Article

Risk rating for mountain pine beetle infestation of lodgepole pine forests over large areas with ordinal regression modelling

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Abstract

The mountain pine beetle Dendroctonus ponderosae Hopkins is endemic to lodgepole pine, Pinus contorta var. latifolia Engelmann, forests in western Canada. However, the current beetle epidemic in this area highlights the challenges faced by forest managers tasked with prioritizing stands for mitigation activities such as salvage harvesting and direct control methods. In western Canada, the operational risk rating system for mountain pine beetle is based on biological knowledge gained from a rich legacy of stand-scale field studies. Due to the large spatial (millions of hectares affected) and temporal (over 10 years) extents of the current epidemic, new research into large-area mountain pine beetle processes has revealed further insights into the landscape-scale characteristics of beetle infested forests. In this paper, we evaluated the potential for this new knowledge to augment an established system for rating the short-term risk of tree mortality in a stand due to mountain pine beetle. New variables explored for utility in risk rating include direct shortwave radiation, site index, diameter at breast height, the temporal trends in local beetle populations, Biogeoclimatic Ecosystem Classification and beetle–host interaction variables. Proportional odds ordinal regression was used to develop a model for the Vanderhoof Forest District in west-central British Columbia. Prediction on independent data was assessed with the area under the receiver operator curve (AUC), indicating good discriminatory power (AUC = 0.84) for predicting levels of mountain pine beetle-caused pine mortality.

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... Information on the extent and severity of tree mortality within plantations is required for a variety of forest management activities, including whether to undertake a non-commercial thinning operation or salvage log an area and quantifying the impact on resource volume predictions. The risk of tree mortality is a function of beetle population levels and the ability of a stand to support an epidemic beetle population (i.e., stand susceptibility) (Robertson et al., 2008). Many of the published bark beetle hazard rating systems rely on the measurement of stand-scale attributes such as host tree density, basal area and age (Negron and Popp, 2004) which traditionally have required time-consuming ground surveys and may not be appropriate for risk rating at a landscape scale (Robertson et al., 2008). ...
... The risk of tree mortality is a function of beetle population levels and the ability of a stand to support an epidemic beetle population (i.e., stand susceptibility) (Robertson et al., 2008). Many of the published bark beetle hazard rating systems rely on the measurement of stand-scale attributes such as host tree density, basal area and age (Negron and Popp, 2004) which traditionally have required time-consuming ground surveys and may not be appropriate for risk rating at a landscape scale (Robertson et al., 2008). ...
... As such these results confirm suggestions of McNeil et al. (2007) that forests stressed by drought, insect defoliation or other disturbances may be more susceptible to mortality after several droughts, diseases, or insect attacks. In addition, Robertson et al. (2008) also illustrated 6. Predicted tree mortality, number of dead trees per hectare, based on change metrics derived from three years of MODIS data for pixels with more than 75% P. radiata (see sampling strategy). For interpretation of the color in this figure legend, the reader is referred to the web version of this article. ...
Article
Insect-induced tree mortality can cause substantial timber and carbon losses in many regions of the world. There is a critical need to forecast tree mortality to guide forest management decisions. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery provides inexpensive and frequent coverage over large areas, facilitating forest health monitoring. This study examined time series of MODIS satellite images to forecast tree mortality for a Pinus radiata plantation in southern New South Wales, Australia. Dead tree density derived from ADS40 aerial imagery was used to evaluate the performance of change metrics derived from time series of MODIS-based vegetation indices. Continuous subset selection by LASSO regression and model assessment using a variant of the bootstrap were used to select the best performing change metrics out of a large amount of predictor variables to account for over-fitting. The results suggest that 250 m 16-daily MODIS images are effective for forecasting tree mortality. Seasonal change metrics derived from the Normalized Difference Vegetation Index (NDVI) outperformed the Enhanced Vegetation Index (EVI) and the Normalized Difference Infrared Index (NDII). Temporal analysis illustrated that optimal forecasting power was obtained using change metrics based on three years of satellite data for this population. The forecast could be used to optimise the scheduling of detailed forest health surveys and silvicultural operations which currently are planned based on stratified, annual assessments. This coarse-scale, spatio-temporal analysis represents a potentially cost-effective early warning approach to forecasting tree mortality in pine plantations by identifying compartments that require more detailed investigation.
... This constitutes an improvement compared to other studies (e.g. Netherer and Nopp-Mayr, 2005;Robertson et al., 2008;Klopcic et al., 2009). ...
... Only modelled mean weather values for 1999 to 2010 were available. Occasional extreme events such as heat waves, droughts, and storms or pre- ceding beetle calamities can have a decisive effect on the infesta- tion risk of spruce ( Wichmann and Ravn, 2001;Schelhaas et al., 2003;Engesser et al., 2008;Hanewinkel et al., 2008;Robertson et al., 2008) and interfere with the predictors used in the present study. The integration of such variables into the present model should increase certainty and precision of model predictions. ...
Article
Norway spruce (Picea abies (L.) Karst.) is economically the most important European tree species but is particularly prone to insect infestation calamities. Among the biotic risks threatening Norway spruce in Europe the spruce bark beetle Ips typographus (L.) is the most significant pest. On the basis of projected climate-change scenarios higher temperatures and longer growing seasons will probably lead to even more frequent and serious outbreaks of this pest as a result of more generations per year. At the same time periods of drought may become more frequent and be of longer duration resulting in a physiological weakening of Norway spruce. Hence, it is necessary to develop concepts that can be used in long term silvicultural planning to minimize the risk of bark beetle infestations until trees reach maturity. For an adaptation of forest management it is necessary to identify and quantify risks at the level of silvicultural planning units. Therefore, we developed, a mixed binary linear regression model, which describes the effects of different stand and site variables on the infestation risk that bark beetles exert on spruce stands in the Harz Mountains. The relevant data are based on a decade of detailed forest booking records carried out by the Lower Saxony State Forest in the western Harz Mountains and cover 12,085 individual registrations on 4352 stands. In the model, the stand parameters age and proportion of spruce, and site parameters available water capacity, thermal sum and the Topex-to-Distance Index have significant effects on the infestation risk. It is presumed that the impact of various but unknown silvicultural measures and pest control tactics in managed forests can be quantified by random effects on the forest sub-district level.
... Moreover, integration of remote sensing and other GPS and GIS technologies is applied for detecting and mapping of insect infestations. For example, aerial videography is integrated with GPS and GIS to develop regional mapping for insect infestations over a large agricultural and forest area (Robertson et al. 2008). Such combinations help the agricultural consultant in decision-making. ...
... Also, other remote sensing tools such as airborne video, digital camera systems, and earth-observing satellites were used. Application of such remote sensing technologies provides a good tool for monitoring and decreasing the growing problems caused by bark beetle (Scolytus sp.), mountain pine beetle (Dendroctonus ponderosae Hopkins), southern pine beetle (D. frontalis Zimmermann), Douglas fir beetle (D. pseudotsugae Hopkins), and spruce beetle (D. rufipennis Kirby) on various conifers forests (Coops et al. 2006;Robertson et al. 2008;Meddens et al. 2013;Hart and Veblen 2015). A clear example of the relationship between field-based measures of pest damages, i.e., bark beetle and Landsat spectral change, is reported by Meigs et al. (2011). ...
Article
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The present review provides a perspective angle on the historical and cutting-edge strategies of remote sensing techniques and its applications, especially for insect pest and plant disease management. Remote sensing depends on measuring, recording, and processing the electromagnetic radiation reflected and emitted from the ground target. Remote sensing applications depend on the spectral behavior of living organisms. Today, remote sensing is used as an effective tool for the detection, forecasting, and management of insect pests and plant diseases on different fruit orchards and crops. The main objectives of these applications were to collate data that help in decision-making for insect pest management and decreasing the environmental pollution of chemical pesticides. Airborne remote sensing has been a promising and useful tool for insect pest management and weed detection. Furthermore, remote sensing using satellite information proved to be a promising tool in forecasting and monitoring the distribution of locust species. It has also been used to help farmers in the early detection of mite infestation in cotton fields using multi-spectral systems, which depend on color changes in canopy semblance over time. Remote sensing can provide fast and accurate forecasting of targeted insect pests and subsequently minimizing pest damage and the management costs.
... At the tree level, tree size, crown class, and vigor influence the survival of trees attacked by insect pests (Campbell and Sloan 1977;Haavic and Stephen 2010;Volney 1998). Additionally, a variety of site characteristics, including host tree density (Larsson et al. 1983;McCambridge and Stevens 1982;Mitchell et al. 1983), climate, and site index (He and Alfaro 2000;Robertson et al. 2008) alter tree survival patterns in areas infested by insect pests. Understanding the relationships among tree characteristics, site attributes, and tree survival facilitates the development of management strategies to protect forest health. ...
... Ash species were closely correlated with hydrology due to differing flooding tolerance of different ash species, so differences in mortality rates may be due to species differences. Other site characteristics that covary with hydrology may also be to blame, including stand density, climate, site index, landscape characteristics, and ecological region, which other studies have found to be correlated with tree mortality due to pests and pathogens (He and Alfaro 2000, Jules et al. 2002, Robertson et al. 2008. ...
