Greener Forests and Greener Formulas: Quantitative Methods in Spruce Budworm Insecticide Control
Charm Meskin
2026-10-19
Background
Figure 1. Mature spruce budworm larva feeding on white spruce. Photo: Government of Canada.
Figure 2. Adult female (upper) and male (lower) spruce budworm moths, pinned. Photo: Jean-Paul Laplante, via Government of Canada; Spruce budworm.
Introduction
The eastern spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae), is a moth native to North America whose larvae feed on the needles and buds of spruce and fir trees. It is regarded as the most widespread and damaging native defoliator of coniferous trees in North America (Nealis, V.G, 2024).
The insect completes one life cycle per year. Larvae emerge in spring and feed almost exclusively on current-year growth such as buds and new needles, constructing silk shelters as the host’s shoots expand. Adults emerge in mid-summer and can be carried many kilometres by wind and air currents (Nealis, V.G, 2024). Budworm populations undergo large oscillations, with outbreaks recurring at roughly 35‑year intervals and often lasting more than a decade in eastern Canada.
Distribution
The species inhabits spruce–fir forests from east of the continental divide to the Atlantic coast, occurring in every Canadian province and territory except Nunavut. Defoliation has also been recorded as far north as central Alaska and as far south as the northeastern United States (Nealis, V.G, 2024). Repeated defoliation reduces radial growth regardless of tree species or size and can eventually kill trees (Zhang et al., 2014). Defoliation also creates secondary problems, such as attacks by other pests, infection by pathogens, and increased fire risk and habitat destruction. Apart from habitat destruction and ecological damage, spruce budworm also causes significant economic losses by affecting the timber harvest, as shown by Chang et al. (2012) to cause more than $3.3 billion in losses in New Brunswick alone. Historic outbreaks such as the 1967-1992 Quebec outbreak have shown even larger losses, with 238 million m^3 of timber loss, with an estimated value of $12.5 billion dollars (MacLean, 2015).
Insecticide effectiveness and use
Large-scale aerial spraying of forested land in Canada began in 1945. In New Brunswick alone, between 1952 and 1993, 97% of the province’s 6.2 million hectares of forest land received at least one insecticide application, the majority aimed at spruce budworm. These early pesticides were efficient, nonselective, and persistent, and caused serious environmental impacts, public backlash, and bioaccumulation issues (Heartz et al., 2023). The best-known, DDT, was applied from 1952 to 1968 and still persists in treated soils and adjacent water bodies, with measurable ecosystem effects today. DDT was replaced in the 1970s by fenitrothion, and later aminocarb, phosphamidon, and Bacillus thuringiensis ssp. kurstaki (Btk). These post-DDT products were nonpersistent and are unlikely to be found within the ecosystem todau (Heartz et al., 2023). (Btk) and tebufenozide specifically have been shown to effectively reduce spruce budworm populations (Fuentealba et al., 2019; Doucet et al., 2007), while not having negative effects on non-target caterpillars and parasitoids at low budworm caterpillar densities (Glaus et al., 2023).
In recent years, “early intervention strategies” (EIS) have been examined as a way to make these insecticides more effective while reducing their overall use. These strategies track hotspots of overwintering larvae and apply insecticide preventively, before the larvae can defoliate trees. These were found to be highly effective and further the goals of reducing pesticide use (D. A. MacLean et al., 2019). Other strategies for population control which have proven to be effective are pheromone traps which prevent mating (Roscoe et al., 2022), and the manipulation of endophytic fungi communities naturally present within spruce and fir trees (Ullah et al., 2025).
Overall, issues with classical pesticide persistence, public opinions, and increased understanding of ecological services has urged alternative strategies and chemicals to be used for population control of spruce budworm.
Project details and datasets
Spruce budworm has gained popularity in the public sphere following multiple news reports highlighting the problem of frequent outbreaks. At this year’s Humber Valley Strawberry Festival in Pasadena, NL, spruce budworm moths were so numerous that their gathering resembled a blizzard:
Moth madness at Pasadena festival symptom of spruce budworm battle in N.L.
