Insect outbreaks can cover vast geographic areas making it onerous to cost-effectively monitor populations to address management or ecological questions. Community science (or citizen science), which entails engaging the public to assist with data collection, provides a possible solution to this challenge for the spruce budworm ( Choristoneura fumiferana Clemens), a major defoliating pest in North America. Here, we lay out the Budworm Tracker Program, a contributory community science program developed to help monitor spruce budworm moths throughout eastern Canada. The program outsources free pheromone trap kits to volunteers who periodically check and collect moths from their traps throughout the budworm flight period, then return them in a prepaid envelope to the organizers. Over three years, the program engaged an average of 216–375 volunteers and yielded a data return rate of 68%–89%, for a total of 16 311–54 525 moths per year. Volunteer retention among years was 71%–89%. Data from this program offer compelling evidence for the range of long-distance moth dispersal. Although our program was designed for spruce budworm, this template could easily be adapted for forestry, urban forestry, and agricultural systems to monitor any of the numerous organisms for which there is an established trapping method.

Estimation of pest density is a basic requirement for integrated pest management in agriculture and forestry, and efficiency in density estimation is a common goal. Sequential sampling techniques promise efficient sampling, but their application can involve cumbersome mathematics and/or intensive warm-up sampling when pests have complex within- or between-site distributions. We provide tools for assessing the efficiency of sequential sampling and of alternative, simpler sampling plans, using computer simulation with “pre-sampling” data. We illustrate our approach using data for balsam gall midge (Paradiplosis tumifex) attack in Christmas tree farms. Paradiplosis tumifex proved recalcitrant to sequential sampling techniques. Midge distributions could not be fit by a common negative binomial distribution across sites. Local parameterization, using warm-up samples to estimate the clumping parameter k for each site, performed poorly: k estimates were unreliable even for samples of n∼100 trees. These methods were further confounded by significant within-site spatial autocorrelation. Much simpler sampling schemes, involving random or belt-transect sampling to preset sample sizes, were effective and efficient for P. tumifex. Sampling via belt transects (through the longest dimension of a stand) was the most efficient, with sample means converging on true mean density for sample sizes of n∼25–40 trees. Pre-sampling and simulation techniques provide a simple method for assessing sampling strategies for estimating insect infestation. We suspect that many pests will resemble P. tumifex in challenging the assumptions of sequential sampling methods. Our software will allow practitioners to optimize sampling strategies before they are brought to real-world applications, while potentially avoiding the need for the cumbersome calculations required for sequential sampling methods.

We used field surveys in central New Brunswick, Canada to establish efficient sampling procedures for evaluating densities of balsam gall midge, Paradiplosis tumifex Gagné (Diptera: Cecidomyiidae), and its associated damage in balsam fir, Abies balsamea (Linnaeus) Miller, Christmas trees. Infestation was greater in larger trees than smaller trees and in mid-crown and upper-crown branches than in the lower crown. However, the relationship between gallmaker infestation and site, height class, and crown level was highly complex and may involve covariation of shoot length with height class and crown level. As a result, patterns in infestation did not lend themselves to simple interpretation. This complexity highlights the need to find sampling units that provide simpler but reasonably accurate predictors of gallmaker impact at the whole-tree scale. We identified such a sampling unit: gallmaker density in first-order current-year shoots of a mid-crown branch explained 81% of the variance in total infestation among trees.