Article
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Emerald ash borer (Agrilus planipennis) (EAB), an Asian woodboring beetle accidentally introduced in North America, has killed millions of ash (Fraxinus spp.) trees and is spreading rapidly. This study examined the effects of tree- and site-level factors on the mortality of ash trees in stands infested by EAB in OH, USA. Our data show that ash populations in forested sites can progress from healthy to almost complete mortality of mature trees within 6 years. Although the end result of nearly complete mortality does not vary, survival analysis with 5 years of data showed that some factors affected the rate of mortality. We found more rapid mortality in stands with lower densities of ash trees. This finding supports an extension of the resource dilution hypothesis whereby concentration of EAB on few trees in low ash density areas leads to rapid decline of these trees. This contradicts an extension of the resource concentration theory that greater host density increases relative pest abundance and host mortality. Although reductions in ash density via diversification may be desirable for other silvicultural, conservation, and management objectives in preparation for EAB, our study shows that the management strategy of reducing ash density is unlikely to protect the remaining ash trees. Survival analysis also showed that mortality was more rapid for trees shaded by other trees and for trees initially exhibiting dieback. In management scenarios where hazard tree removal must be spread over several years due to budget constraints, focusing initial tree removal on stressed trees is recommended.
... Several types of predictive models have been developed that are advantageous in specific contexts. For example, forest health survey data have been used in conjunction with forest inventory data for estimating MPB species range expansion (Robertson et al., 2009), relating infestation severity to forest patch characteristics (Bone et al., 2013a), and, most commonly, predicting areas likely to be attacked by MPB in the near future (Zhu et al., 2008;Robertson et al., 2008;Bone et al., 2013b). At even broader scales, climate data has been utilized with forest model outputs for estimating the potential of MPB expansion into the boreal forest of western Canada (Coops et al., 2012). ...
... The basic principles of the ABM are derived from a stand-level mathematical model of MPB dispersal described by Shore and Safranyik (1992). Several MPB risk models have since been developed that use principles defined in the Shore and Safranyik model (e.g., Robertson et al., 2008); however, only few have taken a spatially explicit approach incorporating bottom-up methodology, but these have typically been applied at local scales. The intention with our model is to utilize the mathematical components by the Shore and Safranyik risk rating system for parameterizing how MPB interact with host trees in order to simulate tree mortality patterns at local and broader scales. ...
Article
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Forest insect outbreaks can impose significant tree mortality across vast forested landscapes. The current epidemic of mountain pine beetle, Dendroctonus ponderosae Hopkins, for example, has led to the mortality of pine trees in western Canada and the U.S. spanning tens of millions of hectares. The ecological processes driving mountain pine beetle outbreaks are governed by multiple feedback mechanisms, thresholds, and external constraints that exist along a spatial continuum from individual insect–tree interactions to landscape level change. These components of mountain pine beetle epidemics need to be explicitly parameterized in modeling efforts that aim to predict where insect disturbance will occur in a forest each year and the amount of tree mortality that will ensue as a result. However, do date, minimal efforts exist that examine how local level interactions between beetles and trees translate into broader patterns of tree mortality, and those that do are limited to relatively local scales. In this study, we present an agent-based model that simulates how tree mortality results from the combination of beetle–tree interactions, beetle-to-beetle communication, tree defense to beetle attack, beetle density dynamics, host tree availability, dispersal behavior, and landscape heterogeneity. Our model is tested using data from an area in central British Columbia, Canada, that is near the center of the current outbreak in that region. The model simulates both overall tree mortality and spatial patterns of tree mortality, producing results that are similar to those observed in aerial surveys of tree health. Moving forward, the computational efficiency of our model demonstrates the capability to be applied to large, regional landscapes when implemented with sufficient computing resources.
... Furthermore, we employed the Hosmer and Lemeshow test model (Fagerland and Hosmer, 2012) to estimate the fitting degree. The results showed that the P value was 0.942, which is higher than the minimum test standard of 0.05 (Robertson et al., 2008), indicating that the model fit well. ...
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Are traditional marketing mix strategies still suitable for hotel banquet marketing? Using the binary logistic regression analysis method, this study used 763 banquet sales records at the Quanzhou Hilton Hotel to comprehensively test the influence of traditional marketing mix strategies on banquet marketing effects. By focusing on new marketing methods (such as video, the Internet, and WeChat marketing), this study tested the effectiveness of traditional marketing strategies in the new media era. The findings revealed that a combination of products is easier to market than a single product, whereas price is still a key factor in hotel banquet marketing. However, sales channels and personal identity have no significant effects on banquet marketing. Finally, based on the failure cases analysis, this study proposed a feasible path for promoting banquet marketing.
... In the last decade various methods have been used to analyze and model the spatial distribution of MPB infestation and other pine beetle infestations across the world. These include: regression ( Robertson et al. 2008;Negron et al. 2008;Preisler et al. 2012), cellular automata ( Bone et al. 2006;Perez and Dragicevic 2012;Pukkala et al. 2014) and agent-based models (Perez and Dragicevic 2010; Fahse and Heurich 2014). Further, the MPB epidemic is a complex spatial process and depends on various factors ranging from individual tree conditions to climate ( Bone and Altaweel 2014;Safranyik et al. 2010). ...
Conference Paper
Infestations caused by the mountain pine beetle (MPB) can be seen as complex spatio-temporal process with severe ecological impacts on the forest environment. In order to manage and prevent the insect infestation and reduce significant forest loss it is necessary to improve knowledge about the infestation process. The main objective of this research study is to design and implement a model based on decision trees (DT) mashie learning (ML) technique to forecast the spatial propagation of MPB infestation. The study is implemented in the Bulkley-Nechako region of British Columbia, Canada using data sets for the three time points 2004, 2008 and 2012. The results indicate that the derived DT can accurately characterize the relationships between the considered factors and MPB propagation. The developed DT method can be used to estimate future spread patterns of MPB infestations.
... Forest health assessments aided by bark beetle risk models or rating systems have been conducted in Canada, the US and Europe for several decades (Beukema et al., 1997;Lewis, 2002;Malmström and Raffa, 2000;Robertson et al., 2008). These risk models attempt to predict the susceptibility of forests to bark beetle attack and mortality at the landscape and regional scales. ...
... Western North America is currently experiencing the largest outbreak of the mountain pine beetle in recorded history (Westfall and Ebata 2008 ). During such extreme circumstances normal decision-support systems fail to predict mortality levels (Shore et al. 2006 ), and it is necessary to take largearea mountain pine beetle processes into account (Robertson et al. 2008). Predictive modeling, based on diameter-related mortality patterns, is unlikely to be useful during ''hyperepidemic'' conditions, so our meta-analysis does not include data from the current outbreak. ...
Article
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During outbreaks the mountain pine beetle (Dendroctonus ponderosae Hopkins) kills large lodgepole pine trees (Pinus contorta Dougl. ex Loud.) more frequently than smaller ones. There is, however, considerable variation in the relation of diameter to incidence of attack. In a meta-analysis of published data we found that the relationship was primarily determined by geographic location (elevation, latitude, and longitude). We propose a new tree mortality measure, the probability of death index, defined as the average percentage of mortality for trees >23 cm. The index may improve the precision in predictive modeling of tree mortality, as it provides a biologically relevant measure of mortality, since it only includes trees that contribute to the growth of an epidemic and is not influenced by the number of trees within a diameter class. To be useful to forest managers, it must be possible to predict the index from stand parameters that are easily measured. The usefulness of the index was supported by a meta-analysis, which showed that 53% of the variation in the mortality index was explained by geographic location. Tree density did not explain any additional variation. Future research is needed to evaluate the performance of the probability of death index compared with that of other mortality measures.
... can be collected and analyzed in a timely manner when infestations remain relatively 98 small. However, large outbreaks require that risk models be applied over large areas, 99 which means that models must then rely upon regional inventory records to provide the 100 necessary data (Robertson et al. 2008 Inventory (VRI), which is a photo-based, two-phased vegetation inventory with attributes 103 estimates through a combination of aerial photo interpretation and ground sampling 104 (BCMSRM 2002). The utility of such inventories becomes increasingly limited when 105 bark beetle outbreaks cause changes to forest composition (via beetle-induced tree 106 mortality or harvesting-based mitigation efforts) occur far more swiftly than inventory 107 ...
Article
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The objective of this study is to provide an approach for assessing the short-term risk of mountain pine beetle Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) attack over large forested areas based on the spatial-temporal behavior of beetle spread. This is accomplished by integrating GIS, aerial overview surveys, and local indicators of spatial association (LISA) in order to measure the spatial relationships of mountain pine beetle impacts from one year to the next. Specifically, we implement a LISA method called the bivariate local Moran’s Ii to estimate the risk of mountain pine beetle attack across the pine distribution of British Columbia, Canada. The bivariate local Moran’s Ii provides a means for classifying locations into separate qualitative risk categories that describe insect population dynamics from one year to the next, revealing where mountain pine beetle populations are most likely to increase, stay constant, or decline. The accuracy of the model’s prediction of qualitative risk was higher in initial years and lower in later years of the study, ranging from 91% in 2002 to 72% in 2006. The risk rating can be continually updated by utilizing annual overview surveys, thus ensuring that risk prediction remains relatively high in the short-term. Such information can equip forest managers with the ability to allocate mitigation resources for responding to insect epidemics over very large areas.
