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Article

Evaluation of Adaptive Responses of Juglans neotropica Diels Progenies Based on Dasometric Traits

by
Raúl Armando Ramos-Veintimilla
1,*,
Fernando Romero-Cañizares
2,
Mariela González-Narváez
3,4,
Roy Vera-Velez
5,* and
Mario García-Mora
1
1
Facultad de Recursos Naturales, Escuela Superior Politécnica de Chimborazo, Panamericana Sur km 1 ½, Riobamba 060106, Ecuador
2
Independent Researcher, Riobamba 060111, Ecuador
3
Facultad de Ciencias de la Vida, Escuela Superior Politécnica del Litoral, Guayaquil 090902, Ecuador
4
Centro de Estudios e Investigaciones Estadísticas, Escuela Superior Politécnica del Litoral, Guayaquil 090902, Ecuador
5
Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
*
Authors to whom correspondence should be addressed.
Int. J. Plant Biol. 2025, 16(1), 26; https://doi.org/10.3390/ijpb16010026
Submission received: 31 December 2024 / Revised: 11 February 2025 / Accepted: 18 February 2025 / Published: 24 February 2025
(This article belongs to the Section Plant Biochemistry and Genetics)
Browse Figures
Review Reports Versions Notes

Abstract

:
(1) Background: Juglans neotropica Diels, native to the Andes, is highly valued for its quality wood, medicinal uses, edible fruits, and natural dyes. However, its population has been greatly reduced due to overexploitation, becoming threatened and resulting in genetic stochasticity. Therefore, a prompt ex situ and in situ conservation effort is needed for its conservation and restoration. (2) Methods: A total of 439 trees of J. neotropica Diels were sampled from selected individuals across the northern and central regions of Ecuador. These trees were planted in a randomized complete block design to assess their growth and genetic variability. (3) Results: Annual average tree growth varied significantly among progenies. Based on their dasometric traits, two distinct groups were identified as superior and surveillance. Five trees demonstrated promising traits (TJ182, ChL2314, ChL142, TJ1310, and BSM14), suggesting potential for inclusion in forest genetic improvement programs. (4) Conclusions: Fifteen percent of individuals from the five studied provenances exhibited desirable dasometric characteristics and high-quality wood. In addition, several individuals within the progenies exhibit resistance to biotic agents, indicating a genetic potential for disease.

