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Article

Electrophysiology and Behavior of Tomicus yunnanensis to Pinus yunnanensis Volatile Organic Compounds Across Infestation Stages in Southwest China

1
College of Resources, Environment, and Chemistry, Chuxiong Normal University, Chuxiong 675099, China
2
Key Laboratory of Forest Disaster Warning and Control in Yunnan Province, College of Biodiversity and Conservation, Southwest Forestry University, Kunming 650224, China
3
Guangxi Zhuang Autonomous Region State-Owned Dongmen Forest Farm, Chongzuo 532200, China
4
Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Kunming 650224, China
*
Authors to whom correspondence should be addressed.
Forests 2025, 16(7), 1178; https://doi.org/10.3390/f16071178
Submission received: 2 June 2025 / Revised: 10 July 2025 / Accepted: 12 July 2025 / Published: 17 July 2025
(This article belongs to the Section Forest Health)

Abstract

Tomicus yunnanensis Kirkendall and Faccoli, a native bark beetle species and key pest of Pinus yunnanensis Franch. in southwestern China, relies on host-derived volatile organic compounds (VOCs) for host selection. To unravel these mechanisms, we collected VOCs from P. yunnanensis trunks across four infestation stages (healthy, early-infested, weakened, near-dead) using dynamic headspace sampling. Chemical profiling via gas chromatography–mass spectrometry (GC-MS) identified 51 terpenoids, with α-pinene as the most abundant component. VOC profiles differed markedly between healthy and early-infested trees, while gradual shifts in compound diversity and abundance occurred from the weakened to near-dead stages. Bioactive compounds were screened using gas chromatography–electroantennographic detection (GC-EAD) and a Y-tube olfactometer. Electrophysiological responses in T. yunnanensis were triggered by α-pinene, β-pinene, 3-carene, 2-thujene, and 4-allylanisole. Behavioral tests revealed that α-pinene, 3-carene, and 2-thujene acted as attractants, whereas β-pinene and 4-allylanisole functioned as repellents. These results indicate that infestation-induced VOC dynamics guide beetle behavior, with attractants likely promoting host colonization during early infestation and repellents signaling deteriorating host suitability in later stages. By mapping these chemical interactions, our study identifies potential plant-derived semiochemicals for targeted pest management. Integrating these compounds with pheromones could enhance the monitoring and control strategies for T. yunnanensis, offering ecologically sustainable solutions for pine ecosystems.

1. Introduction

Volatile organic compounds (VOCs) released by host plants serve not only as cues for host identity [1,2,3] but also as dynamic indicators of physiological status and defense capacity, playing a pivotal role in bark beetle host selection [4,5,6]. In conifer species such as Pinus yunnanensis, changes in VOC emissions can reflect gradients of health, from healthy to stressed, weakened, or near-dead, and are closely linked to both primary metabolism and inducible defense responses [7,8]. These volatile signatures form a complex and highly informative “chemical fingerprint” that bark beetles, particularly pioneering individuals, rely on to evaluate host suitability from a distance [9,10]. These individuals make host choices before aggregation pheromones are released, relying entirely on VOC cues to assess host quality. Specific monoterpenes, including α-pinene, β-pinene, and 3-carene, have been shown to vary significantly in concentration and proportion across tree health conditions [11,12]. For Tomicus yunnanensis, the ability to discriminate among VOC blends emitted at different host infestation stages is likely critical to successful colonization. This chemoecological specialization targets physiologically weakened hosts with reduced defensive capacities (e.g., lowered resin production), which are preferentially colonized due to their diminished resistance and heightened suitability for brood development. By selectively attacking compromised trees, bark beetles optimize reproductive efficiency, minimizing energy expenditure in overcoming defenses in healthy hosts while maximizing offspring survival, an evolutionary strategy that balances resource allocation and fitness [13]. Thus, host selection in bark beetles exemplifies a finely tuned sensory adaptation shaped by ecological pressures to exploit vulnerable hosts within heterogeneous plant populations.
Tomicus yunnanensis (Coleoptera: Curculionidae: Scolytinae: Hylurgini), a newly recognized species within the genus Tomicus, is the most devastating wood-boring pest of Pinus yunnanensis in southwestern China [14,15,16]. Initially misclassified as T. piniperda, a species native to Northeast China and Eurasian forests, genetic divergence and morphological distinctions (e.g., elytral punctures and granulation patterns) have confirmed its taxonomic independence, leading to its formal designation as T. yunnanensis [17,18,19]. This beetle exhibits unique ecological adaptations: newly emerged adults infest healthy pine shoots for nutritional maturation, weakening trees prior to reproduction [20,21]. Sexually mature adults then colonize stressed or weakened pines, tunneling into the phloem to lay eggs, where larval development, pupation, and emergence occur, ultimately killing the host. Its life cycle comprises three phases: shoot infestation, trunk infestation, and morning-biased dispersal, with mating, oviposition, and brood development confined to the trunk [22]. Unlike many scolytines, T. yunnanensis combines shoot-feeding behavior (rare in Tomicus spp.) with trunk colonization, a dual strategy that exacerbates pine mortality by sequentially compromising tree vitality and exploiting declining defenses. This life history underscores its ecological specialization and pest status within P. yunnanensis ecosystems.
Within this background, the behavioral transition of T. yunnanensis raises a critical ecological question: how do beetles precisely identify compromised hosts during their shift from shoot-feeding to trunk colonization? To investigate the chemical mechanisms underlying this host discrimination, we systematically analyzed VOCs emitted by P. yunnanensis trunks across distinct infestation stages. Using dynamic headspace sampling, we captured VOCs from trees representing gradients of physiological stress (healthy, early-infested, weakened, near-dead). We aimed to address the following questions: (i) How do volatile emissions from P. yunnanensis vary across different infestation levels? (ii) Which volatile compounds exhibit biological activity against T. yunnanensis? (iii) How does T. yunnanensis respond to these bioactive compounds? By unraveling these chemoecological interactions, our study advances mechanistic models of T. yunnanensis host selection, offering insights for developing semiochemical-based strategies to disrupt infestation behavior and enhance pest management in P. yunnanensis ecosystems.

