Effects of salvage logging and sanitation felling on bark beetle (Ips typographus L.) infestations

Forest Ecology and Management 305 (2013) 273–281

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Effects of salvage logging and sanitation felling on bark beetle (Ips typographus L.) infestations Golo Stadelmann a,⇑, Harald Bugmann a, Franz Meier b, Beat Wermelinger b, Christof Bigler a a b

Forest Ecology, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zurich, Switzerland Forest Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Switzerland

a r t i c l e

i n f o

Article history: Received 21 March 2013 Received in revised form 3 June 2013 Accepted 5 June 2013 Available online 3 July 2013 Keywords: Ips typographus Insect outbreaks Population dynamics Sanitation felling Salvage logging Natural disturbances

a b s t r a c t The European spruce bark beetle (Ips typographus) is the most devastating biotic disturbance agent in Norway spruce (Picea abies) forests of Central Europe and Scandinavia. To reduce damage by bark beetles, foresters aim at (i) preventing outbreaks by salvage logging of storm-damaged timber, and (ii) lowering bark beetle damage by sanitation felling of beetle-infested spruce trees. The effectiveness of these measures are controversially discussed but has not yet been thoroughly analyzed on a quantitative basis. We analyzed a survey dataset with annual resolution that covers 9 years and 487 forest districts (82% of the forested area) all over Switzerland to quantify the drivers of bark beetle infestations, in particular salvage logging and sanitation felling. Poisson log-normal models were used to analyze the dynamics of bark beetle infestations at the forest district level. Bark beetle infestations increased with increasing storm damage, heat sum, volume of Norway spruce stock and the number of infestation spots in the previous year. In contrast, infestations decreased with increasing proportions of sanitation felling relative to the total volume of infested spruce, and with increasing proportions of salvaged windthrown spruce. Our study is the first to quantify the combined effects of salvage logging and sanitation felling on the infestation dynamics of I. typographus in subsequent years, thus allowing forest managers to improve management strategies of bark beetle damage. Sanitation felling and salvage logging reduce the emergence of new infestation spots. In regions with large scale storm damage, salvage logging is clearly more urgent than sanitation felling in the first year and it is therefore recommended to prioritize in the first year after storm events. Ó 2013 Elsevier B.V. All rights reserved.

1. Introduction Bark beetles are one of the most destructive pests in forest ecosystems, leading to landscape-level outbreaks with millions of trees being killed (Dale et al., 2001; Schelhaas et al., 2003). For example, in western Canada infestations by the mountain pine beetle (Dendroctonus ponderosae Hopkins) have recently damaged more than 14 million ha of lodgepole pine (Pinus contorta Douglas) forests, which is considered to be the largest historical mass outbreak of bark beetles (Safranyik et al., 2010). In the ‘Bavarian Forest’ National Park (south-eastern Germany), an ongoing mass outbreak by the European spruce bark beetle (Ips typographus (L.), Curculionidae, Scolytinae) has led to more than 9000 ha of dead Norway spruce (Picea abies (L.) Karst) by the end of 2007 that was further promoted by storm damage, drought and snow break⇑ Corresponding author. Address: Institute of Terrestrial Ecosystems, ETH Zurich, CH-8092 Zurich, Switzerland. Tel.: +41 446339385; fax: +41 446321358. E-mail addresses: [email protected] (G. Stadelmann), harald. [email protected] (H. Bugmann), [email protected] (F. Meier), beat. [email protected] (B. Wermelinger), [email protected] (C. Bigler). 0378-1127/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.foreco.2013.06.003

age (Müller et al., 2008; Lausch et al., 2011). Since bark beetle infested trees are not salvaged in the core zone of the National Park, this is one of the few examples where the natural disturbance regime is allowed to unfold in central Europe. Large-scale infestations by I. typographus are often triggered by heavy windstorms, including recent storms that severely hit European forests such as Vivian/Wiebke in 1990, Lothar in 1999, Gudrun in 2005 and Kyrill in 2007, leading to millions of cubic meters of dead or damaged trees (Wermelinger et al., 1999; Schroeder, 2010; Komonen et al., 2011). Further triggering factors are disturbances that supply initial breeding material such as snow breakage, severe drought or heat waves (Wermelinger, 2004; Netherer and Schopf, 2010). Severe drought reduces tree vigor and thus resistance to pests (Lieutier, 2002; Turtola et al., 2003; Wermelinger et al., 2008) and therefore leads to increased susceptibility to bark beetle infestations (Rouault et al., 2006; Wermelinger et al., 2008; Faccoli, 2009). Similarly, temperature was found to be of key importance for predicting the population dynamics of the ectothermic I. typographus (Stadelmann et al., in press), affecting development rate, voltinism and seasonality (Wermelinger and Seifert, 1998, 1999;