1. Introduction

Juglans neotropica Diels, a native species of the Andean region, grows in various habitats within the Lower Montane Forest [1,2]. It is an endangered woody angiosperm of tropical origin [3]; fossil records and wood anatomical studies indicate that the taxonomic position of this species originates in the genus Enghelardia Blume, which is closely related to the Juglandaceae family. It may have been a precursor to the evolutionary lineage that includes Alfaroa Standal, Pterocarya Kunt, Carya Nutt, and Juglans L [4]. This lineage involves species such as Juglans australis Grisebach in Argentina, J. neotropica Diels in Ecuador, Colombia, and Peru, and J. boliviana (C. DC.) Dode in Bolivia [5,6].
In Ecuador, Juglans neotropica Diels, locally known as tocte or walnut, is highly adapted to the inter-Andean valley and the eastern and western mountain ranges, growing at elevations ranging from 800 to 2800 m above sea level [4,7,8,9]. Juglans neotropica Diels holds substantial socioeconomic significance and it is valued for its high-quality timber and strong market demand [10,11,12]. In addition to its timber, fruits are used in confectionery [13], and leaves are recognized for medicinal properties [14,15,16]. Juglans neotropica Diels also plays an integral role in ecological [9,17] and economic activities, such as soil reclamation in areas degraded by mining, livestock, or erosion, which enhances secondary forests and improves urban landscapes [18]. Furthermore, it provides shade in pastures and temperature regulations in coffee plantations, protects water reservoirs, sustains wildlife habitats, and acts as a source of juglone—a compound with ichthyotoxic and fungistatic properties [19,20]. J. neotropica Diels also has the potential for producing bioactive substances used in the textile agro-industry as a natural dye source [21], as well as for medicinal and food applications due to the valuable plant-based proteins [2]. Juglans neotropica Diels offers critical environmental services in the ecological restoration of degraded soils and helps maintain air and water quality within agroforestry systems, which also improves habitats and food sources for wildlife [22]. Thus, this species plays a pivotal role in adapting to climate change.
As of today, 52% of Juglans neotropica Diels populations have been overexploited due to unregulated logging practices, severely impacting their natural regeneration [10]. As a result, the species is now classified as endangered in the Andean region [23,24]. However, the literature on the genetic diversity of J. neotropica Diels within its distribution range remains scarce, worsening the challenges in conservation and propagation efforts. Nursery of the species requires prolonged periods to produce viable plants suitable for transplantation [25]. Few studies have addressed the evolutionary history, botanical characteristics, ecological roles, uses of J. neotropica Diels, and proposed strategies for its propagation and sustainable management [2]. These findings highlight its potential in maintaining biodiversity and ecological restoration, particularly in mitigating the impacts of climate change-induced soil degradation. Conversely, research on J. pyriformis Krug has primarily focused on taxonomy, distribution, phenology, productivity, biogeography, and the potential use of its seeds as biofuel [26,27]. In Europe, J. regia L. has received significant attention due to its economic importance and the value of its wood and fruits [11,12,28,29].
In Ecuador, research on the genetic diversity of J. neotropica Diels remains significantly scarce. However, the availability of quantitative data regarding growth, development, and yield in J. neotropica Diels plantations remains restricted [2], limiting informed silvicultural management decisions crucial for optimizing timber production. Forest management such as thinning aims to enhance stand structure and maximize timber yield in final harvests. Thus, evaluating the dasometric traits of J. neotropica Diels trees is essential. This study focuses on the Lower Montano thorny steppe bioclimatic conditions in Tunshi, Ecuador, where seeds from central Ecuadorian provinces are being studied in a genetic trial at the Tunshi Experimental Station of the Higher Educational Polytechnic University of Chimborazo (ESPOCH).
Genetic improvement plays a crucial role in the sustainable management of forest resources [30,31,32,33,34,35], enhancing the production quality and quantity of seeds and wood [36]. Significant genetic studies have been conducted to evaluate progenies from carefully selected mother trees with superior traits, followed by the establishment of sexual or vegetative propagation orchards [32,37]. However, despite the substantial economic and environmental benefits of genetic improvement, there remains a lack of comprehensive data on the genetic diversity of many key species [38,39], including Juglans neotropica Diels. Addressing this gap is essential for future conservation efforts and improving forest health productivity and agro-ecosystems, especially in the Andean region [25].
The genetic diversity within the population of Juglans neotropica Diels as a gene pool is a result of competing environmental variations and promoting species adaptation and resilience [30].
In this context, our goal is to evaluate the dasometric traits of J. neotropica Diels trees under these bioclimatic conditions. More specifically, we aim to identify the best-performing progenies and individual trees suited to these environmental conditions and to establish certified plant orchards to facilitate further propagation of the selected progenies.

2. Materials and Methods

2.1. Study Area

This research was conducted in the genetic trial of Juglans neotropica Diels established at the Tunshi Experimental Station located in the Licto parish, Riobamba canton, Chimborazo province (Figure 1). The geographic coordinates are 01°44′44.4″ S and 78°37′42.8″ W, with an elevation of 2711 m above sea level. The life zone is classified as Lower Montane Thorny Steep (eeMB) [40].

2.2. Data Collection

2.2.1. Plant Collection

A total of 439 trees, grouped into 46 progenies and aged 4.7 years old, were systematically evaluated. Data acquisition of these trees was carried out under the Research Network on Conservation, Domestication and Genetic Improvement of Juglans neotropica Diels project, which has been conducted by the Natural Resources Faculty since April 2018 at the Tunshi Experimental Station. All individuals are from open-pollinated seeds.
The experimental trial was established using a plant frame system of 4 m × 4 m (625 trees/ha), employing a randomized complete block design (RCBD) with unbalanced data. Each repetition featured one tree per family, serving as the experimental unit within the single-tree plot configuration. This research adopts a quasi-experimental approach [41] to evaluate the dasometric traits of individuals belonging to selected genetic progenies. These progenies were collected from designated J. neotropica Diels mother trees, and their relevant ID data are documented in Table 1.

2.2.2. Dasometric Characteristics

A set of dasometric traits for each individual and family/progeny was recorded.
Total plant height was measured using a telescopic ruler graduated in centimeters, from ground level to the terminal bud of the tree [42].
Diameter at breast height (DBH) was measured by marking a horizontal line on each tree with paint at 1.3 m from ground level and the diameter was measured using a diameter tape on a centimeter scale [43].
Living crown height was determined with a telescopic ruler, recording from ground level to the insertion point of the first branch [42].
In addition, dasometric indicators were estimated such as the mean annual increment (MAI) for total height in meters, basal area in quadratic meters, and quadratic diameter (Dg) proposed by [44]. Here, ( 4 π ∗ G N ), where
Dg = root mean square diameter (m);
G = basal area (m2);
N = number of trees on the plot;
π = constant equal to 3.141.

