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Genetic Diversity of Ishpingo Exploited Trees (Ocotea quixos (Lam.) Kosterm, Lauraceae)

Authors:
Citation: Draper, D.; Riofrío, L.;
Naranjo, C.; Marques, I. Genetic
Diversity of Ishpingo Exploited Trees
(Ocotea quixos (Lam.) Kosterm,
Lauraceae). Environ. Earth Sci. Proc.
2024,31, 6. https://doi.org/
10.3390/eesp2024031006
Academic Editor: Giorgos Mallinis
Published: 16 December 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Proceeding Paper
Genetic Diversity of Ishpingo Exploited Trees (Ocotea quixos
(Lam.) Kosterm, Lauraceae)
David Draper 1, * , Lorena Riofrío2, Carlos Naranjo 2and Isabel Marques 3, *
1Center for Ecology, Evolution and Environmental Changes & CHANGE—Global Change and Sustainability
Institute, University of Lisbon, 1749-016 Lisbon, Portugal
2Facultad de Ciencias Exactas y Naturales, Universidad Tecnica Particular de Loja (UTPL),
1101608 Loja, Ecuador; mlriofrio@utpl.edu.ec (L.R.); cjnaranjo@utpl.edu.ec (C.N.)
3Forest Research Centre, Associate Laboratory TERRA, School of Agriculture, University of Lisbon,
1349-017 Lisbon, Portugal
*Correspondence: ddmunt@gmail.com (D.D.); isabelmarques@isa.ulisboa.pt (I.M.)
Presented at the 4th International Electronic Conference on Forests Session Forest Biodiversity, Ecosystem
Services, and Earth Observations 19 September 2024.
Abstract: Ocotea quixos (Lam.) Kosterm, known as Ishpingo, is a tree endemic to the Amazonian
rainforests of Colombia, Ecuador, and Peru. In Ecuador, the Ishpingo tree faces significant threats
due to overexploitation for its valuable spices and essential oils, as well as extensive deforestation
and land-use changes. Understanding and preserving the genetic diversity of Ishpingo is vital for
ensuring the species’ survival and continued contribution to the ecological and cultural richness of
the Amazonian rainforest. Nevertheless, we currently lack comprehensive genetic diversity data.
Within this scenario, we developed nuclear microsatellites to analyze the genetic diversity in ten
known Ecuadorian populations of Ishpingo. Results show low levels of genetic diversity, especially
when compared with other Ocotea trees. The mean number of alleles ranged from 2.20 to 4.47, the
observed heterozygosity from 0.33 to 0.62, while the expected heterozygosity (He) was notably higher,
ranging from 0.61 to 0.79. The inbreeding coefficient (Fis) was consistently positive, with some values
close to zero. Despite these results, some populations such as the northern populations of Ishpingo
still harbor moderate levels of genetic diversity, key for the preservation of this species.
Keywords: Ecuador rainforest; Lauraceae; genetic diversity; deforestation; overexploitation
1. Introduction
Habitat changes and the illegal exploitation of natural resources are among the leading
causes of species extinction. Though these factors operate at various scales, both impact
genetic diversity and the ability of species to adapt to changing environmental condi-
tions [
1
]. Populations with limited genetic diversity are more prone to extinction, often due
to reduced gene flow, the loss of alleles through genetic drift and erosion, or the harmful
effects of inbreeding [2].
The impacts of habitat changes are particularly profound in the tropics, a region known
for its exceptionally high biodiversity, yet increasingly vulnerable to land-use changes and
deforestation [
3
]. The fragmentation of tropical forests into isolated patches, largely due to
agricultural expansion and land conversion, along with habitat degradation from activities
such as selective logging, exerts immense pressure on ecosystems, raising uncertainties
about how species will adapt [
4
,
5
]. These challenges are particularly complex for tree
species, as their long lifespans and ability to disperse pollen and seeds over vast distances
may help mitigate the loss of genetic diversity. This makes tree species vital for maintaining
gene flow between fragmented forest areas, serving as important conduits for biodiversity
resilience [
6
]. However, the ability of isolated remnant trees to support the long-term
survival of populations is a complex issue. In many cases, seeds from trees in fragmented
Environ. Earth Sci. Proc. 2024,31, 6. https://doi.org/10.3390/eesp2024031006 https://www.mdpi.com/journal/eesp
Environ. Earth Sci. Proc. 2024,31, 6 2 of 10
landscapes exhibit reduced vigor and signs of inbreeding depression, which can undermine
the genetic health and resilience of future generations [
7
,
8
]. This compromised seed quality
threatens the long-term viability of populations, raising concerns about their ability to
adapt and persist in increasingly fragmented ecosystems.