Figure 3. Photo of moth blizzard at Humber Valley Strawberry Festival, submitted by Melanie Wells
Author: Ashley Fitzpatrick, CBC News. Posted: Aug 12, 2026 https://www.cbc.ca/news/canada/newfoundland-labrador/moth-madness-at-pasadena-festival-symptom-of-spruce-budworm-battle-in-n-l-9.7303533
Though events like this are rare to see, they have drawn interest outside of the scientific community in the role of spruce budworm as a pest and integral part of Canadian forest ecosystems. News articles on their role, like the pest itself, make their rounds every few years. This project will be using the following article as the “anchor” due to its completeness and usefulness to the average Canadian.
Go inside the outbreak ravaging Gros Morne’s forests - Anchor Article
Figure 4. A spruce budworm caterpillar in Gros Morne National Park
Author: Lindsay Bird, CBC News. Posted: Nov 23, 2025 https://www.cbc.ca/news/canada/newfoundland-labrador/spruce-budworm-outbreak-atlantic-voice-9.6983204
Datasets
Though numerous analyses have been done to compare the efficiency of different treatments as part of their implementation in spruce budworm control, these analyses have been done on modern data and new implementations. This project therefore aims to compare the historical trends and evolution in usage of traditional chemicals and “new” chemicals used in spruce budworm population control, using the dataset provided by Heartz et al. (2023) and the Government of New Brunswick, available here: https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecy.4068
By comparing the results of this dataset with local literature on spruce budworm populations at the time, we can make correlations between the type of chemical sprayed, the amount sprayed, and the effect on larval populations. For this comparison, Gray and MacKinnon (2007) which make a comparison between tree mortality and pesticide protection from 1965-1992 was chosen due to covering the same geographic area and time period as the above dataset.
Dataset Analysis
Preliminary
# Preliminary library import
library(tidyverse) #contains dplyr, ggplot2, readr, tidyr
library(lubridate) #parse_date_time, yday, year
library(plotly) #ggplotly()
library(foreign) #reads dbf files# Loading chemical applications table (Heartz et al. 2023)
apps <- read.csv("NBHistoricPesticideApplications.csv") |>
mutate(across(where(is.character), trimws)) # strip stray leading/trailing spaces
# Inspecting the dataset
glimpse(apps)## Rows: 7,205
## Columns: 10
## $ app_ID <chr> "1952_001_1", "1953_001_1", "1953_002_1", "1953_002_2", "195…
## $ app_area <chr> "1952_001", "1953_001", "1953_002", "1953_002", "1953_003", …
## $ year <int> 1952, 1953, 1953, 1953, 1953, 1953, 1953, 1953, 1953, 1953, …
## $ insect <chr> "esb", "esb", "esb", "esb", "esb", "esb", "esb", "esb", "esb…
## $ act_ing <chr> "DDT", "DDT", "DDT", "DDT", "DDT", "DDT", "DDT", "DDT", "DDT…
## $ rate_kgha <dbl> 1.12, 0.56, 0.56, 0.56, 0.56, 0.56, 0.56, 0.56, 0.56, 0.56, …
## $ vol_lha <dbl> 9.34, 4.68, 4.68, 4.68, 4.68, 4.68, 4.68, 4.68, 4.68, 4.68, …
## $ form_type <chr> "oil", "oil", "oil", "oil", "oil", "oil", "oil", "oil", "oil…
## $ tank_mix <dbl> 0.11915, 0.11966, 0.11966, 0.11966, 0.11966, 0.11966, 0.1196…
## $ brand <chr> "unknown", "unknown", "unknown", "unknown", "unknown", "unkn…count(apps, act_ing, sort = TRUE) # the active ingredients (note: Btk is coded "BT")## act_ing n