2.2.3. Qualitative Characteristics

The most significant biotic agent issues were identified and recorded using a documentary measurement tool through a dichotomous variable denoting presence (1) or absence (0); log quality was evaluated through a polytomous variable indicating straightness (1), slight curvature (2), or more than one curvature (3); and apical dominance was observed and documented through a documentary measurement instrument, utilizing a polytomous variable representing complete dominance of the initial axis (1), growth in two branches (2), or complete dominance on side branches (3) [43].

2.3. Statistical Analysis

Progenies of trees with complete information on all dasometric characteristics and qualitative characteristics of interest resulted in a sample size of n = 439 trees. We used descriptive analysis and single-criterion analysis of variance (ANOVA) under a randomized complete block design with unbalanced data. Statistical tests were performed with a significance level of α = 0.05. Normality and homogeneity of variances were checked using the Shapiro–Wilk and Levene tests. The Duncan test at 5% was used to separate means.
To achieve a comprehensive analysis and enhance data discrimination, a multivariate approach was adopted, employing the Biplot analysis [45] under principal coordinate analysis for mixed data types with Gower’s similarity coefficient method alongside clustering analysis using the principal coordinate data linkage Ward [46].
The Biplot analysis technique facilitates the simultaneous graphical representation of rows and columns within a matrix, effectively summarizing information from a rank, r, matrix into a lower-dimensional space of dimension, q (where q < r). The Biplot that maximizes the absorption of information, in terms of variability, from a rank r matrix X is derived from the matrix X [ q ] of rank q, representing the low-rank approximation of X. This is obtained through the singular value decomposition of X [44], expressed as follows:
X [ q ] = U q D ( q ) λ V ( q ) T
where U(q) is the matrix whose columns contain the first q eigenvectors of XXT, D(q)λ is the diagonal matrix with the first q singular values of X, and V(q) is the matrix containing the first q eigenvectors of XTX. This expression also corresponds to the singular value decomposition of X[q]. There are two classic options to achieve better quality representation of either the columns (GH) or the rows (JK).
Galindo [45] and Galindo [46] propose taking A = U(q)D(q)λ and B = D(q)λ V ( q ) T . Thus, the Biplot that was constructed was called HJ-Biplot by its author, respecting the logic of the names proposed by Galindo [45]. Its main characteristic is that both the rows and the columns reach the highest quality of representation. Notably, the internal product of vector markers does not reproduce the original data from the original matrix, even when retaining the q dimensions. However, this discrepancy does not pose an issue as the primary objective typically revolves around obtaining a simultaneous approximation of rows and columns in which both are properly represented. The multivariate analysis employed HJ-Biplot (Principal Component Analysis) and Hierarchical Cluster with the Biplot Coordinate linkage method Ward for mixed data. The analysis was primarily conducted using R Statistical Software [47].

3. Results

3.1. Dasometric Characteristics

Data on the provenances and progenies conformed to a normal distribution, and the null hypothesis of heterogeneity of variance for all seven dasometric characteristics was rejected, allowing the analysis of variance (ANOVA) to proceed (Table 2). There were no significant differences among provenances or progenies except for MAI (p = 0.01) and volume (p = 0.04) among progenies.
According to the Duncan test for four dasometric characteristics of progenies, the TJ20 family from Tungurahua provenance presented the best averages, with 85 cm in MAI height, 420 cm in total height, 2.7 (m2/ha) in basal area, and 8.5 m3/ha in volume. In contrast, the ChL19 and BJ42 progenies, which belong to the Chimborazo and Bolívar provenances, had the lowest averages (Table 3). Measurements of central tendency and dispersion of progenies for the dasometric characteristics are shown in Table 4. In Table 5, the average of six dasometric characteristics for five provenances is presented. Tungurahua, Chimborazo, and Bolívar provenances have volumes greater than 4 m3/ha.
The highest values for the seven dasometric characteristics are found in trees from the Tungurahua, Chimborazo, and Bolívar provenances. In contrast, the lowest values were found in the Imbabura and Pichincha provenances (Figure 2).

