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Article

Impact of Trapping Programs for Ips typographus (Linnaeus) (Curculionidae: Scolytinae) on Predators, Parasitoids, and Other Non-Target Insects

by
Matteo Bracalini
*,
Andrea Martini
,
Lorenzo Tagliaferri
and
Tiziana Panzavolta
Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144 Florence, Italy
*
Author to whom correspondence should be addressed.
Forests 2025, 16(10), 1510; https://doi.org/10.3390/f16101510
Submission received: 1 August 2025 / Revised: 29 August 2025 / Accepted: 19 September 2025 / Published: 24 September 2025
(This article belongs to the Section Forest Biodiversity)
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Abstract

The European spruce bark beetle, Ips typographus (Linnaeus, 1758), poses a significant threat to Picea abies (Linnaeus) Karsten, 1881 forests, with outbreaks often exacerbated by abiotic disturbances like the 2018 Vaia windstorm in the Italian Alps. Pheromone-baited traps are widely used for control, yet their overall efficacy and potential side effects, particularly the incidental capture of non-target insects, remain debated. This study aimed to comprehensively assess the presence and composition of non-target insects in I. typographus pheromone traps, used for both mass-trapping and monitoring, in the affected Alpine regions. We took into account single monitoring traps (dry collection) and three-trap cross configurations for mass-trapping (with preservative liquid), collecting and morphologically identifying insect by-catch. Our results revealed a non-target proportion (excluding bark beetles) significantly higher in mass-trapping (4.15%) compared to monitoring (1.00%), with approximately half being natural enemies of bark beetles. Crucially, we report that bark beetle parasitoids were repeatedly caught, with Tomicobia seitneri (Ruschka, 1924) (the third most abundant non-target species) particularly well represented, and Ropalophorus clavicornis (Wesmaël, 1835) also detected, which is noteworthy given its ecological role despite its lower numbers. Our findings underscore the significant, previously underreported, capture of beneficial parasitoids and highlight the need for careful consideration of non-target catches in I. typographus pest management strategies.

1. Introduction

The European spruce bark beetle, Ips typographus (Linnaeus, 1758) (Coleoptera: Curculionidae: Scolytinae), is one of the most significant bark beetles of spruce (Picea abies (Linnaeus) Karsten, 1881) forests, particularly across Europe. Its capacity for huge outbreaks, often triggered by large-scale abiotic disturbances, poses a substantial threat to forest ecosystems and timber production. Beyond their negative ecological and economic impact, outbreaks of I. typographus may also play a positive ecological role, as the large-scale mortality of host trees alters habitat conditions and creates resource build-ups to which invertebrate communities respond positively. A recent and stark example of these remarkable dynamics occurred in the Italian Alps following the Vaia windstorm in autumn 2018. This catastrophic event led to the widespread destruction of over 40,000 hectares of forest, predominantly spruce stands, creating an unprecedented abundance of susceptible host material [1]. Such events are well-documented to favour bark beetle outbreaks by providing vast breeding grounds and weakening host tree defences [2]. As expected, a severe outbreak of I. typographus has consequently developed and is currently ongoing in the affected Alpine regions.
To control I. typographus infestations, combining various strategies via an Integrated Pest Management approach, while not entirely resolutive, is crucial to mitigate outbreak impact [2]. The removal of fresh dead wood material resulting from disturbances is paramount, as this material serves as prime breeding habitat for this beetle [3]. Furthermore, sanitary felling, the prompt removal of infested trees before new adult emergence, is a cornerstone tactic in an infested forest [4]. Trap trees, which can be broken, windthrown, or even standing trees, possibly lured with synthetic aggregation pheromones, are also used to attract adult beetles during reproduction. After oviposition, it is critical to remove and destroy this material to reduce subsequent population densities [3]. Since this method can be economically demanding, a more cost-effective alternative often employed is the mass-trapping of adult beetles using pheromone-baited traps. Various commercial pheromone attractants and trap designs are available for I. typographus, exhibiting varying degrees of efficacy [5].
Despite the common use of mass-trapping, which often yields a large number of captured beetles, evidence demonstrating its overall efficacy in significantly reducing new infestations remains debated and challenging to quantify [5]. While some studies have reported a decrease in new attacks in areas where mass-trapping was implemented [6], others indicate that traps may only intercept a minor fraction of the total bark beetle population [5,7]. This suggests that high trap catches do not always translate to a substantial reduction in damage [5]. Moreover, the use of pheromone traps presents potential side effects that warrant careful consideration. One significant concern is the “spill-over effect”, where traps attract a large number of insects to an area but fail to capture them all, potentially leading to an increase in new attacks near the traps where mass-trapping is implemented compared to areas not treated [5].
Furthermore, bark beetle pheromones are known to attract a diverse range of non-target saproxylic beetles, including natural enemies of bark beetles [8]. This incidental attraction of beneficial insects, particularly predators and parasitoids, raises concerns about potential negative impacts on the saproxylic community and the natural regulation of bark beetle populations. Several key predators of bark beetles, such as Thanasimus formicarius (Linnaeus, 1758) and T. femoralis (Zetterstedt, 1828) (Coleoptera: Cleridae), have been documented in I. typographus pheromone traps, albeit generally in low proportions [8,9,10,11,12,13,14]. Other coleopteran predators, including Nudobius lentus (Gravenhorst, 1806) (Staphylinidae) and Rhizophagus ferrugineus (Paykull, 1800) (Coleoptera: Monotomidae), have also been observed [10]. Among dipterans, predators in the genus Medetera Fischer von Waldheim, 1819 (Diptera: Dolichopodidae) have been reported [12,15]. Additionally, hymenopteran parasitoids, notably Tomicobia seitneri (Ruschka, 1924) (Hymenoptera: Pteromalidae) and Ropalophorus clavicornis (Wesmaël, 1835) (Hymenoptera: Braconidae), are attracted to I. typographus pheromones [16]. While these studies often report low proportions of natural enemy catches, a comprehensive assessment of the entire natural enemy complex within traps, specifically for I. typographus pheromone use, remains limited. To our knowledge, the study by Hellrigl and Schwenke [17] is the only one addressing the whole complex of by-catches, though their results were mostly limited to a checklist of non-target insects within this context.
The present study aimed to comprehensively assess the presence and composition of non-target insects in pheromone traps used during mass-trapping and monitoring of I. typographus in the Italian Alps. Particular attention was paid to identifying natural enemies of I. typographus to estimate the potential negative ecological effects of this widely implemented pest control practice.

