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viable insurance population
within European Zoo Network
Carlos Iglesias Pastrana1, Francisco Javier Navas González1*, María Josefa Ruiz Aguilera2,
José Antonio Dávila García3, Juan Vicente Delgado Bermejo1 & María Teresa Abelló4
The success and viability of an ex‑situ conservation program lie in the establishment and potential
maintenance of a demographically and genetically viable insurance population. Such population
reserve may support reintroduction and reinforcement activities of wild populations. White‑
naped mangabeys are endangered restricted‑range African primates which have experienced a
dramatic population decrease in their natural habitats over the last few decades. Since 2001, some
European zoos singularly monitor an ex‑situ population aiming to seek the recovery of the current
wild population. The aim of the present paper is to evaluate the genetic status and population
demographics of European zoo‑captive white‑naped mangabeys based on pedigree data. The captive
population is gradually growing and preserves specic reproductive and demographic parameters
linked to the species. The intensive management program that is implemented has brought about
the minimization of inbreeding and average relatedness levels, thus maintaining high levels of
genetic diversity despite the existence of fragmented populations. This nding suggests white‑
naped mangabey ex‑situ preservation actions may be a good example of multifaceted conservation
throughout studbook management which could be used as a model for other ex‑situ live‑animal
e IntergovernmentalScience-Policy PlatformonBiodiversityandEcosystemServices (IPBES) warned about
the high risk of extinction of over one million animal and plant species in 20191. To counteract this global
extinction crisis, ex-situ conservation programmes have been increasingly implemented, seeking the sustain-
able maintenance and breeding of threatened species under controlled conditions outside their natural habitat.
Strategically combined with reintroduction activities, ex-situ techniques have become eective measures to
preserve endangered species, when the ecient preservation of wild populations is compromised2–4. Integral
management of captive-bred populations implies genetic and demographic routine monitoring tasks must be
performed to reach conservation objectives in these captive populations4.
Monitoring tasks seek to ensure that genetic diversity and eective population sizes are maintained within
acceptable levels, while inbreeding and average relatedness between mating animals are reduced to a minimum5,6.
High levels of genetic diversity do not necessarily imply a high heritability of features that may be desirable from
a conservation perspective. Evolutionary potential depends on external, and oen complex, components for
example, the variability that is due to environment. Provided evolutionary potential7 is thought to be partially
driven by genetic diversity8, it is the eectiveness of genetic management policies (environmental factors even if
this are induced by humans), which may determine whether long-term population viability and reintroductions
into the wild are successfully maximized.
e European Association of Zoos and Aquaria (EAZA) gathers together the leading zoos and aquariums in
Europe and the Middle East and regularly designs standards for the conservation of nature and wildlife both at
its member institutions (400 member zoos and aquariums across 48 countries) and outside the zoo premises9.
Under the scope of the Zoos European Directive10, EAZA member institutions are instructed to maintain stand-
ardized individualized records to make the interpretation and utilization of animal databases easily accessible
for all the members involved in cooperative management plans and formal research projects11. Internally, these
databases allow animal management sta to plan and monitor population conservation and care programmes
for long-term survival and potential in-situ conservation assistance12.
University of Córdoba, Córdoba, Spain. Department of Conservation, Córdoba Zoo Park, Córdoba, Spain. Wildlife
Resources Research Institute, Ciudad Real, Spain.
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Updated records of zoo collections are a valuable source of information for scientic researchers pursuing to
reach the key mission conservation goals of zoos and aquaria as stated in the rst set of guidelines of the World
Association of Zoos and Aquariums13. To ensure these goals are accomplished, each individual animal record
should comprise all the relevant data concerning its current status, origin, genealogy, possible transactions, health
and other practical advice (i.e. welfare issues and/or behavioural features)14.
e documentation of the complete historical record of every individual lays the basis for better coordinated
genetic and demographic population management practices in threatened taxa15. is information may not
only enhance the ability to adapt housing and living conditions to approximate captivity to wild environmental
conditions, but also to replicate the genetic interaction of the individuals in this recreated environment16.