3.2. Biotic Agents

Some of the trees of the J. neotropica Diels progenies had holes in their stems, a symptom observed both at the basal part and terminal parts of the stem (Figure 3). This issue causes the tree to stop growing and eventually die. As a survival strategy, the trees tend to sprout from the lower part of the damaged area.
Individuals that presented biotic problems were labeled as trees with severe damage, accounting for 19% (Figure 3a), and were not considered part of the analysis of the dasometric characteristics. In total, 25% of the trees showed slight problems (the presence of insect damage in the tree terminal part on the first log) (Figure 3b), while 56% of the trees did not exhibit any symptoms of the biotic agents (Figure 3c). The Bolívar, Chimborazo, and Tungurahua provenances had around 45% of individuals who were unaffected by biotic agents, whereas the Imbabura and Pichincha provenances had 38% and 20%, respectively, of individuals who were unaffected by biotic agents.
Regarding log quality, the Bolívar, Chimborazo, and Tungurahua provenances had around 30% of their individuals with high-quality or straight logs, 35% of individuals had logs with a slight curvature, and 35% had poor-quality logs. In contrast, the Imbabura provenance had 10% of individuals with quality logs, 70% of trees with logs showing slight curvature, and 20% of trees with logs having more than one curvature (Figure 4). The Bolívar, Chimborazo, and Tungurahua provenances present around 40% of the trees with complete dominance in the main axis, a quality required for producing high-quality wood, while 60% of the trees showed dominance in lateral branches. In contrast, the Imbabura and Pichincha provenances had only about 20% of their studied population displaying complete dominance in the main axis.

3.3. Qualitative and Quantitative Characteristics

The Hj-Biplot analysis explains 83.1% of the total variance, corresponding to 68.2% for the first axis and 14.9% for the second axis (Figure 5).

Cross-Validation

According to this procedure, individuals were classified into two clusters or groups. The first group (red color) consisted of individuals with the best values of the dasometric characteristics (DBH, total height, mean annual increment, living crown height, basal area, quadratic diameter, and wood volume) with the standout trees being provenance Tungurahua, progeny J18 tree 2 (TJ182); provenance Chimborazo, progeny L23 tree 14 (ChL2314); provenance Chimborazo, progeny L14 tree 2 (ChL142); provenance Tungurahua, progeny J13 tree 10 (TJ1310); and provenance Bolivar, progeny SM tree 14 (BSM14). Individuals with lower dasometric characteristics were placed in the second group (blue color).
Similar results were obtained when a heat map was generated for trees exceeding the general average. The top five trees in descending order starting with the best were TJ182, ChL2314, ChL142, TJ1310, and BSM14, based on volume, apical dominance, and tolerance to biotic agents (Figure 6).

