Introduction
Biological control is a critical strategy for pest management, relying on the biological fitness and metabolic rates of predator species. Functional responses are central to predator-prey dynamics, describing how predation rates vary with prey abundance. Trophic interactions, which are integral to community ecology and ecosystem stability influence food webs, drive population dynamics, and shape perceived risk of predation (Islam et al., Reference Islam, Shah, Güncan, DeLong and Zhou2022b, Reference Islam, Shah, Shah, Musa Khan, Rasheed, Ur Rehman, Ali and Zhou2020; Wang and Zou, Reference Wang and Zou2017). These interactions are regulated by species interaction strengths within food webs (Novak and Wootton, Reference Novak and Wootton2010).
The fall armyworm (Spodoptera frugiperda, JE Smith, 1797) (Lepidoptera: Noctuidae) is a highly polyphagous pest that infests over 350 plant species, predominantly from the Poaceae family, causing significant economic damage to major crops like maize, sorghum, rice, and cotton (Kenis et al., Reference Kenis, Benelli, Biondi, Calatayud, Day, Desneux, Harrison, Kriticos, Rwomushana and Van den Berg2023; Montezano et al., Reference Montezano, Sosa-Gómez, Specht, Roque-Specht, Sousa-Silva, Paula-Moraes, Peterson and Hunt2018; Tay et al., Reference Tay, Meagher, Czepak and Groot2023). Originating from tropical and subtropical regions of the Americas, S. frugiperda has rapidly spread across regions like China, and Pakistan prompting the development of effective control strategies to mitigate crop damage (Kenis et al., Reference Kenis, Benelli, Biondi, Calatayud, Day, Desneux, Harrison, Kriticos, Rwomushana and Van den Berg2023). Similarly, Spodoptera litura (F.) (Lepidoptera: Noctuidae), also known as the tobacco cutworm, is a significant pest worldwide. This species infests an extensive host range of 389 plant species across 109 plant families, exacerbating crop damage due to its extensive host range and high reproductive rate (Atwal and Dhaliwal, Reference Atwal and Dhaliwal2009; Qin et al., Reference Qin, Wang, Ding, Huang and Ye2006). The pests (S. frugiperda and S. litura) egg clusters, protected by a tuft of abdominal hair, result in large populations of gregarious hatchlings that disperse to nearby plants (Ullah et al., Reference Ullah, Arshad, Afzal, Khalid, Saleem, Mustafa, Iftikhar, Molina-Ochoa and Foster2016).
The heavy reliance on pesticides to manage pests has led to resistance, reducing their effectiveness (Guo et al., Reference Guo, Guo, Gao, Huang, Wan, He, Xie, Li and Ma2024; Sanches and Wise, Reference Sanches and Wise2024). Resistance has been observed in many classes, including carbamates, organophosphates, and pyrethroids (Liu, Reference Liu2015; Nauen et al., Reference Nauen, Bass, Feyereisen and Vontas2022). In addition to pesticide resistance, there are concerns about adverse effects on non-target organisms and human health (Desneux et al., Reference Desneux, Decourtye and Delpuech2007; Weisenburger, Reference Weisenburger1993). These challenges underscore the need for sustainable pest control strategies, including biological control. In this regard, biological control, through the protection and release of natural enemies, has gained considerable attention. Several parasitoids, such as Glyptapanteles creatonoti (Viereck) and Campoletis chlorideae (Uchida), have been identified as effective agents against S. frugiperda and S. litura (Abbas et al., Reference Abbas, Ullah, Hafeez, Han, Dara, Gul and Zhao2022; Di et al., Reference Di, Zhang, Xu, Zhang, Harwood, Wang and Desneux2021; Islam et al., Reference Islam, Güncan, Zhou, Naeem and Shah2022a, Reference Islam, Shah, Shah, Musa Khan, Rasheed, Ur Rehman, Ali and Zhou2020), Cotesia icipe Fernández-Triana & Fiaboe (Hymenoptera, Braconidae) was reported to be the most dominant parasitoid in Africa (Sisay et al., Reference Sisay, Simiyu, Malusi, Likhayo, Mendesil, Elibariki, Wakgari, Ayalew and Tefera2018). However, research on predator species, particularly focusing on the functional response of ladybird beetles, remain relatively limited.