## 1 Fenitrothion 3577
## 2 DDT 1365
## 3 BT 808
## 4 Aminocarb 749
## 5 Phosphamidon 581
## 6 Trichlorfon 90
## 7 Malathion 10
## 8 Dimethoate 9
## 9 Methoprene 8
## 10 Fenitrothion+Phosphamidon 4
## 11 Mexacarbate 2
## 12 Methomyl 1
## 13 Pyrethrin 1count(apps, form_type) # tank-mix media## form_type n
## 1 585 oil 2
## 2 ATLOX 3409 and water 381
## 3 CYCLOSOL 63 and 585 oil 6
## 4 DOWANOL TPM and ATLOX 3409 and water 88
## 5 DOWANOL and ATLOX 3409 and water 2086
## 6 DOWANOL and CYCLOSOL 63 OR CYCLOSOL 63 and 585 oil 146
## 7 Invadine JVC and water 27
## 8 emulsion 97
## 9 oil 1719
## 10 panasol 3
## 11 summer oil 2
## 12 undiluted 343
## 13 unknown 783
## 14 water 1480
## 15 wettable powder 42count(apps, brand, sort = TRUE) # commercial brands## brand n
## 1 unknown 4562
## 2 Sumathion 950
## 3 Matacil 180F 517
## 4 Dipel 132 405
## 5 Matacil 223
## 6 Thuricide 48LV 121
## 7 Dimecron 116
## 8 Dylox 90
## 9 Futura XLV HP 90
## 10 Futura XLV 40
## 11 NOVABAC3 23
## 12 Dipel 16
## 13 Rogor 40 9
## 14 Futura 7
## 15 Sumathion 20F 6
## 16 CGA13353 4
## 17 GS42710 4
## 18 Noviathon 4
## 19 Sumathion mix 4
## 20 Foray 48B 3
## 21 Dipel 176 2
## 22 Foray 76B 2
## 23 Matacil wp 2
## 24 Zectran 2
## 25 Dipel 45B 1
## 26 Dipel ABG-6103 1
## 27 Lannate 1# Missing-value codes: -9999 for numerical, "unknown" for text.
apps <- apps |>
mutate(across(c(rate_kgha, vol_lha), ~ na_if(.x, -9999)),
across(c(form_type, brand), ~ na_if(.x, "unknown")))
# PLEASE NOTE: Btk is recorded in BIU/ha, every other active ingredient in kg/ha.
apps <- apps |>
mutate(unit = if_else(act_ing == "BT", "BIU/ha", "kg/ha"))# Load areas table read from the .dbf file
# Holds the spatial and delivery-technology fields that the applications CSV lacks
areas <- read.dbf("NBHistoricPesticideAreas.dbf", as.is = TRUE) |>
rename_with(tolower) |> # normalize field-name case
mutate(
area_ha = shape_area / 10000, # Shape_Area is m^2 -> hectares
year = as.integer(year)
) |>
select(app_area, area_ha, app_type, aircraft, guidance, app_sys, num_apps)
names(areas) # confirm the field names above## [1] "app_area" "area_ha" "app_type" "aircraft" "guidance" "app_sys" "num_apps"glimpse(areas)## Rows: 4,545
## Columns: 7
## $ app_area <chr> "1952_001", "1953_001", "1953_002", "1953_003", "1953_004", "…
## $ area_ha <dbl> 78954.7743, 219536.9236, 16547.0359, 320161.9453, 2888.2381, …
## $ app_type <chr> "operational", "operational", "operational", "operational", "…
## $ aircraft <chr> "Boeing Stearman", "Boeing Stearman", "Boeing Stearman", "Boe…
## $ guidance <chr> "visual maps and spray pilot ground sighting", "visual maps a…
## $ app_sys <chr> "boom and nozzle", "boom and nozzle", "boom and nozzle", "boo…
## $ num_apps <int> 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1…count(areas, aircraft) # delivery-technology categories## aircraft
## 1 Boeing Stearman
## 2 Boeing Stearman and Grumman Avenger
## 3 Boeing Stearman and Grumman Avenger and Grumman AgCat and Snow Commander
## 4 Grumman Avenger
## 5 Grumman Avenger and Cessna AgTrucks and DC-6B
## 6 Grumman Avenger and DC-6B
## 7 Grumman Avenger and DC-6B and Thrush Commander and Ayres Turbo Thrush and Bell 206 helicopter
## 8 Grumman Avenger and DC-6B and other single engine
## 9 Grumman Avenger and Grumman AgCat
## 10 Grumman Avenger and Grumman AgCat and Cessna 188 and Bell 206 helicopter
## 11 Grumman Avenger and Grumman AgCat and Cessna AgTruck and Piper Pawnee Brave and Hiller 12E helicopter
## 12 Grumman Avenger and Grumman AgCat and Cessna AgTruck and Piper Pawnee Brave and Hiller 12E helicopter and Bell 206 helicopter
## 13 Grumman Avenger and Grumman AgCat and Cessna AgTruck and Thrush Commander and M-18 helicopter
## 14 Grumman Avenger and Grumman AgCat and Cessna AgTrucks
## 15 Grumman Avenger and Grumman AgCat and Cessna AgTrucks and M-18 helicopter
## 16 Grumman Avenger and Grumman AgCat and DC-6B and Cessna AgTruck and Thrush Commander and Piper Pawnee and M-18 helicopter