4. Discussion

The dasometric characteristics of the evaluated progenies, particularly of the J. neotropica Diels species, have been little investigated. The variation coefficients show high variability among individuals of the progenies; similar data were reported by [26] in a dasometric characterization of Juglans pyriformis Kung. The diameter is an essential measurement to determine the growth of a tree to reach desirable dimensions [18,48].
The diameter at breast height (DBH) of the present investigation (5.70 cm) is similar to the average reported by [49] (6.00 cm) and [50] for J. neotropica Diels. This trend probably occurs because the genetic management carried out during the trial of both the present investigation and [49,50] were very similar in the management and care of the plantation. In a study carried out on J. regia L., the authors of [51] indicate that they found minimal diameters given their age, which has also been reported in other studies where the 7-year-old walnut logs had diameters between 8 and 10 cm [52].
Similar trends have been reported by several researchers studying forest species evaluated at juvenile stages. Among them, the authors of [53,54] indicate that the responses of progenies and populations in dasometric variables at an early age tend to show the minimum effect of the environment. For instance, the authors of [55,56], in studies conducted on Balfourodendron riedelianum Engl., and the authors of [57,58,59], in studies of progeny provenance of other tropical tree species, state that these effects become more evident at older ages. This emphasizes the importance of conducting consecutive analyses until the species reaches maturity. For example, Juglans nigra L. can reach a DBH over 50 cm at approximately 25 years [60], and Juglans cinerea L. can reach 40 DBH in the same period [61], in both cases at ages older than those of the study that concerns us, which provides insight into the development of J. neotropica Diels.
The mean annual average increment (MAI) in height of the present investigation (62.8 cm) is similar to that reported by [50] (62.7 cm) and higher than the MAI values in height reported by [62] (55 cm), and [63] (18 cm). This trend probably occurs because the evaluated individuals came from selected mothers with superior morphological characteristics, in contrast to the plants in the trials conducted by the aforementioned authors, in which the seeds are from an unknown source origin. However, several researchers cited in [2] state that height growth rates are 14 cm/year and 200 cm/year. These rates are higher in areas where the species grows naturally under agroforestry systems and in areas with soils degraded by mining or intensive agriculture under silvicultural management.
When conventional descriptive statistical analysis was used, intrinsic numerical differences in the dasometric characteristics of the Junglas neotropica Diels were observed only between progenies, but not among provenances. Using multivariate analysis techniques, two clearly differentiated clusters formed. Cluster 1 includes trees with the highest or superior values. It should be noted that trees of the TJ20 family, which stood out in the descriptive analysis, also performed well in the multivariate analysis. This indicates that the trees belonging to the progenies TJ182, ChL2314, ChL142, TJ1310, and BSM14 have superior characteristics that should be considered in future forest genetic improvement work.
It is important to mention that some studies can contribute to a better understanding of accession characterization, such as the one on J. neotropica Diels in Bhutan, which analyzed the anatomical characteristics of vessels and rings. This allowed for an evaluation of hydraulic adjustment during drought sensitivity, which can affect its presence in different forest patches [64]. A similar study conducted in Bolivia on dendrochronology showed that Juglans boliviana (C. DC.) Dode has the potential to record past climate variability, providing insights into how forest patches respond to anthropogenic activity [65].
Several researchers have reported similar findings to this study in the literature, stating that tropical tree populations tend to show higher levels of genetic variability among individuals within populations than between them [66,67,68]. This trend probably occurs because interbreeding species tend to exhibit high levels of genetic diversity within populations and relatively low levels of divergence between populations [69]. If this pattern is maintained between provenances, the long-term improvement strategy should consider conducting new collections in other provenances to capture the greatest genetic richness that may exist between regions [70], as well as evaluate these materials in other potential environments for the establishment of J. neotropica Diels plantations.
This assertion is consistent with a study where, when evaluating accessions of Juglans regia L., a diversity of morphological and phenological characteristics could be observed that make them have great potential for use in breeding programs [71], which occurs especially in regions that correspond to the places of origin of the species, with varying levels of diversity [71,72]; however, analogous to the diversity of J neotropica Diels in South America [7], particularly in Ecuador, there are not many forest fragments of this species [18].
One way of understanding the diversity of the genus Juglans is from the study by [73], who found that J. sigillata Dode is closely related to J. regia L. according to SSR data (markers used to determine introgression). This methodology can contribute to the characterization of J. neotropica Diels in Ecuador, which, due to its variable climatic characteristics, may support the species throughout Ecuador’s entropized ecosystems [74], particularly in three ecosystems in the south: Evergreen Montane Forest, Evergreen Seasonal Lower Montane Forest, and Semi-Deciduous Foot Montane Forest [72]. Adding the dasometric information from this study would further enrich our understanding of the species diversity.
Beyond the important and rich information provided by this study for conservation and initiating a breeding program, some characteristics detected in J. regia L., such as grain weight, grain percentage, and grain color, should be considered for research [75].

5. Conclusions

Conventional statistical analyses showed similar patterns in all the quantitative variables evaluated regarding provenance, but not in progeny behavior. The HJ-Biplot analysis categorized the individuals into two groups, superiors and surveillance, allowing for the identification of individuals with greater potential to be considered as parent trees in subsequent forest genetic improvement programs.
The most important sanitary issues identified in the individuals of progenies from the studied provenances were likely caused by the Curculionidae family, with 19% of individuals presenting severe problems that affected growth height and diameter at breast height. A total of 25% of individuals showed slight damage, and 56% exhibited no issues. This trend may be related to genetic variability.
The trees, with codes TJ182, ChL2314, ChL142, TJ1310, and BSM14, of J. neotropica Diels from the provinces of Tungurahua, Chimborazo, and Bolívar excelled in the evaluated dasometric characteristics. They represent the top five progenies with superior trees identified in this genetic study, serving as candidates for future genetic improvement programs.

Author Contributions

Conceptualization and methodology, R.A.R.-V.; formal analysis and data curation, R.A.R.-V., M.G.-N. and F.R.-C.; investigation, R.A.R.-V. and M.G.-M.; writing—original draft preparation, R.A.R.-V., F.R.-C. and M.G.-N.; writing—review and editing, R.V.-V. and M.G.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are available upon request.