Species with economic value face additional risks, not only from direct exploitation
that hampers population regeneration but also from the removal of individuals from wild
populations [
9
11
]. Theoretical studies have predicted a loss of alleles and reduced het-
erozygosity in overexploited populations [
12
,
13
]. This can lead to significant demographic
declines and genetic erosion over successive generations [
14
]. However, not all exploited
populations show a consistent decline in genetic diversity, since some reduced populations
may still retain sufficient genetic variability to avoid species collapse [15,16].
Ocotea quixos (Lam.) Kosterm = Mespilodaphne quixos (Lam.) Rohwer (Ishpingo), com-
monly known as Ecuadorian cinnamon or Andean cinnamon, is a plant species belonging
to the Lauraceae family. It is an endemic evergreen tree from the Amazonian rainforest of
Colombia, Ecuador, and Peru [
17
]. Due to its aromatic bark and distinctive flavor, Ishpingo
has gained recognition as a valuable spice and a cultural emblem in the regions where it
grows [
17
]. The main spice is gathered from the dry cupules, although the bark and leaves
are also harvested and processed to produce Ecuadorian cinnamon, which is known for its
sweet and warm flavor profile [
18
20
]. While similar in some respects to the more common
cinnamon, Ecuadorian cinnamon has its own unique characteristics, often described as
more delicate and nuanced [
17
]. Beyond its applications, Ishpingo holds a very high cul-
tural significance, since local communities often incorporate it in rituals, ceremonies, or in
traditional medicine practices [
21
]. The plant has been known since Inca times, valued for
its aromatic and medicinal properties. After Columbus’ voyages, several expeditions were
performed in search of spice-rich regions, including the nearly mythical land known as
“Tierra de la Canela”. This legendary land was believed to be abundant in valuable spices,
and Ishpingo was one of the key plants associated with these explorations [
22
]. The pursuit
of this fabled region drove expeditions deep into the Amazon, further fueling the legends
surrounding the area’s rich natural resources [
22
]. Nowadays, Ishpingo is one of the key
ingredients used in preparing “colada morada,” a traditional Ecuadorian drink consumed
during the celebration of “Santos Difuntos” (Day of the Dead) [22].
Despite its cultural and economic importance, Ishpingo faces several conservation
challenges due to habitat loss and unsustainable harvesting practices. Ishpingo is a slow-
growing species [
17
]. The cupules are only harvested every two years from plants that are
15 to 20 years old [
17
]. This limited production makes the spice highly expensive [
17
]. In
Ecuador, the intensive exploitation of this tree, together with intensive land-use changes
and high deforestation rates in the national territory [
23
], has led to a severe reduction in
the number of wild populations of Ishpingo [
24
]. In 2017, the situation was so severe that
the government banned its commercialization for 6 months [
24
]. The expansion of roads,
land-use changes, deforestation, and the use of clonal cultivars have been identified as the
factors affecting populations [
24
]. The low number of populations and trees in the country
suggests that the genetic variability of this species might be declining to values constraining
population variability and resilience to changes. In this context, a genetic study based on
nucleotide sequences already reported a very low variability among Ishpingo trees [24].
Given the significance of Ishpingo to local Ecuadorian communities, this study aimed
to assess if the exploitation of its populations are linked to negative impacts on the species’
genetic variability. To achieve this, we developed nuclear microsatellites to analyze the
genetic diversity, population structure, and levels of inbreeding in known Ecuadorian
populations of Ishpingo, with the goal of informing both in situ and ex situ conservation
strategies. Microsatellites are widely used markers for assessing genetic diversity [
25
,
26
].
They are short, repetitive sequences of DNA found throughout the genome, characterized
by being co-dominant markers, generally selectively neutral and highly variable (polymor-
phic) even within populations [
27
]. Microsatellites are often the best choice for studies
on genetic diversity in exploited species due to their high polymorphism, codominance,
Environ. Earth Sci. Proc. 2024,31, 6 3 of 10
reproducibility, and versatility [
28
30
]. These qualities provide unmatched resolution
for understanding genetic structure and informing conservation strategies, especially in
non-model or threatened species.