Pedigree information analysis constitutes an invaluable tool for genetic diversity quantication and demo-
graphic structure evaluation in captive populations. is information can be used to formulate recommendations
to maintain a genetically-healthy population17 with reliable reproduction and increasing group growth rates18.
Such recommendations may involve translocations among zoological nuclei, and the objective selection of most
appropriate individuals for reproduction and/or identication of related animals19.
Pedigree-based strategies are cost-eective alternatives to perform routine genetic diversity evaluations,
population demographics and viability and to track the improvement of genetic diversity16,20. e eectiveness
of pedigree analyses relies on the strict control of genealogical information carried in endangered populations,
from the moment when the base captive-founder populations were established. e integrity of the genealogical
information present in pedigrees may be compromised by problems associated to the veracity and eectivity of
the tools used21–23, pedigree completeness levels 24,25 and of the thoroughness of the operators participating in
the process of data collection and registration21, among others. e estimates derived from the analyses of non-
robust pedigrees (i.e., low depth, missing information, errors, unknown founder relationships, among others) can
be favoured if empirical estimates of relatedness via genetic markers (microsatellites or SNPs) are determined26.
Hence, endeavouring to improve pedigree robustness may always be sought to improve the accuracy of genetic
In this context, budget limitations28,29 may frequently compromise the routinely application of genomic tools
and restrict their utility to small-sized threatened populations, with limited or missing genealogical background,
in which the proportion of polymorphic loci is commonly small19,30,31. Otherwise the use of large numbers of
genomic markers may be needed32. ese limitations may result in allele frequencies of the historical popula-
tion being unknown, which may bias the inference of inbreeding as a direct consequence of potential changes
occurring due to genetic dri33. As a result, molecular techniques, which may not distinguish between identity
by descent (IBD) and identity by state (IBS) probabilities underlying genetically mediated similarities among
relatives34,35, may compliment the information comprised in pedigrees.
Based on the aforementioned comparison, ex-situ management programmes using pedigrees are routinely
carried out by EAZA in a wide range of animal species. ese species mainly consist of terrestrial and marine
mammals (approximately 26% of threatened species at a global level)15. In the case of non-human primates, nearly
60% of the species are endangered and 75% account for wild reduced populations as a result of human-induced
disturbs during the last three decades36.
Among other genus and families, EAZA institutions host the largest captive population of white-naped
mangabeys (Cercocebus atys lunulatus), a West African endemic non-human primate from (Ghana, Republic of
Côte d’Ivoire and Burkina Faso)37 currently classied as ‘Endangered’ by e Red List of IUCN due to habitat
fragmentation and bushmeat38. e genealogical information (ESB, European Studbook) of captive white-naped
mangabeys19 has been monitored in dierent European zoos since 1994.
Since 2000, a European Endangered Species Programme (EEP) was implemented to respond to the classica-
tion of the species as ‘Critically Endangered’ by IUCN19. Supported by the West African Primate Conservation
Action (WAPCA) in Ghana and Côte d’Ivoire since 2010, the rst research outcomes obtained consisted of a
population viability analysis (PVA) simulating dierent scenarios combining deterministic and stochastic factors
potentially aecting white-naped mangabey wild populations’ dynamics. e study concluded genetic diversity
may remain high under all assumptions (> 90%)19, which suggested European captive mangabeys may act as an
insurance population to accomplish in-situ conservation goals.
e present study evaluates the eectiveness of conservation activities along the history of the captive popu-
lation of white-naped mangabeys. e genetic and demographic structure of the captive population, genetic
parameters and the trends described by them were quantied. Aerwards, a breeding strategy is proposed to
recommend the most appropriate animal matings among the individuals present in the current population.
To conclude, the genetic distances among hosting institutions were quantied and traced. e present set of
analyses may guide future conservation aimed breeding strategies and act as a model for other species under
the similar circumstances.
Intensive management policies drive demographic rising. e historical and current distribution
of individuals across institutions is shown in Fig.1. e average (± SD) number of infants born per year in the
historic population was 6.20 ± 4.10, reaching its peak (17) in 2016 and 2018. e average (± SD) number of
complete equivalent generations during the last decade (2008–2018) was 2.39 ± 0.218, and described a linear
increasing tendency until it reached a maximum value of 2.59 in 2018 (Fig.2).
