Do dendrometric and competition variables influence Jatobá-do-cerrado (Hymenaea stigonocarpa Mart. Ex Hayne) fruit yield probability?

Variáveis dendrométricas e competição influenciam a probabilidade de frutificação do jatobá-do-cerrado (Hymenaea stigonocarpa Mart. ex Hayne)?

Abstract

The Brazilian Cerrado has high diversity of species with non-timber potential. Hymenaea stigonocarpa, commonly known as Jatobá-do-cerrado, is among them. This species stands out for its high economic potential, since its fruits are used in the food and pharmaceutical sectors. It is important knowing this species representatives’ yield potential to improve their fruit management practices by analyzing their morphometry in association with their competitive environment. The aim of the present study is to build a probabilistic model for H. stigonocarpa fruit yield based on dendrometric variables and competition indices. In order to do so, 60 individuals belonging to this species were sampled in a Cerrado region in Minas Gerais State. Diameter at breast height (1.30 m - dbh), total height and competition indices at distances of 3, 6 and 9m were calculated. These variables were related to fruit yield and a model was adjusted to estimate the species’ yield probability. The quality of the sampled individuals was checked and each inventoried tree was classified based on stem quality, and on crown quality and lighting. Variable DBH helped estimating the species fruits’ yield probability based on the trend of fruit yield decrease due to individuals’ DBH increase. Likewise, the semi-dependent competition index, at 3m radius, helped estimating fruit yield. Yet, the increased competition has reduced the fruit yield probability. Smaller individuals were less competitive, but they were more likely to achieve higher fruit yield probability than the bigger ones.

Keywords:
forest management; Logit model; non-timber forest products

Resumo

O Cerrado brasileiro apresenta alta diversidade de espécies com potencial não madeireiro. Hymenaea stigonocarpa, conhecida popularmente como Jatobá-do-cerrado, é uma delas. Essa espécie destaca-se pelo seu alto potencial econômico, visto que seus frutos são utilizados nas indústrias alimentícia e farmacêutica. É importante conhecer o potencial produtivo dos representantes dessa espécie para aprimorar as práticas de manejo de frutos, analisando sua morfometria em associação com o ambiente competitivo. O objetivo deste estudo é construir um modelo probabilístico para a produtividade de frutos de H. stigonocarpa com base em variáveis ​​dendrométricas e índices de competição. Para tanto, 60 indivíduos dessa espécie foram amostrados em uma região de Cerrado no estado de Minas Gerais. Foram calculados o diâmetro à altura do peito (DAP), a altura total e os índices de competição nas distâncias de 3, 6 e 9 m. Essas variáveis ​​foram relacionadas à produtividade de frutos e um modelo foi ajustado para estimar a probabilidade de produtividade da espécie. A qualidade dos indivíduos amostrados foi verificada e cada árvore inventariada foi classificada com base na qualidade do caule, na qualidade da copa e na iluminação. A variável DAP ajudou a estimar a probabilidade de produção de frutos das espécies com base na tendência de diminuição da produção de frutos devido ao aumento do DAP dos indivíduos. Da mesma forma, o índice de competição semi-dependente, no raio de 3m, auxiliou na estimativa da produtividade de frutos. No entanto, o aumento da competição reduziu a probabilidade de produção de frutos. Indivíduos menores eram menos competitivos, mas tinham maior probabilidade de atingir maior probabilidade de produção de frutos do que os maiores.

Palavras-chave:
manejo florestal; modelo Logit; produtos florestais não madeireiros

1. Introduction

Cerrado is the second largest biome in South America, since its area covers ​​approximately 41.8 million hectares of natural forests (Strassburg et al., 2017). It is one of the richest savanna biomes in the world (Fonseca et al., 2010; Colli et al., 2020) besides being seen as biodiversity hotspot (Oliveira et al., 2007; Grande et al., 2020; Hofmann et al., 2021). Its great diversity of species represents a source of income and subsistence for traditional populations, mainly when it comes to resources with non-timber forest potential, which provide medicines, food and even handicraft raw materials for these populations (Gonçalves et al., 2015; Bispo et al., 2020).