In this study, our specific objectives were to determine (1) whether overexploitation
has led to a depletion of genetic diversity that could have adverse effects; (2) if the spatial
genetic structure is influenced by the species’ geographical distribution; and (3) whether
there is evidence of inbreeding or reduced gene flow between populations.
2. Material and Methods
2.1. Population Sampling
In this study, 10 populations were sampled in Ecuador, targeting a total of 84 adult
Ishpingo trees (Figure 1). Following the criteria in [
31
], trees with a diameter at breast
height (DBH) greater than 5 cm were considered adults; we have not detected any trees
with a DBH lower than this. In each population, leaf samples were collected from 6 to
10 adult trees, transported to the laboratory, and stored at 80 C until DNA extraction.
Environ. Sci. Proc. 2024, 31, 6 3 of 10
by being co-dominant markers, generally selectively neutral and highly variable (poly-
morphic) even within populations [27]. Microsatellites are often the best choice for studies
on genetic diversity in exploited species due to their high polymorphism, codominance,
reproducibility, and versatility [2830]. These qualities provide unmatched resolution for
understanding genetic structure and informing conservation strategies, especially in non-
model or threatened species.
In this study, our specic objectives were to determine (1) whether overexploitation
has led to a depletion of genetic diversity that could have adverse eects; (2) if the spatial
genetic structure is inuenced by the species’ geographical distribution; and (3) whether
there is evidence of inbreeding or reduced gene ow between populations.
2. Material and Methods
2.1. Population Sampling
In this study, 10 populations were sampled in Ecuador, targeting a total of 84 adult
Ishpingo trees (Figure 1). Following the criteria in [31], trees with a diameter at breast
height (DBH) greater than 5 cm were considered adults; we have not detected any trees
with a DBH lower than this. In each population, leaf samples were collected from 6 to 10
adult trees, transported to the laboratory, and stored at 80 °C until DNA extraction.
Figure 1. Details of the Ishpingo (Ocotea quixos (Lam.) Kosterm) populations sampled in Ecuador.
2.2. DNA Extraction and nSSR Development
Total genomic DNA of Ishpingo samples was extracted using the DNeasy Plant Min-
ikit (Qiagen, Hilden, Germany) following the manufacturer’s instructions and stored at
80 °C. New nuclear SSRs were developed using two small, inserted libraries digested
with HaeII and RsaI and enriched with (CT)n sequences. Following [31], DNA fragments
of each species were ligated into a p-GEM-T Easy Vector, as these were the plasmids trans-
formed using Escherichia coli cells (Promega, Madison, WI, USA). In total, we obtained 26
clones in Ishpingo (16 from HaeII and 10 from RsaI) from which 22 showed a positive hy-
bridization signal. Afterward, positive clones were sequenced with M13 primers using the
following conditions: 3 min at 94 °C, followed by 48 cycles at 94 °C for 1 min, annealing
Figure 1. Details of the Ishpingo (Ocotea quixos (Lam.) Kosterm) populations sampled in Ecuador.
2.2. DNA Extraction and nSSR Development
Total genomic DNA of Ishpingo samples was extracted using the DNeasy Plant
Minikit (Qiagen, Hilden, Germany) following the manufacturer’s instructions and stored at
80
C. New nuclear SSRs were developed using two small, inserted libraries digested with
HaeII and RsaI and enriched with (CT)n sequences. Following [
31
], DNA fragments of each
species were ligated into a p-GEM-T Easy Vector, as these were the plasmids transformed
using Escherichia coli cells (Promega, Madison, WI, USA). In total, we obtained 26 clones in
Ishpingo (16 from HaeII and 10 from RsaI) from which 22 showed a positive hybridization
signal. Afterward, positive clones were sequenced with M13 primers using the following
conditions: 3 min at 94
C, followed by 48 cycles at 94
C for 1 min, annealing at 53
C for
1 min, 2 min at 72
C, and 5 min at 72
C. DNA sequencing was performed in both directions
in a 3730 DNA Analyzer (Applied Biosystems, Foster, CA, USA). At the end, 20 clones of
Ishpingo had readable sequences.