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Faccoli, 2009; Jönsson et al., 2009; Jönsson et al., 2011). Thus, due to climate warming, management of bark beetle damage may become more challenging in the future. In order to plan efficient control measures (i.e., salvage logging or sanitation felling1), it is of key importance to assess the infestation risk by I. typographus on a local and regional scale. Expert systems (Netherer and Nopp-Mayr, 2005), phenology models (Baier et al., 2007) and the combination of both implemented in dynamic simulation models (Seidl et al., 2007; Fahse and Heurich, 2011; Jönsson et al., 2012; Temperli et al., in press) have recently been proposed to improve the assessment of infestation risks by I. typographus. Although simulation models do not usually account for management measures (such as the sanitation felling and debarking or removal of infested trees, or the salvage logging of storm-damaged timber), they are promising tools that need further development by incorporating forest management measures and knowledge gained from empirical analyses. For example, explicit management recommendations have recently emerged from a study by Kautz et al. (2011), who found 65% of subsequent infestations to occur within distances of 100 m from previous infestations, thus recommending sanitation felling within this distance. Other studies have indicated that wind-felled trees remain colonizable for more than three summers, and most of the trees will become infested in that time (Schroeder, 2010; Wermelinger et al., in press). Consequently, forest management may be guided by such information, whereby limited management resources require to set priorities. However, such recommendations demand knowledge of the relative importance of different management measures. Although there is long-term experience and a relatively broad consensus on risk assessment and practical management measures for reducing bark beetle damage (Wichmann and Ravn, 2001), the effects of control measures have not yet been thoroughly evaluated on a quantitative basis. Using a spatio-temporal dataset with nationwide surveys of bark beetle infestations in all forest districts of Switzerland (Meier et al., 2003), we analyzed the interactions of the bark beetle infestations and management measures in Switzerland after the extensive storm damage by Lothar in 1999. We quantified the effects of storm damage, sanitation felling, salvage logging, volume of spruce and climatic factors, and assessed the relative importance of these variables for predicting bark beetle infestations. In the first part of the analysis, we focused on the sanitation measures of bark beetle damage using the complete data set from Switzerland. In the second part, we restricted the analysis to districts that were struck by the storm Lothar in 1999 and we further quantified the effects of salvage logging of the windthrown timber. We specifically addressed three questions: First, does sanitation felling of infested trees reduce the risk of new infestation spots? Second, does salvage logging of storm-damaged timber decrease the number of infestation spots? And third, what is the relative importance of (i) sanitation felling of beetle-infested trees, (ii) salvage logging of storm-damaged trees, (iii) spruce volume and (iv) temperature for the development of infestation spots? The answers to these questions will have considerable implications for the management of bark beetle outbreaks. 2. Materials and methods 2.1. Study area Switzerland has an area of 41,284 km2, of which about one third is forested. The most common tree species is Norway spruce (P. abies (L.) H. Karst.) with 44% of the growing stock (Brändli, 2010). 1 Salvage logging is defined here as the removal of dead or damaged trees that originate from storm damage; sanitation felling denotes the removal of standing Norway spruce trees that were infested by Ips typographus in order to improve stand health.