2. Materials and Methods

2.1. Study Area and Trapping Activity of the Forest Managers

The study was conducted in 2024 within the Alta Badia valley, located in the Italian Eastern Alps, specifically in the Autonomous Province of Bolzano, South Tyrol. This region is characterised by extensive spruce forests, which were severely impacted by the Vaia windstorm in autumn 2018. Following this event, both monitoring and mass-trapping programs for I. typographus, the most significant bark beetle pest in the area, were initiated across South Tyrol by forest managers in spring 2019 and have continued in subsequent years. All traps utilised in both monitoring and mass-trapping programs were Theysohn type (MulitWit Bark Beetle Slit Trap, Witasek, Feldkirchen in Kärnten, Austria), lured with the commercial aggregation pheromone Pheroprax (Basf, Ludwigshafen, Germany). Traps were positioned on valley slopes that had been most severely affected by the bark beetle epidemic.
The Forest Service implemented two distinct trap setups for the monitoring and mass-trapping programs, which differed in the number of sites, trap configuration, and scheduling, as described below. Trapping stations (spot areas where traps were positioned) were at least 200 m distance from each other. Across the valley, a total of five sites (general areas where trap stations were located) were chosen by the Forest Service (Table 1). For the monitoring program of I. typographus flight activity, pheromone traps have been placed within the Alta Badia valley (1300–1700 m a.s.l.) by the operators from Forestry Service station “La Villa” (Forestry Department of the Autonomous Province of Bolzano), for a total of three monitoring stations on three different sites (three traps in total) (Table 1). Each year, throughout the beetle’s flight period, these traps were checked and emptied every 10 days. At each station, a trap was installed individually (monitoring setup), with its collection container at the bottom left empty of any additional substances (e.g., salt-water solution or insecticide). The data collected from these traps were primarily used by forest managers to construct flight curves and determine the number of beetle generations per year. For this purpose, I. typographus catches were estimated employing a volumetric estimation method, where 10 mL corresponds to approximately 400 beetle individuals.
For mass-trapping efforts, the same three sites as monitoring, plus two additional ones, were chosen by the forest managers in the same valley (1300–1800 m a.s.l.). One mass-trapping station was established in each site, except for Site 1, where two stations were set up. At each mass-trapping station (six in total), traps were installed in groups of three, arranged in a “cross” configuration (mass-trapping setup): two traps positioned side-by-side and a third centrally placed perpendicularly to them. These traps (18 in total) were equipped with collection containers that contained a solution of water and Witasek’s antismell trap salt (Witasek, Feldkirchen in Kärnten, Austria). This specific salt solution, a proprietary blend from Witasek, aims to prevent unpleasant odours and the decomposition of captured insects, facilitating their preservation until trap emptying. Each of the three traps for mass-trapping setups was individually equipped with one pheromone dispenser, resulting in a total of three dispensers per setup, thus increasing the overall pheromone concentration relative to the monitoring setups, which contained only a single trap with one dispenser. Unlike monitoring traps, these mass-trapping traps were emptied less frequently, generally only when their collection containers, which have a capacity of about 2 liters, were full. The primary objective of these mass-trapping traps was to contribute to the direct control of I. typographus populations by removing a significant number of individuals from the environment. In this case, total catches were not quantified.

