What is degree-day modeling?

Degree-days are a method for quantifying the amount of heat energy available in a given day for a cold-blooded (or poikilothermic) organism to grow and develop.  Unlike warm-blooded animals, insects cannot regulate their body temperatures and so their rate of development is depended on environmental conditions – they develop more slowly when it’s cold, more quickly when it’s warmer, and may not develop at all below certain threshold temperatures. Different insects will have different growth rates and responses to environmental temperatures, so degree-day models and developmental thresholds must be matched to particular insect species. Fortunately, degree-day models have now been developed and tested for many common insect pests and are useful for predicting and monitoring insect development and risk to crops from insect pests.

Every degree-day model will have a base temperature (below which no development can occur for a particular insect), and optionally an upper threshold temperature (above which insect development does not accelerate, but remains at a maximum rate). In addition, the model will have a ‘biofix’, which is a date or event that triggers the start of degree-day accumulation. Daily degree-day values are accumulated after this point and developmental events are timed to specific accumulations of degree-days.

How to calculate degree days

The ‘simple average’ degree-day calculation method averages the daily minimum and maximum temperatures, adjusted for the base and upper thresholds. Alternatively, the ‘single sine’ degree-day calculation method uses the area under a sine wave (adjusted based on the lower and upper thresholds), which is more complicated to compute but more accurately tracks how temperatures change throughout a day resulting in better estimates of insect development particularly in the early part of the season when daily temperatures are close to the developmental thresholds. For more information on how to calculate degree-days, see the UC IPM Program’s page on Degree-Day Concepts.

Why use degree-day modeling?

Traditionally, the arrival of insect pests would be predicted based on a calendar date, a crop development stage, or the development of certain wild indicator plants (such as magnolia, lilac, chicory, and thistle). Calendar dates in particular have become less reliable recently as the climate trends warmer, pushing the arrival of spring earlier, and resulting in less predictable spring temperatures. Degree-day models use the actual observed temperatures in a given year, and can even use the weather forecast, to track and predict insect development and pest pressure with greater accuracy over traditional methods.

Degree-day modeling tools and resources

Wisconsin Vegetable Disease and Insect Forecasting Network

This map tool helps you visualize disease and insect pressure across Wisconsin based on degree-day models and NOAA meteorological data. All of the models listed in the table at the bottom of this page are incorporated into VDIFN. You can also input your own degree-day models and view and download weather data for any location in Wisconsin. Our lab manages VDIFN so if you have any questions/comments please reach out to us.

USPest degree-day models and maps

Run by Oregon State University, this tool allows you generate a degree-day model for a single weather station of your specification, or select and run a pest model. This tool also incorporates a 7-day weather forecast, and uses historical weather normals to predict degree-day accumulation for the rest of the year. It also compares current year accumulation with past climate normals, indicating whether we are ahead or behind the average season. You can also use their map maker to visualize degree-day accumulation for an entire state/region.

USA National Phenology Network

The USA-NPN brings together citizen scientists, government agencies, non-profit groups, educators and students of all ages to monitor the impacts of climate change on plants and animals in the United States. This site features excellent maps of seasonal and climatic trends in the US, as well as some maps and models for pests and invasive species. You can also sign up for their newsletter.

PRISM Climate Group weather data portal

Excellent source of climate data for single points or bulk lists of sites if you want to calculate your own degree-days for past years.

List of degree-day models for insect pests of vegetable crops in Wisconsin

Common name	Binomial name	Tmin F	Tmax F	Biofix
Alfalfa weevil	Hypera postica	48	none	Jan 1
Asparagus beetle (common)	Crioceris asparagi	50	86	Jan 1
Black cutworm	Agrotis ipsilon	50	86	May 15*
Brown marmorated stink bug	Halyomorpha halys	54	92	Jan 1
Cabbage looper	Trichoplusia ni	50	90	May 15*
Cabbage maggot	Delia radicum	42.8	86	Jan 1
Colorado potato beetle	Leptinotarsa decemlineata	52	none	May 1*
Corn earworm	Helicoverpa zea	55	92	Aug 1*
Corn rootworm (western & northern)	Diabrotica sp.	52	none	Jan 1
European corn borer	Ostrinia nubilalis	50	86	Jan 1
Flea beetle (crucifer)	Phyllotreta cruciferae	50	none	Jan 1
Flea beetle (mint)	Longitarsus waterhousei	41	none	Jan 1
Imported cabbageworm	Pieris rapae	50	none	Jan 1
Japanese beetle	Popillia japonica	50	100	Jan 1
Lygus bug	Lygus hesperus	52	none	Jan 1
Mint root borer	Fumibotys fumalis	50	none	Apr 1*
Onion maggot	Delia antiqua	39.2	86	Jan 1
Seedcorn maggot	Delia platura	39.2	86	Jan 1
Squash vine borer	Melittia cucurbitae	50	none	Jan 1
Stalk Borer	Papaipema nebris	41	86	Jan 1
Variegated cutworm	Peridroma saucia	41	88	May 1*
Western bean cutworm	Striacosta albicosta	50	none	May 1*
Western flower thrips	Frankliniella occidentalis	45	none	Jan 1

* Note: Models with biofix dates other than Jan 1 are probably less reliable and the biofix may need to be adjusted to match an observed event such as the appearance of egg masses.