Related to variability in geology and climate, Switzerland is usually divided into five biogeographic regions: the Jura mountains, the Swiss Plateau, the northern Swiss Alps, the central Alps, and the southern Swiss Alps (Fig. 1). Current climatic conditions favor Norway spruce in subalpine stands in the northern Swiss Alps (57% of the growing stock, i.e. 241 m3 ha1) and in the eastern central Alps (68%, i.e. 209 m3 ha1) (Brändli, 2010), but in general, climatic conditions allow Norway spruce to grow in all biogeographic regions of Switzerland (Schütt et al., 2006). However, most of the spruce stands in the lower elevations have been planted for economic reasons, resulting in a proportion of 34% (146 m3 ha1) of the growing stock on the Swiss Plateau (Brändli, 2010). 2.2. Datasets Since 1984, the Swiss Forest Protection Service (SFP) at the Swiss Federal Institute for Forest Snow and Landscape Research WSL conducts annual surveys of the bark beetle infestations in Switzerland. Terrestrial observations of variables including the annual amount of bark beetle-infested timber and the count of new infestation spots are recorded at the scale of forest districts. We restricted the dataset to the period 2000–2008 as the volume of not cleared infestations (variable vnci in our data set) was not recorded prior to 2000. Thus, our analyses focused on the bark beetle epidemics that began after the storm Lothar (December 1999) and leveled off by 2008 (Fig. 1a). From the complete dataset covering 531 forest districts, we excluded any districts with missing data in the investigated time period, which resulted in a dataset of 487 districts covering 10,435 km2, i.e. 82% of the forested area of Switzerland, with an average forest area of 2140 ha per district (range from 260 to 18,977 ha). From these 487 districts, 347 were affected by Lothar. They are located in the Jura mountains, on the Swiss Plateau and in the northern parts of the northern Swiss Alps (Fig. 1b). Substantial bark beetle outbreaks typically occurred from 2000 to 2006. The other 140 districts, which were not struck by Lothar, mostly stayed in an endemic phase of bark beetle populations (i.e. no mass outbreak occurred; Fig. 1a). As these districts are situated at higher elevations of the northern Swiss Alps, in the central Alps and in the southern Swiss Alps, they are characterized by slightly different climatic conditions than the 347 districts mentioned above (Table 1), i.e. lower annual mean temperature and lower annual precipitation sum with a higher standard deviation of these climate variables. To represent the spatio-temporal dynamics of bark beetle infestations, we used the number of infestation spots (ninf) per forest district. An infestation spot is defined to comprise a spatial cluster of at least 10 bark beetle infested standing trees. The following variables were used to predict ninf, some of which have an annual resolution and some of which are fixed (Table 2). Bark beetle damage of the previous year was recorded both as the volume of not cleared infestations (vnci) and the volume of sanitation felling, summing up to the total volume of bark beetle killed Norway spruce (vdns). The intensity of sanitation felling (isf = 1  vnci/vdns) represents the proportion of the volume of sanitation-felled trees. For districts and years without any bark beetle damage (vdns = 0), isf is not defined. In this case, we assumed the intensity to be 0.75, which was motivated by the fact that forest districts with small values for vdns had similar values for isf (see Results). We further verified the sensitivity of the analyses by setting isf also to 0, 0.5 and 1 for forest districts with vdns = 0, but the parameter estimates were robust and close to those resulting when isf was set to 0.75. The following three variables were recorded only once, and thus were assumed to be fixed (Table 2). The volume of Norway spruce per ha (nsvh) was assessed in 2002, and we assumed it to be constant between 2000 and 2008. Storm damage by Lothar was represented as the volume of total storm-damaged Norway spruce

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Fig. 1. Maps of forest districts in Switzerland indicating (a) the cumulative amount of bark beetle damage in the years 2000–2008 and (b) the amount of Norway spruce damaged by the storm Lothar. Grey lines indicate the borders of the 487 forest districts. Red colors indicate forest districts with damage; darker colors indicate higher damage. Yellow polygons indicate forest districts that were not affected by bark beetles (a) or Lothar (b). Hollow polygons indicate missing data.

Table 1 Annual mean temperature and mean annual precipitation sum during the period of 2000–2008 for all investigated forest districts (n = 487), for the subset of districts affected by the storm Lothar (n = 347) and for the subset of districts not affected by Lothar (n = 140; non-Lothar subset). The standard deviation is denoted with sd.

Full dataset Lothar subset Non-Lothar subset

Temperature (°C)

Precipitation (mm)

Mean

sd

Mean

sd

8.4 9.1 6.7

2.2 1.7 2.1

1378 1413 1291

412 393 456

(vnsd) and as the remaining volume of Norway spruce storm damage not salvaged by September 2000 (rsep). Except for ninf all variables mentioned above were scaled to the district’s forest area and expressed per ha.

To obtain biologically relevant climate data characterizing each forest district, we used the centroid coordinates of the Norway spruce forests per forest district as reference points (further details in Stadelmann et al., in press). We extracted interpolated daily climate data for each reference point derived from the DAYMET model (Thornton et al., 1997). The interpolated climate data had been calculated on a 250 m  250 m grid by the Mountain Hydrology and Mass Movements group at the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. Using a development threshold of 8.3 °C for I. typographus (Wermelinger and Seifert, 1998, 1999), we calculated annual heat sums (hs) based on daily mean temperatures. Summer precipitation (prcp; April–October) was included as a proxy for host vigor. Because elevation is highly correlated with these climate variables it was not used as a predictor variable. We did not consider aspect, either, because many forest districts include a variety of aspects.