Environ. Earth Sci. Proc. 2024,31, 6 4 of 10
Primer 3 [
32
] was used to develop the new primers, which were tested using two
individuals per population. Amplification of SSRs was performed in 15
µ
L reactions
containing 1.25 U MyTaq DNA polymerase and 1
×
MyTaq Reaction Buffer (Meridian
Bioscience, London, UK), 0.4
µ
M Primer F-FAM and R, and 100 ng of genomic DNA, and
amplified following [
31
]. PCR products were genotyped on an Applied Biosystems 3130XL
Genetic Analyzer with 2
µ
L of amplified DNA, 12
µ
L of Hi-Di formamide, and 0.4
µ
L of
GeneScan-600 (LIZ) size standard (Applied Biosystems, Waltham, MA, USA). Microsatellite
fragment analysis was conducted on an AB 3500 Genetic Analyzer (Life Technologies Inc.,
New York, NY, USA). Allele sizes were determined using GeneMarker 3.1. (Softgenetics,
State College, PA, USA).
Eight new nSSRs (Table 1) were selected based on their successful amplification,
polymorphism, and the absence of null alleles verified using MICRO-CHECKER v.2.2.3 [
33
].
These markers were employed to genotype the 84 samples included in this study. For
each microsatellite locus, we calculated the mean number of alleles (A), the mean expected
heterozygosity (He), and the mean observed heterozygosity (Ho) using GenAlEx v6.51 [
34
].
We also tested deviation from the Hardy–Weinberg equilibrium (HWE) using the same
program. In all analyses, significant values were corrected for multiple comparisons by
Bonferroni correction [35].
Table 1. Characteristics of the eight microsatellite markers used to amplify 84 samples of Ocotea
loxensis and O. infrafoveolata. For each locus, the accession number, the mean number of alleles (A),
mean expected heterozygosity (He), and the mean observed heterozygosity (Ho) are shown.
Locus Primers (5–3) Ta (C) Repeat
Motif
Size Range
(bp)
Accession
Number A Ho He
Oqui1 TTCCTTCAAAAGTATGCCCCT 58 (TA)5142–147 PQ724125 3 0.21 0.49
CCCGTAGTTCAGGTAGTCCC
Oqui2 GGTGTGAATGGACTCGGGAT 59 (CCT)3136–142 PQ724126 4 0.23 0.44
CCCGGAGTCAGGACATCAAT
Oqui3 TCATGGATTAGGACGAGATAGCT 58 (CT)9119–131 PQ724127 2 0.16 0.37
TCTCTCTCCCACTCTCCAGT
Oqui4 CATATGCCGGAGTTGAGGGT 59 (TA)13 128–135 PQ724128 4 0.45 0.55
CAGTCTCCTAACGATGGGGT
Oqui5 GAGTTATGAGTAGGATCGGGGA 58 (CCAA)4111–118 PQ724129 3 0.18 0.48
TCGGGTAAACTCTCAAGGGG
Oqui6 AAATGGAAAATCACTGGGTAGGG 59 (ATA)4103–119 PQ724130 4 0.22 0.44
TCTCTAACTCTCTAAACTCCGCC
Oqui7 CCTTAATGTGGAGTTTACCGAGA 58 (GA)5113–123 PQ724131 5 0.26 0.46
TGGTTAACTCTAAACGTGTGGG
Oqui8 TTATCCTATGTGCGCGCTTG 58 (GCT)5115–119 PQ724132 3 0.17 0.37
GCCAACACAAACCACAACTC
2.3. Genetic Diversity and Differentiation
Genetic diversity in Ishpingo populations was assessed by calculating the total num-
ber of alleles (Ta), mean number of alleles per locus (Na), Shannon’s information index
(I), mean expected heterozygosity (He), mean observed heterozygosity (Ho), inbreeding
coefficient (Fis), and the percentage of polymorphic loci (PPL), using GenAlEx 6.51 [
34
].
We analyzed significant differences between populations and species through an ANOVA
followed by a post hoc Tukey’s test (p< 0.05). Genetic differentiation (Fst) between popula-
tions and an analysis of molecular variance (AMOVA) was calculated using ARLEQUIN
(version 3.5) [
36
]. The significance of the AMOVA components was determined through
1000 permutations.
2.4. Genetic Structure of Populations
To visualize the degree of the genetic structure of populations, a principal coordinate
analysis (PCoA) based on Nei’s genetic distance was performed using GenAlEx 6.51 [
34
].
Environ. Earth Sci. Proc. 2024,31, 6 5 of 10
To understand the genetic composition of populations, STRUCTURE v.2.3.4 [
37
] was run
from K = 1 to K = 12 assuming ancestral admixture and correlated allele frequencies. Run
lengths of 300,000 steps were used for each K after a burn-in of 50,000, and 10 repetitions
per K. The optimum K was determined using Structure Selector [
38
], which identifies the
optimal K based on both the posterior probability of the data for a given K and the K.
