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Monitoring the impacts of mountain pine beetle mitigation
Forest Ecology and Management 258 (2009) 1181–1187
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Monitoring the impacts of mountain pine beetle mitigation Michael A. Wulder a,*, Stephanie M. Ortlepp a, Joanne C. White a, Nicholas C. Coops b, Sam B. Coggins b a b
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, British Columbia, V8Z 1M5, Canada Department of Forest Resources Management, 2424 Main Mall. University of British Columbia, Vancouver, V6T 1Z4, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Received 2 April 2009 Received in revised form 29 May 2009 Accepted 8 June 2009
Since 1999, the mountain pine beetle (Dendroctonus ponderosae Hopk. [Coleoptera: Scolytidae]) has impacted over 13 million hectares of pine forests in western Canada. Successful mitigation of the beetle depends on the accurate and timely identification of currently infested trees and on sustained control activities over several successive years. We monitored the success of mitigation activities in reducing damage caused by mountain pine beetle at two sites (A and B) on the leading edge of the current beetle epidemic in western Canada. Using three years of digital high spatial resolution aerial imagery (2006– 2008) and one season of field measurements (2008), we estimated retrospective ratios of trees attacked by beetle in the current year (green attack) to trees attacked in the previous year (red attack), hereafter referred to as G:R. Our results indicate that mitigation activities slowed the rate of population growth, with G:R found to be decreasing or stable over sites A and B while mitigation was ongoing in 2005 and 2006 (site A 1.06:1; site B 0.32:1). When mitigation was discontinued over site A in 2007, the G:R increased markedly (1.94:1), while continued mitigation at site B in 2007 further reduced the G:R (0.22:1). Despite the cost associated with mitigation, its efficacy is rarely assessed and even more rarely documented. The approach presented herein enables a sample-based appraisal of mitigation efforts. Crown Copyright ß 2009 Published by Elsevier B.V. All rights reserved.
Keywords: Insect Mitigation Forest Management Planning Digital imagery Remote sensing Mountain pine beetle
1. Introduction Since 1999, the population of mountain pine beetle (Dendroctonus ponderosae Hopk. [Coleoptera: Scolytidae]) has grown to an epidemic level in western Canada, expanding into areas previously thought to be outside the mountain pine beetle’s geographical range (Westfall and Ebata, 2008). Endemic to British Columbia, the preferred host of the beetle is lodgepole pine (Pinus contorta Dougl. Ex. Loud var. latifolia Engelm.); however, any species of pine is at risk of attack (Furniss and Schenk, 1969). Factors contributing to the current epidemic include alterations to established climatic limitations to mountain pine beetle survival (Re´ginie`re and Bentz, 2007; Aukema et al., 2008; Raffa et al., 2008) and an abundance of suitable hosts resulting from almost one hundred years of successful fire suppression (Taylor and Carroll, 2004). By 2008, mountain pine beetle had impacted more than 13 million hectares of pine forest in western Canada (Raffa et al., 2008). The total cumulative volume losses associated with the current epidemic in British Columbia are estimated at 620 million m3, representing 46% of the total merchantable pine volume on British Columbia’s timber harvesting land base (Walton et al., 2008). The magnitude of the current mountain pine beetle
* Corresponding author. Tel.: +250 363 6090; fax: +250 363 0775. E-mail address: [email protected] (M.A. Wulder).
epidemic has converted the forest in the impacted area from a small net carbon sink to a large net carbon source (Kurz et al., 2008). Concern is now focussed on the possibility of further range expansion by the beetle into the pine forests of Canada’s boreal region (Westfall, 2006; Raffa et al., 2008). 1.1. Background 1.1.1. Mitigation of mountain pine beetle Options for controlling the mountain pine beetle populations are limited: with the exception of a characteristically short twoweek flight period (4 to 6 weeks in cool weather) that normally occurs mid-summer, the entire year-long lifecycle (for univoltine populations) of the mountain pine beetle is spent under the bark of the host tree (Safranyik and Carroll, 2006). Mature adult beetles emerge and disperse from their parental hosts in late July to early August in search of a new host for colonization, oviposition, reproduction, and completion of their lifecycle (Amman and Cole, 1983). Once a host is successfully attacked, the beetles will construct galleries in the living phloem under the bark and lay their eggs. After one week, the eggs typically will hatch and the larvae will begin to feed on the phloem, remaining under the bark for the duration of the winter, and emerging as adults the following year (Amman and Cole, 1983). Mitigation of mountain pine beetle is either through direct or indirect control. Indirect control is preventative management that
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seeks to limit the number of susceptible host trees on the landscape (Carroll et al., 2006a), and includes silvicultural treatments such as: prescribed burning, stand thinning, or alteration of the age class distribution or species mix within a stand (Whitehead et al., 2004; Fettig et al., 2007). Direct control attempts to limit a mountain pine beetle population’s rate of increase, and preferably, return the population to an endemic state. Direct control programs generally target green attack trees, with the objective of destroying the host tree before the beetles contained therein have the opportunity to emerge and disperse. Infested trees in the red attack stage are detected during annual airborne forest health surveys conducted throughout the province and green attack trees are then detected by way of their spatial association with these surveyed red attack trees (Mitchell and Preisler, 1991; Wulder et al., 2009). Since emergence typically occurs in late July to mid-August, mitigation of green attack trees should be planned for winter and spring, and subsequent ground surveys to assess population levels would then be conducted in late summer or early fall. Various methods of direct control have been implemented, either as single tree treatments (e.g., felling and burning, felling and bark removal, standing bark removal, monosodium methane arsenate injections, and single tree harvest), or as stand level treatments (e.g., harvest, prescribed burn) (Maclauchlan and Brooks, 1998; Carroll et al., 2006a; Coops et al., 2008). Single tree treatments are costly and time consuming because they require extensive ground surveys to accurately identify green attack trees, and therefore are best implemented when populations of mountain pine beetle are small (Whitehead et al., 2004; Trzcinski and Reid, 2008). Carroll et al. (2006a) identified three criteria for successful direct control of mountain pine beetle populations: early detection of infestations, aggressive direct control, and continuation of direct control until the desired population level is reached. It is the latter, the sustained maintenance of mitigation over successive years, that is most critical (Coggins et al., 2008), since it is unlikely that ground surveys will successfully identify all green attack trees in any given year. 1.1.2. Green attack to red attack ratio The ratio of green attack to red attack trees (G:R) is used to indicate a general trend in a mountain pine beetle infestation in a given area (i.e., is the infestation increasing or decreasing?). The G:R is an assessment of the manifestation of a mountain pine beetle infestation, enabling an evaluation of the actual damage caused by the beetle. As such, it serves as a proxy for estimating changes in the size of the beetle population and is one of the indicators used to determine strategies for forest management units in British Columbia (e.g., suppression, salvage, monitoring) (British Columbia Ministry of Forests, 1995). A ratio less than one is indicative of a declining population; a ratio greater than one is indicative of an increasing population (Wulder et al., 2006). It should be noted that while the G:R is useful for indicating general trends in an infestation, it does not provide a direct measure of the beetle population in a given area, nor does it indicate how well these invading beetles have survived and reproduced. The latter is typically determined by late spring assessments of brood production in relation to stand density and overwintering mortality. These assessments result in the estimation of an R value, which is an estimate of the rate of beetle population increase and an important indicator of the potential threat of a mountain pine beetle population in an area (Carroll et al., 2006a). According to calculations made by the British Columbia Ministry of Forests and Range (2002), the theoretical maximum G:R, derived from the maximum beetle reproductive rate, is approximately 10:1. Since this theoretical maximum does not take