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Table 2 Description of variables derived from the interpolated climate data and from the surveys of the Swiss Forest Protection survey group. The standard deviation is denoted with sd. Variable Explanation

Temporal Mean resolution

ninf linf vdns vnci isf nsvh hs prcp vnsd

Annual Annual Annual Annual Annual Fixed Annual Annual Fixed

rsep

Number of new infestation spots per district Number of new infestation spots of the previous year ha1 of forest Volume of bark beetle killed Norway spruce of the previous year in m3/ha1 of forest Volume of not cleared infestations (of Norway spruce) of the previous year in m3/ha1 of forest Intensity of sanitation felling of the previous year Volume of Norway spruce in m3/ha1 of forest Heat sum in dd (degree-days; based on developmental threshold of 8.3 °C for the European spruce bark beetle) Precipitation between April and October in mm Volume of Norway spruce storm damage by Lothar in m3/ha1 of forest. vnsd00 denotes the predictor for the year 2000. Lagged effects of damages as predictors for subsequent years: vnsd01 and vnsd02 = predictors for the years 2001 and 2002, respectively Remaining volume of not cleared Norway spruce storm damage by Lothar in m3/ha1 of forest by September 2000. Lagged effects rsep01 and rsep02 = predictors for the years 2001 and 2002, respectively

Fixed

0.00853 0.90 0.10 0.80 147.49 1207.17 908.59 6.92

1.67

sd

0.0162 2.18 0.78 0.28 78.67 425.75 266.25 10.04

4.03

Note: vnsd and rsep were measured in 2000; nsvh was surveyed in 2002.

2.3. Statistical analyses In the first part of the data analysis, we used the full dataset (487 forest districts) that covered all biogeographic regions and a broad climatic range. This dataset contained districts with storm damage from Lothar as well as districts that had not been affected by Lothar. We used this dataset to analyze the effects of sanitation felling on bark beetle damage. In the second part of the data analysis, only those 347 districts were included in the dataset that had been affected by Lothar. With this dataset, we focused on the effects of salvage logging after storm damage on bark beetle damage and on the effects of sanitation felling. In a previous study (Stadelmann et al., in press), we estimated the parameters of just a limited number of models in a Bayesian framework. In the current study, we analyzed the data in a classical (frequentist) framework because of the large number of models, which would have been too time-consuming to compute using Bayesian methods. However, some models were also calculated with Bayesian methods using the WinBUGS software (Lunn et al., 2000) resulting in similar parameter estimates compared to the frequentist approach. The analyses were performed using a Poisson distribution: y

f ðyit ; kit Þ ¼

kitit  ekit yit

ð1Þ

where the dependent variable yit represents the number of new infestation spots per district i in year t (variable ninf in Table 2) given an expected count of kit . The linear predictor was linked to the expected count using a log function:

logðkit Þ ¼ logðAi Þ þ X it b þ ai þ eit

ð2Þ

with log (Ai) denoting an offset that accounts for the variable size of the forested area of each district (Ai) and Xitb being a linear combination of the design matrix Xit for the predictor variables and a vector b with the fixed effects. To provide for the non-independence of the repeated measures (Pinheiro and Bates, 2000) we added a random effect ai for the intercept of district i with ai  Normalð0; r2a Þ, which estimates the variability between forest districts. eit is an observation level random effect with eit eNormalð0; re2 Þ that was included to account for overdispersion (Zuur et al., 2012). This mixed-effects model will be referred to as a Poisson log-normal (PLN) model. To allow for temporal autocorrelation in the series of infestation spots, we inserted a one year lag dependence of the density of infestation spots (variable linf), i.e. the number of infestation spots per ha in district i during the previous year was considered as a predictor variable to explain yit (Congdon, 2010). To obtain comparability of the resulting effect sizes, the predictor

variables were scaled by their mean and standard deviation (see Table 2), which also improved convergence of the models. An information-theoretic approach for model selection was used to define models a priori and compare them using AIC (Akaike Information Criterion) and Akaike weights (Burnham and Anderson, 2002; Stauffer, 2008), i.e. meaningful models were defined using different combinations of the predictor variables (Supplementary material S1 and S2). The Akaike weight of a model corresponds to the probability that this model best describes the data. The Akaike weights wi are defined as: R  1  X 1 xi ¼ e2Di = e2Di