2. Materials and Methods

2.1. Insect Collection and Species Identification

The adults of T. yunnanensis used in this experiment were collected from Jiulong Mountain Forest Farm in Zhanyi County, Qujing City, Yunnan Province (25°0′35″ N, 103°7′15″ E). The samples were readily distinguishable by granules or punctures on the second interstria along the declivity, as well as the lengths of elytral interstrial hairs and hairs arising from punctures [19]. Female and male individuals were distinguished by the shape (semicircular vs. rectangular) and size (large vs. small) of the last abdominal tergites [19,23]. In addition, live beetles were sexed based on the chirps produced by the male stridulatory apparatus [23]. Finally, live beetles of female adults identified in this study were temporarily stored in vials in a fridge at 4 °C.

2.2. VOC Extraction and Characterization in Pinus yunnanensis Across Infestation Stages

Following the classification criteria for P. yunnanensis infestation stages (Table 1), we selected five trees per category: healthy, early-infested, weakened, and near-dead. Sampling was conducted in Jiulong Mountain Forest Farm, a secondary forest consisting of naturally regenerated stands rather than plantation-derived trees. The study area includes both pure P. yunnanensis stands and mixed stands of P. yunnanensis and broad-leaved species. For consistency, all sampling was performed exclusively within pure P. yunnanensis stands. Trees were classified into four categories based on infestation status, and representative samples were collected from each category. To minimize spatial autocorrelation, a minimum distance of 2 m was maintained between sampled trees within each category. Trees selected for volatile collection were undisturbed by human activity and measured an average height of 5 ± 0.3 m and diameter of 8 ± 0.5 cm. Trunk volatiles were collected using a dynamic headspace sampling system. Each trunk was enclosed in an odorless transparent polyethylene bag (PTEK, Wursthüllen, Kempten, Germany), with purified air supplied at 400 mL/min through an activated charcoal filter (ORBO™-32, Supelco, Bellefonte, PA, USA). Volatiles were adsorbed onto 120 mg of Porapak Q (50–80 mesh, Supelco, USA) at the outlet, maintained at a flow rate of 300 mL/min for 12 h. Post-collection, trapped compounds were eluted with 300 μL of chromatography-grade n-hexane (Tedia, Fairfield, OH, USA) into 2 mL amber glass vials (Agilent, Santa Clara, CA, USA; PTFE-lined) and concentrated under nitrogen gas to a final volume of 100 μL. The final extracts were stored at −20 °C until GC-MS analysis. This protocol ensured standardized VOC capture across infestation stages while minimizing contamination, enabling robust comparative profiling of host-derived chemical cues.
Volatile compound analysis was performed using an Agilent HP7820A/5977B GC-MS system. Samples (1 μL) were injected in split mode at a 30:1 ratio and separated on an HP-5MS capillary column (Agilent, Santa Clara, CA, USA) (30 m × 0.25 mm × 0.25 μm) under ultra-high purity helium carrier gas flowing at 1.0 mL/min (10 psi head pressure). The oven temperature program was initiated at 40 °C (2 min hold), followed by a 5 °C/min ramp to 280 °C (5 min hold). MS detection utilized electron ionization (70 eV) with an ion source temperature of 230 °C and a mass scan range of m/z 50–600. Compounds were identified by matching the mass spectra to the NIST 98 library, comparing retention indices with published standards. Compounds were considered positively identified when the match quality was ≥85% and confirmed against the literature data [24]. This protocol ensured robust compound characterization while maintaining analytical reproducibility across samples.

2.3. Identification of Semiochemicals Mediating Behavioral Responses in Tomicus yunnanensis

Antennal electrophysiological responses of T. yunnanensis were analyzed using gas chromatography–electroantennographic detection (GC-EAD) [25]. Beetle heads were excised and mounted on a micromanipulator, with a glass reference electrode inserted into the hemolymph cavity and a recording electrode positioned to enclose the antennal club. Both electrodes contained Ag/AgCl wires immersed in Ringer’s solution to ensure electrical continuity. A humidified airstream (400 mL/min) continuously delivered volatiles to the antenna. Samples (2.0 μL) were injected into the GC inlet (split 1:1) via a quadri-port manifold, directing one stream to the GC column and the other through a heated transfer line (260 °C) to the antennal preparation. The GC parameters matched those of the GC-MS system (HP-5MS column, splitless mode, identical temperature program). Signals were amplified using an Autospike system (v3.6, Syntech, Kirchzarten, Germany), visualized in real-time, and recorded for analysis. Biological replicates comprised 5–8 trials to account for intraspecific variability. This setup enabled the precise correlation of antennal responses with specific volatile compounds eluting from the GC column.
The behavioral preferences of T. yunnanensis were assessed using a Y-tube olfactometer with an internal diameter of 2.0 cm. The main arm of the device was 6 cm long, and each side arm was 12 cm long, forming a 75-degree angle between them. The Y-tube olfactometer was placed at room temperature and 65% relative humidity, and all experiments were conducted in complete darkness. The compounds used for detection were purchased from Beijing Bailingwei Technology Co., Ltd. (Beijing, China), with a purity of chromatographic grade. A volume of 40 μL of each compound (0.45 mg/L), along with 40 μL of dichloromethane as the control, was applied to glass wool. After a 5 min equilibration at room temperature, the prepared samples were loaded into spherical chambers connected to the arms of the Y-tube. Purified, humidified air (300 mL/min, charcoal-filtered) was delivered into the release tubes containing the beetles. Each trial lasted 5 min; a beetle was considered to have made a choice when it entered a lateral arm and reached or passed its midpoint. Individuals failing to respond within this period were recorded as non-responders and excluded from the analysis. Each compound was tested across five biological replicates (30 beetles per replicate). To mitigate positional bias, the Y-tube was replaced, cleaned with ethanol, and oven-dried at 100 °C after every 30 beetles. Tested beetles were discarded to prevent habituation. The choice rate for each option was calculated as the ratio of the number of beetles that made a specific choice to the total number of tested individuals. This protocol ensured standardized odor delivery, minimized environmental interference, and accounted for individual behavioral variability.

