Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

doi:10.1016/j.ecolmodel.2009.05.015

Ecological Modelling

Volume 221, Issue 2, 24 January 2010, Pages 290-302

https://doi.org/10.1016/j.ecolmodel.2009.05.015 Get rights and content

Abstract

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.

Introduction

Some species of spruce bark beetles (e.g., Ips typographus L. and Pityogenes chalcographus L.) can break out under favourable ecological and trophic conditions. The outbreaks of spruce bark beetles can have devastating consequences on forests. This has been confirmed by data regarding the sanitary felling of conifers in Slovenia during the period from 1995 to 2006. In 2005, for example, around 747,000 m³ of wood were felled due to bark beetles, which is 22.9% of the total felled wood, or 9.9% of the total yield in Slovenia (ZGS, 2006). Such episodes allow us to define spruce bark beetles according to the classification of disturbance described by Anko (1993), as a complex, natural, and chronic disturbance (sometimes even as an acute disturbance). A natural disturbance of the forest ecosystem means a swing between succession and dynamic equilibrium (Anko, 1993). In light of climate change, spruce bark beetles can be treated as a disturbance that affects the dynamics of the forest ecosystem, and also as a factor that is affected by such climate changes (Berryman, 1986, Malström and Raffa, 2000).

Studies have shown that the behaviour of spruce bark beetles will likely change due to climate change. For example, researchers are expecting a drastic increase in damages caused by Ips typographus in Scandinavia over the next decade, because higher temperatures will allow this species to produce two complete generations per year instead of the single generation they currently produce (Lange et al., 2006). In Slovenia, I. typographus reproduction is developing towards two complete and one sister generation per year (Jurc, 2008). In Scandinavia, the border for survival of I. typographus may move 600 km north (Lange et al., 2006). Apart from these changes in the speed of bark beetle development, changes in the resistance of Norway spruce (Picea abies (L.) Karst.), and consequently in the physiological interaction between the Norway spruce and this pest, are also expected (e.g., Berryman, 1986, Rolland and Lempérière, 2004, Wermelinger, 2004). Another likely consequence of climate change is a probable shift in the geographical distribution of the Norway spruce and its pests (e.g., Williams and Liebhold, 2002, Lange et al., 2006). Consequently, there will also be a change in the intensity of damages caused by such pests.

The dynamics of spruce bark beetles is a complex phenomenon. Risk evaluation at the individual tree level due to I. typographus is usually connected to exposure, age, trophic capacity, and water. The dynamics of I. typographus outbreaks are generally dependent on population density, tree susceptibility, weather conditions, and human activities. Outbreaks are difficult to predict due to the complexity of their dynamics (Wermelinger, 2004). A model for short-term forecasting of the numbers of spruce bark beetles was created for the Dinaric Mountains region in Slovenia (Jurc et al., 2006). The model was developed using linear regression and model tree induction. The model calculates the number of spruce bark beetles for next month or week based on the known exposition, age of pheromones in traps, number of days since the bark beetles in traps were last counted, average monthly temperature, monthly rainfall, month of the year, and previous number of bark beetles in the trap. A similar model was developed for the Alps in Italy (Faccoli and Stergulc, 2006). This model can forecast short-term trends in the I. typographus population density for the next year and, consequently, can evaluate the risk of an outbreak. The model relies on the rules determined using data obtained from bark beetles caught in pheromone traps during the period from 1996 to 2004. A comparison of the models for Slovenia and Italy shows that both models use number of bark beetles caught in traps as the input for the model; however, there are several differences in methods and time scale of the models predictions. The model for Slovenia was developed using induction of decision trees and the model for Italy is based on two different indexes. The model for Slovenia predicts the abundance of I. typographus and P. chalcographus for next week or month which depends on frequency of beetle counting caught in traps. But the model for Italy can predict the abundance of I. typographus for the following year.

Long-term predictions of damage due to spruce bark beetles and the influence of climate change in Slovenia have not yet been carried out. Due to the complex population dynamics of bark beetles, even short-term predictions are difficult. Therefore, we justifiably expect lower reliability of long-term, compared to short-term, forecasts.

In the present paper, we present a model designed to predict potential sanitary felling of Norway spruce due to bark beetles attack in Slovenia under various climate change scenarios. This model can be defined within the class of correlation models (Malström and Raffa, 2000). The correlation model attempts to determine the causes and consequences of bark beetle outbreaks over a large area, with the help of research on the relationships between variables describing the environment and the intensity of damage caused by bark beetles. An example correlation model is found in Williams and Liebhold (2002). Their model examines potential shifts in outbreaks of the southern pine beetle (Dendroctonus frontalis Zimm. and D. ponderosae Hopk.) in North America due to climate change. They used a discriminant function model, which includes climate variables, forest type groups, and damage due to southern pine beetles. When making predictions using the climate change model, they considered changes in the range of the forest and changes in climatic variables. This procedure can yield important results, but such results are still based on the assumption that the relationships between variables do not change under the new conditions which are conditioned by climate change. This assumption, and the limitations it imposes, also applies to the model described in this paper.