... It would be overly simplistic for us to conclude that forest managers should seek to systematically alter the spatial arrangement of potential hosts in order to keep beetle populations at endemic levels; however, there are lessons to be learned from the most recent outbreak in British Columbia that could inform future forest managers. Moreover, as the current mountain pine beetle epidemic in western North America continues to spread beyond the beetle's historic range, our contemporary understanding of host susceptibility [56,606162 will need to be revisited to incorporate new knowledge of the beetle in novel habitats. This study suggests that the dynamic relationship between beetles and the spatial pattern of potential hosts is one of the factors that need to be studied further. ...
Article
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The current outbreak of mountain pine beetle, Dendroctonus ponderosae Hopkins, has led to extensive tree mortality in British Columbia and the western United States. While the greatest impacts of the outbreak have been in British Columbia, ongoing impacts are expected as the outbreak continues to spread eastward towards Canada’s boreal and eastern pine forests. Successful mitigation of this outbreak is dependent on understanding how the beetle’s host selection behaviour is influenced by the patchwork of tree mortality across the landscape. While several studies have shown that selective mechanisms operate at the individual tree level, less attention has been given to beetles’ preference for variation in spatial forest patterns, namely forest fragmentation, and if such preference changes with changing population conditions. The objective of this study is to explore the influence of fragmentation on the location of mountain pine beetle caused mortality. Using a negative binomial regression model, we tested the significance of a fragmentation measure called the Aggregation Index for predicting beetle-caused tree mortality in the central interior of British Columbia, Canada in 2000 and 2005. The results explain that mountain pine beetle OPEN ACCESS Forests 2013, 4 280 exhibit a density-dependent dynamic behaviour related to forest patterns, with fragmented forests experiencing greater tree mortality when beetle populations are low (2000). Conversely, more contiguous forests are preferred when populations reach epidemic levels (2005). These results reinforce existing findings that bark beetles exhibit a strong host configuration preference at low population levels and that such pressures are relaxed when beetle densities are high.
... Due to the damage potential of outbreaks, risk-rating models have been developed for several bark beetle species to support forest management at a local to regional scale (Netherer and Nopp-Mayr, 2005;Robertson et al., 2008;Yemshanov et al., 2009). The models are based on classification of forest site and stand characteristics associated with infestations, such as a high density of older coniferous trees, stand exposure and local risk for drought stress. ...
Article
Spruce bark beetle outbreaks are common in Norway spruce forests following windstorm damage, due to ample availability of brood material. The realization of an outbreak depends on factors regulating the Ips typographus population dynamics, such as weather conditions and salvage cutting. In this study, we take an ecosystem modelling approach to analyse the influence of multiple environmental factors on the risk for I. typographus outbreaks. Model calculations of I. typographus phenology and population dynamics as a function of weather and brood tree availability were developed and implemented in the LPJ-GUESS ecosystem modelling framework. The model simulations were driven by gridded climate data covering Sweden with a spatial resolution of 0.5° and a daily temporal resolution. Records on storm damage and I. typographus outbreak periods in Sweden for the period of 1960–2009 were used for model evaluation, and a sensitivity analysis was performed to examine the model behaviour. The model simulations replicated the observed pattern in outbreak frequency, being more common in southern and central Sweden than in northern Sweden. A warmer climate allowing for more than one generation per year can increase the risk for attacks on living trees. The effect of countermeasures, aiming at either reduce the availability of brood material or the I. typographus population size, is dependent on a non-linear relation between I. typographus attack density and reproductive success. The sensitivity analysis indicated a major reduction in the risk of attacks on living trees by timely salvage cutting and cutting of infested trees. Knowledge uncertainties associated with attacks on standing trees, i.e. factors influencing tree defence capacity and I. typographus reproductive success, should be further addressed.
... The relationships among tree defense, tree diameter, and beetle population density also suggest caution when trying to extrapolate process from pattern. It has long been recognized that outbreaks are associated with large trees (Amman and Baker 1972;Björklund and Lindgren 2009;Cole et al. 1976;Hicke and Jenkins 2008;Robertson et al. 2008;Safranyik and Carroll 2006). Our results agree with that view. ...
Article
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Chemical signaling mediates nearly all aspects of species interactions. Our knowledge of these signals has progressed dramatically, and now includes good characterizations of the bioactivities, modes of action, biosynthesis, and genetic programming of numerous compounds affecting a wide range of species. A major challenge now is to integrate this information so as to better understand actual selective pressures under natural conditions, make meaningful predictions about how organisms and ecosystems will respond to a changing environment, and provide useful guidance to managers who must contend with difficult trade-offs among competing socioeconomic values. One approach is to place stronger emphasis on cross-scale interactions, an understanding of which can help us better connect pattern with process, and improve our ability to make mechanistically grounded predictions over large areas and time frames. The opportunity to achieve such progress has been heightened by the rapid development of new scientific and technological tools. There are significant difficulties, however: Attempts to extend arrays of lower-scale processes into higher scale functioning can generate overly diffuse patterns. Conversely, attempts to infer process from pattern can miss critically important lower-scale drivers in systems where their biological and statistical significance is negated after critical thresholds are breached. Chemical signaling in bark beetle - conifer interactions has been explored for several decades, including by the two pioneers after whom this award is named. The strong knowledge base developed by many researchers, the importance of bark beetles in ecosystem functioning, and the socioeconomic challenges they pose, establish these insects as an ideal model for studying chemical signaling within a cross-scale context. This report describes our recent work at three levels of scale: interactions of bacteria with host plant compounds and symbiotic fungi (tree level, biochemical time), relationships among inducible and constitutive defenses, population dynamics, and plastic host-selection behavior (stand level, ecological time), and climate-driven range expansion of a native eruptive species into semi-naïve and potentially naïve habitats (geographical level, evolutionary time). I approach this problem by focusing primarily on one chemical group, terpenes, by emphasizing the curvilinear and threshold-structured basis of most underlying relationships, and by focusing on the system's feedback structure, which can either buffer or amplify relationships across scales.
... site index) of host trees, and to their level of physiological stress (stem density, soil characteristics, etc.) (Shore & Safranyik, 1992;Reynolds & Holsten, 1994;Negrón, 1998;Perkins & Roberts, 2003). These empirical models typically have good predictive power at the stand scale once beetle density is known, but have had less success when applied to the landscape (Dymond et al., 2006;Nelson et al., 2006;Robertson et al., 2008), suggesting that additional factors may drive bark beetle population dynamics at that scale. ...
Article
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Aim Bark beetle outbreaks have recently affected extensive areas of western North American forests, and factors explaining landscape patterns of tree mortality are poorly understood. The objective of this study was to determine the relative importance of stand structure, topography, soil characteristics, landscape context (the characteristics of the landscape surrounding the focal stand) and beetle pressure (the abundance of local beetle population eruptions around the focal stand a few years before the outbreak) to explain landscape patterns of tree mortality during outbreaks of three species: the mountain pine beetle, which attacks lodgepole pine and whitebark pine; the spruce beetle, which feeds on Engelmann spruce; and the Douglas-fir beetle, which attacks Douglas-fir. A second objective was to identify common variables that explain tree mortality among beetle–tree host pairings during outbreaks. Location Greater Yellowstone ecosystem, Wyoming, USA. Methods We used field surveys to quantify stand structure, soil characteristics and topography at the plot level in susceptible stands of each forest type showing different severities of infestation (0–98% mortality; n= 129 plots). We then used forest cover and beetle infestation maps derived from remote sensing to develop landscape context and beetle pressure metrics at different spatial scales. Plot-level and landscape-level variables were used to explain outbreak severity. Results Engelmann spruce and Douglas-fir mortality were best predicted using landscape-level variables alone. Lodgepole pine mortality was best predicted by both landscape-level and plot-level variables. Whitebark pine mortality was best – although poorly – predicted by plot-level variables. Models including landscape context and beetle pressure were much better at predicting outbreak severity than models that only included plot-level measures, except for whitebark pine. Main conclusions Landscape-level variables, particularly beetle pressure, were the most consistent predictors of subsequent outbreak severity within susceptible stands of all four host species. These results may help forest managers identify vulnerable locations during ongoing outbreaks.
... This result is in agreement with previous studies which have demonstrated a positive relationship between the risk of tree mortality caused by I. typographus and the proportion of spruce (Netherer and Nopp-Mayr, 2005;Overbeck and Schmidt, 2012). In addition, host tree basal area (Negrón and Popp, 2004;Negrón et al., 2008) and crown closure (Powell et al., 2000;Robertson et al., 2008) have been shown to be positively related to risks of infestation by D. ponderosae, and both of these variables are positively related to volume (Popescu et al., 2003;Gobakken and Naesset, 2004). The linear increase in risk with increasing values of spruce volume (m 3 ha À1 ) demonstrated by the fitted values (Fig. 6d) may be a result of an increased probability of presence of trees susceptible to I. typographus colonization within a 100 Â 100 m pixel. ...
