RESEARCH ARTICLE

Resilience of progeny of Swietenia macrophylla to the simulated attack of Hypsipyla grandella in nursery

Jorge Manuel Revilla-Chávez1, 2; Rubén Darío Manturano-Pérez3; Antony Cristhian Gonzales-Alvarado4

Rubén Casas-Reátegui5; Linda Ibeth Briceño Dueñas3; Jorge Arturo Mori-Vásquez6

Alexandre Magno Sebbenn2, 6

1 Research Institute of the Peruvian Amazon-IIAP, Regional Directorate of Ucayali, Federico Basadre Highway km 12400, Yarina Cocha, Ucayali, Peru.

2 São Paulo State University (UNESP), School of Engineering, Ilha Solteira, CP 31, CEP 15385-000, Ilha Solteira, São Paulo State, Brazil.

3  Universidad Nacional de Ucayali, Facultad de Ciencias Forestales y Ambientales, carretera Federico Basadre km 6,200, Pucallpa, Ucayali, Peru.

4  Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, São Bernardo do Campo 09606-045, SP, Brazil.

5 Universidad Nacional Intercultural de la Amazonía - UNIA, San José Highway km 0.5 Yarina Cocha, Ucayali, Peru.

6 Instituto Florestal de São Paulo, São Paulo, CP 1322, CEP 01059-970. SP, Brazil.

* Corresponding author: jrevilla@iiap.gob.pe (J. M. Revilla-Chávez).

Received: 11 December 2024. Accepted: 12 May 2025. Published: 25 May 2025.

Abstract

The resilience of seedlings from four open-pollinated families of Swietenia macrophylla to simulated attacks by Hypsipyla grandella was evaluated at the nursery stage to determine the possibility of early selection of individuals from the most resilient families and establish sustainable forest plantations in the Peruvian Amazon. Significant differences were detected among families for diameter (D), sprout length (SL), and basal sprout area (BA). The coefficient of determination for genotypic effects was moderate (range: 0.248 – 0.457) for H (plant height), D, SL, and BA, and low (< 0.15) for plant base height (HB), number of sprouts (NR), number of branches (NB), and number of leaves (NL). The genetic correlation for the traits H, D, SL, BA, NR, NB, and NL ranged from 0.228 to 0.996, indicating that an increase in one of these traits can result in an increase in the other. This is important because there is the possibility of early selection of families for the traits D, SL, and BA for the development of plantations with families resistant to attack. Therefore, the genetic and phenotypic variation observed in the families suggests the possibility of early selection as a promising strategy for genetic improvement programs, using a larger number of families than those used in the present study, since theoretically larger samples may contain greater genetic variation between and within families.

Keywords: Amazonia; early selection; progeny; shoot borer; mahogany.

DOI: https://doi.org/10.17268/sci.agropecu.2025.029

Cite this article:

Revilla-Chávez, J. M., Manturano-Pérez, R. D., Gonzales-Alvarado, A. C., Casas-Reátegui, R., Briceño Dueñas, L. I., Mori-Vásquez, J. A., & Sebbenn, A. M. (2025). Resilience of progeny of Swietenia macrophylla to the simulated attack of Hypsipyla grandella in nursery. Scientia Agropecuaria, 16(3), 397-406.

1. Introduction

Mahogany, Swietenia macrophylla King (Meliaceae) is one of the most valuable large, deciduous Neo­tropical tree species on the world market (Gullison et al., 1996; Degen et al., 2012; Sebbenn et al., 2012). Its wood has excellent aesthetic, physical, and me­chanical characteristics, remarkable workability, and is used in the manufacture of luxury furniture, inte­rior decoration for civil construction, and musical in­struments (Carvalho, 2006; André et al., 2008). The geographic range of S. macrophylla extends from southern Mexico to the southern Amazon basin in Bolivia, Brazil, and Peru (Lamb, 1966). In adulthood, individuals can reach a diameter at breast height > 2 m and a tree height of up to 50 m (Gullison et al., 1996), but population density is generally low, <1 tree/ha (Grogan et al., 2008). Logging of S. macro­phylla began in the 16th century in Central American populations (Mejía et al., 2008), but large-scale har­vesting began in South American populations in the 20th Century (Grogan et al., 2008), where due to over-exploitation during the 1970s and 1980s resulted in a decline in their natural populations (Alcalá et al., 2015). In Peru, the species has been ex­ploited since the 1920s (Mejía et al., 2008). As a re­sult, many natural S. macrophylla populations have become spatially isolated, resulting in a loss of ge­netic diversity (Novick et al., 2003; Breed et al., 2012; Degen et al., 2012; Sebbenn et al., 2012; Alcalá et al., 2015; Oliveira et al., 2020; Andrade et al., 2022). Due to that, S. macrophylla was included on the list of endangered species of the Convention on Interna­tional Trade in Endangered Species of Wild Fauna and Flora (CITES) Appendix II (CITES, 2019).