into account mortality factors, maximum field measurements of G:R have rarely exceeded 5:1, and more commonly in British Columbia, G:R do not exceed 2:1 in northern areas, and 4:1 in southern areas (British Columbia Ministry of Forests and Range, 2002). Trzcinski and Reid (2009) estimated the maximum rate of increase based on 10-year historical data in the Kootenay National Park to be 3:1 with a 95% confidence interval of 1.4:1–7.1:1. It is posited that larger G:R are influenced by immigration of beetles from other areas. Wulder et al. (2008) generated retrospective G:R using a time series of QuickBird multi-spectral and panchromatic high spatial resolution imagery acquired in consecutive years by backcasting the current year’s red attack damaged trees as the previous year’s green attack. Their results show that image-based G:R closely match G:R derived from field surveys. The ongoing collection and interpretation of similar imagery would facilitate the estimation of annual G:R ratios, thereby providing ongoing information about trends in mountain pine beetle populations. 1.1.3. Goals and objectives The goal of this research is to develop and present an approach for assessing the effectiveness of sustained mitigation on an expanding mountain pine beetle population located on the leading edge of the current beetle epidemic in western Canada. The objectives were to use a combination of field measures and high spatial resolution aerial imagery to generate annual G:R for the study sites, and then compare these annual G:R to information on the location and timing of mitigation activities in the study sites and in areas immediately surrounding the study sites. 2. Methods 2.1. Study site The study area is located in the Boreal Plains ecozone (Ecological Stratification Working Group, 1996) and within the rain shadow of the Rocky Mountains to the west, resulting in average annual precipitation of only 400 mm. Elevation in the area ranges from 719 to 2302 m, with an average elevation of 1257 m (S.D. 249 m). The forests in the study area are dominated by lodgepole pine, but also include alpine fir (Abies lasiocarpa (Hook) Nutt), Engelmann spruce (Picea engelmannii Parry ex Engelm.), white spruce (Picea glauca (Moench) Voss), black spruce (Picea mariana (Mill) BSP), jack pine (Pinus banksiana Lamb.), and tamarack (Larix laricina (Du ROI) K. Koch) (Lands Directorate, 1986). Prior to 2003, the study area had no previous recorded history of mountain pine beetle infestation (Westfall, 2004). It is posited that the infestation originated as a result of one large dispersal of beetles from a heavily infested area of pine forest east of Prince George, British Columbia, in 2002 (Westfall, 2005; Safranyik and Carroll, 2006). Previously, the Rocky Mountains in this northern area were considered an insurmountable topographic barrier to beetle expansion. Subsequent research has confirmed the plausibility of such long range dispersal by mountain pine beetle (Jackson et al., 2008). Notions of climate change related expansion in mountain pine beetle range have also been suggested for this region (Carroll et al., 2004). Mitigation commenced in this area in 2004. By 2005, the majority of mountain pine beetle control efforts in western Canada were focussed in this area in an attempt to prevent the beetle from spreading across Canada (Westfall, 2006). The two sample sites that were selected (A and B) were both predominantly pine stands with similar climatic and topographic conditions (Table 1). These climatic and topographic factors are known to influence the susceptibility and subsequent potential of a forest stand to support populations of mountain pine beetle (Shore and Safranyik, 1992; Carroll et al., 2004; Carroll et al., 2006b;
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Table 1 Summary of topographic and climatic characteristics of sites A and B. Elevation (m)
Site A Site B
Annual degree days >5 8C
Min. January temp. (8C)
Mean August temp. (8C)
Min
Max
Mean
Min
Max
Mean
Min
Max
Mean
Min
Max
Mean
1034 1006
1557 1321
1323 1201
790 920
1113 1104
951 1019
13.3 13.7
12.8 13.0
13.0 13.3
11.5 12.3
13.6 13.4
12.5 12.9
Aukema et al., 2008). The sites are located approximately 54 km apart; located near the border between British Columbia and Alberta and the communities of Tumbler Ridge and Grande Prairie (Fig. 1). The western site (A) has an area of 24 km2 and the eastern site (B) has an area of 30 km2. Despite their climate similarities the two sites have been subject to different levels of mitigation (Table 2): site A is located in an area that was mitigated in 2005, followed by a marked reduction in mitigation effort in 2006, and no mitigation in 2007, whereas site B was not mitigated in 2005 and received increasing mitigation focus in 2006 and 2007. 2.2. Data 2.2.1. High spatial resolution imagery Digital high spatial resolution colour aerial imagery were acquired from a fixed-wing aircraft with a Canon EOS-1Ds Mark II camera. The camera features a metal-oxide-semiconductor (CMOS) sensor that results in imagery with an effective resolution of 16.7 megapixels. Image geo-referencing was supported by an onboard global positioning system (GPS) coupled with an inertial navigation system (INS). The imagery was captured over three spectral ranges which approximate to: 0.4–0.5 mm (blue), 0.5– 0.6 mm (green), and 0.6–0.7 mm (red). In mid-August 2006 and mid-September 2007, images were acquired for both sites (A and B) at a 10 cm spatial resolution; in mid-July 2008, images were acquired at a 20 cm spatial resolution at both sites. The images were provided as mosaiced, registered products by the vendor, (a high-spatial resolution satellite orthorectified image was used as a
base for registration with an estimated horizontal error of <5 m). The 2006 and 2007 images were resampled to 20 cm to facilitate image-to-image registration to the 2008 image. 2.2.2. Field surveys At the end of August 2008, field surveys were conducted at nine plots in site A and 11 plots in site B to supplement the image data and facilitate estimation of 2008 G:R. Field plots were circular with a 30 m radius. At each plot the geographic centre was recorded using a GPS which was differentially corrected post-collection to an estimated accuracy of 2.2 m. The species and stem diameter (diameter at 1.3 m up the stem) for each tree in the plot was measured and crown area (m2) measurements recorded for atleast two dominant trees in the plot. Finally, mountain pine beetle attack status of each tree was assessed according to a four category classification system where 0 is healthy, 1 is green attack, 2 is red attack, and 3 is grey attack (Coggins et al., 2008). 2.2.3. Mitigation Information on mitigation activities in the area was compiled from provincial government agencies into a GIS database, which identified the location, year, type and (if available) number of trees mitigated. In order to examine the context of mitigation activities surrounding each of the study sites, site-specific mitigation data were augmented with information on all mitigation activities within a 20 km buffer surrounding each of the study sites (Table 2). Both single tree and stand level direct control treatments were applied.
Fig. 1. Study area on the Alberta and British Columbia border in western Canada, including the location of sites A and B.