Pedigree completeness indexes (PCIs) for one, two, three, four, ve and six generations, the maximum number
of traced generations, maximum number of complete generations and number of equivalent generations in the
two population sets, are shown in Table1.
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e maximum progeny per male and female decreased almost linearly in the current population. However,
the mean (± SD) progeny per male was 1.57 ± 4.17 in the historic population and 2.07 ± 4.19 in the current popu-
lation; 1.68 ± 3.02 and 1.92 ± 2.78 in the historic and current population, respectively, for females. e female/
male ratio is increased in the current population (1.22/1) in respect of the historic population (0.90/1). e
percentage of males with progeny selected for breeding, that is all males whose ospring has acted as a breeding
male or female, was 45.62% and 84.10% in the historic and current population, respectively; 41.34% and 75.73%
for females, all females whose ospring has acted as a breeding female or male (Table1). e average generation
interval and the mean age of parents at ospring’s birth and dispersion statistics (SD and SEM) are presented
in Table2, respectively.
Identity by descent estimators and degree of non‑random mating. Although mean (± SD)
inbreeding is low (3.19% ± 0.07% in the historic population and 1.64% ± 0.05%) in the current population),
highly inbred animals are present in each population set (12.75% and 4.16% of the animals in the historic and
current population, respectively).
Figure1. Historical and current distribution of individuals across institutions.
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Figure2. Evolution of birth number and equivalent complete generations in the historic population (n = 298)
from 1951 to 2019. Provided we measured the variability of time-series data, we relied on the standard error of
the mean (SEM) rather than the standard deviation (SD), as it removes variability imposed by the trend in the
data, which the SD does not.
Table 1. Summary of statistics of genealogy, demographic and ospring analysis in the historical and current
populations of white-naped mangabey.
Population size 298 120
Maximum number of traced generations, n 6 6
Pedigree completeness level at 1st generation, (Known parents) 82.38 92.08
Pedigree completeness level at 2nd generation, (Known grandparents) 52.43 66.45
Pedigree completeness level at 3rd generation, (Known great grandpar-
ents) 20.72 32.91
Pedigree completeness level at 4th generation, (Known great great
grandparents) 4.19 7.65
Pedigree completeness level at 5th generation, (Known great great great
grandparents) 0.29 0.67
Pedigree completeness level at 6th generation, (Known great great great
great grandparents) 0.000052 0.01
Mean number of maximum generations (± SD) 2.24 ± 1.51 2.95 ± 1.51
Mean number of complete generations (± SD) 1.28 ± 0.85 1.56 ± 0.76
Mean number of equivalent generations (± SD) 1.60 ± 0.97 2.00 ± 0.89
Demographic and ospring analysis
Males% 52.68 45.00
Mean (± SD) number of infants per male, n 1.57 ± 4.17 2.07 ± 4.19
Maximum infant number per male, n 27 20
Average age of males in reproduction, years 16.10 15.22
Females% 47.31 55.00
Mean (± SD) number of infants per females, n 1.79 ± 3.02 1.92 ± 2.78
Maximum infant number per female, n 15 10
Average age of females in reproduction, years 16.57 14.00
Female/male ratio 0.90/1 1.22/1
Progeny from males selected for breeding, % 45.62 84.10
Progeny from females selected for breeding, % 41.34 75.73
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e percentage of inbred animals was 23.15% and 17.5%; the average (± SD) coancestry was 4.21% ± 2.00% and
4.18% ± 2.00%; and the degree of non-random mating presented mean values of −0.02 ± 0.07 and −0.03 ± 0.05,
for the two population sets, respectively. e highest values for these three parameters were 0.25 (25%) for dif-
ferent ages between 1985 and 2018, 0.0914 (9.14%) for coancestry in 1997 and 0.225 for non-random mating
degree in 1999.
Matings resulting in highly inbred animals have occurred in the population: 2 (0.67%) mating between full
sibs, 18 (6.04%) mating between half-sibs y 18 (6.04%) mating between parent-ospring.