2.2. Study Design and Sampling

The present study was conducted in 2024 in collaboration with operators from Forestry Service station “La Villa”. Samples were taken from traps used by the Forest Service for its activities of monitoring and mass-trapping. Traps in the monitoring stations were installed on 12 April 2024, while those in mass-trapping stations were placed in the field in May. The pheromone lures in the monitoring traps were replaced twice during the study period (27 May 2024 and 8 July 8 2024), and similarly, in the mass-trapping stations, lures were replaced twice (20 June 2024 and 8 August 2024).
In the three monitoring stations, insect samples were collected from 22 April 2024 to 29 August 2024, during the regular check dates (every 10 days). At each check date, 100 mL insect sample was randomly collected from the total insect catches of each trap using a calibrated measuring device. If the total catches in a trap were less than 100 mL, all captured insects were collected. Traps in mass-trapping stations were only emptied on three specific dates: 20 June 2024; 8 August 2024; and 4 September 2024. Due to the substantial volume of captured insects and the reduced frequency of sampling, on each of these dates, 250 mL samples were collected from each of the six stations. To ensure that samples were representative of the total trap contents, the material collected in each trap was thoroughly homogenized prior to sampling. This step was necessary to avoid potential biases resulting from vertical stratification of insects within the container, which could occur due to differences in body size, density, or time of capture. By mixing the entire contents before sampling, we aimed to obtain a more uniform and representative sample composition, minimizing methodological errors in subsequent analyses. All collected samples, from both monitoring and mass-trapping traps, were immediately preserved in 70% ethanol and transported to the laboratory for subsequent morphological examination.

2.3. Morphological Identification

While the number of I. typographus specimens was estimated using the volumetric method, all non-target insects in collected samples were counted in the laboratory. Morphological identification of non-target insects was performed in the laboratory using a stereomicroscope. All sampled coleopterans were identified at least at the Family level; only too degraded individuals were not identified. For other insect Orders, and for the challenging beetle Family Staphylinidae, specimen identification was focused on groups already known to be predators of bark beetles. For the identification of Cleridae, which are major predatory beetles of bark beetles, taxonomic keys from Thomaes et al. [18] and Öztürk and Yüksel [19] were utilised. Predators belonging to the Family Monotomidae were identified using keys from Peacock [20]. For the identification of other non-target bark beetle species, keys from Balachowsky [21] and Noblecourt [22] were consulted. For natural enemies belonging to Hymenoptera, keys by Bouček et al. [23] were used, while we referenced Oosterbroek [24] and Robinson and Vockeroth [25] for predators belonging to Diptera.

2.4. Statistical Analysis

To compare different percentages, the chi-square test was used (using Brandt and Snedecor formula in case of multiple comparisons), and to compare I. typographus catches from monitoring traps in different sites, the one-way analysis of variance (ANOVA), with “site” as a factor, was used. Statistical significance was set at α = 0.05, post hoc comparisons were conducted using Tukey’s Honestly Significant Difference (HSD) test to identify which specific group pairs were significantly different. Before statistical analysis, the data were evaluated for the assumptions of normality and homogeneity of variance. All statistical analyses were performed using IBM SPSS (Statistical Package for the Social Sciences) Statistics (Version 29.0.2.0, Armonk, NY, USA). Given the different number of traps in each setup, we used rarefaction and extrapolation techniques [26] to compare catches from the two trap types. This analysis was performed using Hill numbers, including species richness (q = 0), Shannon diversity (q = 1), and Simpson diversity (q = 2). The rarefaction and extrapolation curves were computed with the iNEXT online software, https://chao.shinyapps.io/iNEXTOnline/ (accessed on 23 August 2025) [27].