Article
Bark beetle outbreaks have increased in Europe and North America. To mitigate damage efficiently during outbreaks, robust models predicting where the risk for tree mortality is highest across forest landscapes and better understanding of the underlying mechanisms are required. Using Boosted Regression Trees, we modelled relative risks of infestation by the spruce bark beetle Ips typographus (L.) across a 130,000 ha managed lowland forest landscape in southern Sweden during three years of an outbreak and at a resolution of 100 × 100 m. A second nearby landscape of similar size was used for validation. Both predictors reflecting forest susceptibility and beetle pressure were used. Forest susceptibility predictors included volume per ha of host and non-host trees, tree height and distance to the nearest clear-cut harvested during the last four years, all based on interpretations of satellite images. Bark beetle predictors were based on locations and sizes of previous year infestation spots recorded by helicopter. Model outcomes were similar across years, and there was no major reduction in performance when extrapolating predictions in space or time, indicating the modelled relationships have high reliability. Area under curve (AUC) values varied from 0.729 to 0.818. Including bark beetle predictors increased the AUC value somewhat in one of two years. The most important predictor was volume per ha of the host tree, Norway spruce Picea abies (L.) Karst., which reflects the probability of bark beetles encountering suitable trees. This variable was strongly positively correlated with risk up to 200 m3 ha−1. Unexpectedly, the volume of the non-host birch was also positively correlated with infestation risk up to 25 m3 ha−1. Tree height was associated with increased infestation risk above heights of 10 m in 2008 and 15 m in 2009. In 2007 and 2008 there was a weak negative relationship between infestation risk and distance to the nearest clear-cut. Additionally, our study shows that in managed forest landscapes the I. typographus-killed trees are distributed in many small infestation spots spread out over the landscape. We demonstrate that high-resolution risk-rating maps can be successfully created for large landscapes using easily accessible satellite data of forest characteristics and aerial surveys of infestation spots. The distribution of killed trees in many small infestation spots, poses a challenge for the forest owners to find and remove colonized trees before the new generation emerge. Our results suggest that mitigation efforts in managed lowland forest should focus on high volume spruce stands.
... The common distances in the short-distance range dispersal are 30e50 m (Robertson et al., 2007;Safranyik et al., 1989;Safranyik, Linton, Silversides, & McMullen, 1992), whereas the long-distance flight dispersal that depends on the wind speed, preflight weight, flight duration, and lipid content (Evenden, Whitehouse, & Sykes, 2014) can be more variable, ranging from several to tens of kilometers. In field observations, 2e3 km were commonly found to be the maximum distance beetles can disperse by entering a new stand from surrounding areas (Robertson, Wulder, Nelson, & White, 2008;Robertson et al., 2009), whereas laboratory flight mill bioassay showed that the mean MPB flight distance ranged between 2.12 and 5.95 km (Evenden et al., 2014). Since there is no consensus about which mode is more important in driving the beetle expansion, we defined a number of neighborhood distances: 30 m, 100 m, 250 m, 500 m, 1 km, 1.5 km, 2 km and 3 km. ...
Article
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The recent widespread mountain pine beetle (MPB) outbreak in the Southern Rocky Mountains presents an opportunity to investigate the relative influence of anthropogenic, biologic, and physical drivers that have shaped the spatiotemporal patterns of the outbreak. The aim of this study was to quantify the landscape-level drivers that explained the dynamic patterns of MPB mortality, and simulate areas with future potential MPB mortality under projected climate-change scenarios in Grand County, Colorado, USA. The outbreak patterns of MPB were characterized by analysis of a decade-long Landsat time-series stack, aided by automatic attribution of change detected by the Landsat-based Detection of Trends in Disturbance and Recovery algorithm (LandTrendr). The annual area of new MPB mortality was then related to a suite of anthropogenic, biologic, and physical predictor variables under a general linear model (GLM) framework. Data from years 2001–2005 were used to train the model and data from years 2006–2011 were retained for validation. After stepwise removal of non-significant predictors, the remaining predictors in the GLM indicated that neighborhood mortality, winter mean temperature anomaly, and residential housing density were positively associated with MPB mortality, whereas summer precipitation was negatively related. The final model had an average area under the curve (AUC) of a receiver operating characteristic plot value of 0.72 in predicting the annual area of new mortality for the independent validation years, and the mean deviation from the base maps in the MPB mortality areal estimates was around 5%. The extent of MPB mortality will likely expand under two climate-change scenarios (RCP 4.5 and 8.5) in Grand County, which implies that the impacts of MPB outbreaks on vegetation composition and structure, and ecosystem functioning are likely to increase in the future.
... The decline is mainly caused by synergistic effects of a large sacle outbreak in the bark beetle Dendroctonus ponderosae (Scolytinae), milder winters attributed to long-term changing climate and forestry practices such as the suppression of forest fires resulting in large areas of even-aged monocultures of pine. Between 1995 and 2008 severe and widespread damage to pine forests was documented over 14 million hectares (Westfall 2007;Raffa et al. 2008;Robertson et al. 2009;Kärvemo 2010). This area is approximately 7-times larger than the total forest area in Slovakia. ...
Article
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Wind is both an ecological provider and disturbance facilitator influences trees and other organisms in forests. Impacts of wind on indu-vidual trees and forests mainly depend on the strength (or intensity) of the wind and the stability of the trees. Wind causes large-scale damage to forests and serious economical losses for the forestry sector within Europe. Therefore, knowledge of interactions between wind and trees and/or forests provides the baseline for developing adequate prevention or mitigation of the negative consequences associated with wind disturbances in forest ecosystems. Herein, we analyse the wind as an ecological and disturbance factor in forests in Europe, emphasising forests in Slovakia. Here, strong winds destroy mostly spruce dominated forests in the following regions; Orava, High and Low Tatra Mountains, Great Fatra Mountains, Pohronie, Poľana Mountains and Slovak Ore Mountains. Increasing volumes of timber damaged by windstorms have been documented since 1961, with the maximum damage recorded in 2004. Yearly volumes of damaged timber of approximately 2.5 mil. m 3 are predicted from 2016 to 2030. This highlights the data requirement regarding wind disturbances for integrated forest protection against dangerous winds and other disturbance agents in forest ecosystems in Slovakia and other European countries.
... Western North America is currently experiencing the largest outbreak of the mountain pine beetle in recorded history (Westfall and Ebata 2008). During such extreme circumstances normal decision-support systems fail to predict mortality levels (Shore et al. 2006), and it is necessary to take largearea mountain pine beetle processes into account (Robertson et al. 2008). Predictive modeling, based on diameter-related mortality patterns, is unlikely to be useful during ''hyperepidemic'' conditions, so our meta-analysis does not include data from the current outbreak. ...
Article
During outbreaks the mountain pine beetle (Dendroctonus ponderosae Hopkins) kills large lodgepole pine trees (Pinus contorta Dougl. ex Loud.) more frequently than smaller ones. There is, however, considerable variation in the relation of diameter to incidence of attack. In a meta-analysis of published data we found that the relationship was primarily determined by geographic location (elevation, latitude, and longitude). We propose a new tree mortality measure, the probability of death index, defined as the average percentage of mortality for trees>23cm. The index may improve the precision in predictive modeling of tree mortality, as it provides a biologically relevant measure of mortality, since it only includes trees that contribute to the growth of an epidemic and is not influenced by the number of trees within a diameter class. To be useful to forest managers, it must be possible to predict the index from stand parameters that are easily measured. The usefulness of the index was supported by a meta-analysis, which showed that 53% of the variation in the mortality index was explained by geographic location. Tree density did not explain any additional variation. Future research is needed to evaluate the performance of the probability of death index compared with that of other mortality measures.
... They found through modelling that location and slope were the major factors driving variations in the probability of red tree outbreaks. The GWR model has been used to detect high-risk infestations caused by mountain pine beetle invasions of lodge-pole pine forests over large areas (Robertson et al., 2008). ...
Article
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In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.
... The benefit of using GWR is that it can allow variables to vary over space and need not assume that the same relationships are valid for the whole area of study. GWR model has been used to detect high-risk infestations caused by mountain pine beetle invasions of lodge-pole pine forests over large areas [14]. ...
Article
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The aim of this study is to identify the environmental factors that may influence the onion anthracnose-twister disease incidence and severity. In this study, Geographically Weighted Regression (GWR) analysis was used to identify the dominant environmental factors that might influence the occurrence of Anthracnose-twister disease of onion using Geographic Information System approach. The onion disease records were acquired from the Institute of Climate Change and Environmental Management. The weather parameters such as relative humidity, cumulative rainfall and temperature were acquired from the National Aeronautics and Space Administration website while the river parameters were generated from Sentinel-2 images. This study has identified the ‘distance to river’ and ‘rainfall’ factor as the two (2) important factors that may influence the occurrence of the disease. The predictive surface map generated from GWR model was able to predict the occurrence of the disease in onion field by as much as 86% in the study area. The results of the study can be used to forecast the occurrence of anthracnose-twister disease in the onion fields the future.
... However, the addition of weather and host characteristics improves our detection ability. Susceptibility indices for MPB typically focus on detailed host and stand characteristics [54][55][56][57] . This is because managers can actively modify stand characteristics in most cases. ...
Article
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Mountain pine beetle (MPB) outbreaks have caused major economic losses and ecological consequences in North American pine forests. Ecological and environmental factors impacting MPB life-history and stands susceptibility can help with the detection of MPB infested trees and thereby, improve control. Temperatures, water stress, host characteristics, and beetle pressure are among those ecological and environmental factors. They play different roles on MPB population dynamics at the various stages of an outbreak and these roles can be affected by intensive management. However, to make detailed connections between ecological and environmental variables and MPB outbreak phases, a deeper quantitative analysis on local scales is needed. Here, we used logistic regressions on a highly-detailed and georeferenced data set to determine the factors driving MPB infestations for the different phases of the current isolated MPB outbreak in Cypress Hills. While we showed that the roles of ecological and environmental factors in a forest intensively controlled for MPB are consistent with the literature for uncontrolled forests, we determined how these factors shifted through onset, peak, and collapse phases of the intensively controlled forest. MPB presence mostly depends on nearby beetle pressure, notably for the outbreak peak. However additional weather and host variables are necessary to achieve high predictive ability for MPB outbreak locations. Our results can help managers make appropriate decisions on where and how to focus their effort, depending on which phase the outbreak is in.
