Defoliation Maps Research Articles

Derivation of Pheromone-Based Larval Thresholds in Spruce Budworm Accounting for Distance to Defoliated Forest Stands

Spruce budworm, Choristoneura fumiferana Clem. (Lepidoptera: Tortricidae), is the most severe defoliator of Pinaceae in Nearctic boreal forests. Three tools widely used to guide large-scale management decisions (year-to-year defoliation maps; density of overwintering second instars [L2]; number of males at pheromone traps) were integrated to derive pheromone-based thresholds corresponding to specific intergenerational transitions in larval densities (L2i → L2i+1), taking into account the novel finding that threshold estimates decline with distance to defoliated forest stands (DIST). Estimates of thresholds were highly variable between years, both numerically and in terms of interactive effects of L2i and DIST, which limit their heuristic value. In the context of early intervention strategy (L2i+1 > 6.5 individuals per branch), however, thresholds fluctuated within relatively narrow intervals across wide ranges of L2i and DIST, and values of 40-200 males per trap may thus be used as general guideline.

Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR

The mapping of changes in the distribution of insect-caused forest damage remains an important forest monitoring application and challenge. Efficient and accurate methods are required for mapping and monitoring changes in insect defoliation to inform forest management and reporting activities. In this research, we develop and evaluate a LiDAR-driven (Light Detection And Ranging) approach for mapping defoliation caused by the Common pine sawfly (Diprion pini L.). Our method requires plot-level training data and airborne scanning LiDAR data. The approach is predicated on a forest canopy mask created by detecting forest canopy cover using LiDAR. The LiDAR returns that are reflected from the canopy (that is, returns > half of maximum plot tree height) are used in the prediction of the defoliation. Predictions of defoliation are made at plot-level, which enables a direct integration of the method to operational forest management planning while also providing additional value-added from inventory-focused LiDAR datasets. In addition to the method development, we evaluated the prediction accuracy and investigated the required pulse density for operational LiDAR-based mapping of defoliation. Our method proved to be suitable for the mapping of defoliated stands, resulting in an overall mapping accuracy of 84.3% and a Cohen’s kappa coefficient of 0.68.

Ecosystem Impacts of a Range Expanding Forest Defoliator at the Forest-Tundra Ecotone

Insect outbreaks in northern-boreal forests are expected to intensify owing to climate warming, but our understanding of direct and cascading impacts of insect outbreaks on forest ecosystem functioning is deficient. The duration and severity of outbreaks by geometrid moths in northern Fennoscandian mountain birch forests have been shown to be accentuated by a recent climate-mediated range expansion, in particular of winter moth (Operophtera brumata). Here, we assess the effect of moth outbreak severity, quantified from satellite-based defoliation maps, on the state of understory vegetation and the abundance of key vertebrate herbivores in mountain birch forest in northern Norway. We show that the most recent moth outbreak caused a regional-scale state change to the understory vegetation, mainly due to a shift in dominance from the allelopathic and unpalatable dwarf-shrub Empetrum nigrum to the productive and palatable grass Avenella flexuosa. Both these central understory plant species responded significantly and nonlinearly to increasing outbreak severity. We further provide evidence that the effects of the outbreak on understory vegetation cascaded to cause strong but opposite impacts on the abundance of the two most common herbivore groups. Rodents increased with defoliation, largely mirroring the increase in A. flexuosa, whereas ungulate abundance instead showed a decreasing trend. Our analyses also suggest that the response of understory vegetation to defoliation may depend on the initial state of the forest, with poorer forest types potentially allowing stronger responses to defoliation.