Across the geographic range of S. macrophylla nat­ural distribution, demand for its timber has ex­ceeded available supply due to extinction or de­creases in natural population sizes throughout its range (Reynel et al., 2003; Campos et al., 2009; Castro et al., 2019; Andrade et al., 2022; Arlacon-Méndez et al., 2023). The future of ma­hogany as a commercial timber species is at risk due to over-exploitation and deforestation (Verwer et al., 2008). For this reason, the use of the species in com­mercial reforestation and degraded area restoration programs has been gaining prominence in various places across the Americas (Barrena & Vargas, 2004; Kurihara et al., 2005). However, insects such as Hypsipyla grandella Zeller (Lepidoptera: Pyralidae) have been identified as the main pest and the most important barrier to establishing and developing S. macrophylla commercial plantations (Grijpma & Gara, 1976; Lunz et al., 2009). The caterpillar attacks the terminal bud of the plant causing bifurcations (Grijpma & Gara, 1976; Lunz et al., 2009), or it can feed on the fruits and seeds of the plant (Castro et al., 2019).

Hypsipyla grandella is difficult to control, which is why multiple methods were tested with different re­sults, even though they could significantly reduce populations, although even low population levels could cause important damage to the plantation, among the most commonly used ones are silvicul­tural management, chemical, bioecological control, integrated systems, resistance to hosting and com­binations between methods, are some of them (Álvarez et al., 2021; Guerra-Arevalo et al., 2022; Dueñas, 2022; Borges et al., 2022; Ávila-Arias et al., 2023; Domínguez et al., 2023; García et al., 2024; Ávila-Arias et al., 2025).

One way to address this problem is to establish commercial plantations with seedlings that are resistant to H. grandella attacks (Newton et al., 1993; Mayhew & Newton, 1998; Schabel et al., 1999). To develop a selection strategy, the three aspects of co­existence, prevention, and sustainability must be considered, alongside the use of resistant or tolerant trees based on the antixenosis of H. grandella to the Meliaceae family throughout the Americas (Jiménez, 2007). In terms of improving tree response to H. grandella attacks, the terminal bud of the plant can be eliminated by pruning so that it does not bifur­cate or emit several regrowth sprouts, with subse­quent selection of the most vigorous plants (Navarro et al., 2004; Revilla-Chávez et al., 2024).

In this context, the use of techniques such as the pre­dictive decapitation of S. macrophylla regrowth can help genetic selection by identifying trees with greater tolerance to H. grandella attacks, resulting in improved commercial plantation viability (Cornelius, 2009). Based on this technique, studies have ob­served genetic differences at the individual level, where S. macrophylla from Panama produced an average of 2.2 regrowth sprouts per tree after de­capitation with scissors, while those from Costa Rica had 3.1 regrowth sprouts per tree (Hilje & Cornelius, 2001). In the case of Meliaceae species such as Cedrela sp. and S. macrophylla, the number of re­growth sprouts produced after an H. grandella at­tack represents an important component of attack tolerance, as species show a wide range of re­sponses, from a single regrowth to 10 or more (Hilje & Cornelius, 2001). Thus, simulated attacks using scissors can be conducted across different geno­types early in the nursery phase for later establish­ment in the field. The results suggest that it is feasi­ble to identify genotypes that are more tolerant to attack by using the decapitation test (Hilje & Cornelius, 2001; Revilla-Chávez et al., 2024).