2.4. Data Analyses

Principal component analysis (PCA) was performed on the volatile compounds collected across different infestation stages using the FactoMineR package (v2.6) in RStudio (R v4.0.5), and the results were visualized using the ggplot2 package (v3.4.2). Raw electrophysiological data from T. yunnanensis antennal recordings were processed in OriginPro 2023 (OriginLab, Northampton, MA, USA), where baseline correction and low-pass filtering were applied to synchronize electroantennogram (EAG) and flame ionization detector (FID) signals. Processed datasets were integrated to produce antennal electrophysiograms, correlating compound elution profiles with antennal responses. Behavioral assay data from the Y-tube olfactometer were analyzed using Welch’s unequal variances t-test to address heteroscedasticity, with the results visualized in GraphPad Prism v8.0.2 (GraphPad Software, San Diego, CA, USA). This workflow ensured rigorous statistical validation of chemoecological interactions while maintaining reproducibility across analytical platforms.

3. Results

3.1. VOC Profiling in Pinus yunnanensis Across Infestation Stages

GC-MS analysis of trunk volatiles from P. yunnanensis across four infestation stages identified 51 VOCs, predominantly terpenoids and ketones. Healthy trees emitted 25 VOCs, dominated by α-pinene, followed by β-pinene, 3-carene, and sabinene. Early-infested trees released 26 VOCs, with α-pinene surpassing 3-carene and β-pinene as the primary component. Weakened trees exhibited 19 VOCs, retaining α-pinene as the dominant form but with elevated 3-carene. Near-death trees emitted 25 VOCs, where α-pinene remained prevalent, but β-pinene increased sharply to 14.6%, indicating late-stage chemical shifts.
Comparative analysis of the VOCs emitted by P. yunnanensis trunks across four infestation stages revealed terpenoids as the dominant chemical class, with α-pinene constituting 72.9%–83.9% of the total volatiles. In healthy trees, α-pinene (78.1%) predominated, followed by β-pinene (9.7%) and sabinene (also known as 2-thujene; 3.1%). During early infestation, α-pinene levels remained stable (78.5%), but sabinene decreased by 2.3%. Weakened trees exhibited a 5.3% increase in α-pinene (peaking at 83.9%) alongside a 9.0% decline in β-pinene (3.3%). Notably, β-pinene surged to 14.6% in near-death trees. Principal component analysis (PCA) demonstrated a pronounced VOC compositional shift between healthy and early-infested stages (PC1: 35.2% variance), whereas weakened to near-death stages showed gradual variation in compound diversity and abundance (PC2: 23% variance) (Figure 1).

3.2. Behavioral Bioassays of Tomicus yunnanensis to Semiochemicals: Attraction and Repellency Mediated by Host-Derived Volatiles

GC-EAD was used to identify antennally active VOCs emitted by P. yunnanensis trunks across four infestation stages: healthy, early-infested, weakened, and near-death. Female T. yunnanensis exhibited stage-specific electrophysiological responses to five terpenoids: α-pinene, 4-allylanisole, 3-carene, β-pinene, and 2-thujene (Figure 2). In healthy trees, antennal responses were triggered exclusively by α-pinene and 4-allylanisole (Figure 2A). During early infestation, 3-carene elicited additional responses alongside these two compounds (Figure 2B). Weakened trees evoked the broadest sensitivity, with responses to all five volatiles (Figure 2C), while near-death trees retained reactivity to α-pinene, 4-allylanisole, and 2-thujene (Figure 2D). Both α-pinene and 4-allylanisole elicited consistent antennal activity across all infestation stages, suggesting their role as core host recognition cues. 3-Carene responses emerged during early infestation and peaked in weakened trees, aligning with host stress escalation. β-Pinene sensitivity was limited to the weakened stage, potentially signaling optimal colonization conditions, whereas 2-thujene reactivity intensified in the terminal stages. This dynamic response profile reflects adaptive chemosensory tuning in T. yunnanensis, enabling the precise discrimination of host physiological states through stage-dependent modulation of VOC blends.
Behavioral responses of T. yunnanensis to the five electrophysiologically active compounds were evaluated using a Y-tube olfactometer (Figure 3). The results demonstrated distinct attraction–repellency dichotomies: α-pinene, 3-carene, and 2-thujene significantly attracted beetles (attraction rates: 62%, 54%, and 51%, respectively), whereas β-pinene and 4-allylanisole exhibited strong repellency (repellency rates: 56% and 52.67%).