! ð3Þ

i¼1

whereby Di is the difference in AIC between model i and the model with the lowest AIC, while R denotes the number of models (Burnham and Anderson, 2002). For both analyses (i.e. control of bark beetle infestations by sanitation felling, and combined control measures with sanitation felling and salvage logging) we validated the best-fitting models with a leave-one-out (jackknife) approach, i.e. we refitted the models by leaving out one forest district at a time. The models were then used to compute predictions for the district that was not considered in the model fitting, and to calculate the root mean squared error (RMSE) between observations and model predictions. All analyses were performed using the R software (version 2.15; R Development Core Team, 2012), with the lme4 package (Bates et al., 2012). Graphics were designed with the ggplot2 package (Wickham, 2009) and with ArcGIS 10 (ESRI, Redlands CA, USA). 3. Results 3.1. Storm damage and salvage logging The majority of forest districts in Switzerland (71%) were affected by the storm Lothar (Fig. 1b). However, from 2000 to 2002, most districts had little or no bark beetle damage (Fig. 2). Nearly all districts without storm damage had <1 m3 ha1 bark beetle damage in 2000–2002, while 20% of the districts with storm damage had >5 m3 ha1 subsequent bark beetle damage. The volume of subsequent infestations in 2000–2002 (vdns) was positively associated with vnsd, i.e. increasing storm damage on Norway spruce led to higher bark beetle damage (Fig. 3a). Bark beetle damage amounted to roughly one quarter of the storm damage. The intensity of salvage logging after Lothar was found to decrease with increasing storm damage (Fig. 3b), i.e. a relatively high percentage of storm damage was not cleared in forest districts with high storm damage. Nevertheless, most of the storm damage (84 ± 19%, mean ± standard deviation) was removed by the end of

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Fig. 2. Histogram of the cumulated bark beetle damage (vdns; see Table 2) from 2000 to 2002 per forest district. Red bars: bark beetle damage of forest districts that experienced no damage by the storm Lothar. Blue bars: bark beetle damage in districts with previous storm damage of Norway spruce. Values on the y-axis are scaled to probability densities. Values on the x-axis are represented with a binwidth of 0.2. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

September 2000, and in districts with severe damage (i.e. damage > 30 m3 ha1) still more than 60% of the storm damage was removed. 3.2. Effects of sanitation felling on bark beetle infestations To analyze the effects of sanitation felling on bark beetle damage, 18 models were defined a priori and compared using AIC and Akaike weights (see Supplementary material S1). Based on the Akaike weights (equation 3), there was support for the models SAN02 and SAN05 (i.e. Akaike weights wi > 0; Table 3). The difference between these two models was the additional variable isf in model SAN05, which had a negative effect, but the smallest effect size of all predictor variables (Table 3). The remaining effect sizes were positive and almost identical in the two models, with the following decreasing order of importance: hs, nsvh, linf, prcp, vdns, and isf. Thus, hs had the highest positive effect on bark beetle damage, i.e. the number of infestation spots is expected to increase with increasing hs. Increasing precipitation (prcp) was also associated with more bark beetle infestations, but the effect was much weaker than for hs. The only variable related to stand structure was nsvh, which showed a positive relationship, i.e. a high volume of Norway spruce favored the development of new infestations spots. With an increasing amount of bark beetle damage in the previous year (variables linf and vdns) a rise of new infestation spots in the current year is expected. In contrast, a higher intensity of sanitation felling (isf) reduced the expected number of newly emerging infestation spots. 3.3. Effects of salvage logging on bark beetle infestations In this analysis we included further predictor variables that were related to the storm damage by Lothar and related clearing measures. We defined 130 models a priori, whereby only meaningful variable combinations were allowed (see Supplementary material S2). We found support for 4 models (i.e. Akaike weights wi > 0; Table 4), from which we present the best-fitting model (SAL069). Storm damage by Lothar (vnsd00, vnsd01, rsep02), infestation spots of the previous year (linf), temperature (hs) and stand structure (nsvh) appeared to be important influences on new bark beetle infestations. Further variables regarding bark beetle infestations and their sanitation (isf, vdns) had a relatively low impact on the emergence of new infestation spots. (Table 4). While vdns still had a noticeable positive, significant effect on the emergence of infestation spots, the negative effect of isf was significant, but close to zero.

Fig. 3. Combined box and scatter plot with volume of Norway spruce damage by the storm Lothar (vnsd; see Table 2) on the x-axis versus: (a) volume of bark beetle damage (vdns) from 2000 to 2002, (b) salvage logging intensity of storm damage. Salvage logging intensity (sli) was defined as the proportion of salvaged timber (sli = 1  rsep/vnsd; see variable definitions in Table 2). The width of the boxes was set to 5 m3 ha1. Six values with vnsd > 40 m3 ha1 were plotted as dots.

In general, storm damage facilitated the development of new infestations spots, although these effects emerged not before one year after the storm (Table 4). In the first year following Lothar (i.e. in 2000), the expected count of new infestation spots strongly declined with increasing Norway spruce damage by Lothar (vnsd00), which is likely related to the ample supply of windthrown timber being still more attractive than living spruce trees. A positive effect of vnsd was observed in 2001 only (vnsd01), i.e. increasing spruce damage by Lothar resulted in a higher number of infestation spots in 2001. The volume of non-salvaged storm damage by the end of September 2000 (variable rsep02) was positively related to the lagged emergence of infestation spots in 2002. The variable hs turned out to have a relatively strong positive effect on infestation spots, i.e. the number of infestation spots

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Table 3 Supported models (Eq. (1) and (2)) of the analysis on the management of bark beetle damage. Akaike weights wi (Eq. (3)) were used for multi-model inference. ra and re denote the standard deviation of the random intercept and the observation level random effect, respectively. All other abbreviations are explained in Table 2. Values in round brackets include the 95% confidence intervals. The best-fitting model is shown with gray shading.