3. Results
3.1. Genetic Diversity of Loci
For each locus, the number of alleles ranged from 2 at locus Oqui2 and 5 at locus
Oqui7 (Table 1). Heterozygosity values also varied between loci. Observed heterozygosity
ranged from 0.16 at Oqui3 to 0.45 at Oqui4, whereas expected heterozygosity varied
between 0.37 at Oqui3 and 0.55 at O qui4. No null alleles were detected. However,
significant deviations from the Hardy–Weinberg equilibrium (HWE) were detected in
all loci.
3.2. Genetic Diversity in Ishpingo Populations
The overall genetic diversity exhibited low average values, although results varied
among populations (Table 2). Genetic diversity values were usually significantly higher
in the Northern populations of Ishpingo, GUA, EYA, and LIM, followed by the Central
populations MAC, PYO and PNA, with the Southern populations PLA, CVN and MAC
exhibiting the lowest values (Table 2).
Table 2. Genetic variation in Ishpingo populations. N: number of sampled plants; Na: number of
different alleles; I: Shannon’s information index, Ho: observed heterozygosity; He: expected het-
erozygosity; Fis: inbreeding coefficient among individuals within populations. Different superscript
letters indicate significant differences between populations based on ANOVA followed by the post
hoc Tukey’s test (p< 0.05).
Populations N Na I Ho He Fis
PLA 6 2.21 ±0.11 a1.43 ±0.15 a0.39 ±0.04 a0.72 ±0.09 a0.22 ±0.10 a
CVN 8 2.20 ±0.12 a1.45 ±0.14 a0.37 ±0.07 a0.70 ±0.10 a0.24 ±0.09 a
CAN 6 2.24 ±0.10 a1.41 ±0.10 a0.33 ±0.06 a0.61 ±0.08 a0.21 ±0.08 a
MAC
10
3.21
±
0.26
b
1.19
±
0.11
b
0.41
±
0.05
b
0.73
±
0.11
b
0.14
±
0.06
b
PYO
10
3.21
±
0.14
b
1.21
±
0.08
b
0.41
±
0.03
b
0.61
±
0.14
b
0.08
±
0.07
b
PNA 8
3.21
±
0.21
b
1.17
±
0.07
b
0.46
±
0.05
b
0.63
±
0.11
b
0.09
±
0.05
b
MBJ
10
4.21 ±0.12 c
1.14
±
0.08
b
0.67
±
0.04
b0.79 ±0.08 c0.11 ±0.08 c
GUA 8 4.47 ±0.29 c
1.19
±
0.10
b0.56 ±0.09 c0.74 ±0.06 c0.02 ±0.02 c
EYA 8 4.21 ±0.33 c
1.13
±
0.07
b0.62 ±0.08 c0.77 ±0.11 c0.04 ±0.01 c
LIM
10
4.19 ±0.26 c
1.15
±
0.09
b0.61 ±0.07 c0.73 ±0.08 c0.05 ±0.01 c
average 3.34 1.25 0.48 0.70 0.12
The mean number of alleles (Na) ranged from 2.20 in CVN to 4.47 in GUA (Table 2).
Shannon’s information index (I) varied from 1.13 in EYA to 1.45 in CVN. Observed heterozy-
gosity (Ho) ranged from 0.33 in CAN to 0.67 in MBJ, while the expected heterozygosity
(He) was much higher, varying between 0.61 in CAN to 0.79 in MBJ (Table 2). Inbreeding
coefficient (Fis) values were always positive and ranged from values very close to zero such
as 0.02 in GUA to 0.24 in CVN (Table 2).
The analysis of molecular variance (AMOVA) found that 93.1% of the total variation
was found within populations, while the remaining was explained among populations.
3.3. Genetic Structure of Populations
The first two axes of the PCoA accounted for 35.4% of the total variance, with
24.1% explained by the first axis and 11.3% by the second (Figure 2). The PCoA revealed
distinct groupings (Figure 2). The southern populations CAN, CVN, and PLA clustered
together in a single group on the left side of axis 1 and the upper portion of axis 2. All other
Environ. Earth Sci. Proc. 2024,31, 6 6 of 10
populations were separated primarily along axis 1. The central and northern populations,
PNA, PYO, and MAC, were clearly distinguished from MBJ and GUA, positioned on the
right and upper sections of the plot. Lastly, the northern and most eastern populations,
LIM and EYA, were located on the right and lower section of axis 1, in two separated
clusters (Figure 2).