3. Results

During the trial period, an estimated 106,444 I. typographus individuals were sampled across three monitoring stations, and 180,000 from the six mass-trapping stations (Table 2). Total by-catches amounted to 16,362 individuals, 5.71% of the total sampled catches. They belonged to various Orders, but mainly to Coleoptera (52.44% of by-catches) and Hymenoptera (43.29%) (Table 2). Remarkably, as many as 7550 specimens (46.67% of these by-catches) were non-target bark beetles, and a very similar proportion—7640 specimens (46.69%)—were natural enemies of bark beetles. The remaining 7.14% were other insect categories, mainly coleopterans, dipterans, and hymenopterans.
The trapped non-target bark beetles belonged to 13 different species. Pityogenes chalcographus (Linnaeus, 1761) was the most abundant (about 95% of all non-target bark beetles), with 7,150 individuals, followed by Hylastes cunicularius Erichson, 1836 (146 individuals), and Pityogenes bistridentatus (Eichhoff, 1878) (Coleoptera: Curculionidae: Scolytinae) with 74 specimens (Table 2). Other species were caught in very low numbers, ranging from 2 to 50 specimens.
Natural enemies included predators from the Order Coleoptera (Families Cleridae, Elateridae, Histeridae, Staphylinidae, and Monotomidae) and the Order Diptera (Family Dolichopodidae), as well as parasitoids from the Order Hymenoptera (Families Pteromalidae and Braconidae). The most frequently caught species was the Pteromalidae parasitoid T. seitneri, accounting for 6784 individuals (88.80% of the natural enemy catches) (Table 2). The Braconidae R. clavicornis was the second most common hymenopteran natural enemy, with 299 specimens (3.91% of natural enemies). Although in lower proportions (7.29%), predators were also caught, in particular Coleoptera from the Cleridae and Staphylinidae Families, including T. femoralis and T. formicarius. Interestingly, some specimens of the Medetera genus were also identified.
Total catches of I. typographus (estimated with the volumetric method) in monitoring traps (the only trap type where estimations were performed) showed three distinct peaks, on 13 May 2024, on 17 June 2024, and on 18 July 2024, totaling 210,844 catches (70,281 per trap) over the entire monitoring period (Figure 1). Site 2 (Mon2), which had the highest infestation level, also showed the highest number of catches during the monitoring period (ANOVA, df = 51, F = 8.355, P < 0.001). In addition, this lower-altitude site (Table 1) is the only one with an I. typographus flight peak in springtime (Figure 1). Non-target catches (bark beetles excluded), after the spring period, mirrored the pattern of I. typographus catches, showing two peaks on 17 June 2024 and 29 July 2024. By-catch proportions were also higher in Site 2 compared to other sites (χ2 = 259.568, df = 2, P < 0.001).
The curve for species richness (q = 0) (Figure 2a) shows higher values in monitoring traps than in mass-trapping, yet their confidence intervals overlap. In addition, monitoring traps show higher values for Shannon diversity (q = 1) (Figure 2b). Both curves levelled off very quickly, suggesting that just a small number of caught individuals represented most of the diversity. Mass-traps show a more even distribution among the most common species, as indicated by the higher Simpson diversity (q = 2) (Figure 2c) than monitoring ones. Both curves in Figure 2d rise rapidly and reach near-complete coverage with only a small number of individuals. This indicates that both types of traps are highly efficient in capturing the most common species in the community.
There was a substantial difference in the proportions of non-target insects on the total sampled catches between traps used for mass-trapping and those used for monitoring (Figure 3). This proportion was significantly higher in mass-trapping (0.076) compared to monitoring (0.026) (χ2 = 2,218.439, df = 1, P < 0.001). This was true for all groups, natural enemies (χ2 = 2,170.018, df = 1, P < 0.001), non-target bark beetles (χ2 = 2,218.439, df = 1, P < 0.001), and other insects (χ2 = 96.209, df = 1, P < 0.001). This pattern held true even when both trap types were present at the same station (stations 1, 2, and 3). Specifically, for mass-trapping, the proportions of natural enemies per I. typographus catch were 0.030, 0.043, and 0.022, respectively, compared to 0.008, 0.016, and 0.003 for monitoring traps. Notably, five species were unique to the mass-trapping traps, while only one was missing from them, despite the higher overall species diversity observed in monitoring traps (Table 2).
Total catches in mass-traps were not directly estimated; however, an estimation can be derived based on monitoring trap data. Based on a mean of 70,281 I. typographus catches per monitoring trap over the entire period and apply a mean proportion of 0.038 natural enemies recorded in mass-traps, an estimated mean of 2661 natural enemies per mass-trap was observed. Given that 18 mass-traps were installed in the valley, this suggests that approximately 47,898 specimens of natural enemies and 1,265,058 I. typographus individuals were caught throughout the period.