## 17 Grumman Avenger and Grumman AgCat and Piper Pawnee and DC-6B and Cessna 188 and M-18 helicopter
## 18 Grumman Avenger and Thrush Commander
## 19 Grumman Avenger and Thrush Commander and Cessna AgWagon
## 20 Grumman Avenger and Thrush Commander and helicopter
## 21 Piper Pawnee
## 22 unknown
## n
## 1 132
## 2 724
## 3 354
## 4 430
## 5 28
## 6 68
## 7 46
## 8 79
## 9 87
## 10 307
## 11 651
## 12 571
## 13 37
## 14 117
## 15 108
## 16 80
## 17 329
## 18 120
## 19 138
## 20 75
## 21 2
## 22 62count(areas, app_type) # operational vs experimental## app_type n
## 1 experimental 311
## 2 experimental-JDI 3
## 3 operational 4231# Join chemical applications to their areas on app_area.
# One area can carry several applications, so app_area repeats in `apps` but is unique in `areas`
joined_data <- apps |>
left_join(areas, by = "app_area")
# Provenance check for the methods section.
joined_data |>
summarise(
n_applications = n(),
n_areas = n_distinct(app_area),
n_missing_area = sum(is.na(area_ha)),
year_min = min(year),
year_max = max(year)
)## n_applications n_areas n_missing_area year_min year_max
## 1 7205 4545 0 1952 1993Chemical use observations
How amount applied changes over time
# active ingredient = rate_kgha * area_ha (kg) [chemicals only]
# spray-mix carrier = vol_lha * area_ha (L) [all actives]
# Note: Btk excluded from the mass sum due to different units
amount_year <- joined_data |>
filter(!is.na(area_ha)) |>
mutate(
kg = if_else(unit == "kg/ha", rate_kgha * area_ha, NA_real_),# chemicals only
L = vol_lha * area_ha # all actives
) |>
group_by(year) |>
summarise(total_kg = sum(kg, na.rm = TRUE),
total_L = sum(L, na.rm = TRUE),
.groups = "drop")
# Log-linear trend captures the rise and fall of the program.
m_kg <- lm(log(total_kg) ~ year, data = amount_year)
summary(m_kg)##
## Call:
## lm(formula = log(total_kg) ~ year, data = amount_year)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5296 -0.6023 0.1205 0.4359 1.7827
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 72.68156 23.18872 3.134 0.00327 **
## year -0.03047 0.01175 -2.592 0.01335 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9092 on 39 degrees of freedom
## Multiple R-squared: 0.147, Adjusted R-squared: 0.1251
## F-statistic: 6.721 on 1 and 39 DF, p-value: 0.01335amount_year <- amount_year |> mutate(fitted_kg = exp(predict(m_kg)))ggplot(amount_year, aes(year)) +
geom_col(aes(y = total_kg), fill = "grey75") +
geom_line(aes(y = fitted_kg), colour = "firebrick", linewidth = 1) +
scale_y_continuous(labels = scales::comma) +
labs(x = "Year", y = "Active ingredient applied (kg)",
title = "Total chemical insecticide applied per year, New Brunswick (1952-1993)")
Figure 5. Total mass of chemical active ingredient applied to New Brunswick forests each year, 1952-1993. Bars show observed annual totals; the red line is a log-linear trend fitted by least squares. Btk applications are excluded because their rate is recorded in BIU/ha rather than kg/ha.
## Slope (log kg per year): -0.0305## Std. error of slope: 0.0118## p value: 0.013## R squared: 0.147## Annual change: -3 %ggplot(amount_year, aes(year, total_L)) +
geom_line(colour = "steelblue") + geom_point() +
labs(x = "Year", y = "Spray-mix volume (L)",
title = "Carrier volume applied per year")
Figure 6. Total spray-mix carrier volume applied each year, 1952-1993. Carrier volume is the liquid in which active ingredients were delivered and includes all active ingredients, including Btk. It is distinct from the mass of active ingredient in Figure 5.
comp <- joined_data |> count(year, act_ing)
ggplot(comp, aes(year, n, fill = act_ing)) +
geom_col() +
labs(x = "Year", y = "Number of applications", fill = "Active ingredient",
title = "Shift in active ingredients, 1952-1993")
Figure 7. Number of insecticide applications per year by active ingredient, 1952-1993. The stacked bars show when each compound entered and left the New Brunswick spray program, illustrating the transition from DDT to organophosphates (phosphamidon, fenitrothion) and finally to Btk.