Functional response models quantify the efficiency of predators by measuring their consumption rates at varying prey densities and are influenced by factors such as resource quality, temperature, and prey density, which affect its development, survival, and predation rates (Abbas et al., Reference Abbas, Wei‐Bo, Hafeez, Hasnain, Shoukat, Ali, Xiao, Liu, Ghramh, Khan, Ullah and Chen2025; Di et al., Reference Di, Zhang, Xu, Zhang, Harwood, Wang and Desneux2021; Islam et al., Reference Islam, Shah, Shah, Musa Khan, Rasheed, Ur Rehman, Ali and Zhou2020). These models, such as Holling’s Type I, II, and III models, help assess predator-prey interactions (DeLong and Uiterwaal, Reference DeLong and Uiterwaal2022). Functional responses are essential for understanding how predation rates depend on prey availability and predator characteristics. In particular, Holling’s Type II model, where the attack rate increases initially but then slows down as prey density increases, is the most common for evaluating predators (Abbas et al., Reference Abbas, Wei‐Bo, Hafeez, Hasnain, Shoukat, Ali, Xiao, Liu, Ghramh, Khan, Ullah and Chen2025; Di et al., Reference Di, Zhang, Xu, Zhang, Harwood, Wang and Desneux2021; Islam et al., Reference Islam, Güncan, Zhou, Naeem and Shah2022a, Reference Islam, Shah, Shah, Musa Khan, Rasheed, Ur Rehman, Ali and Zhou2020).
The ladybird beetle Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae) is a well-known polyphagous generalist predator that has been widely studied for its predatory potential against a variety of pests, belonging to order Coleoptera (Colorado potato beetle: Leptinotarsa decemlineata), Hymenoptera (sawfly larvae: Symphyta), Diptera (leafminer: Liriomyza sativae), Hemiptera (aphids: Myzus persicae), and particularly the eggs and larvae of Lepidoptera (common cutworm: S. litura) (Islam et al., Reference Islam, Güncan, Zhou, Naeem and Shah2022a; Koch, Reference Koch2003; Lu et al., Reference Lu, Wu, Jiang, Guo and Desneux2012; Seko and Miura, Reference Seko and Miura2008). H. axyridis is recognized for its high predatory efficiency and has been commercially reared and deployed in biocontrol programs worldwide (Huang et al., Reference Huang, Escalona, Sun, Zhang, Du, Gong, Tang, Liang, Yang, Chen and Yang2025; Jaworski et al., Reference Jaworski, Bompard, Genies, Amiens-Desneux and Desneux2013; Koch et al., Reference Koch, Hutchison, Venette and Heimpel2003; Pang and Li, Reference Pang and Li2025; Yang et al., Reference Yang, Du, Wang, Zhu, Li, Huang and Hu2025). However, its introduction has resulted in significant unintended ecological impacts. It is now considered an invasive species in several regions due to its ability to outcompete native ladybird species, rapid population growth, and broad diet (Raak-van den Berg, Reference Raak-van den Berg2014). The functional response of H. axyridis has been extensively investigated with various pests, including immature stages of Danaus plexippus (Lepidoptera: Nymphalidae) (Koch, Reference Koch2003), Anagasta kuehniella (Lepidoptera: Pyralidae) (de Castro-guedes et al., Reference de Castro-guedes, de Almeida, Do Rocio Chiarello Penteado and Moura2016), Sitotroga cerealella (Lepidoptera: Gelechiidae) (Abdel‐Salam and Abdel‐Baky, Reference Abdel‐Salam and Abdel‐Baky2001), S. litura (Islam et al., Reference Islam, Shah, Shah, Musa Khan, Rasheed, Ur Rehman, Ali and Zhou2020) and S. frugiperda (Di et al., Reference Di, Zhang, Xu, Zhang, Harwood, Wang and Desneux2021). In addition, life table of this predator has been developed on various insects (Islam et al., Reference Islam, Güncan, Zhou, Naeem and Shah2022a), providing an important baseline of information for the utilization of H. axyridis in biological control. Therefore, this study hypothesized that H. axyridis exhibits an effective functional response to the eggs of S. litura and S. frugiperda, indicating as a potential biocontrol agent. The study aimed to estimate the functional response model of H. axyridis for the eggs of S. litura and S. frugiperda by assessing key predatory parameters and comparing its potential against both pests under laboratory conditions. Given its effectiveness, ease of mass production, and widespread use in agricultural production, H. axyridis presents a valuable tool for integrated pest management (IPM) programs.
