scholarly journals Model complexity affects transient population dynamics following a dispersal event: a case study with pea aphids

Ecology ◽  
2009 ◽  
Vol 90 (7) ◽  
pp. 1878-1890 ◽  
Author(s):  
Brigitte Tenhumberg ◽  
Andrew J. Tyre ◽  
Richard Rebarber
Keyword(s):  
Population Dynamics ◽  
Model Complexity ◽  
Transient Population ◽  
Pea Aphids

scholarly journals Individual-based modelling of resource competition to predict density-dependent population dynamics: a case study with white storks

Oikos ◽  
2014 ◽  
Vol 124 (3) ◽  
pp. 319-330 ◽  
Author(s):  
Damaris Zurell ◽  
Ute Eggers ◽  
Michael Kaatz ◽  
Shay Rotics ◽  
Nir Sapir ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Resource Competition ◽  
Density Dependent ◽  
White Storks

scholarly journals Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005

2019 ◽  
Author(s):  
Diana M Hendrickx ◽  
João Dinis Sousa ◽  
Pieter J.K. Libin ◽  
Wim Delva ◽  
Jori Liesenborgs ◽  
...  
Keyword(s):  
Model Complexity ◽  
Individual Based Model ◽  
Policy Makers ◽  
Basic Model ◽  
Hiv Epidemiology ◽  
Hiv Epidemic ◽  
Simplex Virus ◽  
Evidence For Policy ◽  
The Impact

ABSTRACTModel comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a population with Herpes simplex virus type 2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé (Cameroon) were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. Moreover, two models that agree in their predictions of the HIV epidemic in the absence of intervention can have different outputs when predicting the impact of interventions. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

Variability and Parasitoid Foraging Efficiency: A Case Study of Pea Aphids and Aphidius ervi

1999 ◽  
Vol 154 (6) ◽  
pp. 652-673 ◽  
Author(s):  
Anthony R. Ives ◽  
Shon S. Schooler ◽  
Victoria J. Jagar ◽  
Sarah E. Knuteson ◽  
Miodrag Grbic ◽  
...  
Keyword(s):  
Aphidius Ervi ◽  
Foraging Efficiency ◽  
Pea Aphids ◽  
Parasitoid Foraging

Vector Control, Optimal Control, and Vector-Borne Disease Dynamics

2020 ◽  
pp. 267-288
Author(s):  
Michael B. Bonsall
Keyword(s):  
Optimal Control ◽  
Population Genetics ◽  
Population Dynamics ◽  
Vector Control ◽  
Cost Effective ◽  
Disease Suppression ◽  
Medical Interventions ◽  
Vector Borne Disease ◽  
Vector Borne

Understanding methods of vector control is essential to vector-borne disease (VBD) management. Vaccines or standard medical interventions for many VDBs do not exist or are poorly developed so disease control is focused on managing vector numbers and dynamics. This involves understanding not only the population dynamics but also the population genetics of vectors. Using mosquitoes as a case study, in this chapter, the modern genetics-based methods of vector control (self-limiting, self-sustaining) on mosquito population and disease suppression will be reviewed. These genetics-based methods highlight the importance of understanding the interplay between genetics and ecology to develop optimal, cost-effective solutions for control. The chapter focuses on how these genetics-based methods can be integrated with other interventions, and concludes with a summary of regulatory and policy perspectives about the use of these approaches in the management of VBDs.

Integral projection models

2021 ◽  
pp. 181-196
Author(s):  
Edgar J. González ◽  
Dylan Z. Childs ◽  
Pedro F. Quintana-Ascencio ◽  
Roberto Salguero-Gómez
Keyword(s):  
Population Dynamics ◽  
Environmental Variables ◽  
Linear Models ◽  
Vital Rates ◽  
Matrix Population Models ◽  
Generalised Linear Models ◽  
Integral Projection Models ◽  
Integral Projection ◽  
Over Time

Integral projection models (IPMs) allow projecting the behaviour of a population over time using information on the vital processes of individuals, their state, and that of the environment they inhabit. As with matrix population models (MPMs), time is treated as a discrete variable, but in IPMs, state and environmental variables are continuous and are related to the vital rates via generalised linear models. Vital rates in turn integrate into the population dynamics in a mechanistic way. This chapter provides a brief description of the logic behind IPMs and their construction, and, because they share many of the analyses developed for MPMs, it only emphasises how perturbation analyses can be performed with respect to different model elements. The chapter exemplifies the construction of a simple and a more complex IPM structure with an animal and a plant case study, respectively. Finally, inverse modelling in IPMs is presented, a method that allows population projection when some vital rates are not observed.

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