4. Discussion

4.1. Volatile Compound Composition in Pinus yunnanensis

Pinus yunnanensis, similar to other Pinus species, emits a diverse array of volatile organic compounds (VOCs), primarily monoterpenes, whose composition and abundance vary depending on tissue type, physiological condition, and extraction method [26,27]. Early studies using steam distillation identified α-pinene and β-pinene as dominant compounds, jointly comprising over 70% of total emissions [28,29]. Subsequent analyses using solvent extraction also confirmed the prevalence of terpenoids in needles, shoots, and phloem tissues [30,31]. In the present study, 51 VOCs were identified, with monoterpenes accounting for 96.98% of the total shoot volatiles. Unlike earlier methods, the dynamic headspace collection technique applied here offers a more ecologically relevant profile of VOCs under field conditions. This approach captures behaviorally active compounds involved in host recognition and colonization by T. yunnanensis, thereby offering critical insights into chemically chemoecological interactions and chemically mediated host selection mechanisms [32,33,34].
Previous studies have demonstrated that the odorant-binding protein TyunOBP6 is highly expressed in the antennae of T. yunnanensis, exhibiting strong binding affinity to both α-pinene and β-pinene [35]. In the present study, these two monoterpenes were consistently detected at high relative abundances across all infestation stages of P. yunnanensis and elicited clear electrophysiological and behavioral responses. These findings confirm that α-pinene and β-pinene may serve as key semiochemicals involved in the host selection process of T. yunnanensis. However, significant changes were observed in the concentrations of α-pinene, β-pinene, and 3-carene in P. yunnanensis across different stages from the healthy to the near-dead stage. α-Pinene consistently exhibited a high relative abundance across all infestation stages. Notably, its concentration increased from 78.1% in healthy trees to 83.9% in weakened trees; it may reflect an induced chemical defense response against biotic stressors such as bark beetle invasion [36]. As one of the most abundant monoterpenes in conifer resins, α-pinene is known to deter insect colonization and inhibit pathogen growth [7,37]. The upregulation of terpene synthase genes under attack or stress likely contributes to this elevated emission, as trees shift metabolic investment toward secondary defense compounds [38]. At the same time, α-pinene, as a precursor of bark beetle pheromones [39,40], can be utilized by pioneer individuals after host invasion to synthesize aggregation pheromones, thereby attracting additional conspecifics to colonize the host. However, in near-dead trees, α-pinene levels declined to 72.9%, accompanied by a marked increase in β-pinene. This trajectory reveals α-pinene as a constitutive defense compound, whereas β-pinene dynamics correlate with infestation progression, and β-pinene accumulation may signal advanced host degradation. This compositional shift may serve as a deterrent to subsequent colonizers, preventing overcrowding and exemplifying an adaptive strategy to avoid excessive intraspecific competition [41,42].
The content of 3-carene also increased significantly during the early infestation and weakened stages, and behavioral assays confirmed its attractiveness to T. yunnanensis adults. Studies have shown that the attractiveness of 3-carene is significantly enhanced when combined with α-pinene, compared to 3-carene alone [21,43]. This combination, characterized by simultaneous increases in both α-pinene and 3-carene, appears to signal a host condition conducive to reproduction [44]. In contrast, previous studies have indicated that Tomicus minor exhibits lower sensitivity to 3-carene, whereas T. yunnanensis shows strong behavioral responses [18]. This interspecific difference in olfactory sensitivity contributes to spatial niche separation on the trunks of P. yunnanensis, with T. minor predominantly colonizing the lower to middle sections and T. yunnanensis occupying the middle to upper sections, thereby minimizing direct competition [22]. In addition, 2-thujene, a minor monoterpene in the volatile profile of P. yunnanensis, also demonstrated attractant properties in this study. The increased presence of 2-thujene may represent a stress-induced defensive response of the host tree following beetle attack [45]. T. yunnanensis may exploit this compound as an early signal to locate trees in the initial stages of decline, thus gaining a reproductive advantage by securing resources ahead of competitors. Overall, the dynamic fluctuations in α-pinene, β-pinene, and 3-carene not only reflect the physiological state of the host tree but also serve as critical semiochemicals mediating both intra- and interspecific communication among bark beetles. Further research into the temporal and quantitative patterns of these compounds may facilitate the development of “spatiotemporal regulation” strategies for bark beetle management.

4.2. Functional Role of 4-Allylanisole in Mediating Host Selection of Tomicus yunnanensis

4-Allylanisole, an aromatic volatile compound naturally occurring in both host and non-host plants, has been widely documented for its inhibitory effects on bark beetle behavior, notably in suppressing their attraction to primary host tree volatiles [46,47,48]. In this study, the relative concentration of 4-allylanisole in P. yunnanensis trunks progressively declined with escalating levels of tree damage. Concurrently, T. yunnanensis exhibited consistent avoidance behavior toward trunk volatiles across all infestation stages, further supporting the inhibitory role of 4-allylanisole in host selection among Tomicus species. While α-pinene remains a critical attractant in host location [34,46,47,49], its efficacy is significantly reduced when combined with 4-allylanisole, as demonstrated in T. piniperda bioassays [48]. This suggests that 4-allylanisole disrupts beetle chemoreception, potentially masking key monoterpenes such as α-pinene and β-pinene, thereby impairing orientation and host-finding capabilities.
In a parallel unpublished study, we identified 4-allylanisole as a dominant volatile compound emitted by Alnus ferdinandi-coburgii Schneid., a non-host plant of T. yunnanensis. Our behavioral assays demonstrated strong avoidance responses by T. yunnanensis toward this compound, aligning with its classification as a non-host deterrent. These results position A. ferdinandi-coburgii as a potential candidate for the ecological management of T. yunnanensis. Given the potent repellent properties of 4-allylanisole, this compound could enhance semiochemical-based strategies, particularly in “push–pull” systems. By integrating 4-allylanisole as a “push” agent—either alone or combined with attractants—it could deter beetle colonization of susceptible P. yunnanensis stands, thereby mitigating aggregation and subsequent tree damage.