Materials and methods
Insect cultures
Mass rearing of H. axyridis
Colonies of H. axyridis were established using adult aphids supplied with stock culture from the Laboratory of the Entomological Research Institute (AARI), Faisalabad, Pakistan. The prey species used in this study was M. persicae (Hemiptera: Aphididae), commonly known as the green peach aphid. The aphid culture originated in February, 2022 from individuals collected on potato (Solanum tuberosum) fields in Faisalabad, Punjab, Pakistan, and was thereafter continuously reared on potted potato plants at the vegetative-stage (15–25 cm tall, with 3–5 fully expanded leaves). Potato was maintained as the host plant throughout study to avoid host-shifting effects. Harmonia axyridis was fed on aphid and maintained in the laboratory. Aphid colonies were kept in mesh cages (11.8 cm in diameter × 8 cm in height) and supplied with potted potato plants. Each cage was inoculated with 25 pairs of adults (male and female) of H. axyridis. Fresh aphid cultures and host plants were provided daily. Cages were monitored regularly for egg batches which were collected and incubated in an insect growth chamber (26 ± 1°C, 60 ± 5% RH, and a 14:10 L:D photoperiod) until emergence.
Mass rearing of S. litura and S. frugiperda
Larvae of S. litura and S. frugiperda were collected from field and maintained under laboratory conditions (26 ± 1°C, 60 ± 5% RH, and a 14:10 L:D photoperiod). Eggs were placed on moistened filter paper in 07 cm Petri dishes. Newly hatched larvae were reared individually in transparent plastic containers (6.0 cm in diameter × 2.0 cm in height) on an artificial diet until pupation. Pupae were transferred into separate vials for adult emergence. Approximately 25 pairs of adults were kept in rearing cages (20 cm × 20 cm × 20 cm), provisioned with cotton soaked in 10% honey as food and filter paper as an oviposition substrate. Collected egg batches were subsequently used for experiments.
Functional response experiments
Prior to the functional response experiment, adults of H. axyridis, from stock culture were transferred into plastic containers (25 × 14 × 20 cm) with one [air of adults per container. A total of 15 such containers were prepared, each provided with 200 eggs of S. litura and S. frugiperda along with a cotton wick serving as an oviposition substrate. Predators were maintained on these eggs for at least one generation to ensure prey acclimatization and efficient egg consumption. To synchronize predator age, eggs were collected every 24 hours, allowing production of different instar that were close in age (0–6 hours post-molting).
The desired life stages, including larval instars (first to fourth) and adult (males and females), were selected and starved prior to trials (first instars for ~4 h; later instars for ~18 h post molt), individuals were then placed into six-compartment culture plates, each lined with Whatman filter paper and containing moistened cotton to maintain humidity. Freshly laid eggs of S. litura and S. frugiperda were transferred into the the petri dishes (7 cm diameter) using a fine camel hair brush. First and second instar predators prey densities of 5, 10, 15, 20, 25, 30, 35, and 40 eggs were offered. For third and fourth instar , as well as adult females and males, prey densities of 5, 10, 30, 60, 100, 150, 250, and 300 eggs were provided. Each treatment was replicated ten times. Eggs consumed or damaged were not replaced during the 24h feeding period. After 24-hour,, predators were removed, and the number of eggs consumed was recorded.
Data analysis
Functional response
The Shapiro–Wilk test was performed to evaluate the normality of data on mean and proportionate prey consumption by H. axyridis prior to analysis. The results showed that the data were typically non-normal (p < 0.05). To address this, the data on average prey consumption were analysed using a generalized linear model (GLM) assuming a negative binomial distribution to account for overdispersion. Group means were compared using Tukey’s Honestly Significant Difference (HSD) test (p < 0.05).