Environ. Sci. Proc. 2024, 31, 6 6 of 10
The analysis of molecular variance (AMOVA) found that 93.1% of the total variation
was found within populations, while the remaining was explained among populations.
3.3. Genetic Structure of Populations
The rst two axes of the PCoA accounted for 35.4% of the total variance, with 24.1%
explained by the rst axis and 11.3% by the second (Figure 2). The PCoA revealed distinct
groupings (Figure 2). The southern populations CAN, CVN, and PLA clustered together
in a single group on the left side of axis 1 and the upper portion of axis 2. All other popu-
lations were separated primarily along axis 1. The central and northern populations, PNA,
PYO, and MAC, were clearly distinguished from MBJ and GUA, positioned on the right
and upper sections of the plot. Lastly, the northern and most eastern populations, LIM
and EYA, were located on the right and lower section of axis 1, in two separated clusters
(Figure 2).
Figure 2. Genetic relationships between Ishpingo (Ocotea quixos (Lam.) Kosterm) populations based
on a principal coordinate analysis (PCoA). Population labels refer to Figure 1.
The STRUCTURE analysis identied the most likely number of genetic clusters
across the entire dataset as K = 7 (Figure 3). One of these clusters predominantly charac-
terized the southern populations, specically PLA, CVN, and CAN. The central and
northern populations of MAC, PYO, and PNA were structured into two distinct genetic
clusters. While most individuals t into one of these clusters, some showed evidence of
admixture between the clusters, as well as with the southern group. A separate genetic
cluster was identied in the MBJ and GUA populations, with some individuals also dis-
playing signs of admixture. In contrast, the EYA population was dened by a single ge-
netic cluster, as was LIM, each forming their own distinct genetic group (Figure 3).
Figure 2. Genetic relationships between Ishpingo (Ocotea quixos (Lam.) Kosterm) populations based
on a principal coordinate analysis (PCoA). Population labels refer to Figure 1.
The STRUCTURE analysis identified the most likely number of genetic clusters across
the entire dataset as K = 7 (Figure 3). One of these clusters predominantly characterized
the southern populations, specifically PLA, CVN, and CAN. The central and northern
populations of MAC, PYO, and PNA were structured into two distinct genetic clusters.
While most individuals fit into one of these clusters, some showed evidence of admixture
between the clusters, as well as with the southern group. A separate genetic cluster was
identified in the MBJ and GUA populations, with some individuals also displaying signs of
admixture. In contrast, the EYA population was defined by a single genetic cluster, as was
LIM, each forming their own distinct genetic group (Figure 3).
Environ. Sci. Proc. 2024, 31, 6 6 of 10
The analysis of molecular variance (AMOVA) found that 93.1% of the total variation
was found within populations, while the remaining was explained among populations.
3.3. Genetic Structure of Populations
The rst two axes of the PCoA accounted for 35.4% of the total variance, with 24.1%
explained by the rst axis and 11.3% by the second (Figure 2). The PCoA revealed distinct
groupings (Figure 2). The southern populations CAN, CVN, and PLA clustered together
in a single group on the left side of axis 1 and the upper portion of axis 2. All other popu-
lations were separated primarily along axis 1. The central and northern populations, PNA,
PYO, and MAC, were clearly distinguished from MBJ and GUA, positioned on the right
and upper sections of the plot. Lastly, the northern and most eastern populations, LIM
and EYA, were located on the right and lower section of axis 1, in two separated clusters
(Figure 2).
Figure 2. Genetic relationships between Ishpingo (Ocotea quixos (Lam.) Kosterm) populations based
on a principal coordinate analysis (PCoA). Population labels refer to Figure 1.
The STRUCTURE analysis identied the most likely number of genetic clusters
across the entire dataset as K = 7 (Figure 3). One of these clusters predominantly charac-
terized the southern populations, specically PLA, CVN, and CAN. The central and
northern populations of MAC, PYO, and PNA were structured into two distinct genetic
clusters. While most individuals t into one of these clusters, some showed evidence of
admixture between the clusters, as well as with the southern group. A separate genetic
cluster was identied in the MBJ and GUA populations, with some individuals also dis-
playing signs of admixture. In contrast, the EYA population was dened by a single ge-
netic cluster, as was LIM, each forming their own distinct genetic group (Figure 3).
