Daniel A. Herms
The tremendous diversity of ornamental plants, each with its own complement of insect pests, creates a logistical challenge for planning and implementing a successful pest-management program for nurseries and landscapes. Many insects are difficult to detect and monitor, further complicating the accurate timing of pesticide applications. Variation in weather patterns from year-to-year can make calendar-based scheduling inaccurate. The use of plant phenology provides an alternative approach for predicting insect activity. Because the development of both plants and insects is temperature dependent, plants accurately track the environmental factors that affect insect development. This report presents a phenological sequence for 85 plants and 46 insect and mite species for Wooster, Ohio, from 1997-99. Despite dramatic differences in weather during these three years, the order in which the phenological events occurred was generally quite consistent, with only minor deviations from year-to-year. This consistency in the pattern demonstrates that even one year of phenological data can be useful for timing pest-management decisions. To facilitate phenological monitoring by landscape and nursery managers, an area for recording phenological observations has been included with the phenological information presented in Table 1, so that the table can be copied for personal use as a data sheet.
The tremendous diversity of ornamental plants, each with its own complement of insect pests, creates a challenge for planning and implementing a successful pest management program for landscapes. Insecticide applications must be timed precisely to maximize their effectiveness and minimize the number required. This is especially true of the "environmentally friendly" but short-lived "biorational" insecticides such as horticultural oils and soaps, and for insects such as scales and borers that are only susceptible during specific stages. Many insects are difficult to detect and monitor, further complicating the accurate timing of pesticide applications. Consequently, pesticide applications are frequently scheduled on a calendar-day basis. However, because of variation in patterns of degree-day accumulation from place-to-place and year-to-year, calendar-based scheduling is frequently inaccurate.
The use of plant phenology provides an alternative approach for predicting insect activity. Phenology is the study of recurring biological phenomena and their relationship to weather. Bird migration, hunting and gathering seasons, blooming of wildflowers and trees, and the seasonal appearance of insects are examples of phenological events that have been recorded for centuries (Glendenning, 1943; Levitt, 1981). Because the development of both plants (Rathcke and Lacey, 1985) and insects (Tauber and Tauber, 1981) is temperature dependent, plants may accurately track the environmental factors that affect insect development. Indeed, the use of plant phenology to predict insect activity is an old practice, with recorded observations that date back at least to the 18th century (Huberman, 1941).
The critical assumption is that phenological patterns remain constant from year-to-year even when weather patterns differ greatly. A comparison of phenological patterns in the Secrest Arboretum at the Ohio Agricultural Research and Development Center in Wooster in 1997, 1998, and 1999 provides an ideal opportunity for testing this assumption. The weather in 1997 was characterized by a delayed, cool spring, while 1998, the year of El Niño, was characterized by an early, warm spring, and the spring of 1999 was intermediate.
During 1997, the phenology of 56 plant species and/or cultivars and 22 species of insects was monitored. In 1998 and 1999, this list was expanded to 86 plant and 40 insect taxa. Four individuals of each species or cultivar were monitored. To control for microenvironmetal variation, all individuals of a species or cultivar were located either in uniform sun or shade, depending on the environment to which the species is best adapted. Plants in microenvironments that were obviously altered by buildings, parking lots, bodies of water, and other factors were not used.
Plants were monitored at least three times each week, and the dates of "first bloom" and "full bloom" recorded. "First bloom" is defined as the date on which the first flower bud on the plant opens, revealing pistils and/or stamens, and "full bloom" as the date on which 95% of the flower buds have opened (i.e., one bud out of 20 has yet to open). These phenological events can be identified and recorded with precision.
The insect and mite species monitored in this study represent diverse life histories and include defoliators, wood borers, scales, and other sucking insects, gall formers, leafminers, and spider mites. Because of the increasing interest in butterfly gardening, the flight phenologies of several butterfly species are also included. In contrast to methods used to monitor plant phenology, which were designed to minimize variation in order to increase predictive power, sampling protocols for insects were designed to characterize the phenology of the entire population.
Degree-days were calculated using the double sine wave method (Allen, 1976) from daily maximum and minimum temperature data for Wooster (OARDC Weather System, Wooster Station) and a base temperature of 50°F (DD50) and a starting date of January 1.
The results of this survey are presented in Table 1. For clarity, only common names are listed. To achieve standardization, common names of plants follow Dirr (1998), and insect names are official common names as approved by the Entomological Society of America. In general, relative to 1999, plant and insect phenology was substantially accelerated in the warm spring of 1998 and delayed in the cool spring of 1997. Despite the dramatic differences in the weather during these three years, the order in which the phenological events occurred was generally quite consistent, with only minor deviations from year-to-year.
This consistency in the pattern demonstrates that even one year of phenological data can be useful for timing pest-management decisions. For example, a pest-control operator could record what plants happened to be in bloom when a pesticide application was made. If follow-up monitoring showed the application to be effective, then the timing of the spray could be accurately duplicated the following season. If the application was found to be too early or too late, then the timing of the application in future years could be delayed or accelerated relative to the phenological sequence. To facilitate phenological monitoring by landscape and nursery managers, an area for recording data has been included in Table 1 so that the table can be copied for personal use as a data sheet.
Allen, J. C. 1976. A modified sine wave method for calculating degree-days. Environmental Entomology 5:388-396.
Dirr, M. A. 1998. Manual of Woody Landscape Plants: Their Identification, Ornamental Characteristics, Culture, Propagation, and Uses. 5th Edition. Stipes Publishing Co., Champaign, Ill.
Glendenning, R. 1943. Phenology: the most natural of sciences. Canadian Field-Naturalist 57:75-78.
Huberman, M. A. 1941. Why phenology? Journal of Forestry 39:1007-1013.
Levitt, D. 1981. Aboriginal uses of plants. Groote Eylandt. Australian Institute of Aboriginal Studies, Canberra, Australia.
Rathcke, B. and E. L. Lacey. 1985. Phenological patterns of terrestrial plants. Annual Review of Ecology and Systematics 16:179-214.
Tauber, C. A. and M. J. Tauber. 1981. Insect seasonal cycles: genetics and evolution. Annual Review of Ecology and Systematics 12:281-308.