... The most significant predictors of bark beetle disturbance thus need to be identified and integrated into a universal model framework ( Hanewinkel et al., 2010;Seidl et al., 2011). A reliable evaluation of bark beetle outbreak risks on landscape scale can be based on key variables obtained from easily accessible forest data sets in combination with the simulation of insect phenology and tree mortality as demonstrated for D. ponderosae infestations ( Robertson et al., 2008;Safranyik et al., 2012). ...
Article
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Infestations by the Eurasian spruce bark beetle, Ips typographus have recently caused peaks in Norway spruce mortality in Central European forests. In this study, we examined how temperature conditions, chronic and acute drought stress, and stand characteristics influence forest disturbance by the spruce bark beetle. We investigated bark beetle induced salvage logging in Norway spruce stands of Austrian Federal Forests (ÖBf) as a proxy variable for infestation/attack by I. typographus. Utilizing ÖBf forest inventory data and the monitoring tool PHENIPS-TDEF, a well-proven bark beetle phenology model combined with a forest water balance module, we retrospectively simulated effective temperature sums for bark beetle development and transpiration deficits at forest stand level. We examined forest stand properties and the model output variables as predictors of bark beetle attack in decision trees and binary logistic regression analysis. We found that I. typographus infestation increased with a stand predisposition index indicating high share of Norway spruce, increased stand age, and stand density. Stands subject to bark beetle attack in the previous year were highly prone to subsequent damage, which points to attack pressure from increased population densities due to ample supply of breeding material. While chronically dry soil conditions described as shallow, xeric, and of low moisture, were associated with bark beetle infestation to a lesser degree, acute drought in the form of increases in stand transpiration deficits proved to raise the probability of bark beetle attacks. The previous year's and current year's summer (June to August) TDEF total, in combination with effective thermal sums allowing for at least two bark beetle generations and sister broods, were significant predictors of bark beetle attack. We conclude from our results that in the absence of windthrow, a combination of ample host availability, favorable temperature conditions for bark beetle development, and acute disposition of trees to attack caused by drought stress can intensify population growth and very likely lead to bark beetle mass outbreaks.
... As an example, consider landscapescale forest insect infestations (e.g., Bone et al. 2013). The spatial processes of large-area insect infestations cannot be measured directly and the pattern of infested trees is the expression of the process of infestation (Robertson et al. 2008). By quantifying the spatial and temporal patterns of insect infestation, we generate new hypotheses or knowledge on the spatial processes of infestation. ...
Chapter
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In forestry, many fundamental spatial processes cannot be measured directly and data on spatial patterns are used as a surrogate for studying processes. To characterize the outcomes of a dynamic process in terms of a spatial pattern, we often consider the probability of certain outcomes over a large area rather than on the scale of the particular process. In this chapter we demonstrate data mining approaches that leverage the growing availability of forestry-related spatial data sets for understanding spatial processes. We present classification and regression trees (CART) and associated methods, including boosted regression trees (BRT) and random forests (RT). We demonstrate how data mining or machine learning approaches are useful for relating spatial patterns and processes. Methods are applied to a wildfire data and covariate data are used to contextualize the quantified patterns. Results indicate that fire patterns are mostly related to processes influenced by people. Given the growing number of multi-temporal and large area datasets on forests and ecology machine learning and data mining approaches should be leveraged to quantify dynamic space-time relationships.
... We did not calculate mean diameter of larger trees as in [8], but used the area of forest with a mean diameter ≥ 20 cm (Large QMD). Other studies have found positive correlations between MPB severity and canopy cover [18,42] and age [19,27,43]; however, we were not able to examine these attributes with our data. ...
Article
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Mountain pine beetle (Dendroctonus ponderosae Hopkins; MPB) is an aggressive bark beetle that attacks numerous Pinus spp. and causes extensive mortality in lodgepole pine (Pinus contorta Douglas ex Loudon; LPP) forests in the western United States and Canada. We used pre-outbreak LPP attributes, cumulative MPB attack severity, and areal extent of mortality data to identify subwatershed-scale forest attributes associated with severe MPB-caused tree mortality that occurred across the Northern Rockies, USA from 1999–2014. We upscaled stand-level data to the subwatershed scale to allow identification of large LPP areas vulnerable to MPB. The highest mortality occurred in subwatersheds where LPP mean basal area was greater than 11.5 m2 ha−1 and LPP quadratic mean diameter was greater than or equal to 18 cm. A coarse assessment of federally-owned LPP-dominated forestland in the analysis area indicated about 42% could potentially be silviculturally treated. Silvicultural management may be a suitable option for many LPP forests, and our hazard model can be used to identify subwatersheds with LPP attributes associated with high susceptibility to MPB across landscape spatial scales. Identifying highly susceptible subwatersheds can help prioritize general areas for potential treatments, especially where spatially extensive areas of contiguous, highly susceptible LPP occur.
... The scale of the neighborhood depends on the beetles' dispersal ability that varies by topography, wind speed, preflight weight, flight duration, lipid content, and host availability (Evenden et al., 2014). Two modes have been summarized for MPB from field observations and laboratory flight mill bioassay: short-distance and long-distance dispersal (Robertson et al., 2008(Robertson et al., , 2009Evenden et al., 2014). Short-distance dispersal happens within stands typically ranging from 30 to 50 m (Safranyik et al., 1989(Safranyik et al., , 1992Robertson et al., 2007). ...
Article
Cellular automata (CA) is a powerful tool for modeling the evolution of macroscopic scale phenomena as it couples time, space, and variables together while remaining in a simplified form. However, such application has remained challenging in forest insect epidemics due to the highly dynamic nature of insect behavior. Recent advances in temporal trajectory-based image analysis offer an alternative way to obtain high-frequency model calibration data. In this study, we propose an insect-CA modeling framework that integrates cellular automata, remote sensing, and Geographic Information System to understand the insect ecological processes, and tested it with measured data of mountain pine beetle (MPB) in the Rocky Mountains. The overall accuracy of the predicted MPB mortality pattern in the test years ranged from 88% to 94%, which illuminates its effectiveness in modeling forest insect dynamics. We further conducted sensitivity analysis to examine responses of model performance to various parameter settings. In our case, the ensemble random forest algorithm outperforms the traditional linear regression in constructing the suitability surface. Small neighborhood size is more effective in simulating the MPB movement behavior, indicating that short-distance is the dominating dispersal mode of MPB. The introduction of a stochastic perturbation component did not improve the model performance after testing a broad range of randomness degree, reflecting a relative compact dispersal pattern rather than isolated outbreaks. We conclude that CA with remote sensing observation is useful for landscape insect movement analyses; however, consideration of several key parameters is critical in the modeling process and should be more thoroughly investigated in future work.
... GWR performs a local form of linear regression that can be used to model spatially varying relationships [29]. A GWR model has been used to detect high-risk infestations caused by mountain pine beetle invasions of lodge-pole pine forests over large areas [30]. However, GWR has not consistently differentiated between stationary and nonstationary data generating processes. ...
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Date palm cultivation is economically important in the Sultanate of Oman, with significant financial investments coming from both the government and private individuals. However, a widespread Dubas bug (DB) (Ommatissus lybicus Bergevin) infestation has impacted regions including the Middle East, North Africa, Southeast Russia, and Spain, resulting in widespread damages to date palms. In this study, techniques in spatial statistics including ordinary least squares (OLS), geographically weighted regression (GRW), and exploratory regression (ER) were applied to (a) model the correlation between DB infestations and human-related practices that include irrigation methods, row spacing, palm tree density, and management of undercover and intercropped vegetation, and (b) predict the locations of future DB infestations in northern Oman. Firstly, we extracted row spacing and palm tree density information from remote sensed satellite images. Secondly, we collected data on irrigation practices and management by using a simple questionnaire, augmented with spatial data. Thirdly, we conducted our statistical analyses using all possible combinations of values over a given set of candidate variables using the chosen predictive modelling and regression techniques. Lastly, we identified the combination of human-related practices that are most conducive to the survival and spread of DB. Our results show that there was a strong correlation between DB infestations and several human-related practices parameters (R² = 0.70). Variables including palm tree density, spacing between trees (less than 5 x 5 m), insecticide application, date palm and farm service (pruning, dethroning, remove weeds, and thinning), irrigation systems, offshoots removal, fertilisation and labour (non-educated) issues, were all found to significantly influence the degree of DB infestations. This study is expected to help reduce the extent and cost of aerial and ground sprayings, while facilitating the allocation of date palm plantations. An integrated pest management (IPM) system monitoring DB infestations, driven by GIS and remote sensed data collections and spatial statistical models, will allow for an effective DB management program in Oman. This will in turn ensure the competitiveness of Oman in the global date fruits market and help preserve national yields.