4. Discussion

In 1985, Hellrigl and Schwenke [17], working in the same area and using the same pheromone traps, reported a relatively low percentage of natural enemies on the total catches. In contrast, our analysis revealed that approximately half of the captured by-catch were natural enemies of bark beetles. The attractive effect of pheromone traps on natural enemies of bark beetles, particularly predators, has been extensively documented in ecological and entomological research [28,29]. Despite this, a comprehensive review of the available literature indicates that no studies have previously reported in detail the capture of bark beetle parasitoids in pheromone traps, underscoring the novel contribution of our findings. Although some authors, such as Feicht [30], have stated that T. seitneri is very common in I. typographus pheromone-traps, quantitative data on these catches are not provided in their paper or in any other available source.

4.1. Predators

The observed Thanasimus spp. to I. typographus proportion in our study was 1:320, an intermediate value compared to those reported in the literature, ranging from 1:73 to 1:10,100 [11,12,13]. However, a significantly lower proportion (1:4640) was documented by Hellrigl and Schwenke [17] in the same study area. Unlike findings in other studies, where Thanasimus was the most abundant predator genus (e.g., Zurm [10] reported T. formicarius comprising 32% of all predators trapped with the same pheromone), Thanasimus species accounted for only about 9% of all predators in our study. Rove beetle specimens were well represented, especially the two genera Aleochara Gravenhorst, 1802 and Placusa Erichson, 1837 (Coleoptera: Staphylinidae), which are known to include bark beetle predators, with a combined total of 359 individuals. While Placusa has previously been reported in I. typographus pheromone traps [10], Aleochara was not, despite some species within this genus being known predators of Ips [29].
Among the catches, the dipteran genus Medetera was also identified. Pheromone components of I. typographus are known to affect these predator flies, which may use such cues to locate their prey [15]. Although species of this genus have been previously found in I. typographus pheromone traps in great numbers [12,15], only 19 individuals were recorded in our study. This number is considerably lower than that reported in other studies. However, these specimens were predominantly found in mass-traps and were often highly degraded, which may have led to an underestimation of their true abundance.

4.2. Parasitoids

The two parasitoid species identified, T. seitneri and R. clavicornis, are both known as endoparasitoids of adult bark beetles [29]. They are reported to prefer freshly attacked trees, and their attraction to bark beetle pheromones has been suggested [16]. Notably, T. seitneri exhibits a strict association with I. typographus [29]. In our study, T. seitneri was the third most frequently captured non-target species, with its abundance (6784 individuals) only slightly lower than that of P. chalcographus (7150 individuals), a species known for its strong attraction to I. typographus pheromones. Although some authors e.g., [30] have noted the frequent presence of T. seitneri in pheromone traps for I. typographus, quantitative data on the number of captures are notably absent from the literature.