Section snippets

Purpose of the model and definition of the system

The purpose of the model was to predict the potential sanitary felling of Norway spruce due to bark beetles under various climate change scenarios in Slovenia. The spatial framework was the entire territory of Slovenia, with a resolution of 1 km². There were 20,376 model cells, and the time resolution was 1 year. The model was developed using a M5′ model tree. The M5′ algorithm builds tree-based models with top-down induction of decision trees where the leaf is represented by multivariate linear

Model

The model is a regression-type decision tree (Fig. 5) that has 8 levels. The most decisive variable is located at the bottom of the model tree, i.e., at the first level. Therefore, the proportion of Norway spruce in the wood stock, which appears in the first and several other levels of the model tree, is the most decisive variable in the model. The high importance of the SPRUCE variable can be expected from the results of ReliefF (Table 2), for which it exhibited the second highest positive

Discussion

We developed a model that predicts sanitary felling of Norway spruce due to bark beetles for the entire territory of Slovenia at a resolution of 1 km², in order to evaluate the potential damage to Norway spruce due to future climate change and spruce bark beetles. It is critical to understand the degree of reliability and accuracy afforded by the model predictions. The model possesses a correlation coefficient of 51.9% and an MAE of 15.7 m³ km⁻² year⁻¹, demonstrating a medium level of accuracy.

The

Acknowledgements

The authors are thankful to the Slovenian Research Agency for their financial support. We thank the Slovenian Forestry Service for preparing the main databases for the model. In addition, Prof. Dr. Sašo Džeroski helped improve the model. The climate change scenarios were kindly prepared by Dr. Klemen Bergant.

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Citation Excerpt :
Host density was also positively correlated with sanitary felling because of bark beetles (Yildiz et al., 2007, see results). This association was also observed in other species of bark beetles (de Groot et al., 2019; Fettig et al., 2007; Ogris and Jurc, 2010). However, in the case of other bark beetle species such as Ips typographus and western balsam bark beetle (Dryocoetes confuses Swaine), host trees are often found in large monocultures, which greatly increases the probability of attack.
In recent years bark beetles have been shown to be an important risk factor in European forests. An early warning system is needed to mitigate bark beetle damage, and short-term forecasting models that assist efforts to identify attacked trees comprise an important part of such a system. The aim of this study was to develop short-term forecasting models of the probability of bark beetle outbreaks on two important conifer tree species: Norway spruce (Picea abies) and silver fir (Abies alba). For the development of the models, we used a time series of 20 years of sanitary felling because of bark beetles and relief data (altitude, slope and exposition), several soil variables, climate data (temperature and SPI), sanitary felling because of bark beetles, sanitary felling due to harmful abiotic factors, and amount of weakened trees due to bark beetles. The forecasting variable was sanitary felling because of bark beetles in the current year. The models were developed with a general linear model with binomial error distribution. For the probability of bark beetle outbreaks on silver fir, the amount of fir, soil base saturation percentage, sanitary felling of attacked fir, weakened fir, and sanitary felling because of abiotic factors increased the probability of sanitary felling because of fir bark beetles. Altitude, exposition, slope, phosphorus, soil depth, soil cation exchange capacity, SPI and temperature decreased the probability of sanitary felling because of fir bark beetles. For Norway spruce, the amount of Norway spruce, soil base saturation percentage, SPI, temperature, amount of sanitary felling in the previous year, amount of weakened trees in the previous year, and amount of sanitary felling because of abiotic factors in the previous year increased the probability of sanitary felling of Norway spruce because of bark beetles in the current year. Slope, soil cation exchange capacity, and precipitation decreased the probability of sanitary felling because of bark beetles in the current year. The performance of the bark beetle risk model for Norway spruce was very good. The performance of the model for silver fir was also good, but not on par with that for Norway spruce. Therefore, additional research on fir bark beetles is needed to further improve the risk model for bark beetle attacks on silver fir.

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Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

Abstract

Introduction

Section snippets

Purpose of the model and definition of the system

Model

Discussion

Acknowledgements

Ecol. Model.

For. Ecol. Manage.

J. Insect. Physiol.

For. Ecol. Manage.

Ecol. Model.

For. Ecol. Manage.

For. Ecol. Manage.

Comput. Geosci.

Vpliv motenj na gozdni ekosistem in na gospodarjenje z njim

Zb. gozd. lesar.

Temperature-dependent development of the mountain pine beetle (Coleoptera: Acolytidae) and simulation of its phenology

Can. Ent.

Projekcije podnebnih sprememb za Slovenijo

Forest Insects: Principles and Practice of Population Management

The influence of changes in climate and land-use on regeneration dynamics of Norway spruce at the treeline in the Swiss Alps

Silva Fenn.

Assessment of site characteristics as predictors of the vulnerability of Norway spruce (Picea abies Karst.) stands to attack by Ips typographus L. (Col., Scolytidae)

J. Appl. Entomol.

A practical method for predicting the short-time trend of bivoltine populations of Ips typographus (L.) (Col., Scolytidae)

J. Appl. Entomol.

The predictive sample reuse method with applications

J. Am. Stat. Assoc.

Predicting abundance for 80 tree species following climate change in the Eastern United States

Ecol. Monogr.

Podnebne spremembe in ranljivost kmetijstva

Acta Agric. Slov.

Estimating attributes: analysis and extensions of Relief

Insect performance on experimentally stressed woody plants: a meta-analysis

Annu. Rev. Entomol.

Thresholds in the life cycle of the spruce bark beetle under climate change

Int. J. Complex Syst.

Die Lufttemperatur als limitierender Faktor für die Schwärmaktivität zweier rindenbrütender Fichtenborkenkäferarten, lps typographus L. und Pityogenes chalcographus L. (Col., Scolytidae)

J. Pest Sci.

Ghost forests, global warming, and the mountain pine beetle (Coleoptera: Scolytidae)

Am. Entomol.

Assessing the impacts of global warming on forest pest dynamics

Front. Ecol. Environ.