The predator’s egg consumption rate across different life stages was calculated, and the polynomial logistic regression was applied to the proportion of prey consumed in relation to prey density. Similarly, a binomial distribution was to compute the functional response of the predator (Equation 1).
\begin{equation}\frac{{{N_e}}}{{{N_0}}} = \frac{{{\text{exp}}\left( {{P_0} + {P_1}{N_0} + {P_2}N_0^2 + {P_3}N_0^3} \right)}}{{1 + {\text{exp}}\left( {{P_0} + {P_1}{N_0} + {P_2}N_0^2 + {P_3}N_0^3} \right)}}\end{equation}In this study, Ne and N0 represented the number of eggs consumed and the initial egg density, respectively, while Ne/N0 denoted the proportion of eggs consumed. The regression parameters P0, P1, P2, and P3 corresponded to the intercept, linear, quadratic, and cubic terms, respectively. These coefficients were estimated using the maximum likelihood method. The signs of the linear (P1) and quadratic (P2) coefficients were used to determine the type of functional response. A type II functional response was indicated when P1 < 0, whereas a type III response was identified when P1 > 0 and P2 < 0 (Juliano, Reference Juliano, Cheiner and Gurven2001). Identifying the type of functional response is crucial for accurately estimating functional response parameters using the appropriate analytical method. A type II response signifies that egg consumption decreases monotonically as egg density increases, while a type III response reflects positively density-dependent consumption, where the proportion of eggs consumed increases with egg density (Juliano, Reference Juliano, Cheiner and Gurven2001). Roger’s random predator equation is suitable for modelling predation using non-linear regression analysis, particularly in cases where predation significantly reduces egg or host densities (Rogers, Reference Rogers1972) (Equation 2).
\begin{equation}{N_e} = {N_0}\,\left[ {1 - {\text{exp}}\left( {a\left( {{T_h}{N_e} - T} \right)} \right)} \right]\end{equation}Holling’s Disc Equation (2), represents the number of consumed and eggs density offered, likewise a is the instantaneous attack rate, Th is the handling time and T is duration of the experiment (24 h). We fitted the logistic regression using the function ‘glm’, while the coefficients of attack rate and handling time were calculated using the ‘friar’ (Pritchard et al., Reference Pritchard, Paterson, Bovy and Barrios-O’Neill2017) package. All statistical analyses were performed using R software (v4.1.2) (Team, 2021).
Results
Functional response of H. axyridis to S. litura and S. frugiperda eggs
Functional response analysis for S. litura
The maximum likelihood estimates for the logistic regression model applied to S. litura egg consumption are presented in table 1. The results show that second instars had a significant negative linear coefficient (−1.84E-01, p = 0.00335), confirming a Type II functional response. The third and fourth instar stages exhibited Type II responses that demonstrated highly significant negative linear relationships of −3.44E-02 (p < 0.001) and −6.56E-02 (p < 0.001). Adult males along with females displayed significant Type II response patterns while adult females showed the most efficient predation rate (−9.33E-02) which achieved statistical significance (p < 0.001). The logistic regression analysis (table 1) for S. litura eggs revealed that the linear coefficient (P1) was significantly negative for second, third, and fourth instar larvae, adult males, and adult females (p < 0.001), indicating a Type II functional response. In contrast, the first instar larvae showed a non-significant linear coefficient (p > 0.05), exhibiting a lower predatory efficiency.
Maximum likelihood estimates (±SE) for parameters of the logistic model fit to proportion of S. litura
a Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘.’ 1.