A general Landsat model to predict canopy defoliation in broadleaf deciduous forests

Defoliation by insect herbivores can be a persistent disturbance affecting ecosystem functioning. We developed an approach to map canopy defoliation due to gypsy moth based on site differences in Landsat vegetation index values between non-defoliation and defoliation dates. Using field data from two study areas in the U.S. central Appalachians and five different years (2000, 2001, 2006, 2007, and 2008), we fit a sigmoidal model predicting defoliation as a function of the difference in the vegetation index. We found that the normalized difference infrared index (NDII, [Band 4−Band 5]/[Band 4+Band 5]) and the moisture stress index (Band 5/Band 4) worked better than visible-near infrared indices such as NDVI for mapping defoliation. We report a global 2-term fixed-effects model using all years that was at least as good as a mixed-effects model that varied the model coefficients by year. The final model was: proportion of foliage retained=1/(1+exp(3.057−31.483∗[NDIIbaseyear−NDIIdisturbanceyear]). Cross-validation by dropping each year of data and subsequently refitting the remaining data generated an RMS error estimate of 14.9% defoliation, a mean absolute error of 10.8% and a cross-validation R2 of 0.805. The results show that a robust, general model of percent defoliation can be developed to make continuous rather than categorical maps of defoliation across years and study sites based on field data collected using different sampling methods.

Mapping insect defoliation in Scots pine with MODIS time-series data

Insect damage is a general problem that disturbs the growth of forests, causing economic losses and affecting carbon sequestration. Coarse-resolution data from satellites are potentially useful for national and regional mapping of forest damage, but the accuracy of these methods has not been fully examined. In this study, a method was tested for the mapping of defoliation in Scots pine [ Pinus silvestris] forests in southeast Norway caused by the pine sawfly [ Neodiprion sertifer], with the use of multi-temporal MODIS 16-day composite vegetation index data and the TIMESAT processing method. The damage mapping method used differences in summer mean values and angles of the seasonal profiles, indicating decreasing foliage density, to identify pixels that represent areas containing forest damage. In addition to 16-day NDVI the Wide Dynamic Range Vegetation Index (WDRVI) was tested. Damage areas were identified by classifying data into pixels representing damaged versus undamaged forest areas using a boolean combination of thresholded parameters. Classification results were evaluated against the change in LAI estimated from airplane LIDAR measurements, as an indicator of defoliation. The damage classifications detected 71% to 82% of the pixels with damage, and had kappa coefficients varying between 0.48 and 0.63, indicating some overestimation. This was due e.g. to failure to include clear-cut areas in the evaluation data. Damage classification with WDRVI only resulted in slight improvement compared to the NDVI. Only weak relationships were found between the LIDAR-estimated defoliation and the change parameters obtained from MODIS. Consequently, mapping of the degree of defoliation from MODIS was abandoned. In conclusion, the damage detection method based on MODIS data was found to be useful for locating insect damage, but not for estimating its intensity. Control of the detected damage areas using high-resolution remote sensing data, aerial survey, or fieldwork is recommended for accurate delineation in operational applications.

Validation of Spruce Budworm Outbreak History Developed from Aerial Sketch Mapping of Defoliation in New Brunswick

Abstract Aerial sketch mapping (ASM) of annual defoliation provides a means to quantify spruce budworm (Choristoneura fumiferana Clem.) outbreak histories, but accuracy is affected by factors such as navigation and weather conditions. We used ground-based defoliation estimates from 123 permanent sample plots (PSP) in New Brunswick and increment core growth data from a subset of PSPs, to validate ASM estimates of defoliation. From 1985 to 1993, 85% of 332 cases were correctly classified by aerial estimates as nil–light (0–30%) or moderate–severe (31–100%), with the proportion correct varying by measurement year, defoliation severity, and host species. Growth indices generated from 81 visually cross-dated and verified balsam fir (Abies balsamea [L.] Mill.) tree-ring series in 23 PSPs were significantly negatively correlated with aerial-derived cumulative defoliation for 87% of the PSPs, and correlation increased when aerial estimates were combined with ground survey data. We conclude that aerial surveys provide a reasonable estimate of defoliation history to estimate growth reduction.