Article
Bark and ambrosia beetles sometimes kill trees by attacking them en masse; however, their attack is not necessarily successful. Less than half of the fagaceous trees attacked by the ambrosia beetle Platypus quercivorus (Murayama) die, and the factors affecting this mortality are still unknown. To examine this issue, the survival of all stems of fagaceous trees attacked by the ambrosia beetle was investigated in a secondary forest from 2008 to 2010. In an area of 93 ha, 2130 stems (1278 genets) of fagaceous trees were attacked by P. quercivorus during the study period, and 813 of these stems died. A generalized additive mixed model was constructed to predict the probability of mortality of the attacked stems. A best-fit model showed that the probability of mortality was higher in Quercus crispula Blume than in Castanea crenata Sieb. & Zucc. A positive correlation was determined between the density of the attacked trees and the probability of mortality, suggesting that mass attack of P. quercivorus occurs not only on individual trees, but also on groups of trees. Assuming that trees attacked earlier in the season have a higher probability of mortality, the observed negative effects of altitude suggest that P. quercivorus initially seeks hosts at lower elevations.
Article
The outbreaks of shoot beetles (Tomicus yunnanensis Kirkendall and Faccoli and Tomicus minor Hartig) have caused widespread tree mortality in Southwest China. However, multi-scale variables explaining the shoot damage ratio (SDR) caused by shoot beetles have never been studied. The objective of this study was to determine the effects of stand-level and landscape-level variables on SDR during outbreaks of shoot beetles in Yunnan pine forests. Sixty-five plots were generated during 2015–2017 based on beetle infestation maps derived from multi-data Landsat images and field survey. Nine explanatory variables were quantified to explain the SDR severity. The forest cover was obtained from a Worldview-3 high‐resolution image. We used the forest resource planning and design survey data to develop landscape context variables. The beetle pressure variable was calculated using beetle infestation maps. The relative importance of the explanatory variables was analyzed using multi-model inference. We established that SDR was higher in the plots that were closer to roads and severely damaged forest areas in the previous year. SDR was negatively affected by edge density (ED) and forest cover, but positively affected by the mean shape index (SHAPE MN) and aspect. Landscape-level variables are probably the more important predictor, stand-level variables also had a significant effect on the shoot beetle outbreak. The prediction models including stand-level variables and landscape-level variables were built. Identifying variables that drive beetle-caused SDR contributed to the improvement of the existing strategies for outbreak control.
Conference Paper
Ordinal regression which aims to classify instances into ordinal categories has numerous applications. As a supervised learning problem, a large number of labeled data is needed to train an accurate model, in particular when the number of categories is large. Learning an effective ordinal classifier from a small dataset is a challenging task. This paper proposes a framework to transform the ordinal regression problem to a binary classification problem and then recover the ordinal information from the binary outputs. The labeled instances are paired up to train a binary classifier, and therefore, the number of training points is squared, which alleviates the lack of training points. The transformed binary classification problem is solved by a pairwise SVM method. Experimental results demonstrate that on 12 widely used benchmarks, the proposed method is effective comparing with the state-of-the-art ordinal regression methods.
Preprint
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In order to understand the distribution and prevalence of Ommatissus lybicus (Homoptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and highly sophisticated information on the environmental, climatic, and agricultural practices are essential. The analytical techniques available in modern spatial analysis packages, such as Remote Sensing and Geographical Information Systems, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental and human factors. The main objective of this paper is to review remote sensing and geographical information analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus in Oman. An exhaustive search of related literature revealed that there are few studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental and human practice related variables in the Middle East. Our review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance sites that are necessary in designing both local and regional level integrated pest management (IPM) policing of palm tree and other affected cultivated crops.
Preprint
Full-text available
In order to understand the distribution and prevalence of Ommatissus lybicus (Homoptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and highly sophisticated information on the environmental, climatic, and agricultural practices are essential. The analytical techniques available in modern spatial analysis packages, such as Remote Sensing and Geographical Information Systems, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental and human factors. The main objective of this paper is to review remote sensing and geographical information analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus in Oman. An exhaustive search of related literature revealed that there are few studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental and human practice related variables in the Middle East. Our review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance sites that are necessary in designing both local and regional level integrated pest management (IPM) policing of palm tree and other affected cultivated crops.
Research
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A comprehensive listing of publications related to remote sensing of impacts associated with mountain pine beetle (Dendroctonus ponderosae) infestations. Links to abstracts and/or reprints are also provided.
Article
Mass mortality of fagaceous trees due to wilt disease, which has been spreading throughout Japan since the 1980s, is caused by the ambrosia beetle Platypus quercivorus. Quercus crispula is one of the species most susceptible to the disease. Previous studies have examined this disease in secondary forests, where fagaceous trees are dominant and are considered to be distributed uniformly. We examined whether the uneven distribution of Q. crispula in a natural forest affects the spread of this disease. We determined its distribution using Morisita’s index of dispersion (Iδ), and then predicted the probability of mortality using a generalized linear model with topographic variables (altitude and index of convexity), tree size (diameter at breast height, DBH), and basal areas of Q. crispula and Cryptomeria japonica (the dominant species at the study site) per 0.01, 0.09, and 0.25 ha as explanatory variables. The site included 310 Q. crispula within a 14 ha plot in a cool-temperate forest of Japan with no signs of beetle infestation in 2003. The calculated index of dispersion showed a clumped distribution of Q. crispula with an estimated clump size of 0.08 ha. At the end of 2007, 36 Q. crispula in the study site were dead, and DBH and basal area of Q. crispula per 0.09 ha had significant positive effects on the probability of mortality. The basal area of C. japonica, a non-host conifer species for P. quercivorus, per 0.09 ha also had a positive effect on the probability of mortality. These results suggest that P. quercivorus first flew to a cluster of Q. crispula aggregated in about a 0.1 ha area where the density of C. japonica is high, and then DBH played a role in determining the target trees.
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In recent years, the red turpentine beetle (RTB), an invasive pest species, has caused extensive pine mortality in North China. Although some studies have theoretically clarified the interference mechanism of multi-level factors with the development of RTB damage, knowledge about this mechanism from the empirical research is still limited. The aim of this study was to determine whether the primary factors influencing RTB occurrence change during different periods of RTB invasion. Stand-level variables of sample plots were obtained through field investigation and the forest resource survey data including forest stand characteristics, topographic characteristics, and soil properties. Remote sensing classified images were to develop the characteristic variables related to landscape composition and configuration around the sample plots at multiple scales. Generalized linear models (GLMs) and generalized linear mixed models (GLMMs) were used to explore the relative importance of stand-level and landscape-level variables in explaining the severity of RTB damage. Result showed that two stand-level factors, aspect and canopy density, were the best predictors of damage in the early stage of RTB invasion. The landscape-level factor, the proportion of Chinese pine ( Pinus tabuliformis ) patches, was the main predictor of damage in the middle stage of RTB invasion. The most effective spatial scale at which RTB responded to landscape pattern was 250 m. With the increasing severity of RTB damage, the factors driving RTB invasion have shifted from the stand-level to the landscape-level. This calls for an urgent consideration of multi-scale processes to address the changing disturbance regimes in ecosystem management.
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Citation: Windmuller-Campione, M.A.; DeRose, J.; Long, J.N. Landscape-Scale Drivers of Resistance and Resilience to Bark Beetles: A Conceptual Susceptibility Model. Forests 2021, 12, 798. https:// Abstract: Bark beetle (Dendroctonus spp.) outbreaks in the middle latitudes of western North America cause large amounts of tree mortality, outstripping wildfire by an order of magnitude. While temperatures play an important, and direct role in the population dynamics of ectothermic bark beetles, an equally important influence is the nature of the host substrate-the structure and composition of forested communities. For many of the dominant tree species in the western United States, "hazard" indices have been developed for specific bark beetles, which generally include three key variables-host tree size, absolute or relative density of the stand, and percentage of host composition. We provide a conceptual model to apply these three variables across forest ecosystems and bark beetles that shifts the thinking from a species-specific model to a model which focuses on the underlying ecological factors related to bark beetle outbreak susceptibility. We explored the use of our model across multiple scales using the Forest Inventory and Analysis database: Interior West, USA; the states of Colorado and Arizona; and specific national forests within Arizona that are implementing a large-scale restoration effort. We demonstrated that across the Interior West and Colorado, the vast majority of forests have moderate to high susceptibility to bark beetles. Our conceptual model maintains the simplicity of previous "hazard" models but acknowledges the need to consider scale when managing bark beetles. It also shifts the management approach from resistance thinking to the development of "associational resilience", where the focus is not on any one individual stand or area but the longer-term perspective of forest persistence across the landscape.
Technical Report
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In order to understand the distribution and prevalence of Ommatissus lybicus (Homoptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and highly sophisticated information on the environmental, climatic, and agricultural practices are essential. The analytical techniques available in modern spatial analysis packages, such as Remote Sensing and Geographical Information Systems, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental and human factors. The main objective of this paper is to review remote sensing and geographical information analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus in Oman. An exhaustive search of related literature revealed that there are few studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental and human practice related variables in the Middle East. Our review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance sites that are necessary in designing both local and regional level integrated pest management (IPM) policing of palm tree and other affected cultivated crops.