Hymenaea stigonocarpa Mart stands out among Cerrado species with non-timber forest potential. Ex Hayne, commonly known as Jatobá-do-cerrado, Jutaí and Jatobá-capó, belongs to family Fabaceae (Leguminosae) (Lorenzi, 2014). Its morphology is featured by plants approximately 9m high, with stems measuring from 30 to 50 cm, in diameter, whitish flowers and legume-type fruits with 2 to 4 seeds surrounded by a yellowish mealy pulp (Carvalho, 2007; Lorenzi, 2014). According to Silva (2018), Jatobá-do-cerrado blooms from September to March, whereas fruiting often starts in April – the fruiting season can last until November, depending on the region.

H. stigonocarpa fruits have great yield potential in the food and pharmaceutical sectors. Their pulp can be consumed fresh, or used in bread, cake, ice cream and liqueur preparations (Costa, 2015; Menezes Filho and Castro, 2018; Silva et al., 2020). In addition to the pulp, their skin has antioxidant and antifungal properties (Menezes Filho et al., 2019, 2020; Panontin et al., 2020).

Fruit production in woody species of the Brazilian Cerrado is strongly associated with phenological patterns, environmental variability and individual plant attributes, resulting in marked differences in reproductive output among trees (Batalha and Martins, 2019; Felfili et al., 2017). Inter and intraspecific competition in the environment plants find themselves in is decisive for fruit yield due to dispute for nutrients, water and light (Zanine and Santos, 2004; Bastos et al., 2017; Fróes Júnior et al., 2019; Medda et al., 2022). In addition to competition, trees’ dendrometric features are also correlated to fruit yield (Ivanov, 2011; Tonini, 2013; Passos, 2014; Ferreira et al., 2021).

Competition between individuals is an important quantitative variable in forest environments, since it plays key role in individuals’ growth, survival and yield dynamics (Lambrecht et al., 2019; Schons et al., 2020; Lustosa Junior et al., 2021). Using competition indices is one way to represent competition (Schons et al., 2020). Currently used competition indices take into consideration trees’ dendrometric variables and the competing individuals around them; yet, the distance between them may also be considered.

Competition can be calculated by using three different groups: distance-independent, distance-dependent and semi-independent distance. In the first case, trees’ dimensions and competitors’ mean dimensions are compared in the same sampling unit or fragment, without taking into account the distance between them. The same comparison is performed to find the distance-dependent index; however, it is weighted based on the distance between competing trees and the object tree. The same calculation of independent index is applied to semi-independent distance index; but, it is only assessed between trees in smaller and pre-defined competition radii, without taking into account distances to calculate the indices (Stage and Ledermann, 2008; Tomé and Burkhart, 2012).

Accordingly, regression models can be applied to predict fruit yield estimates depending on competition factors, and the binomial logistic model is among the most used ones. Using independent variables, such as diameter, height and competition index, allows explaining the correlations among these factors and their implications in the product yet to be explored (Robayo and Maldonado, 2012; Eisfeld et al., 2018). Therefore, according to the question asked, it is important assessing whether, or not, an event is likely to happen (Garson, 2014).

The aim of the present study was to analyze the association between dendrometric variables and competition in Hymenaea stigonocarpa fruit yield, based on the hypothesis that trees with larger diameter and higher height, under less competition conditions, are more likely to present higher fruit yield.

2. Materials and Methods

2.1. Study site and data collection

In total, 60 Jatobá-do-cerrado (Hymenaea stigonocarpa) individuals were randomly selected to the present study in Curvelo, Inimutaba and Sete Lagoas cities, Minas Gerais State, Brazil. The collected individuals were in thin Cerrado areas and in Cerrado stricto sensu fragments. The region’s phytophysiognomy features a typical cerrado and thin cerrado area showing low, leaning, and tortuous trees with irregular and twisted branches (IBGE, 2012). According to the Köppen-Geiger climate classification developed for Minas Gerais State, there is prevalence of the Aw climate in the Central region; it means tropical climate with dry winter and rainy summer, with higher rainfall levels from November to January (Alvares et al., 2013).

In total, 30 fruit-producing Jatobá-do-Cerrado individuals and 30 non-producers were randomly identified, georeferenced and plated. The trees were measured and monitored from April to August 2018, when the species' fruiting period is observed in this region.

The following dendrometric variables were recorded for each of these individuals: stem basis diameter (SBD), t 0.1 m, expressed in cm; diameter at breast height (DBH, measured at 1.30 m, expressed in cm); total height (Ht, expressed in m); presence of fruits (Pi = 1) and absence of fruits (Pi = 0).