The estimates from Holling’s disc equation (table 2) demonstrated that the attack rate (a) progressively increased with the predator’s developmental stage. Adult females exhibited both the highest attack frequency (a = 0.33594) and the fastest handling duration (Th = 0.2111 h) thus demonstrating superior predation skills. Among larval instars, the fourth instar had the highest attack rate (a = 0.1890) and shorter handling time (Th = 0.2457 h) compared to earlier stages. Predatory efficiency was lowest among first instars since they exhibited shorter attack rates and longer handling periods. table 2 provides the estimated parameters for the Holling’s disc equation. The attack rate (a) was lowest in first instars (a = 0.0418) and increased across instars, reaching the highest value in adult females (a = 0.33594). Similarly, handling time (Th) was longest in first instars (Th = 2.503 h) and shortest in adult females (Th = 0.2111 h), confirming their superior predatory ability.
Parameter estimates of the Holling’s disc equation (Equation 2) for S. litura eggs consumption by H. axyridis
‘a’ is searching rate and ‘Th’ is handling time.
a Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘.’ 1.
Pr is the probability that Holling’s disc equation yields parameters; a is the searching efficiency while Th is the handling time in consuming each milligram of food.
The figure shows that the number of S. litura eggs consumed by H. axyridis increased with prey density but plateaued at higher densities (fig. 1). The figure demonstrates that H. axyridis consumed more S. litura eggs as prey density rose but reached a saturation point at greater densities. At the highest prey density, adult females consumed an average of 100–125 eggs, while fourth instars consumed around 85–113 eggs. First instar larvae consumed between 5 and 10 eggs at lower density levels. This example demonstrates a functional response curve because the number of eggs consumed increased with density but reached a limit, an attribute of Type II functional response. Predators consumed fewer eggs as their density increased leading to the handling time constraints that limited predation.
Consumption of H. axyridis functional response (left). Circles illustrate the consumption by H. axyridis at S. litura eggs as modelled by fitting a Holling’s disc equation (Equation 2). H. axyridis proportional consumption percentage with respect to offered eggs (right).
Functional response analysis for S. frugiperda
The logistic regression estimates for S. frugiperda egg predation are presented in table 3. The results show a significantly negative linear coefficient for second instar (−1.44E-01, p = 0.0167), confirming a Type II response. Similarly, the behaviour of third and fourth instars exhibited a Type II response pattern which had strong negative linear relationships (−3.37E-02, p < 0.001 and −1.01E-01, p < 0.001, respectively). Furthermore, adult males and females demonstrated the most powerful Type II responses and females showed the strongest predation efficiency (−9.66E-02, p < 0.001). The logistic regression study of S. frugiperda eggs revealed Type II functional response that showed negative linear associations between second instar life stages and older stages at p < 0.001 significance. Similar to S. litura, the first instar showed a non-significant linear coefficient, suggesting lower predatory efficiency at early stages.
Maximum likelihood estimates (±SE) for parameters of the logistic model fit to proportion of S. frugiperda
a Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘.’ 1.
The functional response parameters showed adult female consumers had the strongest attack rate (a = 0.344487) and quickest handling time (Th = 0.1985 h) in their feeding behaviour which coincides with their predation style on S. litura. Fourth instar larvae also showed a high attack rate (a = 0.3592) with a handling time of (Th = 0.2520 h). The first instar had the lowest attack rate and longest handling time, reinforcing its lower efficiency in predation. In addition, table 4 presents the Holling’s disc equation estimates. The attack rate (a) was lowest in first instars (a = 0.0314) and highest in adult females (a = 0.3445). Handling time (Th) was longest in first instars (Th = 2.416 h) and shortest in adult females (Th = 0.1985 h), reinforcing their role as the most efficient predators of S. frugiperda eggs.
Parameter estimates of the Holling’s disc equation (Equation 2) for S. frugiperda eggs consumption by H. axyridis
‘a’ is searching rate and ‘Th’ is handling time.
a Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘.’ 1.
Pr is the probability that Holling’s disc equation yields parameters; a is the searching efficiency while Th is the handling time in consuming each milligram of food.
The results in fig. 2 presents that at maximum prey density, adult females consumed 103–133 eggs of S. frugiperda, while fourth instars consumed approximately 86–108 eggs. Third instars fed on 39–47 eggs, whereas second instars consumed between 11 and 15 eggs. First instars had the lowest consumption, with 06–08 eggs consumed at lower prey densities. The overall predation rate on S. frugiperda eggs was slightly higher than that on S. litura eggs, as reflected in the attack rate values. The functional response curve of fig. 2 matches the observed pattern for S. frugiperda as it closely reflects S. litura results. The population exhibited Type II response characteristics by showing reduced prey consumption at higher egg densities. The attack rate demonstrated higher numbers for S. frugiperda as compared to S. litura which suggested that the variation in prey characteristics influences predation efficiency.