Registered values for mean (± SD) Genetic Conservation Index (GCI) were of 2.84 ± 1.48 and 3.52 ± 1.52 for
the historic and current population, respectively. e summary of identity by descent estimators, non-random
mating degree and genetic conservation index parameters is presented in Table3.
e evolution of the non-random mating degree (α), inbreeding rate (F), average relatedness (ΔR), and
Genetic Conservation Index (GCI) of the European captive white-naped mangabey from 1951 to 2019 is repre-
sented in Fig.3. Regression equations for the prediction of the evolution of average inbreeding (F) and average
relatedness (ΔR) up to 15 generations are shown in Fig.4. Linear, logarithmic and polynomic functions were
tested seeking the best tting models to describe the trends presented by each parameter. e polynomic function
was selected upon considering the functions reporting the highest value for the determination coecient (R2)39.
Probabilities of gene origin, ancestral contributions and genetic diversity. e results for the
analysis of the gene origin probabilities, ancestral contributions and genetic diversity, are shown in Table4.
Table 2. Average generational intervals and mean age of the parents at the birth of their ospring (years) and
dispersion statistics (Standard deviation, SD and Standard error of the mean, SEM) for population groups.
Generation interval route Sire to son Dam to son Sire to daughter Dam to daughter To t a l
Historical (n = 298)
n 23 22 39 36 120
Mean 15.07 11.28 14.73 11.28 13.13
SD 5.25 4.55 5.16 4.42 5.12
SEM 1.09 0.97 0.82 0.73 0.46
Current (n = 120)
N 14 14 30 30 88
Mean 13.98 10.62 15.34 11.57 13.08
SD 5.76 4.58 5.27 4.71 5.33
SEM 1.54 1.22 1.41 1.26 0.57
Age of the parents at the birth of
their ospring Sire to son Dam to son Sire to daughter Dam to daughter Total
Historical (n = 298)
n 134 132 113 112 491
Mean 14.93 11.74 14.75 10.96 13.12
SD 4.70 4.84 5.05 4.85 5.15
SEM 0.41 0.42 0.47 0.46 0.23
Current (n = 120)
N 48 48 62 63 221
Mean 14.17 9.99 14.51 10.20 12.23
SD 4.92 3.78 5.13 4.69 5.13
SEM 0.71 0.55 0.74 0.68 0.35
Table 3. Statistics of identity by descent estimators, non-random mating degree and genetic conservation
Historical (n = 298) Current (n = 120)
Inbreeding (F, %) 3.19 ± 0.07 1.64 ± 0.05
Average (± SD) individual increase in inbreeding (ΔF, %) 5.53 ± 0.16 1.54 ± 0.07
Maximum coecient of inbreeding (%) 25.00 25.00
Inbred animals (%) 23.15 17.5
Highly inbred animals (%) 12.75 4.16
Average (± SD) coancestry (C, %) 4.21 ± 2.00 4.18 ± 2.00
Average (± SD) relatedness (ΔR, %) 8.43 ± 4.79 8.36
Average (± SD) Non-random mating rate (α) −0.02 ± 0.07 −0.03 ± 0.05
Average (± SD) Genetic Conservation index (GCI) 2.84 ± 1.48 3.52 ± 1.52
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Considering the marginal genetic contribution, the genetic constitution of a single ancestor (identication
code: 33) explained 16.99% of the total genetic pool within the population (91.62%), 1.69% of the total inbreed-
ing coecient (3.09%) and 1.68% of the total coancestry (3.93%). e 10 ancestors with higher marginal genetic
contributions were responsible for the total inbreeding and 3.72% of the total coancestry in the population.
e mean (± SD) eective population size calculated by the individual inbreeding rate was 47.33 ± 21.04 in
the reference population, whereas the mean (± SD) eective population size based on the individual coancestry
rate (NeCi) was 17.76 ± 1.59. e number of equivalent subpopulations (± SD) was 0.37 ± 0.17.