Chemical composition change over time
ggplot(comp, aes(year, n, fill = act_ing)) +
geom_col(position = "fill") +
labs(x = "Year", y = "Proportion of applications", fill = "Active ingredient")
Figure 8. Proportional composition of applications by active ingredient, 1952-1993. Bars are scaled to 100% each year, showing the relative hand-off from DDT to phosphamidon/fenitrothion and then to Btk, independent of the total number of applications.
# Technology is a property of area, not application.
# Built from joined_data and collapsed to one row per area.
tech <- joined_data |>
distinct(app_area, year, app_type, aircraft, guidance, app_sys, area_ha) |>
mutate(
# collapse the two experimental codes into one
app_type = if_else(str_detect(app_type, "^experimental"), "experimental", app_type),
# "unknown" indicates missing info
across(c(aircraft, guidance, app_sys), ~ na_if(.x, "unknown"))
)
# Coverage?
tech |> filter(!is.na(guidance)) |> count(year)## year n
## 1 1952 1
## 2 1953 21
## 3 1954 4
## 4 1955 42
## 5 1956 29
## 6 1957 35
## 7 1958 10
## 8 1960 15
## 9 1961 68
## 10 1962 58
## 11 1963 51
## 12 1964 65
## 13 1965 457
## 14 1966 193
## 15 1967 161
## 16 1968 56
## 17 1969 31
## 18 1970 58
## 19 1971 54
## 20 1972 98
## 21 1973 101
## 22 1974 68
## 23 1975 138
## 24 1976 119
## 25 1977 75
## 26 1978 49
## 27 1979 71
## 28 1980 46
## 29 1981 80
## 30 1982 108
## 31 1983 329
## 32 1984 571
## 33 1985 651
## 34 1986 307Evolution of spray technologies and methods of application
#short labels for the legend (raw too long)
guid_lab <- c(
"visual maps and spray pilot ground sighting" = "Visual maps + ground sighting",
"visual maps or FPL pointer system" = "Visual maps or FPL pointer",
"visual maps or FPL pointer in Cessna 185 with radio" = "Visual maps/FPL + radio",
"FPL pointer system" = "FPL pointer only",
"FPL pointer system or modified FPL system" = "FPL or modified FPL",
"modified FPL system" = "Modified FPL only",
"FPL pointer system or Litton for DC-6" = "FPL pointer + Litton (DC-6)"
)
fig9 <- tech |>
filter(!is.na(guidance)) |>
mutate(guidance = coalesce(guid_lab[guidance], guidance)) |>
count(year, guidance)
ggplot(fig9, aes(year, n, fill = guidance)) +
geom_col() +
labs(x = "Year", y = "Number of treated areas", fill = "Guidance system",
title = "Spray-guidance technology by year, 1952-1993")
Figure 9. Spray-guidance technology used by treated areas in New Brunswick, 1952-1993. Each bar is the number of treated areas; colours show the guidance method recorded for those areas. Because guidance was recorded at the level of the annual spray program, a single method dominates each year, and the transitions mark when the program changed navigation systems.
sys_lab <- c(
"boom and nozzle" = "Boom and nozzle",
"boom and nozzle or Micronair" = "Boom/nozzle or Micronair",
"boom and nozzle or Micronair AU4000 or Sergonairs"= "Boom/nozzle, Micronair or Sergonairs",
"Micronair AU4000" = "Micronair AU4000",
"Micronair" = "Micronair"
)
fig10 <- tech |>
filter(!is.na(app_sys)) |>
mutate(app_sys = coalesce(sys_lab[app_sys], app_sys)) |>
count(year, app_sys)
ggplot(fig10, aes(year, n, fill = app_sys)) +
geom_col() +
labs(x = "Year", y = "Number of treated areas", fill = "Application system",
title = "Spray-delivery technology by year, 1952-1993")
Figure 10. Spray-delivery (application) system used by treated areas, 1952-1993. Each bar is the number of treated areas; colours show the delivery method recorded. Boom-and-nozzle systems dominate the early record, with Micronair rotary atomisers appearing later as drift-reduction technology.