4.3. Ecological Roles of VOCs in Tomicus yunnanensis Chemical Ecology

Both current and prior studies confirm that key monoterpenes, including α-pinene, β-pinene, β-phellandrene, and 3-carene, exert bioactive effects on T. yunnanensis, mirroring their utility in chemical ecology systems of related bark beetles (Dendroctonus spp., Ips spp., and Tomicus minor) [27,30,50,51]. However, T. yunnanensis displays distinct behavioral responses to these compounds. For instance, Li et al. 1993 reported an attraction rate of 95% to α-pinene and 3-carene in laboratory bioassays, yet field trials with these compounds alone were ineffective in capturing beetles [51]. Yin et al. 2002 further demonstrated that while individual monoterpenes (e.g., α-pinene, β-pinene) lacked efficacy, a blended ratio (20.6:4.7:6.6:1 of α-pinene, β-pinene, β-phellandrene, and 3-carene) achieved an attraction rate of 60.5% [30]. Stage-specific responses were also observed: during shoot-boring phases, beetles were drawn to shoot volatiles dominated by α-pinene (29.20%) and β-phellandrene (30.52%) while avoiding trunk volatiles rich in α-pinene (81.01%) and 3-carene (6.66%) [27]. These findings underscore that T. yunnanensis host selection is mediated not by single compounds but by synergistic interactions among volatiles, dependent on both composition and concentration gradients.
T. yunnanensis exhibited contrasting orientation responses to P. yunnanensis trunk volatiles in this study, suggesting spatial variation in chemical signaling and a selective preference for infestation sites. α-Pinene, the most abundant constitutive volatile in P. yunnanensis, functioned as a consistent attractant across all infestation stages, aligning with its role in primary host recognition. 3-Carene and 2-thujene, which showed stage-specific antennal sensitivity (early-infested and weakened stages), elicited attraction only during active colonization periods. Conversely, β-pinene’s repellent effect peaked during the weakened tree state, coinciding with its elevated emission during advanced host stress. Meanwhile, 4-allylanisole, a known precursor of anti-aggregation pheromone, repelled beetles regardless of host condition. These behavioral outcomes correlate with GC-EAD response profiles (Figure 2), confirming that T. yunnanensis dynamically adjusts host selection strategies based on VOC-mediated cues reflecting tree physiological states. This aligns with the life history strategy of Tomicus species, where shoot feeding during the nutrient accumulation phase supports ovarian development, while trunk boring facilitates mating and oviposition. The observed behavioral dichotomy likely reflects adaptation to spatial heterogeneity in host semiochemicals, optimizing reproductive success by guiding beetles to distinct microhabitats for specific life-stage needs [52]. To enhance semiochemical-based management, future research should prioritize mapping the spatial and geographic distribution of P. yunnanensis volatiles. Regionalized profiling of compound ratios and concentrations could resolve inconsistencies in field trapping efficacy, enabling tailored lure formulations. Such refinements would advance sustainable monitoring and population control by aligning attractant blends with the beetle’s context-dependent chemosensory ecology.

5. Conclusions

In this study, dynamic headspace sampling was utilized to collect volatile organic compounds from Pinus yunnanensis at four distinct infestation stages: healthy, early infestation, weakened, and near-death. GC-MS analysis identified a total of 51 terpene compounds, with α-pinene as the most abundant. Notably, the relative content of α-pinene increased slightly from healthy to weakened trees, while β-pinene reached its highest concentration in near-death trees. GC-EAD screening revealed five electrophysiologically active compounds: α-pinene, β-pinene, 3-carene, 2-thujene, and 4-allylanisole. Behavioral assays using a Y-tube olfactometer indicated that α-pinene, 3-carene, and 2-thujene acted as attractants, whereas β-pinene and 4-allylanisole functioned as repellents. These results highlight the multifaceted role of host-emitted VOCs in mediating host selection by Tomicus yunnanensis and suggest that further research on the temporal dynamics and quantitative variation of these compounds could inform the development of spatiotemporally optimized management strategies for bark beetle control.

Author Contributions

Conceptualization, Z.W. and Z.L.; methodology, J.L., M.Z., L.Q. and Z.L.; software, J.L., M.Z. and L.Q.; validation, Z.W. and Z.L.; formal analysis, J.L., M.Z., L.Q., Z.W. and Z.L.; investigation, J.L., M.Z. and L.Q.; data curation, J.L., M.Z., L.Q., Z.W. and Z.L.; writing—original draft preparation, J.L., M.Z., Z.W. and Z.L.; writing—review and editing, Z.W. and Z.L.; visualization, J.L., M.Z., L.Q., Z.W. and Z.L.; supervision, Z.L.; funding acquisition, J.L., Z.W. and Z.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (31760210), Key Project of Yunnan Applied Basic Research Program (202101AS070009), Yunnan Fundamental Research Projects (202501AU070188, 202401BA070001-023, 2024J0966); the “Xingdian Talents” Youth Top Talent Program (YNWR-QNBJ-2018-131, YNWR-QNBJ-2020-104); and Chuxiong Normal University School-Level Research Team Project (XJTDB03).

Data Availability Statement

The data presented in this study are available upon request from the corresponding authors.