Article
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Dendroctonus ponderosae (Hopkins) is widely distributed across western North America, feeding in at least 12 native species of Pinus L. (Pinaceae). We investigated the existence of heritable differences in two life-history parameters (adult size and development time) of D. ponderosae from a northern population (central Idaho, Pinus contorta Douglas ex Loudon) and a southern population (southern Utah, Pinus ponderosa Douglas ex P. and C. Lawson). We attempted to separate heritable from environmental effects by rearing individuals from both populations through two generations (F1 and F2) in a common standardized laboratory environment with a constant temperature. Two treatment effects were tested for in the F2 generation: (1) geographic location (source host) for F0 D. ponderosae; and (2) the F2 brood host. We hypothesized that, if differences were observed and the F0 source host and region had a greater effect on F2 brood development time and adult size than did the host in which F2 brood were reared, a heritable factor related to the F0 parents was responsible. Time to emergence was significantly shorter for second-generation offspring of the northern population than for second-generation offspring of the southern population, regardless of the F2 brood host. Although both the F2 brood host and F0 source parents were significant in explaining differences observed in the developmental-time distribution of F2 brood, the F0 source effect was found to be much greater. Also, F2 males and females from southern source parents were significantly larger than F2 brood from northern source parents when reared in both F2 brood hosts. Geographic region and original host of F0 source parents had a significant effect on F2 offspring size, whereas the immediate food for F2 brood was not significant in explaining differences. These results suggest genetically based regional differences in D. ponderosae populations.
Book
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An established model for risk rating of Pinus contorta stands for potential mortality caused by mountain pine beetle (Dendroctonus ponderosae) combines information on stand susceptibility and beetle pressure. Susceptibility is determined using attributes in the forest inventory data, while beetle pressure is calculated based on the size and distance to existing infestation locations (distance-based model). An alternate model for calculating beetle pressure is presented in this paper, which uses Voronoi polygons to incorporate size and distance, while emphasizing the density of existing infestation locations (density-based model), in combination with empirical knowledge of beetle dispersal and forest inventory data. Survey data of existing beetle damage were collected using a helicopter mounted global positioning system (GPS) at a study site in central British Columbia, Canada in 1999, 2000, and 2001. These data facilitated the estimation of beetle pressure, and the comparison of risk ratings to actual attack locations. Using the distance-based model, 18% and 27% of areas identified as having a risk rating of greater than 50 in 1999 and 2000 were actually found to be attacked by beetles in surveys conducted in 2000 and 2001. Conversely, 39% and 49% of areas identified as having risk greater than 50 in 1999 and 2000 with the density-based model were attacked in 2000 and 2001. The results suggest that the density-based model of beetle pressure produced risk ratings that had a greater correspondence with actual infestation occurrence than risk ratings generated from the distance-based model. Using data that is typically collected to monitor beetle populations, novel methods of spatial processing may be applied in a transparent manner, generating results that incorporate knowledge of mountain pine beetle dynamics under certain population conditions, into calculations of the risk of mountain pine beetle attack.
Article
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British Columbia is currently experiencing the largest mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic on record. The spatial extent of this infestation highlights the need for large-area forest management. We explore the use of three large-area data sets for implementing a stand-scale model of forest susceptibility that quantifies the probability of loss of pine basal area because of attack by the mountain pine beetle. Using these data sets, we investigate the impact of surrogate variables, which is necessary when variables required for the susceptibility model are not present in a data set. The impact of the source data information content on the susceptibility model output is also analyzed. Results indicate that the susceptibility model is sensitive to both surrogate variables and data sources and suggest that landscape level application of the susceptibility model, which was developed using stand-scale relationships, is problematic. Of particular concern is the use of photointerpreted data sets for model parameterization. The information content in photointerpreted data sets is much different than data on similar forest characteristics collected in the field and provides an inadequate substitute for implementing the forest susceptibility model.
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Decision support systems to aid the management of mountain pine beetles combine characteristics of the stand and beetle infestation to estimate risk of damage. Beetle infestation information is now available in a format amenable to the operational implementation of risk. In this study, an established risk rating system was evaluated to determine the utility of the values generated. For a study area located in British Columbia, Canada, global positioning systems were used to survey an infestation. The annual data was used to generate risk for a given year and to compare the ratings with survey data from the subsequent year. Under epidemic conditions, 30% to 43% of the stands rated as high risk were subsequently infested. Of the infested stands, 72% to 76% had a high risk rating. In general, the risk rating system accurately predicted risk in stands that were infested, but not all high risk stands were subsequently attacked. This highlights the difficulty of modeling processes that have a stochastic component. For operational contexts, the estimation of risk on an annual basis is sufficiently reliable to aid in the strategic planning of forest managers.
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An understanding of mountain pine beetle (Dendroctonus ponderosae Hopkins) dispersal during an outbreak is important for modeling future infestations and aiding management decisions. Data on the spatial pattern of red and green attacked trees were used to characterize the spatial–temporal nature of dispersal. Research goals were to detect evidence of dispersal based on the distance and direction between red and green attacked tree clusters, determine how dispersal changes at different stages of infestation, and to detect landscape variables influencing the observed dispersal patterns. Key variables explored were Biogeoclimatic Ecosystem Classification (BEC), topography, and the local population of susceptible hosts. Dispersal distances of 30 meters and 50 meters were consistently observed among different data subsets. Findings suggest that short-range dispersal often occurs despite an available population of susceptible hosts, and as the infestation grows in intensity, the abundance of dispersing beetles causes spot infestations to coalesce. FOR. SCI. 53(3):395– 405.
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Book
From the reviews of the First Edition."An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."—Choice"Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent."—Contemporary Sociology"An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."—The StatisticianIn this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.
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Natural disturbance has considerable ecological significance, and within woodlands tree-falls significantly change environmental conditions. The spatial characteristics of canopy gaps influence regeneration dynamics, and species diversity and distribution. In this study imagery from a Compact Airborne Spectrographic Imager (CASI) was analysed to produce a vegetation cover map for a range of types of deciduous woodlands. This map was used to delineate canopy gaps in these areas. A raster-based GIS was used to derive a range of measures to describe the spatial characteristics of canopy gaps, in order to infer the relative ecological status of different types of deciduous woodland. For the study sites, spatial characteristics have been used to derive information on: (1) gap creation mechanisms: large gaps are created by progressive enlargement rather than instantaneously by a catastrophic event; (2) regeneration dynamics: semi-natural woodlands have large gaps susceptible to pioneer invasion and small gaps for climax regeneration, plantations have only small gaps; (3) species diversity and distribution: semi-natural woodlands have high potential genetic variability, high probability of persistence of gap species, and a high potential to support 'edge' species, the opposite is the case for plantations. The combination of airborne remotely sensed data and GIS technology holds great potential for ecological studies of woodlands. This approach provides a spatial framework on which to base future pattern-process studies, and the GIS-based output is valuable for environmental management purposes. The analysis of multi-date imagery in this way should provide a basis for monitoring woodland dynamics.
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A system for rating the susceptibility of lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) stands to the mountain pine beetle (Dendroctonus ponderosae Hopkins) was field tested in 38 stands in the Cariboo forest region of British Columbia in a retrospective study. A linear relationship was defined between the percentage of basal area killed by the mountain pine beetle and the susceptibility indices for the sample stands. The system was further tested using an independent data set of 41 stands from across southern British Columbia. Forty of the 41 stands fell within the 95% prediction interval of the original model data for stand susceptibility. This study provides validation for a susceptibility rating model described in 1992. The regression model and associated confidence interval also provide a useful tool for landscape level loss predictions due to the mountain pine beetle.
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Three field tests were conducted in which fresh lodgepole pine (Pinus contorta Douglas var. latifolia Engl.) material, namely bolts with and without bark, bark only, and freshly tapped resin, were placed in beetle-excluding “greenhouse” cages; empty cages served as controls. Two “window” flight traps per cage, at right angles to each other, caught mountain pine beetles (Dendroctonus ponderosae Hopkins) arriving at the cages. Significantly more mountain pine beetles were trapped at cages baited with bolts and wood only than at empty control cages. Primary attraction in the mountain pine beetle is thus established, in the absence of pheromones and normal visual cues (tree stem silhouette). More beetles were trapped at cages baited with bark only and with resin than at empty control cages, but differences were not significant at p = 0.05. The sex ratio of trapped beetles (4.83 females: 1 male) was more than twice as high as the reported sex ratios of free-flying and emerging beetles.
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Stand structure and vigor variables were used to develop a model for predicting the development of a Dendroctonusponderosae Hopk. outbreak in climax Pinuscontorta Dougl. ex Loud. var. murrayana Grev. and Balf. stands in south central Oregon. Stepwise discriminant analysis indicated the significant predictor variables were quadratic mean diameter and the number of rings in the outermost centimetre of radial growth at breast height (p = 0.00001, canonical correlation coefficient = 0.77235). Ninety-three percent of the stands were correctly classified into their appropriate groups (attacked versus unattacked). None of the five indices of competition tested (i) Waring and Pitman's tree vigor index, (ii) Mahoney's periodic growth ratio, (iii) Krajicek's crown competition factor, (iv) Hegyi's competition index, and (v) Curtis's stand density index) were significant discriminators.
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The dynamics of tree and stand growth were studied in six small but expanding mountain pine beetle outbreaks in British Columbia. Stands had exceeded a previously reported hazard threshold of age 80 years by 26 years, and a second frequently used hazard threshold of 20.5 cm mean dbh was exceeded by 37 years. However, stands had exceeded maturity, as defined by the intersection of current annual increment (CAI) and mean annual increment (MAI), by an average of only 17 years. In all cases, the beginnings of the outbreaks were coincident with a period of reduced tree growth. This reduced tree growth was difficult to detect at breast height, with a consequent failure of the periodic growth ratio to indicate susceptibility. Although the stands were past the point of maturity, the dominant and codominant trees continued to add significant wood volume, which could make surveillance for incipient outbreaks and subsequent control actions cost effective.