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Table 2 Annual summary of single tree and stand level direct control mitigation activities located within sites A and B, and located within a 20 km area surrounding sites A and B. 2005 Site Site Site Site
A A 20 km buffer B B 20 km buffer
1 tree mitigated at 1 location 1673 trees mitigated at 330 locations No control activities 1 tree mitigated at 1 location
2006
2007 2
1 tree mitigated at 1 location; 0.6 km harvested 3179 trees mitigated at 73 locations; 21.4 km2 harvested 11 trees mitigated at 1 location 1666 trees mitigated at 554 locations
2.2.4. Forest inventory Forest inventory data (Sandvoss et al., 2005) were used to mask out areas of non-pine forest and non-forest in sites A and B. The mask was used to exclude these areas from selection of sample plots and subsequent analysis as per Skakun et al. (2003). Based on the provincial forest inventory datasets, the average proportion of pine in a stand was 65% in site A and 58% in site B–confirming the general similarity of the sites with respect to species and local environment. 2.3. Methods 2.3.1. Selection of image sample plots To facilitate calculation of G:R, a simple random sample of 1 ha circular image plots were selected from sites A and B. Plots centers were randomly located within the areas of pine forest identified from the forest inventory. To enable identification of red attack with a confidence level of 98% and a 10% allowable error around the mean, we estimated the required number of image sample plots using Eq. (1) (Ko¨hl et al., 2006, p. 87):
n¼
2 tn;1 a=2 VarðYÞ
E2
(1)
No control activities No control activities 154 trees mitigated at 10 locations 4298 trees mitigated at 463 locations
where n is the number of 1 ha plots required to achieve the desired confidence level given by the t value (two tailed, n 1 degrees of freedom), Var(Y) is the approximate variance of the population, and E is the percent allowable error of the mean. The variance of the population is estimated with Eq. (2) (Ko¨hl et al., 2006): VarðYÞ ffi
2 maxðyi Þ minðyi Þ 4
(2)
where the max(yi) and min(yi) are the maximum and minimum number of red attack trees per hectare. The minimum number of red attack trees per hectare is zero, while the maximum number of red attack trees per hectare was estimated from a pilot study (using the 2008 imagery for site A) as being 155 trees per hectare. Based on these equations and our desired confidence level and allowable error around the mean, the variance was estimated at 1501 trees and the required sample size was 82. The 82 image sample plots were distributed between the two sites proportional to area, resulting in 37 image plots in site A and 45 image plots in site B. 2.3.2. Image interpretation For each of the 82 image sample plots, a count of all visible conifer tree crowns in the 2008 imagery was made to estimate the
Fig. 2. Example of a 1 ha image plot. All crowns in the plot were delineated and the number of red attack crowns were enumerated for each year.
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Table 3 Characteristics of image plots and interpretation results for red attack crowns.
Site A Site B
Number of 1 ha image plots
Mean stand density (trees/ha)
Mean % pine
37 45
678 951
65 59
stand density in stems per hectare. The number of red attack crowns in each plot in the 2006, 2007, and 2008 imagery was recorded. For each year of imagery, a count of the red attack crowns was made, as shown in the example in Fig. 2. 2.3.3. Estimation of G:R Red attack in 2007 and 2008 was back cast as green attack in 2006 and 2007, thereby enabling the estimation of G:R for 2006 and 2007. For the calculation of the 2008 G:R, the number of green attack and red attack crowns identified in the field surveys were used, as 2009 imagery would have been necessary to similarly back cast 2009 red attack as 2008 green attack. In order to verify that the red attack crowns identified in the field plots in 2008 were attacked in 2007 and not earlier, the crowns were located on the 2007 imagery and confirmed to appear visually green in that year. 3. Results Mitigation activities within sites A and B and within the greater study site areas are summarized in Table 2. Mitigation was initiated in the area surrounding site A in 2005, with 1673 trees mitigated at 330 locations. In the area surrounding site A, twice as many trees were treated in 2006 as 2005, but at less than 25% of the locations treated in 2005. Stand level treatments were also undertaken in the area surrounding site A in 2006, with approximately 21 km2 harvested. Although there was mitigation in the area surrounding site A, there was little mitigation effort directly located within site A. As indicated in Table 2, the mitigation activities at site B were different than those at site A in terms of both timing and extent. Only single tree treatments were applied at site B; site A had both single tree and patch treatments. Overall, more trees were treated in site B than in site A, but mitigation activities were started earlier in site A. In 2007, 154 trees were mitigated at 10 different locations within site B. Finally, extensive single tree treatments were undertaken in the area surrounding site B in 2007 (4298 trees at 463 locations), while no mitigation was undertaken in site A in 2007. The general stand characteristics and number of red attack crowns interpreted in each of the 82 image plots are summarized
Mean elevation (m)
Number of red attack crowns 2006
2007
2008
1326 1195
28 3
171 19
182 6
in Table 3, while the characteristics of the 2008 field plots are summarized in Table 4. In addition to assessing the attack status of trees in the field plots in 2008, we also collected data on mitigation activities at site B (there were no mitigation activities at the field plots in site A in 2008). By counting the number of stumps remaining in the 30 m field plots we could determine how many trees were treated in 2008 (Table 4). Although field data indicated that 49 trees were treated in the field plots in site B in 2008, two additional unmitigated green attack trees were found, indicating that the mitigation had missed approximately 4% of the green attack in the 11 sub-plots that were field sampled in 2008. In 2006, the G:R for sites A and B were similar at 6.11:1 and 6.33:1, respectively (Table 5), with approximately 60% of image plots at site A and 20% of image plots at site B containing green attack trees (Table 6). In 2007, the G:R at both sites dropped markedly, with the G:R for site A at 1.06:1 and the G:R for site B at 0.32:1. In this year, the percentage of image plots with green attack was 38% at site A and 11% at site B. The 2008 field data indicate that the G:R ratio at site A increased to 1.94:1, while the G:R at site B continued to decrease and was 0.20:1 in 2008. 4. Discussion There are many factors which can influence the rate of increase in mountain pine beetle populations. Sites A and B were selected for their similarity in elevation, climate, topography, and infestation initiation dates. In terms of climatic factors, the two sites are similar, with site B located at a slightly lower mean elevation (100 m lower), and having a slightly higher degree day accumulation (>5 8C). The rate of mountain pine beetle population expansion has been found to be positively correlated with lower elevations and higher degree day accumulations (Safranyik, 1978), therefore it would be expected that these two sites would have similar susceptibility to attack by mountain pine beetle. The severity of mountain pine beetle infestations are typically classified according to the proportion of trees that are attacked in a given area (British Columbia Ministry of Forests and Canadian Forest Service, 2000), and Table 3 indicates that site A had a more severe infestation than site B, with a greater number of total trees
Table 4 Characteristics of 2008 field plots.
Site A Site B a
Number of plots (30 m radius)
Mean stand density (trees/ha)
Mean % pine
Mean elevation (m)
Total number of green attack treesa
Total number of red attack treesa
Total number of mitigated trees
9 11
721 883
68 88
1335 1243
31 2
16 10
0 49
Based on sample size (n = 20) and a confidence level of 95%, the confidence interval 4.36 trees.
Table 5 Estimation of G:R for sites A and B. Estimates of green and red attack trees 2006
Site A Site B a
Estimated G:R 2008a
2007
2006
2007
20081
Green
Red
Green
Red
Green
Red
G:R
G:R
G:R
171 19
28 3
182 19
171 6
31 2
16 10
6.11:1 6.33:1
1.06:1 0.32:1
1.94:1 0.20:1
Estimated from field measurements.
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1186 Table 6 Proportion of image plots with green attack.