Table 4 Supported models (Eqs. (1) and (2)) of the analysis on the management of storm and bark beetle damage. Akaike weights wi (Eq. (3)) were used for multi-model inference. ra and re denote the standard deviation of the random intercept and the observation level random effect, respectively. All other abbreviations are explained in Table 2. Values in round brackets include the 95% confidence intervals. The best-fitting model is shown with gray shading.

tended to increase with increasing hs (Table 4). In the selected models, prcp tended to be slightly positive, but was not or only barely significant. The only information on forest stand structure used in this analysis (nsvh), showed a positive effect, i.e. more infestation spots were expected with higher growing stock of Norway spruce. For forest districts with Lothar damage, sanitation felling turned out to be of minor importance compared to the management of storm damage, heat sum and the volume of Norway spruce.

3.4. Validation of the models We selected four forest districts with differing amounts of storm damage by Lothar (Fig. 4) to visualize the predictions of the best-fitting models SAN05 (Table 3) and SAL069 (Table 4) that were refitted with each of these districts being excluded from the datasets. The outbreak following the storm Lothar began in 2001 and it was generally better represented by model SAL069, i.e. the model including salvage logging (Fig. 4). This model strongly reacted to the Norway spruce damage by Lothar, which was not represented in model SAN05. However, for districts without little storm damage, model SAN05 performed better (Fig. 4). To compare the root mean square error (RMSE) of the predictions over all forest districts, the number of observed and predicted infestation spots was calculated as bark beetle infestation densities per ha, i.e. the high variability in forested area per district was taken into account. The RMSE from predictions for the model SAN05 was 0.0053 (2.5% and 97.5% quantiles: 0.0003 and 0.0388). Similar errors were observed for the model SAL069 including storm damage with an RMSE of 0.0072 (0.0015, 0.0735). To check for multicollinearity between predictor variables, we calculated variance inflation factors (VIF, cf. Fox and Monette, 1992) of the best-fitting models. They were clearly below the critical value of 3 (Zuur et al., 2009). For the model SAN05, all VIFs

were <1.99 and for SAL069 <2.11 (for further information on correlations between predictor variables see Supplementary material S3). 4. Discussion 4.1. Climate effects on bark beetle infestations Most of the 347 districts with storm damage by Lothar are located in the Jura mountains, on the Swiss Plateau and in the lower parts of the northern Swiss Alps (Fig. 1b). These districts are characterized by slightly different climatic conditions than the other 140 districts (Table 1). Specifically, the climatic range of districts with Lothar damage is much smaller and summer temperatures are higher, thus allowing faster development of bark beetle populations with two generations per year, while in mountainous districts the beetles are univoltine. Nevertheless, in both best-fitting models (based on datasets with and without limitation to stormaffected districts), heat sum turned out to be an important influence on bark beetle infestations. The second climate variable, i.e. summer precipitation, is included in some supported models as well, but it has a small effect size. The unexpected positive effect of summer precipitation may be caused by the correlation with heat sum (Supplementary material S3). In the models including only summer precipitation but not heat sum, the effect turned out to be significantly negative (Supplementary material S1), however these models had low Akaike weights. 4.2. Effects of sanitation felling on bark beetle infestations The volume of bark beetle killed Norway spruce (vdns) and the number of infestation spots of the previous year (linf) are important predictors of new infestation spots (Table 3). A large volume of beetle killed Norway spruce and a large number of infestation

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Fig. 4. Temporal development of the number of observed and predicted infestation spots (ninf). Four districts with differing amounts of storm damage by Lothar were used for the predictions based on the refitted models with each of these districts excluded from the datasets. Black dots: observed number of infestation spots. Red lines: predictions of best-fitting model on sanitation felling (SAN05; Table 3). Blue lines: predictions of best-fitting model including sanitation felling of infestations and salvage logging of storm damage (SAL069; Table 4). Since the district shown in the upper left panel was not affected by Lothar, we did not calculate predictions of the model SAL069 for this plot. Note the different scales of the number of infestation spots on the y-axes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