Acknowledgments

We thank the current authorities of the Escuela Superior Politécnica de Chimborazo-Ecuador for trusting the research team of the Juglans research project; Leonardo Gallo from INTA-Argentina for his contribution to the conceptualization of the Juglans genetic trial; and Antonio Fierro, Marlon Avila, and Paul Villegas for help with data collection. Finally, we thank Benjamin Hudock, an American Peace Corps Volunteer in Ecuador, for proofreading the English language version of the manuscript in the correction process sent by the reviewers.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study area in central Sierra in Ecuador where the genetic trial of Juglans neotropica Diels took place.
Figure 1. Study area in central Sierra in Ecuador where the genetic trial of Juglans neotropica Diels took place.
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Figure 2. Box-plot representation of seven dasometric characteristics by provenance (BOL = Bolivar; CH = Chimborazo; IMB = Imbabura; PICH = Pichincha; and TUN = Tungurahua).
Figure 2. Box-plot representation of seven dasometric characteristics by provenance (BOL = Bolivar; CH = Chimborazo; IMB = Imbabura; PICH = Pichincha; and TUN = Tungurahua).
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Figure 3. Image of problematic biotic agents affecting individuals of the Juglans neotropica Diels progeny. (a) J. neotropica Diels tree with severe damage. (b) J. neotropica Diels tree with slight damage. (c) J. neotropica Diels tree without damage.
Figure 3. Image of problematic biotic agents affecting individuals of the Juglans neotropica Diels progeny. (a) J. neotropica Diels tree with severe damage. (b) J. neotropica Diels tree with slight damage. (c) J. neotropica Diels tree without damage.
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Figure 4. Behavior of categorical variables (biotic agents, log quality, and apical dominance) in J. neotropica by provenance.
Figure 4. Behavior of categorical variables (biotic agents, log quality, and apical dominance) in J. neotropica by provenance.
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Figure 5. HJ-Biplot grouping of individuals of the J. neotropica Diels progenies from Chimborazo, Tungurahua, Bolívar, Pichincha, and Imbabura provenances, and their quantitative and qualitative characteristics.
Figure 5. HJ-Biplot grouping of individuals of the J. neotropica Diels progenies from Chimborazo, Tungurahua, Bolívar, Pichincha, and Imbabura provenances, and their quantitative and qualitative characteristics.
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Figure 6. Heat map of the best trees by provenance considering six dasometric characteristics and three qualitative variables.
Figure 6. Heat map of the best trees by provenance considering six dasometric characteristics and three qualitative variables.
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Table 1. Provenance, progeny, and geographical location of seed collection sites of J. neotropica Diels after collecting different numbers of tree samples of five provenances.
Table 1. Provenance, progeny, and geographical location of seed collection sites of J. neotropica Diels after collecting different numbers of tree samples of five provenances.
ProvenanceNo.Progeny CodeGeographical LocationNo. Trees
LatitudeLongitude
Bolivar1BSM1°48′52.6″ S79°4′9.6″ W15
2BJ411°49′10.1″ S79°3’53.6″ W18