Proportion of image plots with green attack
Site A Site B a
2005a
2006
2007
27.03 2.22
60 20
38 11
Back cast from red attack crowns interpreted from the following year’s imagery.
attacked in 2007 and 2008. Although the severity of the infestation may have initially been greater at site A, the marked increase in the number of trees treated at site B in 2006 and 2007 (Table 2) is indicative of the increasing severity of the infestation at this location. From 2005 to 2006 there was an increase in the proportion of image plots with green attack at both sites A and B (Table 6). In 2006, the G:R in sites A and B were similar, indicating that mountain pine beetle populations at both sites were increasing at similar rates. In 2005, extensive direct control activities had been initiated in the area surrounding site A. Notwithstanding these aggressive control efforts, the proportion of image plots with green attack in site A more than doubled in 2006, increasing from 27% of image plots in 2005 to 60% in 2006. However, at site B, where almost no mitigation had taken place in 2005, there was a 10-fold increase in the proportion of image plots with green attack from 2005 (2%) to 2006 (20%). In 2006, the benefits of the direct control tactics implemented in and around site A may be inferred from a marked reduction in the G:R (1.06:1) and a one-third reduction in the number of image plots with green attack (Table 6). In 2006, mitigation activities in and around site A increased in terms of the number of trees treated; however, not all locations or trees marked for control were mitigated. Mitigation data provided by provincial government agencies included the number of trees identified for treatment, as well as the number of trees that were actually treated. In 2006, 3271 trees at 107 sites in the area surrounding site A were identified for mitigation, but only 3179 trees at 73 of these locations were actually mitigated in that year. Given that 97% of the trees identified for mitigation (in terms of gross count) were treated although crews visited only 68% of the target locations, suggests that ground crews ended up treating more green attack trees at fewer locations than were indicated in the original survey. This suggests that the infestation may have been larger or more widespread than expected in this area. There may also be other reasons why 32% of targeted locations were not mitigated, including access, cost, weather, or a combination thereof. The implication of these unmitigated sites is that a number of locations with spot infestations in and around site A continued to support beetle populations, and this is reflected in an increase in the G:R at site A in 2008 (1.94:1) (Table 5), indicating that the population of mountain pine beetle in this area is continuing to expand. Research has demonstrated that singletree treatments are most effective when infestation intensities are low to moderate in both the area being treated and in the surrounding area, and when the treatment is applied intensively throughout a region (Nelson et al., 2006). In the area surrounding site B, aggressive control tactics were initiated in 2006 with 1666 trees being treated at 554 locations. In that year, G:R decreased to 0.32:1, from 6.33:1 in the previous year, and the proportion of image plots with green attack decreased by almost 50% (Table 6). Thus, while the number of trees mitigated in and around site B was not as numerous as in site A in 2006, the number of locations treated was more than seven times greater than the number of locations treated in and around site A. Furthermore, 100% of the locations that were identified for mitigation in and around site B in 2006 were treated. In 2007,
aggressive mitigation continued in (154 trees treated at 10 locations) and around site B (4298 trees treated at 463 locations) in 2007. The G:R at site B continued to decrease in 2008 to 0.2:1. Research has indicated the importance of accurately detecting and mitigating the greatest proportion of green attack trees possible each year (Carroll et al., 2006a; Coggins et al., 2008); however, there are many challenges to the operational detection of green attack using remotely sensed data (Wulder et al., 2009). Failure to mitigate effectively in the context of environmental conditions favourable to the expansion of mountain pine beetle will result in rapidly increasing beetle populations with concomitant negative impacts on pine forests. The number of years for which mitigation activities must be sustained depends not only on the comprehensiveness of the mitigation effort, but also on the initial severity of the infestation prior to mitigation, and the rate of population increase or R value (Carroll et al., 2006a). The greater the severity of the infestation, the R value, and the number of green attack trees that are missed during mitigation, the longer it will take to bring an infestation under control (Carroll et al., 2006a). While it is theoretically possible to detect and mitigate 100% of green attack trees in an area, the 2008 field data from site B indicates that atleast some green attack trees are likely to be missed each year (Table 4). This demonstrates the importance of sustaining mitigation efforts over time in order to ensure that any spot infestations that do appear are detected and treated in a timely fashion (Coggins et al., 2008). As Shore and Safranyik (2004) indicate, even if full mitigation is not possible, partial mitigation can have an effect on the rate of increase in mountain pine beetle populations. The methods presented herein enable the generation of retrospective G:R, which in turn may be used to assess the efficacy of mitigation efforts. Such an approach may be useful for assessing and fine-tuning ongoing monitoring and mitigation efforts, or as a means to evaluate a large-scale mitigation strategy and suggest improvements that can be implemented to address future infestations. Given the costs of mitigation, such assessments are valuable, but are rarely undertaken, and are even more rarely reported in the literature (Coops et al., 2008). 5. Conclusions In this research, we have demonstrated an approach for monitoring the impact of mountain pine beetle mitigation efforts using multi-temporal high spatial resolution aerial imagery and field surveys to estimate retrospective G:R. The monitoring system was applied at two sites located at the leading edge of a mountain pine beetle epidemic in western Canada. Although these two sites have similar climatic, topographic, and forest cover conditions, they differ in the initial severity of their beetle infestations and in the timing, magnitude, and extent of direct control mitigation efforts that have been applied therein. Changes in mountain pine beetle populations, as measured by annual G:R at both sites, allowed us to make inferences concerning the effectiveness of documented mitigation efforts. The approach demonstrated in this study is sample-based, incorporating both field and image accounts of mountain pine beetle damage, and is therefore suitable for assessing the efficacy of mountain pine beetle mitigation programs over large areas, where the cost of exclusively using ground surveys may be prohibitive. Knowledge gained from efficacy assessments can then be used to inform ongoing mitigation efforts, as well as future management scenarios. Acknowledgments This project was funded by the Government of Canada through the Mountain Pine Beetle Program administered by Natural