The aim of this study was to assess the vegetative regrowth of S. macrophylla plants from four different families to simulated attacks by H. grandella in a nursery and examine the possibility of early selection of individuals more suitable for the development of forest plantations in the Peruvian Amazon. We em­phasize that the present study represents an explor­atory investigation (pilot study) to assess the possi­bility of early selection of S. macrophylla individuals for vegetative regrowth before H. grandella attack in the nursery phase. This is not an empirical study aimed at using the selected plants in a program of genetic improvement of the species, as a progeny test with only four S. macrophylla families is insuffi­cient to conduct selection between and within progenies in a breeding program.

2. Methodology

The study was carried out in the Forest Nursery at the Faculty of Forestry and Environmental Sciences of the National University of Ucayali, Manantay dis­trict, Coronel Portillo Province, Ucayali Region, Peru. For the study, open-pollinated seeds from four seed-trees were sampled at four locations: Juanjui (UTM 326823E, 9055066N; elevation of 283 m) and Sisa (326878E; 8767893N; elevation of 430 m), rep­resenting families from the San Martin region; and Primavera (558797E; 8779586N; elevation of 164 m) and Unión (559748E; 8801935N; elevation of 164 m), representing families from the Ucayali region (Figure 1). On September 6, 2018, 175 seeds per family were sown directly into polyethylene bags with fertile sub­strate, composed of two volumes of black soil, one of sand and one of worm humus, with a texture of 40% silt, 30% clay and 30% sand. Of the sown seeds, 27 Juanjui seeds, 16 Sisa seeds, 143 Primavera seeds, and 25 Unión seeds germinated. On December 29, 2018, when the plants reached an average height of 30 cm, 50% of the crowns of 77 plants selected for their best phenotypic characteristics in the nursery were decapitated with pruning shears to simulate an attack by H. grandella (Figure 2). A completely ran­domized design with unbalanced repetitions was applied, with 22 from the Juanjui family, 22 from the Primavera family, 22 from the Unión family, and 11 from Sisa. After decapitation, the plants were eval­uated at 194 days of age. Plant height (H, cm), plant base height (HB, cm), stem diameter (D, cm), num­ber of regrowth sprouts (NR), sum of regrowth length (RL, cm), regrowth basal area (BA, mm2), number of branches (NB), and number of leaves (NL), were evaluated until robust regrowth sprouts were obtained.

Figure 1. Map of Swietenia macrophylla germplasm collection and area of the project; 1=Juanjui (San Martín); 2=Sisa (San Martín); 3=Primavera (Ucayali); 4=Unión (Ucayali).

Figure 2. Decapitation of 50% of the crown of plants in the nursery to simulate the attack of Hypsipyla grandella; a: plants in nursery; b, c: decapitation of the plant; d: disinfection and cut sealing; e, f: regrowth 23 days after decapitation.

A multivariate analysis was conducted to evaluate the genetic and phenotypic correlations among the variables of interest. The variables considered in the study were: plant height (H), plant base height (HB), stem diameter (D), number of regrowths (NR), sum of regrowth length (RL), regrowth basal area (BA), number of branches (NB), and number of leaves (NL).

Initially, the phenotypic data corresponding to these traits were subjected to a cleaning process, which included the elimination of missing values and the correction of potential outliers using standard statistical procedures. Subsequently, a phenotypic correlation matrix was constructed using Pearson's correlation coefficient, as the variables exhibited distributions approximately close to normality. This coefficient is widely used to quantify the linear association between quantitative variables in studies focused on the prediction of plant quantitative traits (Pan et al., 2024).

In parallel, to address genetic correlations, the data were grouped according to their genetic origin or provenance. Phenotypic means were calculated by provenance, and a genetic correlation matrix was developed based on these means, again applying Pearson’s correlation coefficient. This methodology allowed for the analysis of the average behavior of genetic groups and the detection of association patterns among the different traits.