Figure 3. Genetic structure of Ishpingo (Ocotea quixos (Lam.) Kosterm) based on the best assignment
results recovered by STRUCTURE (K = 7). Each sample is represented by a thin vertical line divided
into K-colored segments that represent the individual’s estimated membership fractions in K clusters.
Population labels refer to Figure 1.
4. Discussion
Our study identified low levels of genetic diversity across several populations of
Ishpingo. For example, the averaged observed values of Ho (0.48) were lower than those
reported for related Ocotea species occurring in Ecuador, such as O. rotundata (Ho = 0.65) [
39
],
O. loxensis (Ho = 0.67) [
31
], and O. infrafoveolata (Ho = 0.69) [
31
]. These values are also lower
Environ. Earth Sci. Proc. 2024,31, 6 7 of 10
than the ones reported for heavily harvested Ocotea species, such as O. odorifera (Ho = 0.63),
O. porosa (Ho = 0.52), and O. catharinensis (Ho = 0.57), which have experienced significant
population declines in Brazil [40].
Here, genetic values decreased from North to South Ecuador, with northern pop-
ulations (MBJ, GUA, EYA, LIM) exhibiting higher genetic values than southern ones
(PLA, CVN, CAN). Our results also show strong inbreeding in some Ishpingo populations
(Table 2). This could explain the low level of admixture according to STRUCTURE and
PCoA analyses. This was especially evident in the southern populations PLA, CVN, and
CAN, and in the northern populations EYA and LIM (Figures 2and 3). The overexploita-
tion of these trees, together with habitat disturbances and the fragmentation processes of
the natural forest, which strongly occur in the south of Ecuador [
23
,
41
], could have also
contribute to genetic drift, gene flow, and inbreeding [6].
Although further research is needed, with additional genetic markers and a more
extensive sampling of O. quixos populations, our findings suggest that some populations
are at risk due to very low genetic diversity, potentially compromising their ability to
adapt to future environmental changes [
42
]. This is a concerning pattern seen in several
trees worldwide, which, due to overexploitation for timber, medicinal properties, and
other resources, have faced drastic population declines, loss of genetic diversity, and,
in some cases, extinction. For instance, the overexploitation of Brazilwood (Paubrasilia
echinata (Lam.) Gagnon, H. C. Lima & G. P. Lewis) has driven the species to the brink of
extinction in some regions of Brazil, with the remaining natural populations now under
strict protection to prevent further decline [
43
,
44
]. The widespread logging of Mahogany
(Swietenia macrophylla King) has also resulted in severe population declines, prompting
many countries to impose trade restrictions through mechanisms such as the Convention
on International Trade in Endangered Species (CITES) [
45
]. The overharvesting of Ebony
(Diospyros spp.) has drastically reduced populations, particularly in Madagascar and parts
of Africa. Many species within the Diospyros genus are now classified as endangered or
vulnerable, leading to strict regulations on their trade to protect remaining populations
from further decline [
46
]. In the case of Ishpingo (Ocotea quixos (Lam.) Kosterm), no such
restrictions exist.
The values reported here suggest the need for sustainable management and conser-
vation practices. Protection measures, as well as reforestation and controlled harvesting
programs, are essential to prevent the extinction of Ishpingo and to maintain biodiversity
in their native ecosystems. Owing to the different diversity scattered geographically in
the country, ex situ and in situ conservation actions should be implemented. The northern
populations, EYA and LIM, still possess a rich genetic reservoir that needs to be conserved.
In the other extreme, the southern populations PLA, CVN, and CAN might not have
enough genetic variation to overcome future habitat changes. While specific conservation
programs exclusively dedicated to Ishpingo may be limited, there are a few general efforts
and strategies that help protect this tree and its natural habitat. In local communities
relying on Ishpingo for its aromatic leaves and flowers, promoting sustainable harvesting
is a key conservation strategy. An agroforestry approach integrating these trees with other
native plants would also help to preserve biodiversity while providing a sustainable source
of income for local communities. This approach can balance the need for agricultural
development with the preservation of forest cover.
5. Conclusions
The genetic analysis of Ishpingo trees revealed low levels of genetic diversity, with
metrics such as the mean number of alleles (2.20 to 4.47) and observed heterozygosity
(0.33 to 0.67) significantly lower than those typically found in other Ocotea species. In
addition, the consistently positive Fis values suggest limited genetic mixing and potential
inbreeding, which could further reduce genetic variability over time.
