Pest management is a complex problem that’s becoming more prominent in cannabis agriculture. Cultivators, however, can use temperature manipulation to their advantage to combat infestation issues. But before we review how temperature affects pests, we need to take a 30,000-feet look at the nature of pests and pest control in agriculture.
Cannabis cultivators are quickly discovering that despite being disparagingly referred to as a ”weed” for generations, our favorite plant is still prone to attack by numerous insects, mites, fungi and viruses. When we plant a uniform crop, let alone a crop that may be cloned from a single female plant, we create a potentially unstable agricultural ecosystem. In this sea of genetically uniform green, undesirable organisms that get through physical barriers can explode rapidly and cause significant economic damage.
Fortunately, cannabis growers can arm themselves with an abundance of knowledge accumulated over many decades of study of pest behavior and management in general agriculture. So let’s take a closer look at how pest problems are forecasted in other crops.
First off, a one-question biology quiz: How are plants, fish, reptiles and amphibians, insects and mites, fungi and other microorganisms different from birds and mammals?
Answer: A lot of similarities exist (all these living organisms store genetic information in DNA; they all have energy-production metabolism based on respiration, etc.), but one huge distinction between these diverse groups is that the former don’t use food energy to regulate their body temperatures, as birds and mammals do. Plants, microorganisms and “cold-blooded” animals are poikilothermic, and their metabolism and development are coupled to ambient temperature. So-called “warm-blooded” organisms are homeotherms, and their internal temperature and development are generally independent of ambient temperature.
This means that metabolism and development of plants and pests are dependent on prevailing temperatures. If temperatures are below a critical threshold, although plants and insects may be alive, their development is slowed or even stopped. Once temperatures rise above the developmental threshold, metabolism increases, and development proceeds. At much higher temperatures, metabolism can’t go faster than some genetically determined maximum, and growth has reached a maximum rate. These developmental thresholds are not uniform among plants or insects, and even within a species significant differences may exist in developmental thresholds in geographical sub-populations.
Agriculturists who want some means to predict duration of vegetative growth after planting, development rate of pests and beneficial insects, and harvest can’t simply rely on elapsed time. Cool periods accumulate less heat input needed for growth, prolonging the growing season. So how can we develop a “model,” a mathematical device for predicting important crop-growth events?
What’s needed is a way to combine temperature inputs between minimum and maximum thresholds, or in other words, to not measure calendar time, but “physiological” time. The answer is the concept of “degree days,” with the unit symbol °D. This unit integrates temperature with the amount of time spent between critical thresholds. An hour at one degree above the lower threshold contributes one “degree hour” to a total. If the temperature is five degrees above the threshold for an hour, five degree hours are accumulated, and so forth. This is graphically illustrated above.
Ideally, the thresholds for your crop, its pests and their natural enemies would be well characterized, and in-field (or even in-canopy) instruments would measure temperatures hourly, and the cumulative °D values would be the integration of temperature against time. In practice, daily maximum and minimum temperatures are recorded, and approximation methods (summed triangle areas, sine waves with threshold cutoffs, etc.) are used as approximations of actual temperature fluctuations. Coupled with “scouting” data (estimates of pest numbers with field collections), crop growth and population development models can make reasonably accurate forecasts of pest development, and decisions on whether and when alternative control methods (e.g., pesticides) are warranted become more scientifically based. Literature with methods to estimate temperature thresholds and degree days abound, and should be consulted for additional information.