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Resources Canada, Canadian Forest Service (for more information see http://mpb.cfs.nrcan.gc.ca/). References Amman, G.D., Cole, W.E., 1983. Mountain pine beetle population dynamics in lodgepole pine forests. Part II: population dynamics. USDA Forest Service Intermountain Forest and Range Experiment Station, Ogden, Utah. General Technical Report INT-145, 19 pp. Aukema, B.H., Carroll, A.L., Zheng, Y., Zhu, J., Raffa, K.F., Moore, D., Stahl, K., Taylor, S.W., 2008. Movement of outbreak populations of mountain pine beetle: influences of spatiotemporal patterns and climate. Ecography 31, 348–358. British Columbia Ministry of Forests and Range, 2002. Forest health information management. Ministry of Forests and Range, Forest Practices Branch. Available online: (accessed 18.02.09.). British Columbia Ministry of Forests, 1995. Bark Beetle Management Guidebook. Forest Practices Code, Forest Practices Branch, Victoria, British Columbia. 45 pp. British Columbia Ministry of Forests and Canadian Forest Service, 2000. Forest health aerial overview survey standards for British Columbia: The B.C. Ministry of Forests adaptation of the Canadian Forest Service’s FHN Report 97-1 ‘‘Overview Aerial Survey Standards for British Columbia and the Yukon’’. Version 2.0, Forest Practices Branch, BC Ministry of Forests, Victoria, British Columbia. 46 pp. Carroll, A.L., Taylor, S.W., Re´ginie`re, J., Safranyik, L., 2004. Effects of climate change on range expansion by the mountain pine beetle in British Columbia. In: Shore, T.L., Brooks, J.E., Stone, J.E. (Eds.), Proceedings of the Mountain Pine Beetle Symposium: Challenges and Solutions. October 30–31, 2003, Kelowna, British Columbia. Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Information Report BC-X-399, Victoria, British Columbia, pp. 298, pp. 223–232. Carroll, A.L., Shore, T.L., Safranyik, L., 2006a. Direct control: theory and practice. In: Safranyik, L., Wilson, B. (Eds.), The Mountain Pine Beetle. A Synthesis of Biology, Management, and Impacts on Lodgepole Pine. Natural Resources Canada. Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia, pp. 304, pp. 155–172. Carroll, A.L., Re´ginie`re, J., Logan, J.A., Taylor, S.W., Bentz, B.J., Powell, J.A., 2006b. Impacts of climate change on range expansion by the mountain pine beetle. Mountain Pine Beetle Initiative Working Paper 2006-14. Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia. 20 pp. Coggins, S.B., Wulder, M.A., Coops, N.C., White, J.C., 2008. Linking survey detection accuracy with ability to mitigate populations of mountain pine beetle. The Forestry Chronicle 84, 900–909. Coops, N.C., Timko, J.A., Wulder, M.A., White, J.C., Ortlepp, S.M., 2008. Investigating the effectiveness of mountain pine beetle mitigation strategies. International Journal of Pest Management 54, 151–165. Ecological Stratification Working Group, 1996. A national ecological framework for Canada. Agriculture and Agri-Food Canada, Research Branch, Centre for Land and Biological Resources Research, and Environment Canada, State of the Environment Directorate, Ottawa/Hull. 125 pp. Available online:
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Raffa, K.F., Aukema, B.H., Bentz, B.J., Carroll, A.L., Hicke, J.A., Turner, M.G., Romme, W.H., 2008. Cross-scale drivers of natural disturbances prone to anthropogenic amplification: the dynamics of bark beetle eruptions. BioScience 58, 501–517. Re´ginie`re, J., Bentz, B., 2007. Modeling cold tolerance in the mountain pine beetle, Dendroctonus ponderosae. Journal of Insect Physiology 53, 559–571. Safranyik, L., 1978. Effect of climate and weather on mountain pine beetle populations. In: Kibbee, D.L., Berryman, A.A., Amman, G.D., Stark, R.W. (Eds.), Symposium Proceedings: Theory and Practice of Mountain Pine Beetle Management in Lodgepole Pine Forests. April 25–27, Washington State University, Pullman, Washington. Forest, Wildlife and Range Experimentation Station, University of Idaho, Moscow, Idaho, pp. 224, pp. 77–86. Safranyik, L., Carroll, A.L., 2006. The biology and epidemiology of the mountain pine beetle in lodgepole pine forests. In: Safranyik, L., Wilson, B. (Eds.), The Mountain Pine Beetle. A Synthesis of Biology, Management, and Impacts on Lodgepole Pine. Natural Resources Canada. Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia, pp. 304, pp. 3–66. Sandvoss, M., McClymont, B., Farnden, C., 2005. A user’s guide to the vegetation resources inventory. Timberline Forest Inventory Consultants, Prince George, British Columbia. 90 pp. Available online:
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Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco
Monitoring the impacts of mountain pine beetle mitigation Michael A. Wulder a,*, Stephanie M. Ortlepp a, Joanne C. White a, Nicholas C. Coops b, Sam B. Coggins b a b
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, British Columbia, V8Z 1M5, Canada Department of Forest Resources Management, 2424 Main Mall. University of British Columbia, Vancouver, V6T 1Z4, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Received 2 April 2009 Received in revised form 29 May 2009 Accepted 8 June 2009
Since 1999, the mountain pine beetle (Dendroctonus ponderosae Hopk. [Coleoptera: Scolytidae]) has impacted over 13 million hectares of pine forests in western Canada. Successful mitigation of the beetle depends on the accurate and timely identification of currently infested trees and on sustained control activities over several successive years. We monitored the success of mitigation activities in reducing damage caused by mountain pine beetle at two sites (A and B) on the leading edge of the current beetle epidemic in western Canada. Using three years of digital high spatial resolution aerial imagery (2006– 2008) and one season of field measurements (2008), we estimated retrospective ratios of trees attacked by beetle in the current year (green attack) to trees attacked in the previous year (red attack), hereafter referred to as G:R. Our results indicate that mitigation activities slowed the rate of population growth, with G:R found to be decreasing or stable over sites A and B while mitigation was ongoing in 2005 and 2006 (site A 1.06:1; site B 0.32:1). When mitigation was discontinued over site A in 2007, the G:R increased markedly (1.94:1), while continued mitigation at site B in 2007 further reduced the G:R (0.22:1). Despite the cost associated with mitigation, its efficacy is rarely assessed and even more rarely documented. The approach presented herein enables a sample-based appraisal of mitigation efforts. Crown Copyright ß 2009 Published by Elsevier B.V. All rights reserved.
Keywords: Insect Mitigation Forest Management Planning Digital imagery Remote sensing Mountain pine beetle
1. Introduction Since 1999, the population of mountain pine beetle (Dendroctonus ponderosae Hopk. [Coleoptera: Scolytidae]) has grown to an epidemic level in western Canada, expanding into areas previously thought to be outside the mountain pine beetle’s geographical range (Westfall and Ebata, 2008). Endemic to British Columbia, the preferred host of the beetle is lodgepole pine (Pinus contorta Dougl. Ex. Loud var. latifolia Engelm.); however, any species of pine is at risk of attack (Furniss and Schenk, 1969). Factors contributing to the current epidemic include alterations to established climatic limitations to mountain pine beetle survival (Re´ginie`re and Bentz, 2007; Aukema et al., 2008; Raffa et al., 2008) and an abundance of suitable hosts resulting from almost one hundred years of successful fire suppression (Taylor and Carroll, 2004). By 2008, mountain pine beetle had impacted more than 13 million hectares of pine forest in western Canada (Raffa et al., 2008). The total cumulative volume losses associated with the current epidemic in British Columbia are estimated at 620 million m3, representing 46% of the total merchantable pine volume on British Columbia’s timber harvesting land base (Walton et al., 2008). The magnitude of the current mountain pine beetle
* Corresponding author. Tel.: +250 363 6090; fax: +250 363 0775. E-mail address: [email protected] (M.A. Wulder).
