can be obtained using suitable mathematical models that describe the population dynamics based on individual life history responses to environmental conditions and resource availability. These responses are described by development, fecundity and survival rate functions, which can be estimated from laboratory experiments. If experimental data are not available, data on field population dynamics can be used for their estimation. This is the case of the extrinsic mortality term that appears in the mortality rate function due to biotic factors. We propose a Bayesian approach to estimate the probability density functions of the parameters in the extrinsic mortality rate function, starting from data on population abundance. The method investigates the time variability in the mortality parameters by comparing simulated and observed trajectories. The grape berry moth, a pest of great importance in European vineyards, has been considered as a case study. Simulated data have been considered to evaluate the convergence of the algorithm, while field data have been used to obtain estimates of the mortality for the grape berry moth.

A Bayesian approach for the identification of patient-specific parameters in a dialysis kinetic model

“…Anyway, the Bayesian approach can easily include observations from multiple patients or multiple HD treatments on the same patient, by simply including observations from different treatments in the likelihood function (equation (10)). In case of multiple HD treatments on the same patient, this can be useful to include a higher amount of data to estimate the patient-specific parameters (see, e.g., Lanzarone et al 28 for a multi-period application in another context). Notation …”

“…26 More recently, Bayesian approaches have been considered for estimating the parameters that characterize the dynamics of aquatic communities, 27 and for the estimation of the mortality terms in a stage-structured demographic model. 28 However, to the best of our knowledge, they have been never applied to characterize the dynamics of plasmatic electrolytes and, more in general, they have never been applied to HD patients.…”

“…Such choice has been already adopted and gave fair results. 28 In particular, we use three different parameters based on the state variable, i.e. v for V is and V pl , mex for all M ðsÞ ex , and mic for M ðsÞ ic .…”

Climate warming effects on grape and grapevine moth (Lobesia botrana) in thePalearcticregion

“…Grape and its pests have been the subject of considerable research efforts. Controlling infestation levels of the polyphagous grapevine moth has a high priority and several models have been developed for use in IPM decision support (Baumgärtner & Baronio, 1988;Briolini et al, 1997;Schmidt et al, 2003;Severini et al, 2005;Gilioli et al, 2016;Lanzarone et al, 2017). In the present study, we used a weather-driven PBDM for grape vine and L. botrana that was developed based on European data and initially used to assess the invasiveness and potential distribution and relative abundance of L. botrana in California after its accidental introduction in 2009 .…”

“…Gilioli et al (2016) estimated mortality rates in L. botrana using unpublished field population dynamics data and the Manly (1989) simulation estimation approach, although the results are time and place specific, and sampling errors from various sources affected the field data. Lanzarone et al (2017) used Bayesian methods to estimate the mortality using the same data and, although the fits were better, the method requires field data to implement and hence is not general. Hence, to keep larval populations within relative bounds (< 70 larvae per vine), we used a variant of the Nicholson and Bailey (1935) model, where ignoring the time variable t, the aggregate extrinsic mortality [0 < c (·) < 1] is assumed to increase with both temperature [i.e.…”