4.3. Monitoring vs. Mass-Trapping Setup

A surprising result was the great difference in non-target catches between the two types of setups. When considering only monitoring stations, the percentage of non-target insects (excluding non-target bark beetles) was 1.00%, a figure comparable to that reported by Hellrigl and Schwenke [17] in the same area (0.95%). In contrast, this percentage significantly increased to 4.15% in mass-trapping stations. All groups of non-target insects (i.e., non-target bark beetle species, natural enemies, and other insect taxa) were more abundant in samples from mass-trapping stations than in samples from monitoring stations. However, this increase appeared more pronounced for natural enemies, which constituted 50.01% of all non-target species in mass-trapping stations versus 30.07% in monitoring stations.
This difference may be explained by several methodological and structural distinctions between mass-trapping and monitoring setups. First, mass-traps could have a higher attractiveness or capture efficiency. Mass-trapping setups were equipped with multiple pheromone dispensers, resulting in a higher overall concentration of the I. typographus aggregation pheromone. This likely enhanced the attraction radius and effectiveness of the traps. Contrary to findings elsewhere e.g., [13], this was not attributed to a broader spectrum of saproxylic insects sensitive to chemical cues, but rather to a higher number of catches for some species, given that the monitoring traps had a higher species diversity. While I. typographus attraction might also be enhanced in these traps, other insect species, in particular natural enemies, may exhibit varied responses to an increased pheromone dosage [31], thereby altering the ratio of target to non-target species.
Moreover, it is known that the presence of dead beetles and their dwell time in traps can reduce the pheromone attraction toward the target insect [32,33], and this could have happened in monitoring setups (dry traps) and not in mass-trapping setups because of the presence of the preservative liquid in their containers (Witasek’s antismell trap salt solution). This seems confirmed by the lower proportion of necrophagous insects in mass-trapping setups than in monitoring ones, which represented 3.07% and 0.32%, respectively, of all non-target beetles. This indicates that decaying catches can influence trap attraction, at least for some insect groups, even over short sampling intervals (10 days). However, this frequency might not be sufficient to have a negative influence on bark beetles. In fact, a higher proportion of bark beetles in samples from monitoring traps was observed. Anyway, a proper comparison was not possible as total I. typographus catches were not assessed for mass-traps. A future comparison between different sampling frequencies in dry traps may further clarify the effects of dwell time.
A second hypothesis is that traps could also differ in their capacity to retain captures. The presence of a preservative liquid in the mass-trapping containers (Witasek’s antismell trap salt solution) may have significantly reduced the chances of escape for smaller or more mobile individuals, which might otherwise escape from dry collection traps used for monitoring. In fact, this difference is more evident for T. seitneri, R. clavicornis, dipterans, and ants that can be considered more mobile insects. Regarding T. seitneri, it is reported that despite being highly attracted during mass-trapping, 80% of the specimens are able to escape capture [34]. On the other hand, I. typographus itself appears largely unable to escape traps, given that both dry and wet trap designs demonstrated similar efficiency in capturing this species [35]. Consequently, the higher retention of more mobile non-target insects in mass-trapping setups, combined with the consistent retention of the target species in both types of setups, could significantly shift the observed proportions between target and non-target catches.

5. Conclusions

Our study significantly contributes to the understanding of non-target insect by-catch in I. typographus pheromone traps, particularly within the context of varying trap methodologies. Here, we provide novel insights into the attraction of bark beetle parasitoids, specifically T. seitneri and R. clavicornis, to I. typographus pheromones, with T. seitneri emerging as a remarkably abundant by-catch species. This discovery fills a significant gap in the literature, which has predominantly focused on predatory by-catch. Furthermore, our findings highlight a substantial difference in non-target catches between monitoring and mass-trapping setups. These results underscore the critical need for new studies regarding the ecological impact of pheromone trapping on beneficial insect populations, particularly in the context of natural enemies’ conservation. Trap design, and lure compounds may be then improved to address specific non-targets and their conservation. Finally, the timing of deployment should also be considered when planning trapping programs for I. typographus, since each site may present unique conditions that can be used to minimize impacts on non-target species. In our study, the lowest-altitude site showed a notable I. typographus flight activity in spring, a period when very few non-targets were captured. This suggests that, at this particular site, spring could be a suitable season for intensified trapping without harming non-target insect communities.
Considering the ongoing discussions regarding the overall efficacy of mass-trapping in significantly reducing I. typographus infestations [5], and the notable number of beneficial natural enemies incidentally captured, the widespread application of this method warrants careful consideration. Our study, for instance, estimated—based on the proportion of natural enemies on the total estimated catches from all traps, (see Results)—a substantial by-catch of approximately 48,000 natural enemy specimens in the Badia Valley alone. This removal of insects that are crucial for natural pest regulation, alongside the varying evidence of direct pest reduction, suggests a need for a balanced approach to pest management strategies. In addition, considering that disturbances like bark beetle outbreaks can enhance biodiversity by creating dead wood and altering canopy structure [36,37], there is a high probability that these traps will capture a wide range of saproxylic insects. This raises the concern that, in addition to common by-catch, the traps may incidentally capture rare or endangered species that benefit from the new ecological conditions. Further studies are essential to clarify the precise long-term ecological and economic implications of such by-catch, particularly with respect to population densities of parasitoids and predators affecting bark beetles. This kind of knowledge may help in exploring and developing new methods to minimize non-target captures in future applications.