epidemic has converted the forest in the impacted area from a small net carbon sink to a large net carbon source (Kurz et al., 2008). Concern is now focussed on the possibility of further range expansion by the beetle into the pine forests of Canada’s boreal region (Westfall, 2006; Raffa et al., 2008). 1.1. Background 1.1.1. Mitigation of mountain pine beetle Options for controlling the mountain pine beetle populations are limited: with the exception of a characteristically short twoweek flight period (4 to 6 weeks in cool weather) that normally occurs mid-summer, the entire year-long lifecycle (for univoltine populations) of the mountain pine beetle is spent under the bark of the host tree (Safranyik and Carroll, 2006). Mature adult beetles emerge and disperse from their parental hosts in late July to early August in search of a new host for colonization, oviposition, reproduction, and completion of their lifecycle (Amman and Cole, 1983). Once a host is successfully attacked, the beetles will construct galleries in the living phloem under the bark and lay their eggs. After one week, the eggs typically will hatch and the larvae will begin to feed on the phloem, remaining under the bark for the duration of the winter, and emerging as adults the following year (Amman and Cole, 1983). Mitigation of mountain pine beetle is either through direct or indirect control. Indirect control is preventative management that
0378-1127/$ – see front matter . Crown Copyright ß 2009 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2009.06.008
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seeks to limit the number of susceptible host trees on the landscape (Carroll et al., 2006a), and includes silvicultural treatments such as: prescribed burning, stand thinning, or alteration of the age class distribution or species mix within a stand (Whitehead et al., 2004; Fettig et al., 2007). Direct control attempts to limit a mountain pine beetle population’s rate of increase, and preferably, return the population to an endemic state. Direct control programs generally target green attack trees, with the objective of destroying the host tree before the beetles contained therein have the opportunity to emerge and disperse. Infested trees in the red attack stage are detected during annual airborne forest health surveys conducted throughout the province and green attack trees are then detected by way of their spatial association with these surveyed red attack trees (Mitchell and Preisler, 1991; Wulder et al., 2009). Since emergence typically occurs in late July to mid-August, mitigation of green attack trees should be planned for winter and spring, and subsequent ground surveys to assess population levels would then be conducted in late summer or early fall. Various methods of direct control have been implemented, either as single tree treatments (e.g., felling and burning, felling and bark removal, standing bark removal, monosodium methane arsenate injections, and single tree harvest), or as stand level treatments (e.g., harvest, prescribed burn) (Maclauchlan and Brooks, 1998; Carroll et al., 2006a; Coops et al., 2008). Single tree treatments are costly and time consuming because they require extensive ground surveys to accurately identify green attack trees, and therefore are best implemented when populations of mountain pine beetle are small (Whitehead et al., 2004; Trzcinski and Reid, 2008). Carroll et al. (2006a) identified three criteria for successful direct control of mountain pine beetle populations: early detection of infestations, aggressive direct control, and continuation of direct control until the desired population level is reached. It is the latter, the sustained maintenance of mitigation over successive years, that is most critical (Coggins et al., 2008), since it is unlikely that ground surveys will successfully identify all green attack trees in any given year. 1.1.2. Green attack to red attack ratio The ratio of green attack to red attack trees (G:R) is used to indicate a general trend in a mountain pine beetle infestation in a given area (i.e., is the infestation increasing or decreasing?). The G:R is an assessment of the manifestation of a mountain pine beetle infestation, enabling an evaluation of the actual damage caused by the beetle. As such, it serves as a proxy for estimating changes in the size of the beetle population and is one of the indicators used to determine strategies for forest management units in British Columbia (e.g., suppression, salvage, monitoring) (British Columbia Ministry of Forests, 1995). A ratio less than one is indicative of a declining population; a ratio greater than one is indicative of an increasing population (Wulder et al., 2006). It should be noted that while the G:R is useful for indicating general trends in an infestation, it does not provide a direct measure of the beetle population in a given area, nor does it indicate how well these invading beetles have survived and reproduced. The latter is typically determined by late spring assessments of brood production in relation to stand density and overwintering mortality. These assessments result in the estimation of an R value, which is an estimate of the rate of beetle population increase and an important indicator of the potential threat of a mountain pine beetle population in an area (Carroll et al., 2006a). According to calculations made by the British Columbia Ministry of Forests and Range (2002), the theoretical maximum G:R, derived from the maximum beetle reproductive rate, is approximately 10:1. Since this theoretical maximum does not take
into account mortality factors, maximum field measurements of G:R have rarely exceeded 5:1, and more commonly in British Columbia, G:R do not exceed 2:1 in northern areas, and 4:1 in southern areas (British Columbia Ministry of Forests and Range, 2002). Trzcinski and Reid (2009) estimated the maximum rate of increase based on 10-year historical data in the Kootenay National Park to be 3:1 with a 95% confidence interval of 1.4:1–7.1:1. It is posited that larger G:R are influenced by immigration of beetles from other areas. Wulder et al. (2008) generated retrospective G:R using a time series of QuickBird multi-spectral and panchromatic high spatial resolution imagery acquired in consecutive years by backcasting the current year’s red attack damaged trees as the previous year’s green attack. Their results show that image-based G:R closely match G:R derived from field surveys. The ongoing collection and interpretation of similar imagery would facilitate the estimation of annual G:R ratios, thereby providing ongoing information about trends in mountain pine beetle populations. 1.1.3. Goals and objectives The goal of this research is to develop and present an approach for assessing the effectiveness of sustained mitigation on an expanding mountain pine beetle population located on the leading edge of the current beetle epidemic in western Canada. The objectives were to use a combination of field measures and high spatial resolution aerial imagery to generate annual G:R for the study sites, and then compare these annual G:R to information on the location and timing of mitigation activities in the study sites and in areas immediately surrounding the study sites. 2. Methods 2.1. Study site The study area is located in the Boreal Plains ecozone (Ecological Stratification Working Group, 1996) and within the rain shadow of the Rocky Mountains to the west, resulting in average annual precipitation of only 400 mm. Elevation in the area ranges from 719 to 2302 m, with an average elevation of 1257 m (S.D. 249 m). The forests in the study area are dominated by lodgepole pine, but also include alpine fir (Abies lasiocarpa (Hook) Nutt), Engelmann spruce (Picea engelmannii Parry ex Engelm.), white spruce (Picea glauca (Moench) Voss), black spruce (Picea mariana (Mill) BSP), jack pine (Pinus banksiana Lamb.), and tamarack (Larix laricina (Du ROI) K. Koch) (Lands Directorate, 1986). Prior to 2003, the study area had no previous recorded history of mountain pine beetle infestation (Westfall, 2004). It is posited that the infestation originated as a result of one large dispersal of beetles from a heavily infested area of pine forest east of Prince George, British Columbia, in 2002 (Westfall, 2005; Safranyik and Carroll, 2006). Previously, the Rocky Mountains in this northern area were considered an insurmountable topographic barrier to beetle expansion. Subsequent research has confirmed the plausibility of such long range dispersal by mountain pine beetle (Jackson et al., 2008). Notions of climate change related expansion in mountain pine beetle range have also been suggested for this region (Carroll et al., 2004). Mitigation commenced in this area in 2004. By 2005, the majority of mountain pine beetle control efforts in western Canada were focussed in this area in an attempt to prevent the beetle from spreading across Canada (Westfall, 2006). The two sample sites that were selected (A and B) were both predominantly pine stands with similar climatic and topographic conditions (Table 1). These climatic and topographic factors are known to influence the susceptibility and subsequent potential of a forest stand to support populations of mountain pine beetle (Shore and Safranyik, 1992; Carroll et al., 2004; Carroll et al., 2006b;
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Table 1 Summary of topographic and climatic characteristics of sites A and B. Elevation (m)
Site A Site B
Annual degree days >5 8C
Min. January temp. (8C)
Mean August temp. (8C)
Min
Max
Mean
Min
Max
Mean
Min
Max
Mean
Min
Max
Mean
1034 1006
1557 1321
1323 1201
790 920
1113 1104
951 1019
13.3 13.7
12.8 13.0
13.0 13.3
11.5 12.3
13.6 13.4
12.5 12.9
Aukema et al., 2008). The sites are located approximately 54 km apart; located near the border between British Columbia and Alberta and the communities of Tumbler Ridge and Grande Prairie (Fig. 1). The western site (A) has an area of 24 km2 and the eastern site (B) has an area of 30 km2. Despite their climate similarities the two sites have been subject to different levels of mitigation (Table 2): site A is located in an area that was mitigated in 2005, followed by a marked reduction in mitigation effort in 2006, and no mitigation in 2007, whereas site B was not mitigated in 2005 and received increasing mitigation focus in 2006 and 2007. 2.2. Data 2.2.1. High spatial resolution imagery Digital high spatial resolution colour aerial imagery were acquired from a fixed-wing aircraft with a Canon EOS-1Ds Mark II camera. The camera features a metal-oxide-semiconductor (CMOS) sensor that results in imagery with an effective resolution of 16.7 megapixels. Image geo-referencing was supported by an onboard global positioning system (GPS) coupled with an inertial navigation system (INS). The imagery was captured over three spectral ranges which approximate to: 0.4–0.5 mm (blue), 0.5– 0.6 mm (green), and 0.6–0.7 mm (red). In mid-August 2006 and mid-September 2007, images were acquired for both sites (A and B) at a 10 cm spatial resolution; in mid-July 2008, images were acquired at a 20 cm spatial resolution at both sites. The images were provided as mosaiced, registered products by the vendor, (a high-spatial resolution satellite orthorectified image was used as a
base for registration with an estimated horizontal error of <5 m). The 2006 and 2007 images were resampled to 20 cm to facilitate image-to-image registration to the 2008 image. 2.2.2. Field surveys At the end of August 2008, field surveys were conducted at nine plots in site A and 11 plots in site B to supplement the image data and facilitate estimation of 2008 G:R. Field plots were circular with a 30 m radius. At each plot the geographic centre was recorded using a GPS which was differentially corrected post-collection to an estimated accuracy of 2.2 m. The species and stem diameter (diameter at 1.3 m up the stem) for each tree in the plot was measured and crown area (m2) measurements recorded for atleast two dominant trees in the plot. Finally, mountain pine beetle attack status of each tree was assessed according to a four category classification system where 0 is healthy, 1 is green attack, 2 is red attack, and 3 is grey attack (Coggins et al., 2008). 2.2.3. Mitigation Information on mitigation activities in the area was compiled from provincial government agencies into a GIS database, which identified the location, year, type and (if available) number of trees mitigated. In order to examine the context of mitigation activities surrounding each of the study sites, site-specific mitigation data were augmented with information on all mitigation activities within a 20 km buffer surrounding each of the study sites (Table 2). Both single tree and stand level direct control treatments were applied.