Herd relationships and breeding strategy. e mean (± SD) number of animals per zoo was
8.51 ± 10.26, ranging from 1 to 40. Related to Wright’s F statistics, the inbreeding coecient relative to the total
population40 was −0.01, the inbreeding coecient relative to the subpopulation41 was −0.16 and the correla-
tion between randomly drawn gametes from the subpopulation relative to the total population (FST) was 0.13
(Table5). ere were considered a total of 561 Nei’s genetic distance between the 35 zoos. e average (± SD)
Nei’s genetic distance was 0.253 ± 0.126. e mean (± SD) coancestry within subpopulations was 0.16 ± 0.02
(16.00% ± 2.00%) and the mean inbreeding was 0.032 ± 0.02 (3.20% ± 2.00%). In the metapopulation, the mean
(± SD) coancestry and self-coancestry were 0.04 ± 0.02 and 0.52, respectively.
Zoo structure assessment revealed none of the zoos could be considered the population nucleus neither
totally isolated. e number of zoos that used foreign father was 19, whereas 17 used own fathers and 14 used
both foreign and own fathers. In total, 28 pairs of zoos showed the greatest Nei’s genetic distance (50%) among
them. e minimum Nei’s genetic distance was 0.0619 (6.19%) and was shared between one pair of zoos (Sup-
plementary TableS1). A cladogram representing all the relationships between the 34 zoos is shown in Fig.5.
Figure3. Evolution of (A) non-randon mating degree (α), (B) inbreeding rate (F), (C) average relatedness
(ΔR) and (D) Genetic Conservation Index (ICG) for the white-naped mangabey captive population from 1951
to 2019. Provided we measured the variability of time-series data, we relied on the standard error of the mean
(SEM) rather than the standard deviation (SD), as it removes variability imposed by the trend in the data, which
the SD does not.
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Figure4. Regression equations for average inbreeding (F) and average relatedness (ΔR) expressed in % from 1ª
to 6ª generation, and their prediction from 7ª to 15ª generation. Provided we measured the variability of time-
series data, we relied on the standard error of the mean (SEM) rather than the standard deviation (SD), as it
removes variability imposed by the trend in the data, which the SD does not.
Table 4. Summary of results for founder analysis, measures of genetic diversity and diversity loss. GDL
Genetic diversity loss.
Parameter Reference population (both parents known historically) (n = 240)
Historical population 298
Current population 120
Base population (one or more unknown parents) 58
Actual base population (one unknown parent = half founder) 11
Number of founders, n 29
Number of ancestors, n 33
Eective number of non-founders (Nef) 51.32
Number of founder equivalents (fe) 15.41
Eective number of ancestors (fa) 11
Founder genome equivalents (fg) 11.85
fa/fe ratio 0.71
fg/fe ratio 0.77
Genetic diversity, GD (%) 95.78
Genetic diversity in the reference population considered to compute
the genetic diversity loss due to the unequal contribution of founders,
GD (%) 96.75
GDL due to bottlenecks and genetic dri since founders (GL) (%) 4.22
GDL due to unequal founder contributions (%) 3.24
GDL due to genetic dri (%) 0.97
Ancestors explaining 25% of the gene pool (n) 1
Ancestors explaining 50% of the gene pool (n) 5
Ancestors explaining 75% of the gene pool (n) 10
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Conservation measurements implemented in captive European white-naped mangabeys have focused on main-
taining a healthy ex-situ population mimicking the natural framework of the species. e captive population
has maintained high genetic diversity and minimized inbreeding levels since 1951 (see Fig.3). Two of the high-
est annual birth rates were experienced in 2016 and 2018 (see Fig.2)4. e minimum number of animals born
per year (≤ 4) describes a cyclical trend which lasts approximately 20years, a period aer which white-naped
mangabeys naturally display signs of reproductive senescence42.