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The objective of this study was to gauge the effectiveness of using SPOT-5 10-m multispectral imagery to detect and map red-attack damage for an area near Cranbrook, British Columbia, Canada. A logistic regression model was used to incorporate SPOT imagery with elevation and associated derivatives for red- attack detection and mapping. Separate independent sets of calibration and validation data, collected via a detailed aerial survey, were used to train the classification algorithm and vet the output maps of red-attack damage. The output from the logistic regression model was a continuous surface indicating the probabil- ity of red-attack damage. Using a greater than 50% probability threshold, red-attack was mapped with 71% accuracy (with a 95% confidence interval of ±9%). This level of accuracy is comparable to that achieved with Landsat single-date imagery in an area with similar levels of infestation. If a synoptic view of mountain pine beetle red-attack damage at the landscape level is required, and if Landsat data are unavailable, SPOT-5 10-m multispectral imagery may be considered an alternative data source, albeit an expensive one, for detecting and mapping mountain pine beetle red-attack damage.
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British Columbia is currently experiencing the largest mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic on record. The spatial extent of this infestation highlights the need for large-area forest management. We explore the use of three large-area data sets for implementing a stand-scale model of forest susceptibility that quantifies the probability of loss of pine basal area because of attack by the mountain pine beetle. Using these data sets, we investigate the impact of surrogate variables, which is necessary when variables required for the susceptibility model are not present in a data set. The impact of the source data information content on the susceptibility model output is also analyzed. Results indicate that the susceptibility model is sensitive to both surrogate variables and data sources and suggest that landscape level application of the susceptibility model, which was developed using stand-scale relationships, is problematic. Of particular concern is the use of photointerpreted data sets for model parameterization. The information content in photointerpreted data sets is much different than data on similar forest characteristics collected in the field and provides an inadequate substitute for implementing the forest susceptibility model.
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The identification and classification of mountain pine beetle, Dendroctonus ponderosae (Hopk ins), red-a ttack damag e patterns in a mature lodgepole pine (Pinus contorta) forest located in the Fort St. James Forest District, British Columbia, was accomplished using 1999 Landsat TM satellite imagery, 1999 mountain pine beetle field and aerial survey point data, and GIS forest inventory data. Unrelated variance in the observed spectral response at mountain pine beetle field and aerial survey points was reduced following image stratification with the GIS forest inventory data and removal of other factors uncharacteristic of red-attack damage. Locations of known mountain pine beetle infestation were used to train a maximum-likelihood algorithm; overall classification accuracy was 73 percent, based on an assessment of 360 independent validation points. If local stand variability is reduced prior to signature generation, accuracies and map products can be useful for those involved in active forest management decision-making regarding mountain pine beetle infestations.
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Disturbances such as fire, insect outbreaks, and blowdown are important in shaping subalpine forests in the Rocky Mountains, but quantitative studies of their inter- actions are rare. We investigated the combined effects of past disturbances, current vege- tation, and topography on spatial variability of the severity of a fire that burned approxi- mately 4500 ha of subalpine forest during the extreme drought of 2002 in northwestern Colorado. Ordinal logistic regression was used to spatially model fire severity in relation to late 1800s fires, a 1940s spruce beetle outbreak, forest cover type, stand structure, and topography. The late 1800s fires reduced the probability of burning in 2002, and the 1940s beetle outbreak slightly increased the probability of fire, particularly at high severity. Aspen (Populus tremuloides) and lodgepole pine (Pinus contorta) stands, which established after the late 1800s fires, were less likely to burn, whereas Engelmann spruce (Picea engel- mannii)-subalpine fir (Abies lasiocarpa) stands were more likely to burn. The highest elevations ($3100 m) had the lowest probability of burning, whereas intermediate elevations (2900-3100 m) had an increased probability of burning at high severity. The influences of the late 1800s fires and 1940s beetle outbreak on stand structure and forest cover type may be more important than their direct effects on fuels. The most important predictors deter- mining fire severity were stand structure, forest cover type, the late 1800s fires, and ele- vation. Although, in other studies, the effects of pre-burn stand conditions and topography declined with increasingly severe fire weather, in the case of the 2002 fire in Colorado, these predictors explained 42% of the variability of fire severity. Thus, these results suggest that pre-burn stand conditions are important influences on burn severity even for fires burning during extreme drought.
Article
Dendroctonus ponderosae Hopkins was studied in lodgepole pine, Pinus contorta Douglas, at 4 elevations between 1923 and 2750 m in northwestern Wyoming. The beetle had a 1-year life cycle at 1923 and 2130 m. At 2450 m, part of the population completed a generation in one year, but the remainder required two years. Two years usually were required to complete a generation at 2573-2750 m. Life tables showed high mortality rates and declining populations at the 3 highest elevations, in contrast to high survival rates and increasing populations at the lowest elevation. Cool temperatures at high elevations delayed development, so the beetle overwintered in stages that were particularly vulnerable to winter temperatures. The conclusion is that mountain pine beetle populations are regulated by weather at high elevations.
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Dispersing Dendroctonus ponderosae landed preferentially on lodgepole pines with fire scars and decay (P = 0.023 and P = 0.008, respectively, by joint binomial distribution analysis).
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A computer simulation model based on laboratory and field studies of mountain pine beetle (Dendroctonus ponderosae Hopkins) interactions with lodgepole pine (Pinus contorta var. latifolia) is presented. The experimental results provide the basis for the underlying assumptions and equations concerning host resistance, beetle numbers, and nutrient availability. This simulation is not intended to predict numerical levels in any particular region, but instead provides a basis for considering how host and beetle factors can interact to affect population behavior. The model generates patterns of population behavior characteristic of D. ponderosae and other primary bark beetle species, and shows a variable relationship of population density with population growth. The system has two equilibrium points, one of which is stable, and the other is unstable. The unstable equilibrium represents a threshold that separates regions of qualitatively different population behavior (endemic from epidemic). Each stand is characterized by a unique population outbreak threshold, and this value is strongly affected by age class. The simulation model was used to evaluate management practices for controlling D. ponderosae outbreaks. The most important factors were found to be those that directly affect host vigor. Stand thinning seems to provide the most effective long-term protection from beetle outbreaks. Forest Sci. 32:789-805.
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Ninety-four unmanaged lodgepole pine stands, from a broad geographical range in the western United States, were examined to evaluate the relationship between stand density and susceptibility to mountain pine beetle (MPB), Dendroctonus ponderosae Hopkins, attack. Population trends were not significantly related to variation in stand density as measured by stand density index (SDI). Percentage of trees killed per hectare by MPB in stands with >80% lodgepole pine did vary significantly with changes in SDI. From these data three SDI zones were identified as follows: 1) stands with SDI's of <125 showed low potential for attack, 2) stands between 125 and 250 SDI showed much greater levels of tree mortality, gradually decreasing toward the 250 SDI, 3) tree mortality decreased in stands as density increased beyond the 250 SDI value.
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Question: Can the distribution and abundance of Vaccinium myrtillus be reasonably predicted with soil nutritional and climatic factors? Location: Forests of France. Methods: We used Braun-Blanquet abundance/dominance information for Vaccinium myrtillus on 2905 forest sites extracted from the phyto-ecological database EcoPlant, to characterize the species ecological response to climatic and edaphic factors and to predict its cover/abundance at the national scale. The link between cover/abundance of the species and climatic (65 monthly and annual predictors concerning temperature, precipitation, radiation, potential evapotranspiration, water balance) and edaphic (two predictors: soil pH and C:N ratio) factors was investigated with proportional odds models. We evaluated the quality of our model with 9830 independent relevés extracted from Sophy, a large phytosociological database for France. Results: In France, Vaccinium myrtillus is at the southern limit of its European geographic range and three environmental factors (mean annual temperature, soil pH and C:N ratio) allow prediction of its distribution and abundance in forests with high success rates. The species reveals a preference for colder sites (especially mountains) and nutritionally poor soils (low pH and high C:N ratio). A predictive map of its geographic range reveals that the main potential habitats are mountains and northwestern France. The potential habitats with maximal expected abundance are the Vosges and the Massif central mountains, which are both acidic mountains. Conclusions: Complete niche models including climate and soil nutritional conditions allow an improvement of the spatial prediction of plant species abundance at a broad scale. The use of soil nutritional variables in distribution models further leads to an improvement in the prediction of plant species habitats within their geographical range.
Article
An analysis of semiochemical communication between host trees, bark beetles and commensal or entomophagous insects discloses five principal means by which semiochemicals can influence the population dynamics of bark beetles. These are: mediation of aggregation and mass attack on new hosts, cessation of aggregation and shifting of attack to uninhabited hosts, induction of aggregation by competing species, inhibition of aggregation by competing species, and mediation of host finding by commensal and entomophagous insects. Further analysis suggests major points of natural vulnerability which lead to six fundamental strategies for potential pest management: prevention of production of aggregation pheromones, sabotage of olfactory perception, exploitation of semiochemical-based secondary attraction, exploitation of antiaggregation pheromones, exploitation of repellent allomones, and exploitation of the kairomonal response by entomophagous insects. Investigations of the many possible tactics arising from these strategies have led to three types of operational pest management programs: prevention of pheromone production by excluding bark beetles from their hosts; suppression of bark beetle populations through the utilization of semiochemical-baited traps, trees or logs; and the use of antiaggregation pheromones to protect vulnerable hosts from attack.