Additionally, a Principal Component Analysis (PCA) was performed on the phenotypic data matrices. This technique facilitated the reduction of data dimensionality, allowing a graphical representation of individuals and variables based on the principal sources of variability. Variables were interpreted according to their contributions to each principal component, highlighting those that explained the highest percentage of total variability. The optimal number of components retained was determined using the elbow method, a widely employed technique for identifying the appropriate number of components in clustering and dimensionality reduction analyses (Crista et al., 2024).

Finally, the results derived from the multivariate analysis were interpreted comprehensively, identifying the most relevant phenotypic and genetic traits, the patterns of association among them, and their relationship with the different provenances analyzed. This methodological strategy provided a robust basis for understanding the existing phenotypic and genetic diversity, as well as for designing strategies aimed at selecting and conserving superior genetic materials.

3. Results and discussion

From the evaluation it is observed that the Juanjui, Primavera, Unión and Sisa origins had the best growth in descending order, while Primavera, Sisa, Juanjui and Unión in descending order had the greatest standard deviations (Figure 3). In the same way significant differences between at least two means of families were detected for stem diameter (D), regrowth length (RL), and regrowth basal area (BA), suggesting the possibility of genetic improve­ment through selection between families (Table 1). These results show that before the attack of H. grandella in the nursery stage, it is possible to con­duct early selection of S. macrophylla families to quickly obtain genetic gains to establish experi­mental and commercial plantations.

Swietenia macrophylla is commonly used in refor­estation projects (Barrena & Vargas, 2004; Kurihara et al., 2005; Ríos-Saucedo et al., 2017). Among the evaluated traits, the regrowth length (RL) is im­portant for the management of S. macrophylla seedlings for reforestation purposes since individu­als with greater RL can reach 6 m in height more quickly (Hilje & Cornelius, 2001). When experiencing recurrent attacks, this means healthy segments can develop until the next attack, thus improving wood quality (Cornelius, 2009). As the simulated H. grandella attack resulted in significant differences between families for regrowth length (RL) and other traits (D, BA), RL should be considered an important variable for early selection, rather than just consid­ering growth in height and diameter for seedling selection.

For the traits plant base height (HB), number of regrowths (NR), number of branches (NB), and number of leaves (NL), the coefficient of genotypic determination (C2i) was low (ranged from 0.002 – 0.144), where for the plant height (H), diameter (D), regrowth lengths (RL), and regrowth basal area (BA) traits C2i was moderate (ranged from 0.248 – 0.457, Table 1). These results indicate that H, D, RL, and BA may be more effective in increasing the population mean of traits by mass selection at the nursery trial stage and 194 days after the simulated H. grandella attack. This is particularly the case with RL which showed the highest values of C2i. However, the mean standard error of C2i(SE) was generally high for all traits (SE: ranging from 0.028 – 0.46), which is related to the low total number of evaluated families (4) and individuals (77) in the progeny test. Thus, we strongly recommend that future studies include at least 500 individuals in the progeny test.

Figure 3. Means and standard deviations of Swietenia macrophylla provenances for the variables A. plant height (H, cm), B. plant base height (HB, cm), C. stem diameter (D, cm), D. number of regrowth sprouts (NR), E. sum of regrowth length (RL, cm), F. number of leaves (NL), G. number of branches (NB) and H. regrowth basal area (BA, mm2) at 114 days in the nursery.

Table 1

Mean, coefficient of genotypic determination (C2i), coefficient of individual genetic variation (CVgi (%)) and expected genetic gain by massal selection (G(%)) of traits

LRT: Likelihood ratio test, χ2 deviance chi-square; *p < 0.05, with 0.5 degree of freedom; ± SE is the mean standard error.

The coefficient of individual additive genotypic variation (CVgi) was moderated for RL, BA, NB, and NL (ranging from 12.1% – 17%), and low for H, HB, D, and NR (ranging from 1.4 –7.7%). These results reinforce the possibility of obtaining genetic gains by mass selection due to the presence of additive genetic inheritance for the traits. For example, the mass selection of 26% of plants suggests an expected genetic gain ranging among traits from 0.02 – 6.9%. There are no other studies on S. macrophylla that report C2i (or h2i) and CVgi values for all traits evaluated in the present study, and most have focused mainly on plant H and DBH. Estimates of h2i and CVgi for height and DBH in S. macrophylla have shown variation across sites and age of trees. Estimates on h2i between 1.6 and 5 years of age have reported values ranging from 0.05–0.6 for H and from 0.07 – 0.55 for DBH, while estimates of CVgi have ranged from 5.1–20.1% for H and from 0.5% – 21.9% for DBH (Navarro & Hernández, 2004; Wightman et al., 2008; Abarquez et al., 2015). The results for C2i and CVgi are within the observed ranges identified in previous studies for h2i and CVgi.