## Figure 11 — Operational vs. experimental
tech |>
filter(!is.na(app_type)) |>
count(year, app_type) |>
ggplot(aes(year, n, fill = app_type)) +
geom_col() +
scale_fill_manual(values = c(operational = "#4E79A7",
experimental = "#F28E2B")) +
labs(x = "Year", y = "Number of treated areas", fill = "Application type",
title = "Operational vs. experimental applications, 1952-1993")
Figure 11. Operational versus experimental insecticide-treated areas by year, 1952-1993. Experimental areas include the original ‘experimental’ and ‘experimental-JDI’ records. Spikes in experimental activity mark the periods of most intensive field research on spruce budworm control.Operational spraying is attributed to non-research directed population control.
#Proportional companion
tech |>
filter(!is.na(app_type)) |>
count(year, app_type) |>
ggplot(aes(year, n, fill = app_type)) +
geom_col(position = "fill") +
scale_fill_manual(values = c(operational = "#4E79A7",
experimental = "#F28E2B")) +
scale_y_continuous(labels = scales::percent) +
labs(x = "Year", y = "Proportion of treated areas", fill = "Application type")
Figure 12. Proportional share of operational versus experimental treated areas by year, 1952-1993. Bars are scaled to 100% each year, isolating relative research effort from the overall size of the program.
Results and Conclusions
Data coverage and provenance
The joined dataset (areas+ applications) contains 7,205 insecticide applications across 4,545 distinct treated areas, spanning 1952–1993. Every application matched a spatial record, with zero applications missing a treated area, so all mass- and area-weighted calculations use the full record. Applications are classified as 4,231 operational, 311 experimental, and 3 experimental-JDI areas. Two coverage issues were found in the data: (a) No applications recorded for 1959 due to a pause in the program (TBM Avengers Archive, 2010); (b) Applications for 1969 and 1980 are known to be incomplete in the source data. Figures should therefore be treated as a faithful record of what was digitised rather than a complete census of what was sprayed.
Insecticide application over time
There is a known shift to chemicals which carry lesser ecological burden over time, supported overall by this analysis. There has also been an observed reduction in pesticide application by mass during the 1952-1993 period (Figure 5), though it is important to note that Btk was excluded from this particular analysis due to incompatible units (BIU/ha) and there has been a documented shift towards Btk as an insecticide over time, hence conclusions can only be drawn on the change in chemical insecticide application over time. The distribution is strongly non-linear with many irregular years, marked by a peak approximately every 5 years with gradual reduction over the coming years. This is consistent with research on EIS in population control and likely shaped experimental design for future studies, which typically use a 5 year cycle of application (D. A. MacLean et al., 2019).
A log-linear trend fitted across the whole period is negative and statistically significant (slope = −0.0305, SE = 0.0118, p = 0.013), implying an average decline of roughly 3% per year in applied mass. Critically, however, this model explains only 14.7% of the variance (R² = 0.147). The low R² is due to the limited capacity of a linear model to explain the variability in chemical insecticide application over the course of the program.
Figure 6 shows the spray-mix carrier volume in litres applied per year. This measures the liquid in which active ingredients were delivered rather than the quantity of toxin and is available for every active ingredient including Btk. Carrier volume generally tracks the same rise-and-fall as applied mass, but the two are not proportional: the ratio of carrier to active ingredient changes as formulation and delivery technology changed. The 1957 and 1976 peaks are still present, but other years show a mismatch, such as a decline to 0 in carrier volume coinciding with a peak in active ingredient application in 1982.
Figures 7 and 8 document the replacement of one chemistry by another. Figure 7 (counts of applications) shows when each compound entered and left the program; Figure 8 (proportions) then removes the effect of program size to show when each chemical was most used and when it was phased out of use. The sequence is a clear succession from DDT to the organophosphates phosphamidon and fenitrothion through the 1960s and 1970s, with Btk entering in the mid 1980s and rising to dominate the final years of the record. A small number of applications use a fenitrothion–phosphamidon tank mixture, shown as their own category. Multiple other insecticides (please see glossary for all definitions) were also documented from the 1960s through the 1980s, which, though chemical, share the mechanism of death with Btk by interfering with or inhibiting essential bodily functions. Some of these are now considered obsolete due to their harmfulness to non-target species, such as aminocarb (Tzilivakis et al., 2026).