Fig. 1. Study area on the Alberta and British Columbia border in western Canada, including the location of sites A and B.
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Table 2 Annual summary of single tree and stand level direct control mitigation activities located within sites A and B, and located within a 20 km area surrounding sites A and B. 2005 Site Site Site Site
A A 20 km buffer B B 20 km buffer
1 tree mitigated at 1 location 1673 trees mitigated at 330 locations No control activities 1 tree mitigated at 1 location
2006
2007 2
1 tree mitigated at 1 location; 0.6 km harvested 3179 trees mitigated at 73 locations; 21.4 km2 harvested 11 trees mitigated at 1 location 1666 trees mitigated at 554 locations
2.2.4. Forest inventory Forest inventory data (Sandvoss et al., 2005) were used to mask out areas of non-pine forest and non-forest in sites A and B. The mask was used to exclude these areas from selection of sample plots and subsequent analysis as per Skakun et al. (2003). Based on the provincial forest inventory datasets, the average proportion of pine in a stand was 65% in site A and 58% in site B–confirming the general similarity of the sites with respect to species and local environment. 2.3. Methods 2.3.1. Selection of image sample plots To facilitate calculation of G:R, a simple random sample of 1 ha circular image plots were selected from sites A and B. Plots centers were randomly located within the areas of pine forest identified from the forest inventory. To enable identification of red attack with a confidence level of 98% and a 10% allowable error around the mean, we estimated the required number of image sample plots using Eq. (1) (Ko¨hl et al., 2006, p. 87):
n¼
2 tn;1 a=2 VarðYÞ
E2
(1)
No control activities No control activities 154 trees mitigated at 10 locations 4298 trees mitigated at 463 locations
where n is the number of 1 ha plots required to achieve the desired confidence level given by the t value (two tailed, n 1 degrees of freedom), Var(Y) is the approximate variance of the population, and E is the percent allowable error of the mean. The variance of the population is estimated with Eq. (2) (Ko¨hl et al., 2006): VarðYÞ ffi
2 maxðyi Þ minðyi Þ 4
(2)
where the max(yi) and min(yi) are the maximum and minimum number of red attack trees per hectare. The minimum number of red attack trees per hectare is zero, while the maximum number of red attack trees per hectare was estimated from a pilot study (using the 2008 imagery for site A) as being 155 trees per hectare. Based on these equations and our desired confidence level and allowable error around the mean, the variance was estimated at 1501 trees and the required sample size was 82. The 82 image sample plots were distributed between the two sites proportional to area, resulting in 37 image plots in site A and 45 image plots in site B. 2.3.2. Image interpretation For each of the 82 image sample plots, a count of all visible conifer tree crowns in the 2008 imagery was made to estimate the
Fig. 2. Example of a 1 ha image plot. All crowns in the plot were delineated and the number of red attack crowns were enumerated for each year.
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Table 3 Characteristics of image plots and interpretation results for red attack crowns.
Site A Site B
Number of 1 ha image plots
Mean stand density (trees/ha)
Mean % pine
37 45
678 951
65 59
stand density in stems per hectare. The number of red attack crowns in each plot in the 2006, 2007, and 2008 imagery was recorded. For each year of imagery, a count of the red attack crowns was made, as shown in the example in Fig. 2. 2.3.3. Estimation of G:R Red attack in 2007 and 2008 was back cast as green attack in 2006 and 2007, thereby enabling the estimation of G:R for 2006 and 2007. For the calculation of the 2008 G:R, the number of green attack and red attack crowns identified in the field surveys were used, as 2009 imagery would have been necessary to similarly back cast 2009 red attack as 2008 green attack. In order to verify that the red attack crowns identified in the field plots in 2008 were attacked in 2007 and not earlier, the crowns were located on the 2007 imagery and confirmed to appear visually green in that year. 3. Results Mitigation activities within sites A and B and within the greater study site areas are summarized in Table 2. Mitigation was initiated in the area surrounding site A in 2005, with 1673 trees mitigated at 330 locations. In the area surrounding site A, twice as many trees were treated in 2006 as 2005, but at less than 25% of the locations treated in 2005. Stand level treatments were also undertaken in the area surrounding site A in 2006, with approximately 21 km2 harvested. Although there was mitigation in the area surrounding site A, there was little mitigation effort directly located within site A. As indicated in Table 2, the mitigation activities at site B were different than those at site A in terms of both timing and extent. Only single tree treatments were applied at site B; site A had both single tree and patch treatments. Overall, more trees were treated in site B than in site A, but mitigation activities were started earlier in site A. In 2007, 154 trees were mitigated at 10 different locations within site B. Finally, extensive single tree treatments were undertaken in the area surrounding site B in 2007 (4298 trees at 463 locations), while no mitigation was undertaken in site A in 2007. The general stand characteristics and number of red attack crowns interpreted in each of the 82 image plots are summarized
Mean elevation (m)
Number of red attack crowns 2006
2007
2008
1326 1195
28 3
171 19
182 6
in Table 3, while the characteristics of the 2008 field plots are summarized in Table 4. In addition to assessing the attack status of trees in the field plots in 2008, we also collected data on mitigation activities at site B (there were no mitigation activities at the field plots in site A in 2008). By counting the number of stumps remaining in the 30 m field plots we could determine how many trees were treated in 2008 (Table 4). Although field data indicated that 49 trees were treated in the field plots in site B in 2008, two additional unmitigated green attack trees were found, indicating that the mitigation had missed approximately 4% of the green attack in the 11 sub-plots that were field sampled in 2008. In 2006, the G:R for sites A and B were similar at 6.11:1 and 6.33:1, respectively (Table 5), with approximately 60% of image plots at site A and 20% of image plots at site B containing green attack trees (Table 6). In 2007, the G:R at both sites dropped markedly, with the G:R for site A at 1.06:1 and the G:R for site B at 0.32:1. In this year, the percentage of image plots with green attack was 38% at site A and 11% at site B. The 2008 field data indicate that the G:R ratio at site A increased to 1.94:1, while the G:R at site B continued to decrease and was 0.20:1 in 2008. 4. Discussion There are many factors which can influence the rate of increase in mountain pine beetle populations. Sites A and B were selected for their similarity in elevation, climate, topography, and infestation initiation dates. In terms of climatic factors, the two sites are similar, with site B located at a slightly lower mean elevation (100 m lower), and having a slightly higher degree day accumulation (>5 8C). The rate of mountain pine beetle population expansion has been found to be positively correlated with lower elevations and higher degree day accumulations (Safranyik, 1978), therefore it would be expected that these two sites would have similar susceptibility to attack by mountain pine beetle. The severity of mountain pine beetle infestations are typically classified according to the proportion of trees that are attacked in a given area (British Columbia Ministry of Forests and Canadian Forest Service, 2000), and Table 3 indicates that site A had a more severe infestation than site B, with a greater number of total trees
Table 4 Characteristics of 2008 field plots.