The qualitative variables of each individual were assessed based on the classification by Souza and Soares (2013):

1. Stem quality (Qf): 1 = defect-free stem; 2 = stem with slight defects (cracks, fungi, insects); and 3 = stem with major defects;

2. Crown quality (Qc): 1 = healthy, symmetrical and undamaged crown; 2 = crown with medium asymmetry, 3 = crown with high asymmetry;

3. Crown lighting (IL): 1 = crown without lighting; 2 = crown with partial lighting and 3 = crown in full sun.

Competition between individuals was assessed through the semi-distance-independent method (Castro et al., 2014) to check the influence of individuals within a given competition radius. In order to do so, the competing trees, with DBH larger than 5 cm within the maximum radius of 9 m, among all assessed Jatobá-do-cerrado individuals, were counted and their dimensions were measured: diameter at breast height (DBH, expressed in cm), total height (Ht, expressed in m) and distance from the object tree (in m).

2.2. Data analysis

The sampled H. stigonocarpa individuals were stratified based on DBH class and height to assess the association between dendrometric variables and fruit yield. Stratification was carried out based on the means and standard deviation recorded for DBH and Ht - three classes were defined for each variable.

Class I encompassed individuals smaller than the mean (Xm) minus one standard deviation unit, i.e., XI < Xm - 1s. Class II encompassed trees with values ​​ranging from the means, plus or minus one standard deviation, i.e., Xm − 1s ≤ XII < Xm + 1s. Class III comprised trees with dendrometric variable values higher than the mean value plus one standard deviation: XIII ≥ Xm +1s (Mariscal Flores, 1993). The total rate of measured individuals per stratum and the rate of individuals producing fruit were calculated.

The four semi-independent distance indices described in Table 1, within the 9, 6 and 3m radii, for each index, were used to assess the competition in each measured tree, according to Castro (2012).

Table 1
Semi-distance independent competition indices used to estimate the Hymenaea stigonocarpa fruit yield probability.

Index	Author (s)	Index interpretation	Index
		Castro (2014)
$\text{ISD}1=\frac{DB{H}_{\text{i}}^2}{\overline{d}{n}^2}$	Adapted from Glover and Hool (1979)	Higher index, less competition	(1)
$\text{ISD}2=\frac{H{t}_i}{{\overline{Ht}}_n}$	Adapted from Glover and Hool (1979)	Higher index, less competition	(2)
$\text{ISD}3=\frac{DB{H}_i^{2}H{t}_i}{\overline{d}{n}^2{\overline{Ht}}_n}$	Adapted from Glover and Hool (1979)	Higher index, less competition	(3)
$\text{ISD}4=\text{BALi}$	Stage (1973)	Lower index, less competition	(4)

• wherein: DBHi = stem diameter, with bark, of the object tree, measured at 1.30 m (cm); Hti = total stem height of the object tree (m); BALi = sum of the sectional areas of the stems of neighboring trees that are larger than the stem of the object tree; nj= number of competing stems limited to competition radii 9, 6 or 3 m; = mean of stem diameters of n trees close to the object tree (cm) that are limited to competition radii 9, 6 or 3 m; = mean stem height of n trees close to the object tree (m), that are limited to competition radii of 9, 6 or 3 m.

Pearson's correlation coefficient was used to select the best index and dendrometric variable to model H. stigonocarpa fruit yield after the competition indices were calculated.

The Logit probability model was adopted to estimate fruit yield probability. The qualitative binary response was taken into consideration in this model, which only presents two possibilities as answer, 0 (for absence of fruit yield) and 1 (for fruit yield occurrence).

The following Equation 1 was initially considered to calculate the Logit model (Gujarati and Porter, 2011):

$P_i=E(Y_i=1|X_i)=f\left(\beta X\right)$ (1)

wherein, Pi is the individual’s probability to produce fruits, f is a cumulative distribution function whose X is the different explanatory variables and β is the parameters to be estimated.

This association presents the following structure in the Logit model (Equation 2):

$P_i=\frac{1}{1+e^{-z_i}}=\frac{e^z}{1+e^z}$ (2)

wherein, Z = βX, and β is an unknown parameter and X is the vector of variables to be used - as many as necessary, and viable.