Acknowledgments

We thank Li Cao and Ping Wen at the Xishuangbanna Tropical Botanical Garden (XTBG), Chinese Academy of Sciences (CAS), for their technical support in conducting GC-MS analyses and GC-EAD experiments. We also acknowledge Yanqiong Peng’s research group at XTBG, CAS, for providing access to laboratory facilities and experimental resources. We would also like to sincerely thank the editor and two anonymous reviewers for their valuable and constructive feedback, which has greatly improved the quality of our manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Pincebourde, S.; van Baaren, J.; Rasmann, S.; Rasmont, P.; Rodet, G.; Martinet, B.; Calatayud, P.A. Plant-Insect interactions in a changing world. Adv. Bot. Res. 2017, 81, 289–332. [Google Scholar]
  2. Aartsma, Y.; Bianchi, F.J.; vander Werf, W.; Poelman, E.H.; Dicke, M. Herbivore-induced plant volatiles and tritrophic interactions across spatial scales. New Phytol. 2017, 216, 1054–1063. [Google Scholar] [CrossRef] [PubMed]
  3. Maffei, M.E.; Gertsch, J.; Appendino, G. Plant volatiles: Production, function and pharmacology. Nat. Prod. Rep. 2011, 28, 1359–1380. [Google Scholar] [CrossRef] [PubMed]
  4. Beyaert, I.; Hilker, M. Plant odour plumes as mediators of plant-insect interactions. Biol. Rev. 2014, 89, 68–81. [Google Scholar] [CrossRef] [PubMed]
  5. Gershenzon, J.; Dudareva, N. The function of terpene natural products in the natural world. Nat. Chem. Biol. 2007, 3, 408–414. [Google Scholar] [CrossRef] [PubMed]
  6. Dicke, M.; Baldwin, I.T. The evolutionary context for herbivore-induced plant volatiles: Beyond the ‘cry for help’. Trends Plant Sci. 2010, 15, 167–175. [Google Scholar] [CrossRef] [PubMed]
  7. Keeling, C.I.; Bohlmann, J. Genes, enzymes and chemicals of terpenoid diversity in the constitutive and induced defence of conifers against insects and pathogens. New Phytol. 2006, 170, 657–675. [Google Scholar] [CrossRef] [PubMed]
  8. Krokene, P. Conifer defence and resistance to bark beetles. In Bark Beetles: Biology and Ecology of Native and Invasive Species; Vega, F.E., Hofstetter, R.W., Eds.; Elsevier: Amsterdam, The Netherlands, 2015; pp. 177–207. [Google Scholar]
  9. Byers, J.A. Host-tree chemistry affecting colonization in bark beetles. In Chemical Ecology of Insects 2; Cardé, R.T., Bell, W.J., Eds.; Chapman & Hall.: Boca Raton, FL, USA, 1995. [Google Scholar]
  10. Raffa, K.F.; Erbilgin, N.; Klepzig, K.D.; Smalley, E.B. Interactions among conifer terpenoids and bark beetles across multiple levels of scale: An attempt to understand links between population patterns and physiological processes. Oecologia 2005, 146, 1–14. [Google Scholar]
  11. Chen, J.; Yuan, X.; Yan, W.; Zhang, L.; Liu, X. Composition and variation of volatile organic compounds emitted by Pinus yunnanensis under different health conditions. For. Res. 2020, 33, 345–353. [Google Scholar] [CrossRef] [PubMed]
  12. Wang, J.H.; Gao, W.Z.; Cai, H.Z.; Teng, J. Research progress on chemical ecological management of three Tomicus Species (Coleoptera: Scolytidae) in Yunnan province of China. J. Entomol. Sci. 2025, 60, 192–204. [Google Scholar]
  13. Byers, J.A.; Zhang, Q. Chemical ecology of bark beetles in regard to search and selection of host trees. In Recent Advances in Entomological Research; Springer: Berlin/Heidelberg, Germany, 2011; pp. 150–190. [Google Scholar]
  14. Liu, N.Y.; Li, Z.B.; Zhao, N.; Song, Q.S.; Zhu, J.Y.; Yang, B. Identification and characterization of chemosensory gene families in the bark beetle, Tomicus yunnanensis. Comp. Biochem. Physiol. Part D Genom. Proteom. 2018, 25, 73–85. [Google Scholar] [CrossRef] [PubMed]
  15. Lü, J.; Hu, S.J.; Ma, X.Y.; Chen, J.M.; Li, Q.Q.; Ye, H. Origin and expansion of the Yunnan Shoot Borer, Tomicus yunnanensis (coleoptera: Scolytinae): A mixture of historical natural expansion and contemporary human-mediated relocation. PLoS ONE 2014, 9, e111940. [Google Scholar] [CrossRef] [PubMed]
  16. Zhu, J.Y.; Zhao, N.; Yang, B. Global transcriptome profiling of the pine shoot beetle, Tomicus yunnanensis (Coleoptera: Scolytinae). PLoS ONE 2012, 7, e32291. [Google Scholar] [CrossRef] [PubMed]
  17. Liu, H.; Zhang, Z.; Ye, H.; Wang, H.; Clarke, S.R.; Lu, J. Response of Tomicus yunnanensis (Coleoptera: Scolytinae) to infested and uninfested Pinus yunnanensis bolts. J. Econ. Entomol. 2010, 103, 95–100. [Google Scholar] [CrossRef] [PubMed]
  18. Wu, C.X.; Liu, F.; Zhang, S.F.; Kong, X.B.; Zhang, Z. Semiochemical regulation of the intraspecific and interspecific behavior of Tomicus yunnanensis and Tomicus minor during the shoot-feeding phase. J. Chem. Ecol. 2019, 45, 227–240. [Google Scholar] [CrossRef] [PubMed]
  19. Kirkendall, L.R.; Faccoli, M.; Ye, H. Description of the Yunnan shoot borer, Tomicus yunnanensis Kirkendall & Faccoli sp. n. (Curculionidae, Scolytinae), an unusually aggressive pine shoot beetle from southern China, with a key to the species of Tomicus. Zootaxa 2008, 1819, 25–39. [Google Scholar] [CrossRef]
  20. Duan, Y.; Kerdelhué, C.; Ye, H.; Lieutier, F. Genetic study of the forest pest Tomicus piniperda (Col., Scolytinae) in Yunnan province (China) compared to Europe: New insights for the systematics and evolution of the genus Tomicus. Heredity 2004, 93, 416–422. [Google Scholar] [CrossRef] [PubMed]