The genetic (rg) and phenotypic (rf) correlation coefficients between pairs of traits ranged from -0.727 – 0.996 (Table 2). The rg and rf correlations between HB and H and D were higher than zero (ranged from 0.64 – 0.881), where between HB and NR, RL, BA, NB, and NL were lower than zero (ranged from -0.059 to -0.727). For the other pairwise traits, the rg and rf correlations were higher than zero (0.028 – 0.996). We arbitrarily classified the magnitude of rg and rf values higher than zero as low (r < 0.3), moderate (0.3 ≤ r < 0.6), and strong (r ≥ 0.6). The rg and rf correlations were generally moderated or high (90.5%). The rg correlation was low between RL x NL (0.228), and the rf correlation was low between H x NR, H x NB, and NR x NL (ranging from 0.195 – 0.282). For the other pairs of traits, the rg and rf correlations were moderate or high (ranging from 0.302 – 0.996). These results indicate that an increase in one of the traits results in an increase in the other, especially for pairwise traits showing high genetic correlations.

Regrowth length (RL) is an important trait for the recovery of plants after decapitation or simulated attacks by H. grandella (Ríos-Saucedo et al., 2017). Thus, RL is a key trait consideration in early selection strategies because it helps individuals quickly surpass the critical phase (6 m in height), which occurs in the first three years (Hilje & Cornelius, 2001). After this phase, the risk of H. grandella attack decreases significantly. Because attacks occur in periodic and recurrent episodes, the selection of individuals with more vegetative regrowth can lead to improved growth with intact sections and relatively long stems (Hilje & Cornelius, 2001). The generally moderate to high genetic correlation (rg) found between RL and H, D, NR, BA, NB traits (0.441 – 0.996) indicates that selecting plants with a higher RL will result in indirect selection for other traits. Furthermore, due to the substantial phenotypic correlation (rf) found between RL with H and D (0.893 and 0.526, respectively), traits that are easily measured, early selection strategies for vegetative regrowth before H. grandella attacks at the nursery stage are expected to be effective.

Principal Components Analysis (PCA) allowed for the graphical representation of the relationships between the phenotypic variables and the evaluated provenances. The first two principal components (Dim1 and Dim2) explained 64.2% and 22.2% of the total variability, respectively, together accounting for 86.4% of the observed phenotypic variation (Figure 4). The vectors of the variables indicated patterns of association: the sum of shoot lengths (RL) and the number of leaves (NL) showed a strong positive correlation, projecting in similar directions. Likewise, the basal shoot area (BA) and the number of branches (NB) showed a moderate positive association. In contrast, the number of shoots (NR) was located almost in the opposite direction to plant height (H) and the height at the base of the plant (HB), suggesting a negative correlation between regrowth frequency and plant size.

Table 2

Genetic (upper diagonal) and phenotypic (lower diagonal) correlation between pairwise traits

Plant height (H), plant base height (HB), stem diameter (D), number of regrowth (NR), sum of regrowth length (RL), regrowth basal area (BA), number of branches (NB), and number of leaves (NL).

In relation to the provenances, Sisa projected toward the positive side of Dim1, suggesting a greater influence of traits associated with a high number of regrowth (NR). Juanjui was located toward the negative side of Dim1, indicating contrasting traits, likely related to greater plant height (H) and base height (HB). Primavera was positioned near the origin of the coordinate plane, indicating intermediate phenotypic values for most variables. Unión, meanwhile, separated along Dim2, suggesting particular traits possibly related to stem diameter (D) and other secondary variables. Overall, PCA facilitated the identification of key traits that differentiate the provenances, with NR, RL, and NL contributing the most to the observed variation. These results provide valuable information for selecting materials with greater regrowth potential and for understanding the genetic structure among the provenances studied.