If Pi is the probability of fruit occurrence in a Jatobá-do-cerrado individual, its non-occurrence is explained by (1 – Pi), thus (Equation 3):

$1-P_i=\frac{1}{1+e^{Zi}}$ (3)

Accordingly, one can write:

$\frac{P\text{i}}{1-Pi}=\frac{1+e^{Z_i}}{1+e^{-Z_i}}=e^{Z_i}$ (4)

Equation 4 presents the odds ratio of a producing Jatobá-do-Cerrado individual (yield probability divided by non-production probability). By returning the natural logarithm of Equation 4, one finds (Equation 5):

$L_i=ln\left(\frac{P\text{i}}{1-Pi}\right)=Zi=\beta X$ (5)

The maximum likelihood (MV) method was used to estimate the parameters. It was possible finding the variation in Logit, as independent variables’ values changed, by estimating the parameters following the equation’s independent variables (dendrometric variables and competition index). Negative parameters point out inverse correlation, i.e., phenomenon probability decreases as the X value (independent variables) increases. Software R and Microsoft Excel® were used for statistical analyses purposes.

The measured individuals were analyzed for fruit-yield presence or absence depending on quality class based on qualitative variables (stem quality, crown quality and crown lighting) in order to observe their influence on the yield of trees belonging to this species.

3. Results

3.1. Yield distribution based on diameter and height stratification

Diameter and height class stratification showed that smaller H. stigonocarpa individuals accounted for higher tree fruit yield rates (Table 2). In total, 92% of individuals in stratum I were producing fruits according to variable DBH, whereas 46% and 11% fruit yield was observed for strata II and III, respectively. Total height stratification followed the same DBH trend, and fruit yield occurred in 92%, 44% and 18% of individuals that were sampled in strata I, II and III, respectively.

Table 2
Distribution of Hymenaea stigonocarpa individuals based on stratification by diameter at breast height (DBH), total height (Ht) and rate of individuals producing fruits in each stratum.

Variable	Stratum
	Small	Medium	Large
DBH	< 9.13	9.13 ≤ DBH ≤ 27.84	>27.84
% of individuals	20	65	15
% of producing individuals in the stratum	92	46	11
Ht	< 4.41	4.41 ≤ Ht ≤ 9.53	>9.53
% of individuals	21.7	60.0	18.3
% of individuals producing in the stratum	92	44	18

3.2. Adjustment model

Pearson’s correlation coefficients recorded for both the dendrometric variables and the semi-distance-dependent competition indices are shown in Table 3. Variables DBH, Ht and DAS presented significant negative correlation to H. stigonocarpa fruit yield. The ISD2-3 competition index, which takes into account the 3m competition radius, was the only one showing significant correlation to variable yield.

Table 3
Pearson’s correlation among dendrometric variables, competition indices ‘semi-independent from distance’ and Hymenaea stigonocarpa fruit yield probability.

	DBH	Ht	DAS	Yield (Pi=0 or Pi=1)
DBH	1.00	-	-	-
Ht	0.72	1.00	-	-
DAS	0.91	0.71	1.00	-
Yield (Pi=0 or Pi=1)	-0.47*	-0.59*	-0.47*	1.00
ISD1-9	0.28	0.41	0.26	-0.20
ISD2-9	0.08	0.39	0.10	-0.16
ISD3-9	-0.02	0.24	-0.05	-0.22
ISD1-6	0.38	0.32	0.34	-0.25
ISD2-6	-0.03	0.23	-0.05	-0.24
ISD3-6	0.42	0.36	0.40	-0.26
ISD1-3	0.19	0.09	0.09	-0.29
ISD2-3	0.08	0.15	0.02	-0.30*
ISD3-3	0.29	0.11	0.18	-0.25
BAL-9	-0.14	0.08	-0.13	-0.14
BAL-6	-0.09	0.20	-0.11	-0.13
BAL-3	-0.03	0.13	-0.03	-0.07

• wherein: DBH = diameter at breast hight (1.30 m); Ht = total height; DAS = diameter at 0.10 m; ISDn-9= competition index ‘semi-independent from distance’ at 9m radius; ISDn-6 competition index semi-independent from distance at 6m radius; ISDn-3 competition index semi-independent from distance at 3m radius; BAL-i competition index semi-independent from distance at radius of i = 3, 6 or 9m.
• ^*
  Significant coefficient at p-value = 0.05.

Therefore, DBH and the semi-independent competition index of the ISD2-3 distance were chosen as independent variables to make adjustments in the Logit model because they are closely correlated to fruit yield probability. Although variables DAS and Ht showed significant correlation, they were not used in the model due to the close association between Ht and the competition index, which uses variable height in its calculation; and because DAS and DBH are closely correlated to each other, and present equal yield probability value.