Transient synchronization following invasion: revisiting Moran's model and a case study

AbstractSynchrony in forest insect outbreaks is important because the resulting regionalized outbreak dilutes the regulating effects of natural enemies, reduces the landscape's ability to buffer the disturbance, exacerbates the economic burden on individual stakeholders, and overwhelms the logistical abilities of managers to suppress populations and mitigate impacts. Understanding the process of synchronization of dynamics is therefore a crucial aspect of understanding outbreak dynamics. We studied the second‐order log‐linear (autoregressive) model to ask what patterns of synchronization across invasion fronts may be expected from Moran's model. Generally, we show that the time to synchronization in the log‐linear model is a complex function of a number of parameters of which the overall strength of regulation, the strength of delayed statistical density dependence, and the relaxation time seem to be of particular importance. Interestingly, while environmental correlation is the crucial determinant of the magnitude of asymptotic synchrony, it does not appear to influence the transient process of synchronization. However, synchronization proceeds much more quickly among weakly periodic populations than among populations that are strongly periodic. As a case study, we investigate synchronization following colonization by gypsy moth (Lymantria dispar) populations located along the species's expanding invasion front in northeastern USA. Data consisted of more than 100 years of county quarantine records and 30 years of detailed defoliation maps. We found that the dynamics of new populations tended to be initially out of synch with the broadly synchronized outbreaks within the established range. However, the outbreak dynamics of these new populations lock on to the regional patterns very quickly—within 10–15 years of invasion. Focusing on parameters that produce periodicity comparable to that seen in real gypsy moth populations, we discuss how the observed synchronization compares to that predicted by the log‐linear model. While our results are equivocal, the synchronization appears to be surprisingly rapid, so more mechanistic models may be needed to explain the synchronization observed in this case study.

Area-Wide Analysis of Hardwood Defoliator Effects on Tree Conditions in the Allegheny Plateau

Abstract The effects of defoliation caused by three foliage feeding insects, the gypsy moth (Lymantria dispar), the cherry scallopshell moth (Hydria prunivorata), and the elm spanworm (Ennomos subsignarius), on tree mortality and crown conditions were evaluated using data collected from 1984 to 1999 in the Allegheny National Forest located in northwestern Pennsylvania. While previous studies have focused on the effects of defoliation on trees in individual stands, this study differed in that it used exhaustive maps of defoliation and an areawide network of plots to assess these effects. A geographic information system was used to map the coincidence of USDA Forest Service Forest Inventory and Analysis and Forest Health Monitoring plot locations with defoliation polygons derived from aerial surveys to calculate cumulative years of defoliation for each pest. Over 85% of the Allegheny National Forest land area was defoliated at least once during the 16-year period from 1984 to 1999. Frequency of defoliation by specific defoliator species was closely associated with the dominance of their primary hosts in stands. Frequency of defoliation was often associated with crown dieback and mortality, but these relationships were not detectable in all species. These results suggest that when impacts are averaged over large areas (such as in this study) effects of defoliation are likely to be considerably less severe than when measured in selected stands (as is the approach taken in most previous impact studies).

Susceptibility of northern British Columbia forests to spruce budworm defoliation

Stand susceptibility to defoliation by spruce budworm, Choristoneura fumiferana (Clem.), was examined in the Fort Nelson area of the Prince George Forest Region of British Columbia. In a retrospective study, defoliation maps of the study area were overlaid onto British Columbia Ministry of Forests cover type maps using a geographic information system. Analysis of the combined data identified forest characteristics associated with increased susceptibility to defoliation by spruce budworm. These were stands where the leading species was white spruce ( Picea glauca (Moench) Voss), or where spruce was associated with aspen ( Populus tremuloides Michx. and P. balsamifera L.) in mixed stands. Susceptibility to defoliation also was related to site quality, level of crown closure and stand age. Spruce stands on medium quality sites (site index 15 to 25 m, at reference breast height age 50 years) were more susceptible than stands on both poor- and high-quality sites. When spruce was mixed with aspen, stands on higher quality sites were more susceptible to budworm attack than poor sites. Open stands, where crown closure was <50%, were more susceptible to attack by spruce budworm than closed canopy stands. Older stands (120–199 years) were more susceptible to budworm attack than younger stands (40–110 years). In defoliated plots monitored for 6 years, tree mortality and top-kill reached a maximum of 30.4 and 47.2%, respectively. The losses varied with level of defoliation and were reduced by applications of the biological pesticide Bacillus thuringiensis.