e demographic evolution of captive population is parallel to the improvement of the risk situation faced
by white-naped mangabeys wild populations, which promoted the reclassication of the species by e Red List
of IUCN to the lower threat category of “Endangered” in 2015. e inclusion of twenty-one new institutions
reinforced EAZA’s network and brought about the addition of new founders (twenty-eight unrelated, wild-born
individuals) and genealogy-known individuals to the ex-situ population since 201219. e progressive increase
in pedigree knowledge up to 90% at rst generation occurred in the context of the scarcely available data from
other threatened species held at osite emplacements for similar conservation purposes (for instance, 27%-35%
known pedigree for sable antelope32,43 and 70.9% for African Penguin44).
is lack of information occurs even if institutions make every eort to implement the most ecient standard-
ized methods. Pedigrees can remain problematic due to multiple reasons, including diculties associated with
discerning parentage with herd or ock breeding22,23, low generation depth24, unknown founder relationships25,
and human error21, among others45.
As a result, the analysis of incomplete pedigree records may lead to biased calculations of demographic and
genetic parameters, even if self-sustainability could be expected from most managed populations46. For instance,
78% of bird and 52% of mammal captive populations registered in EAZA’s studbooks47, have pedigree complete-
ness index levels below 85% and 58% fail to achieve the target conditions for sustainability (eective population
size, growth rates, sex ratio and similar life-time family sizes across zoos)46.
e pedigree completeness levels in our study provide the rst evidence of the success of white-naped man-
gabey ex-situ programme, which in turn enhances the possibilities for protection and recovery at medium and
long-term, as long as genealogical recording and intensive management husbandry practices continue19.
e captive population constitutes itself a short-term backup reserve if the imminent extinction of wild
populations occurred. In fact, it is the intensive management implemented, which aims at preserving the demo-
graphic and biologic structure of white-naped mangabeys wild counterparts, which potentializes the breeding
capacities of the individuals to eectively retain high levels of genetic diversity. Maximum progeny per male
and female were higher in the historic population. However, this could be ascribed to the fact that in the origin
of the captive population, the main objective was to ensure a number of animals which may permit the captive
population’s long-term viability48.
High mean progeny per male and female in current population denote the balance of the dierential contri-
bution of individuals to reproduction may have eectively contributed to the maintenance of genetic diversity49.
is was supported by the negative values of FIS (Table5), suggesting breeding policies implemented may enable
maximizing the likelihood of unrelated matings pairs50.
Mean age of animals at breeding (Table1) and mean age of parents at the birth of their ospring selected for
breeding (Table2) were lower in the current population. is may be indicative of the attempts to maximize
reproductive potential promoting maternal reproductive skills and interactions during high fertility periods42.
In these regards, feeding and handling in early growth stages, rst parturition and lactation must be appropriate
to ensure reproductive success is not aected51.
Prolonging generational intervals can eectively increase the number of animals selected for breeding, pro-
gressively increasing eective population sizes and, therefore, generating a proportional reduction in inbreeding52,
which maximizes the preservation of genetic diversity. To increase selection pressure, older animals with more
progeny registries may be required, which may extend generation intervals. Shortening generation intervals
may imply younger animals with fewer progeny registries may be considered, which may decrease selection
pressure. is negative correlation could be compensated as young animals oen present a greater genetic value
provided they are the result from maximized genealogical diversity practices53. By contrast, reduced generation
Table 5. Wright’s Fixation statistics and zoo’s genetic distancing parameters.
Parameter Val u e
FIS (inbreeding coecient relative to the Subpopulation) −0.16
FST (Correlation between random gametes drawn from the subpopulation relative to the total population) 0.13
FIT (inbreeding coecient relative to the total population) −0.01
Mean (± SD) number of animals per subpopulation 8.51 ± 10.26
Number of genetic Nei distances 561
Average (± SD) Nei genetic distance 0.25 ± 0.13
Mean (± SD) coancestry within subpopulations 0.16 ± 0.02
Mean (± SD) coancestry in the metapopulation 0.04 ± 0.02
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intervals may imply a larger number of animals reach sexual maturity age (set around 6years old) earlier, with
the consequent increase in birth number and population growth rate.