The following model was selected based on the correlations:

$ln\left(\frac{Pi}{1-Pi}\right)={\beta }_0+{\beta }_{1}DBH+{\beta }_2\text{ISD}2+u_i$ (6)

wherein, ln is the natural logarithm of the probability to produce (Pi) divided by the probability of not to produce $\left(1-Pi\right)$, ${\beta }_0,{\beta }_{1}e{\beta }_2$ are the model parameters to be estimated; DBH is the diameter at breast height at 1.30 m, and ISD2 is the competition index calculated at 3m radius, and $u_i$ is the random error.

It was possible getting to Equation 6, described below, after making adjustments in the Logit model to estimate H. stigonocarpa fruit yield probability. According to Table 4, parameters associated with DBH and competition index variables were statistically significant (Equation 7).

Table 4
Results of the adjustment of the Logit function to estimate the probability of fruit production of H. stigonocarpa.

Variables	Coefficients	Standard Error	Z-test	Pr>|z|
Intercept	3.985	1.171	3.404	0.001 ***
DBH	-0.174	0.052	-3.328	0.001 ***
ISD2	-1.787	0.669	2.671	0.008 **

• ^***
  Significant coefficient with p-value = 0.001;
• ^**
  Significant coefficient with p-value = 0.01.

$ln\left(\frac{Pi}{1-Pi}\right)=3.985-0.174\text{*}DBH-1.787\text{*ISD}2$ (7)

The adjustment in the equation allowed inferring that the coefficient of variable DBH is more significant than that of ISD2, but both were negative. Thus, Li (Z) assumes higher values for most individuals that have high degree of competition and lower ISD2 values; moreover, individuals’ fruit yield probability is closer to 1, as depicted in Figure 1A.

Figure 1
(A) Probability of fruit presence (Pi = 1) described by the logistic distribution function; (B) Probability of fruit presence (Pi = 1) for trees under competition and without competition.

The initial hypothesis was partially rejected. While lower competition was associated with higher fruit production probability, increasing DBH and height were negatively related to fruit production. Figure 1B allowed analyzing that individuals that did not have competition, presented decreased yield probability and tended to zero, because DBH increased. H. stigonocarpa trees influenced by competition presented reduced yield probability in comparison to those that did not face competition. Trees with smaller diameter recorded higher yield probability in both groups (without and with competition).

3.3. Correlation between yield and qualitative variables

Figure 2 shows H. stigonocarpa individuals’ rates according to the assessed qualitative variables. Overall, it was observed that most of the assessed individuals presented features that point out good stem quality. Approximately 65% of individuals had defect-free stem, and they were grouped in class 1 due to this variable. Approximately 55% of these individuals had healthy, symmetrical and undamaged crown and most of them (65%) were under partial crown shade.

Figure 2
Rate of trees by class of (A) stem quality; (B) crown quality and (C) crown lighting level based on Jatobá-do-cerrado fruit yield. Pi = 0, trees that did not produce fruit and Pi = 1 trees that produced fruit.

The analysis of stem quality (Figure 2A) showed that both fruit-producing and non-producing individuals occurred across all stem quality classes. A similar pattern was observed for crown quality, with productive and non-productive individuals distributed among crown symmetry classes (Figure 2B). Regarding crown illumination, differences in fruit production were descriptively associated with lighting conditions, as productive individuals were observed across all illumination classes, whereas non-productive individuals occurred only under partial crown illumination (Class 2) or full sunlight (Class 3) (Figure 2C). Fruit production varied among crown lighting classes, suggesting a potential association that deserves further investigation using inferential approaches.

4. Discussion

According to the present study, there are variations in H. stigonocarpa fruit yield depending on variables ‘diameter at breast height (DBH)’ and ‘total height (Ht)’. Individuals’ growth dynamics influences forest species’ seeds and fruit yield, which is directly related to environmental factors (Potts et al., 2020), presence of pollinators (Fagundes et al., 2007), physiological factors (Souza et al., 2013) and tree dimensions (Snook et al., 2005; Neves et al., 2015). The structural heterogeneity of cerrado vegetation plays a key role in shaping growth strategies and reproductive patterns of tree species, and larger size does not necessarily imply higher reproductive output (Felfili et al., 2017).

Based on the herein carried out sampling, more than 80% of the productive H. stigonocarpa individuals belonged to the lower DBH and Ht classes, with up to 27.84 cm DBH and 9.53m in height. Costa (2012) assessed Jatobá-do-cerrado (H. stigonocarpa) and found that the sampled trees at different sizes had 88% of productive individuals in the medium DBH classes, ranging from 15 to 35 cm, and Ht ranging from 7.5 to 12.5 m. He also highlights that the most productive trees were not necessarily those presenting the largest diameter. Tonini et al. (2020) assessed Bertholetia excelsa seed yield and found that DBH explained 34% variation in seed weight.