  21. Yan, G.; Zhang, M.D.; Qian, L.B.; Ze, S.Z.; Yang, B.; Li, Z.B. Electrophysiological and behavioral responses of Tomicus yunnanensis to plant volatiles from primarily infected Pinus yunnanensis in Yunnan, southwest China. J. Environ. Entomol. 2021, 43, 1389–1397. [Google Scholar]
  22. Cui, Y.J.; Zhang, M.D.; Zhu, H.I.; Yang, P.; Yang, B.; Li, Z.B. Fine structure of the mouthparts of three Tomicus beetles co-infecting Pinus yunnanensis in southwestern China with some functional comments. Insects 2023, 14, 933. [Google Scholar] [CrossRef] [PubMed]
  23. Qian, L.B.; Zhang, M.D.; Liu, J.J.; Li, Z.B. Effects of 4 kinds of odor-active compounds of non-host alnus ferdinandi-coburgii on the post-embryonic development of Tomicus yunnanensis(Coleoptera: Curculionidae: Scolytinae). J. Southwest For. Univ. 2023, 43, 96–102. [Google Scholar]
  24. Adams, R.P. Identification of Essential Oil Components by Gas Chromatography/Mass Spectrometry, 4.1; Allured Pub Corp: Carol Steam, IL, USA, 2017; pp. 9–53. [Google Scholar]
  25. Althoff, E.R.; Aukema, B.H.; Sullivan, B.T. Pheromone composition of the eastern larch beetle Dendroctonus simplex Leconte (Coleoptera: Curculionidae): Quantitative analyses and olfactory responses. J. Chem. Ecol. 2025, 51, 18. [Google Scholar] [CrossRef] [PubMed]
  26. Heng, G.X.; McMillin, J.; Wagner, M.; Zhou, J.; Zhou, Z.; Xu, X. Altitudinal variation in foliar chemistry and anatomy of yunnan pine, Pinus yunnanensis, and pine sawfly (Hym., Diprionidae) performance. J. Appl. Entomo. 1999, 123, 465–471. [Google Scholar]
  27. Yan, Z.; Ma, H.; Ze, S. Difference of taxis responses of Tomicus yunnanensis to volatile extracts from trunks and branches of Pinus yunnanensis. J. Envir. Entomol. 2011, 33, 191–194. [Google Scholar]
  28. Ding, J.K.; Ding, L.S. Chemical constituents of pine needle oil from Pinus yunnanensis and Pinus kesiya. Plant Diver. Resour. 1987, 9, 505–508. [Google Scholar]
  29. Yang, Y.; Yang, M.F.; Yang, Z.H.; Huang, J.Y.; Wang, C.Y. Chemical constituents of volatile from pine needles of Pinus yunnanensis. Sci. Silvae Sin. 2009, 45, 173–177. [Google Scholar]
  30. Yin, C.X.; Gao, Z.L.; Lv, J.; Ye, H. Test on the taxis responses of Tomicus piniperda to the volatiles of Yunnan pine shoot. Entomol. Knowl. 2002, 39, 384–386. [Google Scholar]
  31. Yin, X.B.; Geng, S.X.; Zheng, W. Differences of physical and chemical characteristics of oleoresin among provenances from Pinus yunnanensis. J. W. China For. Sci. 2007, 36, 34–41. [Google Scholar]
  32. Agelopoulos, N.G.; Pickett, J.A. Headspace analysis in chemical ecology: Effects of different sampling methods on ratios of volatile compounds present in headspace samples. J. Chem. Ecol. 1998, 24, 1161–1172. [Google Scholar] [CrossRef]
  33. Faccoli, M.; Anfora, G.; Tasin, M. Responses of the Mediterranean pine shoot beetle Tomicus destruens (Wollaston) to pine shoot and bark volatiles. J. Chem. Ecol. 2008, 34, 1162–1169. [Google Scholar] [CrossRef] [PubMed]
  34. Munro, H.L.; Gandhi, K.J.; Barnes, B.F.; Montes, C.R.; Nowak, J.T.; Shepherd, W.P.; Villari, C.; Sullivan, B.T. Electrophysiological and behavioral responses Dendroctonus frontalis and D. terebrans (Coleoptera: Curculionidae) to resin odors of host pines (Pinus spp.). Chemoecology 2020, 30, 215–231. [Google Scholar] [CrossRef]
  35. Bo, J.; Li, W.; Li, X.; Li, Z.; Mao, X.; Yang, B.; Zhao, N. Mechanisms of impact of Alnus ferdinandi-coburgii odor substances on host location of Tomicus yunnanensis. Insects 2025, 16, 553. [Google Scholar] [CrossRef] [PubMed]
  36. Jones, K.L. Influence of Semiochemical Cues on Mountain Pine Beetle Flight and Subsequent Effect of Flight on Host Colonisation Processes. Master’s Thesis, Department of Biological Sciences University of Alberta, Edmonton, AB, Canada, 2019. [Google Scholar]
  37. Zhao, T.; Krokene, P.; Hu, J.; Christiansen, E.; Björklund, N.; Långström, B.; Borg-Karlson, A.K. Induced terpene accumulation in Norway spruce inhibits bark beetle colonization in a dose-dependent manner. PLoS ONE 2011, 6, e26649. [Google Scholar] [CrossRef] [PubMed]
  38. Singh, P.; Kalunke, R.M.; Giri, A.P. Towards comprehension of complex chemical evolution and diversification of terpene and phenylpropanoid pathways in Ocimum species. RSC Adv. 2015, 5, 106886–106904. [Google Scholar] [CrossRef]
  39. Blomquist, G.J.; Figueroa-Teran, R.; Aw, M.; Song, M.; Gorzalski, A.; Abbott, N.L.; Chang, E.; Tittiger, C. Pheromone production in bark beetles. Insect Biochem. Mol. Biol. 2010, 40, 699–712. [Google Scholar] [CrossRef] [PubMed]
  40. Seybold, S.J.; Bohlmann, J.; Raffa, K.F. Biosynthesis of coniferophagous bark beetle pheromones and conifer isoprenoids: Evolutionary perspective and synthesis. Can. Entomol. 2012, 132, 697–753. [Google Scholar] [CrossRef]
  41. Franceschi, V.R.; Krokene, P.; Christiansen, E.; Krekling, T. Anatomical and chemical defenses of conifer bark against bark beetles and other pests. New Phytol. 2005, 167, 353–376. [Google Scholar] [CrossRef] [PubMed]
  42. Sun, J.; Lu, M.; Gillette, N.E.; Wingfield, M.J. Red turpentine beetle: Innocuous native becomes invasive tree killer in China. Annu. Rev. Entomol. 2013, 58, 293–311. [Google Scholar] [CrossRef] [PubMed]
  43. Sullivan, B.T. Composition of attractant semiochemicals of north American species of Dendroctonus bark beetles: A review. Forests 2024, 15, 642. [Google Scholar] [CrossRef]