spots indicate a high risk of new infestation spots in the following year. Yet, several management measures may be taken to reduce or prevent further bark beetle infestations. For example, a higher sanitation felling intensity isf decreases the number of infestation spots that are expected in the following year (Table 3), however, the negative effect is rather small. Sanitation felling is a management measure that is only effective when carried out in time, i.e. before the beetles have emerged (Wermelinger et al., 2012). This may be difficult to achieve, because there is often a lag between infestation and its visual manifestation. Our dataset does not contain information whether all sanitation felling had been carried out in time, which may be reflected in the low effect size of isf. Not surprisingly, we found that the volume of Norway spruce per ha (nsvh) implies a higher risk of bark beetle infestations (Netherer and Nopp-Mayr, 2005; Schroeder, 2010; Lausch et al., 2011; Stadelmann et al., in press). Many current spruce stands in the lower elevations and in the Pre-Alps are even-aged and have been planted on sites that naturally would support mixed forests. These artificial stands are more susceptible to storm damage than close-to-nature stands (Mayer et al., 2005; Jurc et al., 2006). Consequently, a decrease of the proportion of spruce in these stands would reduce the infestation risk by I. typographus (Griess and Knoke, 2011) and lower the overall risk of disturbances (Brang, 2001).

4.3. Effects of salvage logging on bark beetle infestations Our analyses confirm that storm damage leads to an increased risk of bark beetle infestations (Fig. 3a and Table 4) as the former supply initial low-defense breeding material (Wermelinger et al., 1999). Since bark beetles prefer newly dead trees (Komonen et al., 2011; Schroeder and Lindelöw, 2002), spruce damage by Lothar led to a lower expected number of new infestation spots in the year 2000 (vnsd00), i.e. the first year after the storm. With an increase of bark beetle populations, infestations of living trees in 2001 were favored by Lothar storm damage (vnsd01), i.e. increasing storm damage coincide with an increase in the number of new infestation spots in 2001. Based on their effect size, these two predictors were more important than heat sum (hs), but the latter has a narrower confidence interval, indicating a high explanatory power. The following variables had an inferior effect (listed in decreasing order of importance; see model SAL069 in Table 4): rsep02, nsvh, linf, vdns, isf. Most of the Norway spruce storm damage by Lothar (vnsd) had been removed by the end of September 2000 (Fig. 3b). Nevertheless, outbreaks occurred in almost all districts affected by Lothar (Fig. 1), which implies that mass infestations by I. typographus cannot be prevented after severe storm damage even with thorough salvage logging. Nevertheless, we expect fewer infestation spots in subsequent years, provided that the

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volume of non-salvaged Norway spruce storm damage is reduced within the first season after a storm. A further step towards improved predictions of bark beetle outbreaks would require to explicitly account for spatial dependencies between adjacent forest districts, e.g. because storm damage in one district may initiate an outbreak that spreads into neighboring districts. However, even if two adjacent districts border each other, there is not necessarily an exchange of bark beetles, e.g. because the border area is not forested, spruce is lacking in the forests of adjacent districts, or the border may be located at high elevations such that beetles cannot disperse. 4.4. Implications for windthrow and bark beetle management The analyses conducted in this study yield several management implications. First, sanitation felling leads to a decreased risk of new infestation spots, as indicated by the intensity of sanitation felling (isf). However, the negative effect size is relatively small. Nevertheless, sanitation felling lowers the expected number of infestation spots in the following year provided that it is carried out in time, i.e. before bark beetles have left their brood tree. Since most of the bark beetles in the lowlands and about half of the beetles in higher elevations overwinter in their brood tree (Komonen et al., 2011; Wermelinger et al., 2012), sanitation felling in winter is expected to be more effective than control measures in summer. However, particularly at high altitudes a thick snow cover often precludes control measures in winter. Thus, sanitation felling is often accomplished in late spring or in the summer season with the disadvantage of missing a part of the bark beetle populations and of simultaneously killing many antagonists (Wermelinger et al., 2012). Second, salvage logging reduces the risk of new infestation spots. Subsequent bark beetle damage is lower in districts with efficient salvage logging than in other districts. Storm damage by Lothar was strongly correlated with infestation spots in the year 2001. By contrast, an increase of storm damage led to a lower expected number of infestation spots in the year 2000, i.e. the first season after the storm. This finding confirms the observation that bark beetles first infest the readily colonizable breeding material, i.e. the storm-damaged timber, which is attractive during one or two years in the lower elevations and up to three years in higher elevations following windthrow (Schroeder, 2010; Wermelinger et al., in press). Infestations of this breeding material led to an increase in the bark beetle populations mainly during the first season following windthrow, but did not yet result in large-scale infestations of standing spruce trees. In the first season, hardly any infestations on healthy spruce trees were observed in the surroundings of storm-damaged stands (F. Meier, personal communication). However, in the second year after Lothar, i.e. in 2001, a strong increase of infestation spots was found in districts with incomplete salvage logging of storm damage. This finding agrees with Komonen et al. (2011), who observed infestations of windthrown timber whereas no standing trees were attacked in the first summer after the storm. However, due to increasing beetle pressure, the largest proportion of living trees were killed in the second season. With increasing salvage logging intensity, fewer infestations are to be expected including shorter outbreak periods with lower infestation peaks. The peaks are reached earlier in those districts with a thorough removal of storm damage than in districts with incomplete salvage logging (cf. Schroeder and Lindelöw, 2002). Thus, salvage logging is an efficient measure for reducing subsequent bark beetle damage. Last, the combined effects of storm damage and salvage logging have a stronger influence than temperature, volume of Norway spruce, sanitation felling and infestation spots of the previous year. Specifically, the effect of salvage logging turned out to be clearly