Site A Site B a
Number of plots (30 m radius)
Mean stand density (trees/ha)
Mean % pine
Mean elevation (m)
Total number of green attack treesa
Total number of red attack treesa
Total number of mitigated trees
9 11
721 883
68 88
1335 1243
31 2
16 10
0 49
Based on sample size (n = 20) and a confidence level of 95%, the confidence interval 4.36 trees.
Table 5 Estimation of G:R for sites A and B. Estimates of green and red attack trees 2006
Site A Site B a
Estimated G:R 2008a
2007
2006
2007
20081
Green
Red
Green
Red
Green
Red
G:R
G:R
G:R
171 19
28 3
182 19
171 6
31 2
16 10
6.11:1 6.33:1
1.06:1 0.32:1
1.94:1 0.20:1
Estimated from field measurements.
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1186 Table 6 Proportion of image plots with green attack.
Proportion of image plots with green attack
Site A Site B a
2005a
2006
2007
27.03 2.22
60 20
38 11
Back cast from red attack crowns interpreted from the following year’s imagery.
attacked in 2007 and 2008. Although the severity of the infestation may have initially been greater at site A, the marked increase in the number of trees treated at site B in 2006 and 2007 (Table 2) is indicative of the increasing severity of the infestation at this location. From 2005 to 2006 there was an increase in the proportion of image plots with green attack at both sites A and B (Table 6). In 2006, the G:R in sites A and B were similar, indicating that mountain pine beetle populations at both sites were increasing at similar rates. In 2005, extensive direct control activities had been initiated in the area surrounding site A. Notwithstanding these aggressive control efforts, the proportion of image plots with green attack in site A more than doubled in 2006, increasing from 27% of image plots in 2005 to 60% in 2006. However, at site B, where almost no mitigation had taken place in 2005, there was a 10-fold increase in the proportion of image plots with green attack from 2005 (2%) to 2006 (20%). In 2006, the benefits of the direct control tactics implemented in and around site A may be inferred from a marked reduction in the G:R (1.06:1) and a one-third reduction in the number of image plots with green attack (Table 6). In 2006, mitigation activities in and around site A increased in terms of the number of trees treated; however, not all locations or trees marked for control were mitigated. Mitigation data provided by provincial government agencies included the number of trees identified for treatment, as well as the number of trees that were actually treated. In 2006, 3271 trees at 107 sites in the area surrounding site A were identified for mitigation, but only 3179 trees at 73 of these locations were actually mitigated in that year. Given that 97% of the trees identified for mitigation (in terms of gross count) were treated although crews visited only 68% of the target locations, suggests that ground crews ended up treating more green attack trees at fewer locations than were indicated in the original survey. This suggests that the infestation may have been larger or more widespread than expected in this area. There may also be other reasons why 32% of targeted locations were not mitigated, including access, cost, weather, or a combination thereof. The implication of these unmitigated sites is that a number of locations with spot infestations in and around site A continued to support beetle populations, and this is reflected in an increase in the G:R at site A in 2008 (1.94:1) (Table 5), indicating that the population of mountain pine beetle in this area is continuing to expand. Research has demonstrated that singletree treatments are most effective when infestation intensities are low to moderate in both the area being treated and in the surrounding area, and when the treatment is applied intensively throughout a region (Nelson et al., 2006). In the area surrounding site B, aggressive control tactics were initiated in 2006 with 1666 trees being treated at 554 locations. In that year, G:R decreased to 0.32:1, from 6.33:1 in the previous year, and the proportion of image plots with green attack decreased by almost 50% (Table 6). Thus, while the number of trees mitigated in and around site B was not as numerous as in site A in 2006, the number of locations treated was more than seven times greater than the number of locations treated in and around site A. Furthermore, 100% of the locations that were identified for mitigation in and around site B in 2006 were treated. In 2007,
aggressive mitigation continued in (154 trees treated at 10 locations) and around site B (4298 trees treated at 463 locations) in 2007. The G:R at site B continued to decrease in 2008 to 0.2:1. Research has indicated the importance of accurately detecting and mitigating the greatest proportion of green attack trees possible each year (Carroll et al., 2006a; Coggins et al., 2008); however, there are many challenges to the operational detection of green attack using remotely sensed data (Wulder et al., 2009). Failure to mitigate effectively in the context of environmental conditions favourable to the expansion of mountain pine beetle will result in rapidly increasing beetle populations with concomitant negative impacts on pine forests. The number of years for which mitigation activities must be sustained depends not only on the comprehensiveness of the mitigation effort, but also on the initial severity of the infestation prior to mitigation, and the rate of population increase or R value (Carroll et al., 2006a). The greater the severity of the infestation, the R value, and the number of green attack trees that are missed during mitigation, the longer it will take to bring an infestation under control (Carroll et al., 2006a). While it is theoretically possible to detect and mitigate 100% of green attack trees in an area, the 2008 field data from site B indicates that atleast some green attack trees are likely to be missed each year (Table 4). This demonstrates the importance of sustaining mitigation efforts over time in order to ensure that any spot infestations that do appear are detected and treated in a timely fashion (Coggins et al., 2008). As Shore and Safranyik (2004) indicate, even if full mitigation is not possible, partial mitigation can have an effect on the rate of increase in mountain pine beetle populations. The methods presented herein enable the generation of retrospective G:R, which in turn may be used to assess the efficacy of mitigation efforts. Such an approach may be useful for assessing and fine-tuning ongoing monitoring and mitigation efforts, or as a means to evaluate a large-scale mitigation strategy and suggest improvements that can be implemented to address future infestations. Given the costs of mitigation, such assessments are valuable, but are rarely undertaken, and are even more rarely reported in the literature (Coops et al., 2008). 5. Conclusions In this research, we have demonstrated an approach for monitoring the impact of mountain pine beetle mitigation efforts using multi-temporal high spatial resolution aerial imagery and field surveys to estimate retrospective G:R. The monitoring system was applied at two sites located at the leading edge of a mountain pine beetle epidemic in western Canada. Although these two sites have similar climatic, topographic, and forest cover conditions, they differ in the initial severity of their beetle infestations and in the timing, magnitude, and extent of direct control mitigation efforts that have been applied therein. Changes in mountain pine beetle populations, as measured by annual G:R at both sites, allowed us to make inferences concerning the effectiveness of documented mitigation efforts. The approach demonstrated in this study is sample-based, incorporating both field and image accounts of mountain pine beetle damage, and is therefore suitable for assessing the efficacy of mountain pine beetle mitigation programs over large areas, where the cost of exclusively using ground surveys may be prohibitive. Knowledge gained from efficacy assessments can then be used to inform ongoing mitigation efforts, as well as future management scenarios. Acknowledgments This project was funded by the Government of Canada through the Mountain Pine Beetle Program administered by Natural
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