  44. Wang, J.; Zhang, S.; Zheng, Y. Feeding preferences and responses of Monochamus Saltuarius to volatile components of host pine trees. Insects 2022, 13, 888. [Google Scholar] [CrossRef] [PubMed]
  45. Manuel, C.F.; Leonardo, B.; Ivette, S.; Cristian, M.; Andrés, Q. Volatiles induction in response to mechanical damage is reduced by domestication in murtilla. Bol. Latinoam. Caribe Plant. Med. Aromat. 2019, 18, 435–443. [Google Scholar]
  46. Sullivan, B.T.; Munro, H.L.; Shepherd, W.P.; Gandhi, K.J. 4-allylanisole as a lure adjuvant for Dendroctonus frontalis (Coleoptera: Curculionidae: Scolytinae) and two associated beetles. J. Appl. Entomol. 2022, 146, 813–822. [Google Scholar] [CrossRef]
  47. Emerick, J.J.; Snyder, A.I.; Bower, N.W.; Snyder, M.A. Mountain pine beetle attack associated with low levels of 4-allylanisole in ponderosa pine. Environ. Entomol. 2008, 37, 871–875. [Google Scholar] [CrossRef] [PubMed]
  48. Haack, R.A.; Lawrence, R.K.; Petrice, T.R.; Poland, T.M. Disruptant effects of 4-allylanisole and verbenone on Tomicus piniperda (Coleoptera: Scolytidae) response to baited traps and logs. Great Lakes Entomol. 2004, 37, 131–141. [Google Scholar] [CrossRef]
  49. Lehmanski, L.M.A.; Kandasamy, D.; Andersson, M.N.; Netherer, S.; Alves, E.G.; Huang, J.; Hartmann, H. Addressing a century-old hypothesis–do pioneer beetles of Ips typographus use volatile cues to find suitable host trees? New Phytol. 2023, 238, 1762–1770. [Google Scholar] [CrossRef] [PubMed]
  50. Hofstetter, R.W.; Gaylord, M.L.; Martinson, S.; Wagner, M.R. Attraction to monoterpenes and beetle-produced compounds by syntopic Ips and Dendroctonus bark beetles and their predators. Agric. For. Entomol. 2012, 14, 207–215. [Google Scholar] [CrossRef]
  51. Li, L.S.; Shu, N.B.; Huai, K.Y. Trapping experiments of Tomicus piniperda to the chemical volatiles. Entomol. Knowl. 1993, 30, 159–161. [Google Scholar]
  52. Lieutier, F.; Långström, B. The genus Tomicus. In Bark Beetles: Biology and Ecology of Native and Invasive Species; Vega, F.E., Hofstetter, R.W., Eds.; Academic Press: Cambridge, MA, USA, 2015. [Google Scholar]
Figure 1. Principal component analysis (PCA) of VOCs emitted by Pinus yunnanensis trunks across infestation stages: healthy, early-infested, weakened, and near-death.
Figure 1. Principal component analysis (PCA) of VOCs emitted by Pinus yunnanensis trunks across infestation stages: healthy, early-infested, weakened, and near-death.
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Figure 2. GC-EAD recordings of Tomicus yunnanensis antennal responses to VOCs emitted by Pinus yunnanensis at four infestation stages: healthy (A), early-infested (B), weakened (C), and near-death (D). EAD-active compounds are labeled above corresponding FID peaks. Yellow, purple, and cyan traces represent synchronized EAD responses from three biological replicates.
Figure 2. GC-EAD recordings of Tomicus yunnanensis antennal responses to VOCs emitted by Pinus yunnanensis at four infestation stages: healthy (A), early-infested (B), weakened (C), and near-death (D). EAD-active compounds are labeled above corresponding FID peaks. Yellow, purple, and cyan traces represent synchronized EAD responses from three biological replicates.
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Figure 3. Choice rate (%) of Tomicus yunnanensis when selecting between volatiles from five GC-EAD-active compounds.
Figure 3. Choice rate (%) of Tomicus yunnanensis when selecting between volatiles from five GC-EAD-active compounds.
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Table 1. Classification criteria for P. yunnanensis infestation stages.
Table 1. Classification criteria for P. yunnanensis infestation stages.
StagePine Needle ColorationShoot Infestation Rate (%)Trunk and Crown Traits
HealthyGreen to light green1–20Shoots and primary branches exhibit boreholes and resin exudates
Early-infestedGray-green21–50Shoots and trunks exhibit abundant boreholes and resin exudates, accompanied by crown dehydration and progressive wilting
WeakenedGrayish-yellow51–100The trunk exhibits numerous boreholes and resin exudates, while the crown shows complete dehydration, chlorosis, and wilting
Near-DeadReddish-yellow-The trunk exhibits numerous emergence holes
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Liu, J.; Zhang, M.; Qian, L.; Wang, Z.; Li, Z. Electrophysiology and Behavior of Tomicus yunnanensis to Pinus yunnanensis Volatile Organic Compounds Across Infestation Stages in Southwest China. Forests 2025, 16, 1178. https://doi.org/10.3390/f16071178

AMA Style

Liu J, Zhang M, Qian L, Wang Z, Li Z. Electrophysiology and Behavior of Tomicus yunnanensis to Pinus yunnanensis Volatile Organic Compounds Across Infestation Stages in Southwest China. Forests. 2025; 16(7):1178. https://doi.org/10.3390/f16071178

Chicago/Turabian Style

Liu, Jinlin, Mengdie Zhang, Lubing Qian, Zhenji Wang, and Zongbo Li. 2025. "Electrophysiology and Behavior of Tomicus yunnanensis to Pinus yunnanensis Volatile Organic Compounds Across Infestation Stages in Southwest China" Forests 16, no. 7: 1178. https://doi.org/10.3390/f16071178

APA Style

Liu, J., Zhang, M., Qian, L., Wang, Z., & Li, Z. (2025). Electrophysiology and Behavior of Tomicus yunnanensis to Pinus yunnanensis Volatile Organic Compounds Across Infestation Stages in Southwest China. Forests, 16(7), 1178. https://doi.org/10.3390/f16071178

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