By highlighting the observed patterns of genetic diversity, such as the higher values
in northern populations and the lower values in southern ones, we provided insights into
Environ. Earth Sci. Proc. 2024,31, 6 8 of 10
potential priority areas for conservation. For instance, northern populations of Ishpingo
like those in EYA and LIM exhibit moderate levels of genetic diversity, making them critical
to the species’ conservation. These populations may serve as genetic reservoirs for efforts
aimed at preserving and restoring the species. In contrast, populations with lower diversity,
such as PLA, CVN, and CAN, might require targeted interventions to mitigate genetic
bottlenecks or inbreeding effects. Additionally, the data on heterozygosity and inbreeding
coefficients can help in designing breeding programs or habitat restoration projects that
promote genetic health and connectivity among populations.
By linking genetic metrics to practical conservation strategies, this study underscores
the importance of integrating genetic data into management plans to ensure the long-
term survival of Ishpingo trees, maintaining its ecological role and cultural significance in
Amazonian rainforests. The lack of extensive genetic diversity data remains a significant
challenge. This study provides a foundation, but further research is needed to develop
effective conservation strategies and ensure the long-term survival of Ocotea quixos in its
native habitat.
Author Contributions: Conceptualization, I.M. and D.D.; methodology, D.D.; formal analysis, I.M.,
D.D., L.R. and C.N.; investigation, I.M., D.D., L.R. and C.N.; project administration: I.M.; funding
acquisition: I.M.; writing—original draft preparation, I.M. and D.D. All authors have read and agreed
to the published version of the manuscript.
Funding: This research received national funds through the FCT—Fundação para a Ciência e
a Tecnologia, I.P., Portugal through the research unit UIDB/00329/2020 (CE3C) and DOI iden-
tifier 10.54499/UIDB/00329/2020, by project reference UIDB/00239/2020 of the Forest Research
Centre and DOI identifier 10.54499/UIDB/00239/2020, and LA/P/0092/2020 of Associate Labora-
tory TERRA, DOI 10.54499/LA/P/0092/2020, and under the Scientific Employment Stimulus—
Individual Call (CEEC Individual)—2021.01107.CEECIND/CP1689/CT0001 and DOI identifier
10.54499/2021.01107.CEECIND/CP1689/CT0001 (IM).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The original contributions presented in the study are included in the
article, further inquiries can be directed to the corresponding authors.
Acknowledgments: We thank Yesenia Vega for her help during some field collections.
Conflicts of Interest: The authors declare no conflicts of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or
in the decision to publish the results.
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The concepts, methodologies and applications of some of the major molecular or DNA markers commonly used in plant science have been presented. The general principles of molecular marker techniques have been elucidated with detailed explanation of some prominent basic concepts associated with marker applications: marker polymorphism, dominant or co-dominant mode of inheritance, agronomic trait-marker linkage, genetic mutations and variation. The molecular marker methods that have been extensively reviewed are RFLP, RAPD, SCAR, AFLP, SSR, CpSSR, ISSR, RAMP, SAMPL, SRAP, SSCP, CAPS, SNP, DArT, EST, and STS. In addition, the practicality of the retrotransposon-based marker methods, IRAP, REMAP, RBIP, and IPBS, have been discussed. Moreover, some salient characteristics of DNA markers have been compared and the various marker systems classified as PCR- or non-PCR-based, dominantly or co-dominantly inherited, locus specific or non-specific as well as the level of polymorphisms and efficiency of marker reproducibility. Furthermore, the principles and methods of the following DNA markers have been highlighted: Penta-primer amplification refractory mutation system (PARMS), Conserved DNA-Derived Polymorphism (CDDP), P450-based analogue (PBA) markers, Tubulin-Based Polymorphism (TBP), Inter-SINE amplified polymorphism (ISAP), Sequence specific amplified polymorphism (S-SAP), Intron length polymorphisms (ILPs), Inter small RNA polymorphism (iSNAP), Direct amplification of length polymorphisms (DALP), Promoter anchored amplified polymorphism (PAAP), Target region amplification polymorphism (TRAP), Conserved region amplification polymorphism (CoRAP), Start Codon Targeted (SCoT) Polymorphism, and Directed Amplification of Minisatellite DNA (DAMD). Some molecular marker applications that have been recently employed to achieve various objectives in plant research have also been outlined. This review will serve as a useful reference resource for plant breeders and other scientists, as well as technicians and students who require basic know-how in the practicality of molecular or DNA marker technologies.