Forecasting Gypsy Moth (Lepidoptera: Lymantriidae) Defoliation with a Geographical Information System

Maps of defoliation caused by the gypsy moth, Lymantria dispar (L.), as well as point estimates of egg mass density and counts of male moths captured in pheromone-baited traps collected from the Shenandoah National Park and George Washington National Forest from 1989- 1992 were assembled in a geographic information system. A maximum likelihood estimation procedure was used to fit 15 logistic regression models that predicted the probability of noticeable defoliation in 1-ha grid cells from various combinations of egg mass densities, counts of males in pheromone traps, presence of defoliation in the previous year, and distance to the expanding gypsy moth population front. Models that incorporated egg mass density estimates and distance to the infested front provided the most reliable predictions of defoliation probability. The performance of these models was comparable with decision errors encountered using various egg mass density thresholds alone. The errors associated with application of egg mass density thresholds and the various models were high and highlighted the need for improved methods for predicting defoliation.

Developing and Validating a Model for Predicting Gypsy Moth (Lepidoptera: Lymantriidae) Defoliation in Connecticut

A logistic regression model was developed that predicts the probability of forest defoliation by the gypsy moth, Lymantria dispar L., in Connecticut. Data used to develop the model were obtained from sketch maps of defoliation in Connecticut from 1982 to 1994, interpolations (using ordinary point kriging) of fixed area egg mass counts from permanent plots in Connecticut from 1986 to 1994, digital soil maps, and digital elevation models. Subjective comparisons of predicted and actual defoliation maps over years used to fit model parameters were similar. The model was validated with data from years not used in developing the model (1975 to 1985 and 1995). When defoliation was averaged over all locales for validation years, average predicted defoliation tracked actual average defoliation, although the association between them was not significant. Correlations between predicted and actual defoliation, when pairs being compared were at the same locations, were below 0.2 for years in which 2% of the state was defoliated, correlations ranged up to 0.9. The model developed here should be useful in providing probabilities of defoliation that can be used in population suppression programs.

Use of a Geographic Information System To Evaluate Regional Treatment Effects in a Gypsy Moth (Lepidoptera: Lymantriidae) Management Program

The effectiveness of aerial applications of Bacillus thuringiensis and diflubenzon (Dimilin) in a gypsy moth, Lymantria dispar (L.), management program was evaluated using a geographic information system. System data included counts of overwintering egg mass densities, defoliation maps, and treatment block boundaries collected by the Appalachian Integrated Pest Management Program in Virginia and West Virginia from 1989 to 1992. Diflubenzuron treatments resulted in greater foliage protection and population reduction than did applications of B. thuringiensis except when egg mass densities before treatment were < 1,000 egg masses per hectare. Generally, neither treatment provided foliage protection in the year following treatment, especially when treatment blocks were small or near to defoliating populations, or both.

Spread of Gypsy Moth (Lepidoptera: Lymantriidae) in the Central Appalachians: Comparison of Population Boundaries Obtained from Male Moth Capture, Egg Mass Counts, and Defoliation Records

Since its introduction near Boston in 1869, the gypsy moth, Lymantria dispar (L.), has spread over 1,000 km to the southwest. To measure its current rate of spread through the central Appalachian Mountains we estimated population boundaries, which are lines that separate areas with population densities generally above and below a specific threshold. Population boundaries were estimated in northwestern Virginia and southeastern West Virginia using male moth counts (1988-1994), egg mass counts (1988-1991), and defoliation maps (1988-1994). The boundary of 1 moth per trap was on average 110 km from the boundary of defoliation, and the male moth capture rate increased 10 times per 29 km perpendicular to the population front. Approximately 11 yr separated the time when traps caught 1 moth per trap until defoliation first occurred in the same area. The rates of gypsy moth spread estimated using different census methods and from different population thresholds changed almost synchronously from year to year. Only spread rates estimated from defoliation data had a different temporal pattern. Gypsy moth spread rate declined from 1988 to 1994 by 35%, as measured from time series of spread rates and boundary compression (reduction of the distance between adjacent boundaries). Reduction in gypsy moth spread rate may have been the result of intensive population management in the area.