Evolution of application and guidance technologies
Figures 9 and 10 show the delivery technology used, as the share of treated areas employing each guidance system and each application (spray-delivery) system. Because most area records list more than one system, the values do not sum to 100%; each line is the proportion of areas on which that technology was used.
Figure 9 shows the progression of spray guidance from early visual maps and pilot ground-sighting, through FPL pointer systems, to modified FPL systems and specialised aids such as the Litton system for the DC-6 and radio-directed navigation in the Cessna 185. Figure 10 shows the corresponding change in spray delivery method, with boom-and-nozzle systems being most common in the early record and Micronair rotary atomisers (and, briefly, Sergonairs) appearing later, a technology adopted largely to control droplet size and reduce drift due to air currents and winds. It should be noted that early years of the program have a higher incidence of “unknown” guidance records and as such may not be most accurate.
This indicates that the program’s precision increased over time, since later applications used finer control of where and how spray was deposited, which is consistent with the falling dose-per-hectare seen in Figure 5. Guidance and delivery are not independent of chemistry, and in part better technologies allow for less product to be used.
Operational vs experimental applications
In order to examine how research on spruce budworm changed over time, a comparison was made between operational forestry applications and experimental research applications. Figure 11 therefore separates operational spray blocks from experimental ones by year. Operational applications dominate throughout (4,231 of 4,545 areas), but the experimental component is episodic rather than steady. Research activity clusters in particular years (1958, 1965-1966, 1968, 1971-1972, 1974, 1976, 1980, 1982, 1986, 1990, 1992) rather than being spread evenly.
Spraying and budworm populations connections
Many analyses on modern data have been conducted to confirm the efficacy of modern insecticide agents as part of research or meta-analysis. However, such analyses are rarely done on historical data, and historical data on spruce budworm populations is difficult to compare to the Heartz et al. (2023) dataset due to a mismatch of control/test treatment, location, or timescale. For comparison to literature, Gray and MacKinnon (2007), which covered spruce budworm defoliation in New Brunswick from 1965-1992 will be used here.
This analysis documents how spruce budworm management in New Brunswick changed between 1952 and 1993 by analyzing its chemicals, volumes, and delivery technology. Gray and MacKinnon (2007) independently established what that program achieved through comparing reported vs expected defoliation by spruce budworm to determine the efficiency of the NB spray program at protecting stands. Together the two datasets describe both the inputs and the effect of one of the largest forestry insecticide programs in Canadian history.
Gray and MacKinnon (2007) found that protection peaked from 1976-1982, which coincides with a peak in insecticide application in 1976 in this dataset. This could be evidence of reactive spraying due to the recorded severe defoliation in the years prior (1974-1975, Figure 1 in Gray and MacKinnon). Literature on EIS has shown that insecticide application can be very effective at reducing budworm populations even if it is not applied every year, and can reduce overall necessity for pesticide use (D. A. MacLean et al., 2019). However, they note that their estimations of “without protection” are conservative, as it is not possible to remove the stand mortality prevented by protection that is not a direct cause of defoliation prevention.
Limitations
Unfortunately, due to Btk being measured in BIU/ha, a potency unit, instead of kg/ha, it had to be excluded from Figure 5 of the analysis due to non-convertability between the units. Because the record also shows a documented shift toward Btk across the 1980s, the true trend in total insecticidal pressure is flatter than implied by Figure 5. Therefore, any statement that “spraying declined” must be limited to “chemical spraying declined”.
As noted prior, the dataset used is not fully complete, with data missing in 1969 and 1980. Treated area is also an over-estimate, because area boundaries were hand-drawn and buffer zones such as streams and dwellings were not removed. Absolute mass values should therefore be read as upper bounds, and may not be fully accurate to actual spraying numbers.
Overall Conclusions
Overall, there was an observed reduction in chemical insecticde use throughout the New Brunswick Forest Protection Limited program, with a transition from DDT to organophosphates to Btk, and, most recently, to biological lures, traps, and insecticides. Furthermore, delivery technologies became more precise, allowing for less product to be used to achieve the same effect. Research of the spruce budworm also showed sporadic occurrence rather than fixed year ranges, with the majority of spraying being conducted for population control purposes instead. Comparison to known literature allows for correlations to be made between budworm populations and spray volumes and technologies, showing that reactive spraying has occurred before, and that the program was overall successful.