3BJ421°48′59.1″ S79°4’12.5″ W3
4BJ441°42′26.0″ S79°2′39.0″ W9
5BJ451°48′19.0″ S79°3′58.0″ W12
6BJ471°42′11.9″ S79°2′38.7″ W16
7BJ481°48′26.2″ S79°6′5.4″ W3
Chimborazo1ChAG2°14′25.6″ S78°48′5.8″ W3
2ChG1°36′13.5″ S78°39′30.3″ W7
3ChGST1°36′13.5″ S78°39′30.3″ W5
4ChRC1°39′48.0″ S78°39′16.0″ W6
5ChJ501°38′13.8″ S78°36′56.7″ W7
6ChL12°11′59.2″ S78°50′50.7″ W20
7ChL101°43′36.1″ S78°36′22.9″ W5
8ChL121°54’49.2″ S78°38’32.4″ W16
9ChL141°54’39.8″ S78°38’32.0″ W18
10ChL162°12′6.6″ S78°50′54.6″ W8
11ChL172°13′39.0″ S78°53′35.0″ W8
12ChL191°39’26.0″ S78°34’6.7″ W5
13ChL21°39’28.4″ S78°34’2.4″ W16
14ChL211°43’38.4″ S78°35’18.5″ W18
15ChL221°39’13.5″ S78°42’37.8″ W11
16ChL231°38′33.2″ S78°33′32.6″ W14
17ChL251°40′19.6″ S78°39′34.4″ W10
18ChL271°39′35.0″ S78°40′49.0″ W14
19ChL321°40′27.2″ S78°38′25.9″ W11
20ChL351°36′8.8″ S78°31′29.6″ W7
21ChL41°43′28.3″ S78°36′17.4″ W13
22ChL51°43′19.1″ S78°36′1.6″ W8
23ChL71°43′28.3″ S78°36′17.4″ W4
Tungurahua1TJ131°12′17.0″ S78°32′13.7″ W10
2TJ141°0′0.0″ S78°35′21.0″ W13
3TJ151°16′47.0″ S78°36′58.6″ W5
4TJ161°18′21.3″ S78°36′13.1″ W8
5TJ181°15′35.5″ S78°40′43.2″ W6
6TJ191°19′47.6″ S78°37′54.9″ W8
7TJ201°14′27.7″ S78°38′33.4″ W3
8TJ221°18′18.9″ S78°36′15.3″ W10
9TJ231°10′32.4″ S78°32′50.3″ W11
10TJ241°19′29.0″ S78°37′53.8″ W10
11TJ371°12′17.0″ S78°32′13.7″ W8
12TJ81°13’16.2″ S78°32’16.6″ W8
13TJ91°14′22.1″ S78°38′24.5″ W13
14TSB1°15′11.6″ S78°37′32.1″ W3
Pichincha1PQ10°15’39.1″ S78°33’22.2″ W5
Imbabura1IICh80°21’10.0″ N78°11’30.0″ W8
B = Bolivar; Ch = Chimborazo; T = Tungurahua; P = Pichincha; I = Imbabura.
Table 2. Normality and homogeneity tests and analyses of variance by provenance and progeny for six dasometric characteristics of Juglans neotropica Diels.
Table 2. Normality and homogeneity tests and analyses of variance by provenance and progeny for six dasometric characteristics of Juglans neotropica Diels.
Shapiro–WilkLevene TestANOVA (p-Value)
ProvenancesProgenies
DBH<0.050.330.320.11 ns
Total Height<0.050.100.790.06 ns
MAI Height<0.050.240.920.01 *
Living Crown Height<0.050.140.990.12 ns
Basal Area<0.050.250.280.06 ns
Quadratic Diameter<0.050.330.320.11 ns
Volume<0.050.840.600.04 *
DBH = diameter at the breast height; MAI = mean annual increment. * Significance (p < 0.05); ns: not significant (p > 0.05).
Table 3. Mean value of MAI, total height, basal area, and volume for progenies of Juglans neotropica Diels.
Table 3. Mean value of MAI, total height, basal area, and volume for progenies of Juglans neotropica Diels.
FamilyMAI Height (cm)RangeTotal Height (cm)RangeBasal Area (m2/ha)RangeVolume (m3/ha)Range
TJ2085.2a419.2a2.7a8.5a
ChAG80.3ab377.6abc1.8bcd5.1bcd
ChRC78.1abc388.9ab2.7a8.4a
TJ1871.8abcd359.2abcd2.5ab7.3ab
BJ4770.2bcd357.2abcd1.6cd4.7bcd
ChL1468.0bcde346.2bcde1.5cd4.7bcd
ChL267.3bcde342.0bcde1.7cd4.7bcd
BSM66.1bcde328.4bcde1.5cd4.0cd
TJ1366.0bcde335.6bcde2.0bc5.3bc
TJ1465.6bcde340.4bcde1.8bcd4.6bcd
ChL2165.5bcde336.0bcde1.7cd4.0cd
TJ2265.2cde332.0bcde1.7cd4.4bcd
ChL1664.7cde325.6bcde1.5cd3.6cd
ChL2363.8cde330.5bcde1.9bcd4.6bcd
BJ4863.7cde328.4bcde1.8bcd4.4bcd
BJ4563.7cde326.4bcde1.6cd3.9cd
TJ1563.3cde316.5bcde1.6cd3.9cd
ChJ5062.8cde319.0bcde1.5cd3.8cd
ChL1762.6cde315.1bcde1.7bcd3.9cd
TJ2462.5cde322.1bcde1.7bcd4.5bcd
ChG62.5cde312.7bcde1.9bcd4.7bcd
ChL562.5cde325.1bcde1.8bcd4.9bcd
TSB62.3cde313.8bcde1.6cd3.8cd
ChL3562.2de321.9bcde1.9bcd4.4bcd
TJ962.1de318.9bcde1.8bcd4.4bcd
ChL1262.1de320.3bcde1.6cd3.7cd
ChL162.0de323.8bcde1.6cd3.6cd