Author Contributions

Conceptualization, T.P. and M.B.; methodology, T.P. and M.B.; formal analysis, T.P. and M.B.; investigation, T.P., A.M., L.T. and M.B.; data curation, T.P., A.M., L.T. and M.B.; writing—original draft preparation, T.P. and M.B.; writing—review and editing, T.P. and M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We thank the staff of the Forest Service of the Autonomous Province of Bolzano for their support and valuable assistance in the collection of specimens. We are also grateful to the experts from entomologiitaliani.net for their assistance with the identification of several beetle species, particularly Davide Pedersoli and Marco Bastianini for their help with the Family Carabidae, and Edoardo Pulvirenti for his contribution regarding the Family Elateridae. Finally, we also extend our gratitude to our colleagues Antonio Belcari, Patrizia Sacchetti (University of Florence), and Marc Pollet (Royal Belgian Institute of Natural Sciences) for their valuable advice on Dolichopodidae (Diptera).

Conflicts of Interest

The authors declare no conflicts of interest.

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Forests 16 01510 g001
Figure 1. (a) Ips typographus (Linnaeus) flight curves based on total estimated trap catches in monitoring traps, and (b) non-target catches (bark beetles excluded) obtained from 100mL samples collected every 10 days from the same monitoring traps. Monitoring trap identifiers are Mon1, Mon2, and Mon3.
Figure 1. (a) Ips typographus (Linnaeus) flight curves based on total estimated trap catches in monitoring traps, and (b) non-target catches (bark beetles excluded) obtained from 100mL samples collected every 10 days from the same monitoring traps. Monitoring trap identifiers are Mon1, Mon2, and Mon3.
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Forests 16 01510 g002
Figure 2. Size-based rarefaction (solid lines) and extrapolation curves (dashed lines) representing species diversity for Hill numbers of order q = 0 (a), q = 1 (b), and q = 2 (c). (d) Plot of sample coverage for rarefied samples (solid line) and extrapolated samples (dashed line) as a function of sample size. mas = mass-trapping traps, mon = monitoring traps.
Figure 2. Size-based rarefaction (solid lines) and extrapolation curves (dashed lines) representing species diversity for Hill numbers of order q = 0 (a), q = 1 (b), and q = 2 (c). (d) Plot of sample coverage for rarefied samples (solid line) and extrapolated samples (dashed line) as a function of sample size. mas = mass-trapping traps, mon = monitoring traps.
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Forests 16 01510 g003
Figure 3. Percentages (pie charts) and number (bar charts) of non-target insect specimens in all samples collected, separated by group, in monitoring (a) and mass-trapping (b) stations. Monitoring trap identifiers are Mon1, Mon2, Mon3; mass-trap identifiers are Mass 1, Mass 2, etc.
Figure 3. Percentages (pie charts) and number (bar charts) of non-target insect specimens in all samples collected, separated by group, in monitoring (a) and mass-trapping (b) stations. Monitoring trap identifiers are Mon1, Mon2, Mon3; mass-trap identifiers are Mass 1, Mass 2, etc.
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Table 1. Sites and traps included in the study, from which samples were obtained. The table provides the abbreviated name assigned to each station.
Table 1. Sites and traps included in the study, from which samples were obtained. The table provides the abbreviated name assigned to each station.
SitesCoordinatesMean Altitude m a.s.l.Monitoring Trapping StationsMass-Trapping Stations
Site 1N46.578903 E11.9103831600Mon1Mass1A
Mass1B
Site 2N46.628673 E11.8989671300Mon2Mass2
Site 3N46.548217 E11.9686401700Mon3Mass3
Site 4N46.568657 E11.8923621500 Mass4
Site 5N46.528091 E11.8837751800 Mass5
Table 2. List of insect species collected in mass-trapping and monitoring traps throughout the study period.
Table 2. List of insect species collected in mass-trapping and monitoring traps throughout the study period.