Climate and outbreaks of the forest tent caterpillar

Some have suggested that the periodic outbreaks of the forest tent caterpillar. Malacosoma disstria are triggered by weather the temperature at the time of early larval feeding, and overwintering temperatures To assess the role of these factors, defoliation maps, compiled annually from flight surveys for the province of Ontario. were compared to similarly scaled temperature records An analysis of the year to year variation shows no relationship between the pattern of increases or declines in defoliation and either temperatures during early larval development, or overwintering temperatures Four periods of defoliation by forest tent caterpillars were observed in Ontario over 41 yr. but at individual sites extensive defoliation did not occur for each of the outbreak periods Defoliation was less severe in regions with low overwintering temperatures, but was not related to the average number of degree days m the early spring Outbreaks were most common in areas where deciduous forests were extensive, and the mean overwintering temperatures were above −40°C While these weather variables do not apparently explain the details of population dynamics of forest tent caterpillars, extreme weather conditions might synchronize populations

Regional Correlation of Gypsy Moth (Lepidoptera: Lymantriidae) Defoliation with Counts of Egg Masses, Pupae, and Male Moths

Three different gypsy moth, Lymantria dispar (L.), sampling techniques were compared for their spatial correlation with regional defoliation maps. Counts of gypsy moth pupae and egg masses under burlap bands, and counts of male moths in pheromone–baited traps were taken in a network of 150 plots distributed irregularly throughout Massachusetts. These counts were compared with aerial sketch maps of gypsy moth defoliation collected during the same period and digitized into cells (2 by 2 km) cells in a geographic information system. The spatial correlation between counts of the three gypsy moth life stages and defoliation was examined using indicator cross–correlograms. A cross–correlogram quantifies the spatial covariation between two variables by plotting the cross–correlation for a series of interpoint distances. Cross–correlograms indicated that there was substantial correlation between egg mass counts and subsequent defoliation. These correlations extended to 10 cells (20 km) in some cases. Similar patterns were observed for counts of pupae. In contrast, there was little cross–correlation between defoliation and counts of male moths. These results indicate that counts of egg masses (or pupae) under burlap bands may be the most suitable variable to measure for predicting gypsy moth defoliation on a regional scale. The lack of correlation between male moth counts and regional defoliation is discussed.

Forest Defoliators and Climatic Change: Potential Changes in Spatial Distribution of Outbreaks of Western Spruce Budworm (Lepidoptera: Tortricidae) and Gypsy Moth (Lepidoptera: Lymantriidae)

Changes in geographical ranges and spatial extent of outbreaks of pest species are likely consequences of climatic change. We investigated potential changes in spatial distribution of outbreaks of western spmce budworm, Choristoneura occidentalis Freeman, and gypsy moth, Lynumtria dispar (L.), in Oregon and Pennsylvania, respectively, using maps of historical defoliation, climate, and forest type in a geographic information system. Maps of defoliation frequency at a resolution of 2 × 2 km were assembled from historical aerial survey data. Weather maps for mean monthly temperature maxima and minima and precipitation over 30 yr were developed by interpolation. Relationships between defoliation status and environmental variables were estimated using linear discriminant analysis. Five climatic change scenarios were investigated: an increase of 2°C, a 2°C increase with a small increase and a small decrease in precipitation, and projections of two general circulation models (GCMs) after 100 yr at doubled carbon dioxide. With an increase in temperature alone, the projected defoliated area decreased relative to ambient conditions for budworm and increased slightly for gypsy moth. With an increase in temperature and precipitation, defoliated area increased for both species. Conversely, defoliated area decreased for both when temperature increased and precipitation decreased. Results for the GCM scenarios contrasted sharply. For the other, defoliation by budworm was projected to cover Oregon completely, whereas no defoliation was projected by gypsy moth in Pennsylvania. For the other, defoliation disappeared completely for budworm and slightly exceeded that under ambient conditions for gypsy moth. The results are discussed in terms of current forest composition and its potential changes.