Consumption of H. axyridis functional response (left). Circles illustrate the consumption by H. axyridis at S. frugiperda eggs as modelled by fitting a Holling’s disc equation (Equation 2). H. axyridis proportional consumption percentage with respect to offered eggs (right).
Discussion
The evaluation of predator efficiency on specific prey requires assessment of functional response traits. The predation behaviour of H. axyridis has been studied through functional response experiments with many crop pests (Lee and Kang, Reference Lee and Kang2004; Wu et al., Reference Wu, Zhang, Yan and Zhang2018). However, no prior study reports predatory potential on S. litura and S. frugiperda eggs. This study carried out to understand the predatory efficiency of H. axyridis, at different predatory stages, against S. litura and S. frugiperda eggs at various temperatures. The results of this study confirm that H. axyridis exhibits a Type II functional response when preying on both S. litura and S. frugiperda eggs. Studies of generalist predators have previously demonstrated that Type II responses occur when predator efficacy is limited by handling time changes at elevated prey population levels (Islam et al., Reference Islam, Shah, Rubing, Razaq, Yabo, Xihong and Zhou2021). As prey density increased the proportion of eggs consumed decreased due to the increased handling time constraints on the prey.
The functional response parameters indicated that adult females were the most effective predators, characterized by the highest attack rates and shortest handling times. This result is in agreement with previous studies demonstrating that adult H. axyridis exhibit greater foraging efficiency than their larval counterparts (DeLong et al., Reference DeLong, Uiterwaal and Dell2021). Adult predators achieve higher predation efficiency because they have larger body size, better mobility and higher energy needs that push up their prey consumption (Ortiz et al., Reference Ortiz, Ramos-Jiliberto and Arim2023). This study demonstrated that among larvae, fourth instar larva experienced both the greatest number of attacks as well as the shortest handling period from predators which indicates that predatory effectiveness rises with developmental age. These results are inconsistent with earlier studies who reported that later instars of coccinellid predators consumed significantly more prey than earlier instars (Pandi et al., Reference Pandi, Paul, Vivek and Shankarganesh2012). The first instar had the lowest predation efficiency, likely due to its small size and limited mobility, restricting its ability to handle and consume eggs effectively (Kivelä et al., Reference Kivelä, Davis, Esperk, Gotthard, Mutanen, Valdma and Tammaru2020).
The functional response curves of H. axyridis showed similar patterns when feeding on S. frugiperda and S. littura but predation rates were marginally higher for S. frugiperda eggs. These variations could be due to different egg conditions probably caused this discrepancy through size variations or textural differences and nutrient variations that potentially influence prey acceptance (Church et al., Reference Church, Donoughe, De Medeiros and Extavour2019; Li et al., Reference Li, Ma, Hou, Nkunika, Desneux and Zang2023). Previous research demonstrates that physical defences and chemical components of egg affects predators respond to their prey (Eisner et al., Reference Eisner, Eisner, Rossini, Iyengar, Roach, Benedikt and Meinwald2000; Sloggett, Reference Sloggett2022). The attack rate on S. frugiperda eggs is higher than S. litura thus indicating that H. axyridis shows a slight preference for this prey species in mixed species environments. The optimization of biological control strategies depends on understanding pest-predator preferences because it enables selection of predators which maximize pest management results (Jaworski et al., Reference Jaworski, Bompard, Genies, Amiens-Desneux and Desneux2013; Lucas et al., Reference Lucas, Coderre and Brodeur1998; Pang and Li, Reference Pang and Li2025).