OrderFamily/SubfamilySpeciesMonitoring SetupMass-Trapping Setup
Target species
ColeopteraCurculionidae ScolytinaeIps typographus (Linnaeus)106,444180,000
Other bark beetles
ColeopteraCurculionidae ScolytinaeCryphalus asperatus Gyllenhal19
Cryphalus intermedius Ferrari02
Crypturgus cinereus (Herbst)124
Crypturgus pusillus (Gyllenhal)13
Dryocoetes autographus (Ratzeburg)123
Hylastes cunicularius Erichson31115
Hylurgops palliatus (Gyllenhal)11
Orthotomicus erosus (Wollaston)06
Phthorophloeus spinulosus Rey513
Pityogenes bistridentatus (Eichhoff)1262
Pityogenes chalcographus (Linnaeus)15945556
Polygraphus poligraphus (Linnaeus)140
Trypodendron lineatum (Olivier)842
Other Scolytinae02
Natural enemies
ColeopteraCarabidaeOcydromus tibialis (Duftschmid)10
CarabidaeOcydromus deletus deletus (Audinet-Serville)01
CleridaeThanasimus femoralis (Zetterstedt)1511
CleridaeThanasimus formicarius (Linnaeus)124
CleridaeTrichodes sp.01
ElateridaeAthous (Haplathous) subfuscus (Müller)012
ElateridaeMelanotus castanipes (Paykull)02
HisteridaePlegaderus vulneratus (Panzer)23
Histeridae spp. 76
MonotomidaeRhizophagus ferrugineus (Paykull)515
MonotomidaeRhizophagus nitidulus (Fabricius)04
NitidulidaePityophagus ferrugineus (Linnaeus)14
NitidulidaeEpuraea sp.118
StaphylinidaeNudobius lentus (Gravenhorst)1139
StaphylinidaePlacusa sp.5146
StaphylinidaeAleochara sp.18622
TenebrionidaeCorticeus sp.27
DipteraDolichopodidaeMedetera sp.118
HymenopteraBraconidaeRopalophorus clavicornis (Wesmael)8291
PteromalidaeTomicobia seitneri (Ruschka)5786206
Other insects
ColeopteraAnobiidae Ernobius sp.01
Anobiidae Hadrobregmus pertinax (Linnaeus)13
Buprestidae sp. 01
CerambycidaeAcanthocinus griseus (Fabricius)26
CerambycidaeCallidium violaceum (Linnaeus)01
CerambycidaeClytus lama Mulsant01
Ciidae spp. 13
Curculionidae spp. 22
Dermestidae spp. 22
ElateridaeAmpedus scrofa (Germar)20
Ampedus nigrinus (Herbst)01
Athous (Athous) vittatus (Fabricius)11
Cardiophorus ruficollis (Linnaeus)141
Dalopius marginatus (Linnaeus)01
Elateridae spp. 27
LycidaePlatycis minutus (Fabricius)10
Melyridae spp. 30
Mordellidae spp. 2710
Nitidulidae spp. 231
ScarabaeidaeHoplia argentea (Poda)10
ScarabaeidaeAphodius sp.22
SilphidaeNecrodes littoralis (Linnaeus)01
SilphidaeNicrophorus vespillo (Linnaeus)31
SilphidaeNicrophorus vespilloides Herbst3525
SilphidaeOiceoptoma thoracicum (Linnaeus)338
SilphidaeThanatophilus rugosus (Linnaeus)23
SilphidaeThanatophilus sinuatus (Fabricius) 116
Silvanidae spp. 03
Staphylinidae spp. 60110
Trogossitidae spp. 03
Coleoptera spp. 1915
Blattodea spp. 11
Dermaptera spp. 017
Diptera spp. 18392
Embioptera spp. 04
Hemiptera spp. 240
HymenopteraApidae spp. 35
Chrysididae spp. 32
Formicidae spp. 3165
Siricidae spp. 12
Sphecidae spp. 05
VespidaeVespula vulgaris (Linnaeus)04
Hymenoptera spp. 05
Lepidoptera spp. 30
Mecoptera spp. 02
Raphidioptera spp. 01
Total 274013,622
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Bracalini, M.; Martini, A.; Tagliaferri, L.; Panzavolta, T. Impact of Trapping Programs for Ips typographus (Linnaeus) (Curculionidae: Scolytinae) on Predators, Parasitoids, and Other Non-Target Insects. Forests 2025, 16, 1510. https://doi.org/10.3390/f16101510

AMA Style

Bracalini M, Martini A, Tagliaferri L, Panzavolta T. Impact of Trapping Programs for Ips typographus (Linnaeus) (Curculionidae: Scolytinae) on Predators, Parasitoids, and Other Non-Target Insects. Forests. 2025; 16(10):1510. https://doi.org/10.3390/f16101510

Chicago/Turabian Style

Bracalini, Matteo, Andrea Martini, Lorenzo Tagliaferri, and Tiziana Panzavolta. 2025. "Impact of Trapping Programs for Ips typographus (Linnaeus) (Curculionidae: Scolytinae) on Predators, Parasitoids, and Other Non-Target Insects" Forests 16, no. 10: 1510. https://doi.org/10.3390/f16101510

APA Style

Bracalini, M., Martini, A., Tagliaferri, L., & Panzavolta, T. (2025). Impact of Trapping Programs for Ips typographus (Linnaeus) (Curculionidae: Scolytinae) on Predators, Parasitoids, and Other Non-Target Insects. Forests, 16(10), 1510. https://doi.org/10.3390/f16101510

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