Simulate Agricultural Production and Evolution of Pesticide Resistance

Simulates individual-based models of agricultural pest management and the evolution of pesticide resistance. Management occurs on a spatially explicit landscape that is divided into an arbitrary number of farms that can grow one of up to 10 crops and apply one of up to 10 pesticides. Pest genomes are modelled in a way that allows for any number of pest traits with an arbitrary covariance structure that is constructed using an evolutionary algorithm in the mine_gmatrix() function. Simulations are then run using the run_farm_sim() function. This package thereby allows for highly mechanistic social-ecological models of the evolution of pesticide resistance under different types of crop rotation and pesticide application regimes.

Resistance Evolution (resevol) simulation package

The resevol R package is a tool for simulating social-ecological individual-based models (IBMs) for the ecology and evolution of agricultural pest species. Simulations model a spatially explicit landscape broken down into one or more independent farms on which one of up to 10 crops can be grown and one of up to 10 pesticides can be applied. Crop and pesticide application can be rotated during a simulation at different spatial and temporal scales to simulate the effects of heterogeneity of pest environment. Haploid or diploid pest genomes are modelled explicitly with an arbitrary number of loci that map to any number of traits. This mapping of loci to traits can be set with a pre-specified trait correlation structure, which is found using an evolutionary algorithm run using the mine_gmatrix() function. Individual pest traits can affect movement, reproduction, feeding, pesticide tolerance, metabolism, and other individual characteristics. Simulations of pest populations dynamics run with the run_farm_sim() function can track individual pest locations, pedigree, behaviour, and trait evolution.

This software was developed as part of the project for Enhancing Diversity to Overcome Resistance Evolution (ENDORSE) led by Dr Luc Bussière, Dr Ricardo Polanczyk, and Dr Matthew Tinsley (Co-Investigators: Nils Bunnefeld, Yelitza Colmenarez, Natália Corniani, Renata de Lima, Brad Duthie, Steve Edgington, Leonardo Fraceto, Belinda Luke, and Rosie Mangan). The ENDORSE project is a joint Newton funded international partnership between the Biotechnology and Biological Sciences Research Council (BBSRC) in the UK and the São Paulo Research Foundation (FAPESP) in Brazil under BBSRC award reference BB/S018956/1 and FAPESP award reference 2018/21089-3. ENDORSE is a partnership among Universidade Estadual Paulista (UNESP), the University of Stirling (UoS), and the Centre for Agricultural and Biosciences International (CABI). This software package is authored by Brad Duthie and Rose McKeon, and is maintained by Brad Duthie.

Installation

Install from CRAN

To install this package from CRAN.

install.packages("resevol")

Install with GitHub

To install this package from GitHub, make sure that the devtools library is installed.

install.packages("devtools")
library(devtools)

Use install_github to install using devtools.

install_github("bradduthie/resevol")

Documentation

To get started with the resevol package, we strongly recommend first reading through the Get Started vignette.