The Type II functional response exhibited by H. axyridis demonstrates a decline in predation efficiency with higher prey densities but mostly because of the time necessary to handle prey (Feng et al., Reference Feng, Zhou, An, Yu and Liu2018). The ability of H. axyridis to allocate energy differently based on prey density presents crucial biological control implications since the beetle shows better pest control potential at lower prey numbers instead of outbreak prevention at high prey densities (Li et al., Reference Li, Yu, Mao, Kang, Xu and Wu2024). The developmental constraint affects the potential use of H. axyridis as a biological control agent but its remarkable predation rates on later life stages and adults present opportunities for its use in biological control programs (Islam et al., Reference Islam, Shah, Güncan, DeLong and Zhou2022b; Zhang et al., Reference Zhang, Cao, Wang, Zhang and Liu2014). Studies have demonstrated that the introduction of effective natural enemies can contribute significantly to pest suppression, particularly when combined with other integrated pest management (IPM) strategies (Gontijo, Reference Gontijo2019; Li et al., Reference Li, Ma, Hou, Nkunika, Desneux and Zang2023; Pang and Li, Reference Pang and Li2025).
Predation efficiency reveals different insights into laboratory-based functional response studies yet field conditions bring additional elements which modify predation efficiency. Temperature together with humidity and alternative prey sources and habitat complexity define how predators choose their feeding locations as well as their foraging efficiency levels (Wasserman et al., Reference Wasserman, Alexander, Weyl, Barrios‐O’Neill, Froneman and Dalu2016). For instance, temperature has been shown to impact metabolic rates and activity levels in coccinellid predators, affecting their predation rates (Sørensen et al., Reference Sørensen, Toft and Kristensen2013). Temperature elevation causes increased predation through better predator mobility and digestion yet severe temperatures lead to reduced predator performance (Walker et al., Reference Walker, Wilder and González2020). Future studies should investigate the thermal response of H. axyridis predation to determine optimal release conditions for biological control.
Additionally, habitat complexity, such as vegetation structure and prey refugia, can influence the ability of predators to locate and capture prey. Studies reveal that adding structural complexity to environments cuts down predation success because it creates shelter areas for prey thereby reducing the number of encounters (Warfe and Barmuta, Reference Warfe and Barmuta2004). Understanding how environmental factors influence H. axyridis predation will be crucial for improving its effectiveness in pest management programs. Furthermore, the compatibility of H. axyridis with other IPM techniques, such as biological pesticides, pheromone traps, and resistant crop varieties, should be explored to develop sustainable pest management strategies. The use of conservation biological control practices, such as maintaining flowering plants to support natural enemy populations, could further enhance the effectiveness of H. axyridis in agricultural landscapes.
Conclusion
This study demonstrates that H. axyridis exhibits a Type II functional response when preying on the eggs of S. litura and S. frugiperda, with adult females being the most effective predatory stage.The slightly higher predation rate on S. frugiperda eggs indicate that prey traits may influence predation efficiency. Although handling time at higher prey densities limits predation capacity, H. axyridis still shows considerable potential as a biocontrol agent in the early stages of pest outbreaks. Incorporating H. axyridis into IPM programs could strengthen sustainable pest management strategies, reducing reliance on chemical pesticides and promoting ecological balance. Further research should emphasize field evaluations, identification of preferred prey species, and assessments of environmental adaptability to optimize the biocontrol potential of H. axyridis.
Acknowledgements
This work was supported by the Ministry of Science and Technology of China (2022YFD1500701). The authors also acknowledge Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R5), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Author contributions
Arzlan Abbas: conceptualization, writing – original draft, methodology, investigation, formal analysis, data curation, writing – review and editing. Ayesha Iftikhar: methodology, investigation, formal analysis, critically revised the manuscript. Muhammad Yasir Ali: supporting, writing – review and editing. Hasnain Ali: formal analysis, writing – review and editing. Sarah I. Othman: supporting, writing – review and editing. Rasha E Abo-Eleneen: supporting, writing – review and editing. Faisal Hafeez: supervision, funding, resources and writing – review and editing. Chen RiZhao: supervision, supporting, funding, resources and writing – review and editing. All the authors have read and agreed to the published version of the manuscript.
Competing interests
The authors declare that they have no conflict of Interest.
Ethical approval
Not applicable.
Availability of data and materials
Not applicable.