TJ3761.7de314.4bcde1.6cd4.2bcd
ChL3261.2de315.7bcde1.5cd3.7cd
ChL2761.1de321.5bcde1.6cd4.2bcd
ChL2560.5de312.0cde1.7bcd4.3bcd
ChL460.0de312.2cde1.5cd3.6cd
TJ859.6de306.9cde1.6cd3.9cd
BJ4459.6de307.5cde1.4cd3.2cd
ChL759.3de314.3bcde1.7cd4.6bcd
ChL2259.2de307.2cde1.7bcd4.0cd
TJ1958.5de293.8de1.4cd2.3cd
BJ4158.3de302.5cde1.7bcd4.0cd
CHGST57.0de294.3de1.7bcd3.5cd
ChL1056.6de293.1de1.3cd3.0cd
TJ2356.3de297.1de1.5cd3.6cd
BJ4255.9de285.7de1.2cd1.9d
TJ1653.7e269.4e1.3cd2.4cd
ChL1952.8e284.4de1.1d3.0cd
MAI = mean annual increment; progenies with same letter are not significantly different. B = Bolivar; Ch = Chimborazo; and T = Tungurahua.
Table 4. Measurements of central tendency and dispersion of the dasometric characteristics of J. neotropica Diels progenies evaluated in the ESPOCH genetic trail.
Table 4. Measurements of central tendency and dispersion of the dasometric characteristics of J. neotropica Diels progenies evaluated in the ESPOCH genetic trail.
Dasometric CharacteristicsMeanSDMinMax
Diameter breast height (cm)5.71.12.910.1
Total height (cm)322.359.9192.0551.0
Mean annual increment height (cm)63.012.733.8114.7
Living crown height (cm)291.577.4138.0551.0
Basal area (m2/ha)1.70.70.45.0
Quadratic diameter (cm)0.60.10.31.0
Volume (m3/ha)4.22.60.515.6
SD = standard deviation; Min = minimum; Max = maximum.
Table 5. The mean ± standard deviation (SD) of dasometric characteristics of genetic progenies of Juglans neotropica Diels.
Table 5. The mean ± standard deviation (SD) of dasometric characteristics of genetic progenies of Juglans neotropica Diels.
ProvenanceDBH (cm)MAI Height (cm)Total Height (cm)Living Crown Height (cm)Basal Area (m2/ha)Volume (m3/ha)
Bolívar5.6 ± 1.063.5 ± 14.2323.86 ± 66.9292.1 ± 87.31.6 ± 0.64.0 ± 2.4
Chimborazo5.8 ± 1.163.2 ± 12.0324.8 ± 55.3292.3 ± 75.61.7 ± 0.74.2 ± 2.6
Imbabura5.3 ± 0.956.8 ± 7.2277.2 ± 36.9251.0 ± 44.81.4 ± 0.53.0 ± 1.4
Pichincha5.0 ± 1.862.0 ± 26.7302.7 ± 127.1263.2 ± 151.21.4 ± 1.03.7 ± 4.9
Tungurahua5.8 ± 1.262.7 ± 12.8320.2 ± 61.1293.5 ± 71.91.7 ± 0.74.3 ± 2.7
DBH = diameter at the breast height; MAI = mean annual increment.
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Ramos-Veintimilla, R.A.; Romero-Cañizares, F.; González-Narváez, M.; Vera-Velez, R.; García-Mora, M. Evaluation of Adaptive Responses of Juglans neotropica Diels Progenies Based on Dasometric Traits. Int. J. Plant Biol. 2025, 16, 26. https://doi.org/10.3390/ijpb16010026

AMA Style

Ramos-Veintimilla RA, Romero-Cañizares F, González-Narváez M, Vera-Velez R, García-Mora M. Evaluation of Adaptive Responses of Juglans neotropica Diels Progenies Based on Dasometric Traits. International Journal of Plant Biology. 2025; 16(1):26. https://doi.org/10.3390/ijpb16010026

Chicago/Turabian Style

Ramos-Veintimilla, Raúl Armando, Fernando Romero-Cañizares, Mariela González-Narváez, Roy Vera-Velez, and Mario García-Mora. 2025. "Evaluation of Adaptive Responses of Juglans neotropica Diels Progenies Based on Dasometric Traits" International Journal of Plant Biology 16, no. 1: 26. https://doi.org/10.3390/ijpb16010026

APA Style

Ramos-Veintimilla, R. A., Romero-Cañizares, F., González-Narváez, M., Vera-Velez, R., & García-Mora, M. (2025). Evaluation of Adaptive Responses of Juglans neotropica Diels Progenies Based on Dasometric Traits. International Journal of Plant Biology, 16(1), 26. https://doi.org/10.3390/ijpb16010026

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