Glossary
Active ingredient - The chemical that produces an insecticidal effect, typically diluted by a carrier such as water.
Aminocarb chemical structure
Aminocarb (C₁₁H₁₆N₂O₂) - Carbamate class insecticide introduced in 1956 with low toxicity to mammals that has since been found to be obsolete.
BIU/ha - Billion international units per hectare, a measure of potency
Boom and nozzle mechanism structure
Boom-and-nozzle - The conventional system of aerial pesticide application consisting of a boom (long bar) and hydraulic nozzle that forces liquid through an orifice to form droplets. Droplet size depends on nozzle type, orifice size and pressure.
Btk - Bacillus thuringiensis var. kurstaki, a bacterial insecticide which damages larva of Lepidopterans by Cry crystals (protein crystals made as a natural part of the bacterium’s life cycle) reacting with their alkaline stomach environment to form toxins that poke holes in the insect’s stomach.
Carbamate pesticides - A synthetic organic compound derived from carbamic acid to control pest populations by inhibiting acetylcholinesterase, thereby inhibiting many necessary nervous system functions such as nerve signalling. This process is reversible, distinguishing it from organophosphate pesticides.
DDT chemical structure
DDT - An organochlorine insecticide that was first synthesized in 1874. It is slightly to moderately toxic to many classes of animals, including mammals, and result in reproductive damage, tumours, and sometimes death.
Dimethoate chemical structure
Fenitrothion chemical structure
Fenitrothion (C₉H₁₂NO₅PS) - Brownish-yellow oil organophosphate class pesticide used as a selective acaricide against sucking insects such as flies, mosquitos, cockroaches, and herbivorous pests.
FPL pointer system - Forest Protection Limited pointer system of navigation used by pilots in the program.
Litton (DC-6) - Inertial navigation system fitted to Douglas DC-6 spray tankers, the Lockheed F-104 Starfighter, and functions through determining the position of the plane through accelerometers and gyroscopes.
Malathion chemical structure
Malathion (C₁₀H₁₉O₆PS₂) - Colourless liquid organophosphate class pesticide used to kill many insects including head lice and fleas. It has been found to cause cancer.
Methomyl chemical structure
Methoprene chemical structure
Methoprene (C19H34O3) - Synthetic mimic of juvenile hormone, a growth regulator. Its applications disrupts insect development.
Mexacarbate chemical structure
Mexacarbate (C₁₂H₁₈N₂O₂)- White crystalline carbamate class pesticide, toxic upon contact as well as ingestion.
Image of the micronair mechanism from Micron Sprayers
Micronair - A wind-driven rotary atomizer that spins liquid off a rotating cage to produce a narrow, controlled droplet spectrum. Introduced to aerial work in the late 1950s.
Organophosphate pesticides - Organophosphates inhibit acetylcholinesterase, similarly to carbamates, thereby disrupting the nervous system. However, unlike carbamates, their effects are not reversible.
Phosphamidon chemical structure
Phosphamidon (C₁₀H₁₉ClNO₅P) - Pale yellow liquid organophosphate class pesticide, used specifically as an acaricide.
Pyrethrin chemical structure
Pyrethrin (C₄₃H₅₆O₈) - Natural insecticide extracted from Chrysanthemum flowers which acts upon contact as a poison.
Sergonair - High speed atomizer produced by SERG International. There is an extremely limited amount of information available about Sergonair, leading the author to believe it was either limited in use, a proprietary product that was later renamed, possibly to Accuair, or that this information is classified.
Spray-mix volume - Total amount of diluted liquid applied per unit area.
Trichlorfon chemical structure
Trichlorfon (C₄H₈Cl₃O₄P) - White crystalline organophosphate class pesticide used as a prodrug. Once inhaled, absorbed, or ingested by an organism, it is activated into 2,2-dichlorovinyl dimethyl phosphate (DDVP) where it is used typically for indoor pest control.
Tebufenozide chemical structure
Tebufenozide (C22H28N2O2) - A carbohydrazide that triggers premature molting in caterpillars by acting as an agonist on ecdysone.
References
Peer-reviewed sources
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Gen AI statement
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