Figure 4. Principal component analysis (PCA) for the Juanjui, Primavera, Unión and Sisa provenances for the variables plant height (H, cm), plant base height (HB, cm), stem diameter (D, cm), number of regrowth sprouts (NR), sum of regrowth length (RL, cm), regrowth basal area (BA, mm2), number of branches (NB), and number of leaves (NL).

The results of the Principal Component Analysis (PCA) show clear patterns of phenotypic differentiation among the evaluated provenances, based on variables primarily related to regrowth behavior and plant structural growth. Sisa's separation toward positive values of the first principal component (Dim1) suggests greater regrowth vigor, characterized by a greater number of regrowth (NR) and greater total regrowth length (RL), which could be associated with adaptive strategies in the face of environmental disturbances. In contrast, Juanjui's position on the negative side of Dim1 indicates a phenotypic profile centered on larger structural size, such as plant height (H) and base height (HB), but with a lower propensity for regrowth. This pattern could reflect adaptations to more stable environments, where height growth represents a competitive advantage.

Primavera's proximity to the origin suggests a provenance with intermediate behavior, while Unión, with its separation along Dim2, could represent a particular phenotypic variability, possibly associated with stem diameter (D) or traits related to bole robustness. These findings are consistent with recent studies highlighting the importance of phenotypic variability in genetic conservation strate-gies and the selection of superior materials (Zhou et al., 2021; Silva et al., 2023). The identification of key traits, such as the number of shoots and the sum of shoot lengths, provides a solid basis for future breeding programs aimed at enhancing the resilience and productivity of the study populations. Furthermore, the combined use of genetic and phenotypic correlations, along with PCA, proves to be an effective tool for exploring intraspecific diversity and for outlining management and conservation strategies tailored to the genetic characteristics of each provenance.

4. Conclusions

The conclusions should be interpreted with caution, as the study was based on a limited sample of four open-pollinated families of Swietenia macrophylla. After simulating an attack by Hypsipyla grandella, genetic differences were observed in stem diameter, regrowth length, and basal area, suggesting potential for genetic improvement through early selection. Regrowth length emerged as the most relevant trait, showing genetic correlations with plant height and diameter, enabling indirect selection at the nursery stage. Furthermore, height, diameter, and basal area of regrowth showed moderate genotypic determination coefficients, supporting their use in mass selection. Principal Component Analysis (PCA) revealed structured differentiation among provenances, with plant height, basal height, number of regrowth, and regrowth length contributing most to multivariate discrimination, indicating underlying genetic patterns that could be strategically exploited in breeding and conservation programs.

Acknowledgments

We thank the National University of Ucayali for financing this project, the Peruvian Amazon Research Institute for technical support, and Dr. Jonathan Cornelius for the scientific suggestions in the present study. We also thank Dr. Evelyn R. Nimmo for assistance with English language editing.

Contribution from authors

J. M. Revilla-Chávez: Writing – original draft. R. D. Manturano-Pérez: Acquisition of financing, Methodology and review. A. C. Gonzales-Alvarado: Data curation. R. Casas-Reátegui: Conceptualization, formulation or evolution of general research goals and objectives. L. I. Briceño Dueñas: Data curation. J. A. Mori-Vásquez: Methodology, Development or design of methodology; Model Creation. A. M. Sebbenn: Proofreading and editing, Formal analysis.

ORCID

J. M. Revilla-Chávez https://orcid.org/0000-0001-5978-5146

R. D. Manturano-Pérez https://orcid.org/0000-0002-5063-8593

A. C. Gonzales-Alvarado https://orcid.org/0000-0003-3793-0271

R. Casas-Reátegui https://orcid.org/0000-0003-3781-166X

L. I. Briceño Dueñas https://orcid.org/0009-0003-1857-2517

J. A. Mori-Vásquez https://orcid.org/0000-0003-0570-8369

A. M. Sebbenn https://orcid.org/0000-0003-2352-0941

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