A troubleshooting guide for mechanistic plant pest forecast models

Roger D. Magarey, Scott A. Isard

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

There is copious literature on development and validation of models to forecast risk to crops from arthropods and diseases; however, there is little published on causes of failure associated with these models. This manuscript provides mechanistic model builders and users with a list of likely problems, potential causes, possible solutions, and associated references. The problems are divided into four categories: environmental inputs, model construction and parameterization, validation, and implementation. The list is based on the authors' extensive experiences developing and running mechanistic modeling systems. A multidisciplinary approach involving researchers with expertise in pest biology, crop management, meteorology, and information technology is recommended for delivering the most effective pest forecast models.

Original languageEnglish (US)
Number of pages1
JournalJournal of Integrated Pest Management
Volume8
Issue number1
DOIs
StatePublished - Jan 1 2017

Fingerprint

plant pests
pests
information technology
mechanistic models
model validation
crop management
crop
arthropods
researchers
meteorology
arthropod
parameterization
Biological Sciences
forecast
pest
crops
modeling

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science
  • Plant Science
  • Insect Science
  • Management, Monitoring, Policy and Law

Cite this

@article{23da28542cdf4ef7b0ab63ab1b15b65d,
title = "A troubleshooting guide for mechanistic plant pest forecast models",
abstract = "There is copious literature on development and validation of models to forecast risk to crops from arthropods and diseases; however, there is little published on causes of failure associated with these models. This manuscript provides mechanistic model builders and users with a list of likely problems, potential causes, possible solutions, and associated references. The problems are divided into four categories: environmental inputs, model construction and parameterization, validation, and implementation. The list is based on the authors' extensive experiences developing and running mechanistic modeling systems. A multidisciplinary approach involving researchers with expertise in pest biology, crop management, meteorology, and information technology is recommended for delivering the most effective pest forecast models.",
author = "Magarey, {Roger D.} and Isard, {Scott A.}",
year = "2017",
month = "1",
day = "1",
doi = "10.1093/jipm/pmw015",
language = "English (US)",
volume = "8",
journal = "Journal of Integrated Pest Management",
issn = "2155-7470",
publisher = "Oxford University Press",
number = "1",

}

A troubleshooting guide for mechanistic plant pest forecast models. / Magarey, Roger D.; Isard, Scott A.

In: Journal of Integrated Pest Management, Vol. 8, No. 1, 01.01.2017.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A troubleshooting guide for mechanistic plant pest forecast models

AU - Magarey, Roger D.

AU - Isard, Scott A.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - There is copious literature on development and validation of models to forecast risk to crops from arthropods and diseases; however, there is little published on causes of failure associated with these models. This manuscript provides mechanistic model builders and users with a list of likely problems, potential causes, possible solutions, and associated references. The problems are divided into four categories: environmental inputs, model construction and parameterization, validation, and implementation. The list is based on the authors' extensive experiences developing and running mechanistic modeling systems. A multidisciplinary approach involving researchers with expertise in pest biology, crop management, meteorology, and information technology is recommended for delivering the most effective pest forecast models.

AB - There is copious literature on development and validation of models to forecast risk to crops from arthropods and diseases; however, there is little published on causes of failure associated with these models. This manuscript provides mechanistic model builders and users with a list of likely problems, potential causes, possible solutions, and associated references. The problems are divided into four categories: environmental inputs, model construction and parameterization, validation, and implementation. The list is based on the authors' extensive experiences developing and running mechanistic modeling systems. A multidisciplinary approach involving researchers with expertise in pest biology, crop management, meteorology, and information technology is recommended for delivering the most effective pest forecast models.

UR - http://www.scopus.com/inward/record.url?scp=85038869312&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85038869312&partnerID=8YFLogxK

U2 - 10.1093/jipm/pmw015

DO - 10.1093/jipm/pmw015

M3 - Article

AN - SCOPUS:85038869312

VL - 8

JO - Journal of Integrated Pest Management

JF - Journal of Integrated Pest Management

SN - 2155-7470

IS - 1

ER -