more relevant than sanitation felling. This effect is probably related to the volume of storm damage, which was much higher than the volume of bark beetle-killed Norway spruce. Consequently, in case of little storm damage the influence of sanitation felling may be more important, since bark beetle populations are removed directly, while salvage logging only leads to a reduction of breeding material. In view of the distinct impact of temperature on the infestation dynamics of bark beetles the ongoing climate warming will strongly affect future bark beetle outbreaks. Since the volume of Norway spruce in a forest stand turned out to be of major importance for the occurrence of I. typographus, a reduction of spruce proportions towards a more natural species mixture in lowland forests would reduce infestation risks. Both salvage logging and sanitation felling reduce the risk of subsequent infestation spots, whereby the effect of sanitation felling is mostly effective in absence of large storm damage. To conclude, in areas with large scale storm damage salvage logging is to prioritize against sanitation felling in the first season after the storm event. Acknowledgments This project was funded by a research grant of ETH Zurich (no. TH-03 06-2). We thank Luzi Bernhard for providing the DAYMET data and Beat Forster for helpful discussions on the relevant needs of forest managers. Furthermore, numerous district foresters made this study possible by dutifully and continuously providing bark beetle data. We further thank two reviewers for constructive comments on the manuscript. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.foreco.2013. 06.003. References Baier, P., Pennerstorfer, J., Schopf, A., 2007. PHENIPS – a comprehensive phenology model of Ips typographus (L.) (Col., Scolytinae) as a tool for hazard rating of bark beetle infestation. For. Ecol. Manage. 249, 171–186. Bates, D.M., Maechler, M., Bolker, B.M., 2012. lme4: linear mixed-effects models using S4 classes. Brändli, U.-B., 2010. Schweizerisches Landesforstinventar. Ergebnisse der dritten Erhebung 2004–2006. Birmensdorf, Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft WSL. Bern, Bundesamt für Umwelt BAFU. Brang, P., 2001. Resistance and elasticity: promising concepts for the management of protection forests in the European Alps. For. Ecol. Manage. 145, 107–119. Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York. Congdon, P.D., 2010. Applied Bayesian hierarchical methods. Chapman and Hall/ CRC. Dale, V.H., Joyce, L.A., McNulty, S., Neilson, R.P., Ayres, M.P., Flannigan, M.D., Hanson, P.J., Irland, L.C., Lugo, A.E., Peterson, C.J., Simberloff, D., Swanson, F.J., Stocks, B.J., Wotton, B.M., 2001. Climate change and forest disturbances. BioScience 51, 723–734. Faccoli, M., 2009. Effect of weather on Ips typographus (Coleoptera Curculionidae) phenology, voltinism, and associated spruce mortality in the southeastern Alps. Environ. Entomol. 38, 307–316. Fahse, L., Heurich, M., 2011. Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level. Ecol. Model. 222, 1833– 1846. Fox, J., Monette, G., 1992. Generalized collinearity diagnostics. J. Am. Stat. Assoc. 87, 178–183. Griess, V.C., Knoke, T., 2011. Growth performance, windthrow, and insects: metaanalyses of parameters influencing performance of mixed-species stands in boreal and northern temperate biomes. Can. J. For. Res. 41, 1141–1159. Jönsson, A.M., Appelberg, G., Harding, S., Bärring, L., 2009. Spatio-temporal impact of climate change on the activity and voltinism of the spruce bark beetle, Ips typographus. Glob. Change Biol. 15, 486–499. Jönsson, A.M., Harding, S., Krokene, P., Lange, H., Lindelow, A., Okland, B., Ravn, H.P., Schroeder, L.M., 2011. Modelling the potential impact of global warming on Ips typographus voltinism and reproductive diapause. Clim. Change 109, 695–718.

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