The allocation and distribution of growth resources in plants are essential for fruit production (Staggemeier et al., 2017). The observed patterns may reflect differences in resource allocation strategies among individuals, as reported for woody species in seasonally dry environments. Larger trees, characterized by greater height and DBH, generally exhibit higher maintenance demands, which may limit the resources available for reproductive investment under conditions of water and nutrient restriction, such as those typical of the Cerrado. In this context, the higher fruit production probability observed in smaller individuals may be associated with lower maintenance costs and reduced competitive demands, rather than indicating a direct causal shift in allocation strategies.

Environmental stressors and competitive interactions may reduce resource availability and negatively affect reproductive performance, particularly in environments subject to climatic variability such as the Cerrado (Hofmann et al., 2021).

Furthermore, medium or large non-productive individuals need a production-rest period; they would not produce in one year, but they would return to production in the following year, as observed among Hymenaea courbaril individuals (Shanley and Medina, 2005).

Adjustments in the model and the interpretation of data in Table 4 showed that Logit values ​​will be inversely proportional, because the coefficients multiplying the independent variables are negative. Based on the first analysis, increase in DBH and in competition index values makes Logit tend to decrease, and it makes yield probability decrease. Accordingly, DBH importance in explaining H. stigonocarpa yield is outstanding, just as the competition index.

Thus, individuals without competition within a radius smaller than 3m had higher probability of fruiting, likely because they competed less for nutritional resources and water, a fact that influences this species’ flowering and fruiting (Silva, 2018). Moreover, these individuals attract more pollinators because they live in a more preserved and inviting environment, given the larger number of flowers and fruits (Fuchs et al., 2003; Silingardi, 2007; Nazareno and Reis, 2012). Jansen et al. (2021) assessed the yield aspects of Bertholletia excels and also found competition influence on fruit yield.

It is possible investing in management practices to increase trees’ yield and to enhance their features by developing a probabilistic model to estimate the probability of producing (Pi = 1) or not producing (Pi = 0) fruits.

Higher fruit yield in trees accounting for the best stem quality (Bole Quality 1) can be explained by their lower stress, given that these trees’ stems were free from any defect in comparison to the stem classes linked to light availability and to large defects (cracks, fungi, insects). According to DaMatta and Ramalho (2006), plant growth, development, biomass accumulation and yield performance is directly influenced by the stress these plants are exposed to, since it activates specific tolerance mechanisms that involve a complex network of biochemical and molecular processes.

On the other hand, the presence of productive individuals in places with crown without lighting reflects this species’ adaptability, since some individuals produce fruits even in trees under partial and full lighting. However, yield in trees without lighting was only observed in 10% of individuals, and this finding points towards higher fruit yield in trees under lighting, likely due to their greater ability to capture light (Snook et al., 2005).

5. Conclusions

The smallest trees are the ones most likely to produce in comparison to DBH. Competition analyzed through the semi-distance-dependent index was significant and had straight influence on Jatobá-do-cerrado fruit yield probability.

Acknowledgements

We would like to thank the National Council for Scientific and Technological Development (CNPq) and the Minas Gerais State Research Support Foundation (Fapemig) for the corresponding author's research grant.

Data Availability statement

The database can be obtained by the link: https://onedrive.live.com/?cid=0d5e200b9eb7db71&id=0D5E200B9EB7DB71%21s8a22d24ad29b4eec84627b4d47513327&resid=0D5E200B9EB7DB71%21s8a22d24ad29b4eec84627b4d47513327&ithint=file%2Ctxt&e=9qEbBC&migratedtospo=true&redeem=aHR0cHM6Ly8xZHJ2Lm1zL3QvYy8wZDVlMjAwYjllYjdkYjcxL0VVclNJb3FiMHV4T2hHSjdUVWRSTXljQkxDS1V6OF9xS09fYXlOREFYdXcyN1E_ZT05cUViQkM&v=validatepermission.

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Edited by

• Editor:
  Takako Matsumura Tundisi

Publication Dates

• Publication in this collection
  20 July 2026
• Date of issue
  2026

History

• Received
  19 Sept 2025
• Accepted
  26 Feb 2026