Estimating Gypsy Moth (Lepidoptera: Lymantriidae) Egg Mass Density Using Male Moths Captured in Pheromone-Baited, Milk-Carton Traps

We attempted to develop an accurate and efficient means to estimate gypsy moth egg mass density or, alternatively, develop techniques to aid in prioritizing areas that might require egg mass sampling. Results indicate that it is possible to determine the probability of finding some level of egg mass density in the vicinity of a pheromone trap depending on the number of moths captured in that trap. A linear relationship was found between number of moths captured and gypsy moth egg mass density, but this relationship has little predictive value. Wing length of male moths collected in pheromone traps was used to estimate defoliation and male moth dispersal. Wing length of moths captured in pheromone traps was found not to be a reliable indicator of whether or not defoliation occurred. However, capture of small moths, which develop in defoliated areas, in traps located in nondefoliated areas indicated that these moths probably dispersed from other, defoliated areas. Capture of small moths may be useful to determine whether or not to initiate egg mass sampling at the trap location. An algorithm to interpret data from pheromone traps is presented. Trap data interpretation involves use of male wing length, number of moths captured, and defoliation maps. The information obtained from the algorithm will be most useful to evaluate an area for the need to conduct egg mass sampling. Forest managers can evaluate the risk of failing to detect high egg mass density with the need to allocate sampling resources optimally.

Geostatistical Model for Forecasting Spatial Dynamics of Defoliation Caused by the Gypsy Moth (Lepidoptera: Lymantriidae)

Outbreaks of the gypsy moth, Lymantria dispar (L.), typically occur over large areas but are difficult to predict. Previously developed models forecast defoliation from preseason counts of egg masses in a given stand. In this study, we take a different approach to defoliation prediction: forecasts are based upon the statistical autocorrelation of defoliation through space and time. Spatial and temporal autocorrelation of defoliation in historical data was quantified at a variety of scales using variograms. We used a 30-yr time series of aerial sketch maps of gypsy moth defoliation in Massachusetts to calculate these variograms. The variograms were then used to parameterize a geostatistical estimation technique: three-dimensional simple kriging. Kriged estimates are weighed averages of values from nearby locations and are typically used to interpolate two-dimensional data. In this study, we used kriging to extrapolate future defoliation maps into a third dimension, time. Kriged estimates were expressed as probabilities of detectable defoliation. Predicted probabilities were estimated for each year of the time series and were compared with actual defoliation maps for that year. The kriging procedure usually performed well in predicting the spatial distribution of outbreaks in a given year, but the magnitude of regionwide outbreaks generally lagged a year behind actual values. Though this approachis not currently suitable for operational use, it represents a novel approach to landscape level forecasting of insect outbreaks. These models may ultimately outperform current forecasting systems.

Characterizing Spatial Patterns of Gypsy Moth Regional Defoliation

Abstract Aerial sketch maps of defoliation caused by the gypsy moth, Lymantria dispar (L.), in Massachusetts from 1961 to 1986 were digitized into an array of 1.9 x 1.9 km cells. Defoliation frequency was mapped by summing defoliation incidence for each cell. Spatial autocorrelation analysis indicated that defoliation was not distributed randomly over the state but was instead distributed in clumps of varying size. Directional spatio-temporal autocorrelation analysis showed no evidence for unidirectional spread of defoliation through time. Yearly defoliation, as a proportion of maximum, was used in a clustering algorithm to categorize different portions of the state in terms of defoliation synchrony, Two-state transition models were used to characterize defoliation initiation and termination. Different regions showed different probabilities of both outbreak initiation and termination. Transition probabilities varied substantially relative to the amount of defoliation in adjoining areas, indicating an apparent "spread" of defoliation. For. Sci. 35(2):557-568.