Additionally, the balance between such strategies may lead to the success of the breeding programme, as
suggested by the relatively low negative values of FIS, which may be indicative of the promotion of breeding
policies that consider unrelated animals at a rate at which the population does not excessively depart from
Mean generation intervals were higher for the current sire-daughter and dam-daughter pathways, which could
be explained by a sex-ratio which favours females (Table1), a common demographic feature to wild populations
of the genus Cercocebus54 which could be ascribed to the philopatric nature of primate females.
is biological condition provides primates with an important functional role for ecosystem health and
wellbeing which simultaneously enables the survival and success of ospring to breed55. Additionally, in Old
World monkeys (Family Cercopithecidae), milk amount and quality may be inuenced by ospring sex, to the
detriment of baby females56,57, which determines a lower growth rate in their early stages and a delay in the mean
age of prepuberal females in reproduction.
Figure5. Cladogram constructed from Nei’s genetic distances among EAZA member institutions that house
white-naped mangabeys in their facilities.
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Parents’ mean age at their ospring’s birth was slightly lower than generation intervals (Table2), suggesting
selection of breeding animals whose ospring may potentially breed is performed slightly later than the moment
when their rst ospring is born. is way, data and reproductive records (health status, sexual cyclicity and
maternal skills) may adjust to life expectancy (males: 26.7years; females: 34.7 years58) and maximum periods of
fertility (males: 19years; females: 15 years19) of captive individuals.
Historical and current percentages of females with progeny selected for breeding were lower than those
of males (also slightly older). is suggests breeding selection policies pay a greater attention to males [either
phenotypically (for instance, considering their behaviour, adaptability to environment or resistance to stress58),
functionally (reproductive eectiveness) or conservationally (higher levels of genetic diversity and reduced
inbreeding)] as suggested for other species59. is policies simulate the sexual dispersion of this species, in which
the males constitute the migratory sex60.
e implementation of a EEP since 2000 signicantly contributed to inbreeding and average relatedness
reduction19. However, levels above 1% and highly inbred animals can be found in the captive population (Table3),
suggesting matings between closely-related animals may still occur. Although inbred individuals could be out-
crossed with unrelated individuals from the wild61, obtaining new founders from wild populations is dicult,
provided these populations currently describe a decreasing trend.
Inbreeding has remained below coancestry levels, suggesting matings among closely-related individuals were
unintentionally performed62. e dierent subpopulations are substantially separated, making it dicult to
involve dierent genetic resources. is is consistent with the degree of non-random mating (α) and FIS values,
which suggested higher rates of random matings among closely-related individuals may occur, which is common
in small-sized populations which develop in limited spaces.
Current ΔF slightly exceeds the recommended maximum of 1%, level below which the tness of a popula-
tion steadily decreases63–65. Hence, eective population size may still not reach the recommended threshold to
maintain genetic variability (≥ 50 individuals). However, the trends described for the historical evolution of ΔF
report promising outcomes, as there has been a decrease of around 4 points, which may imply genetic variability
may be recovering acceptable levels. As Lee and Wilcken66 stated, a population of any size can be sustainable if
a supplementing source population can eectively suit the required harvest of new individuals and cooperation
across institutions is well-established. e incorporation of Accra’s Zoo (within the species geographical range) in
2010, meant an invaluable source for genetically unrelated wild-born animals which may prevent genetic erosion.
e number of equivalent subpopulations below 1 revealed a high level of population structuration. Accord-
ing to Fernández, etal.67, population subdivision may be benecial, provided the extinction risk derived from
compromising events such as accidents or health-related factors, may only cause the disappearance of population
sections. Furthermore, genetic diversity may reach its highest levels when populations subdivide into as many
separate groups as possible. Still, caution should be taken, provided the benets of subdivision may be counter-
acted by the negative eects derived from the reduction in eective size and increase in inbreeding.
Although population structure can greatly aect ΔF, it hardly aects coancestry increase, hence NeCi may
more accurately estimate eective population size than NeFi68. Hence, progressively adding individuals through
the participation of new institutions may be benecial to maintain a high degree of genetic diversity for as long
as possible19. Simultaneously, the proportion of translocated males is higher than that of females. is practice
may be an additional attempt to simulate the male sexual dispersion of the species60, an implicit evolutionary
strategy for the prevention of inbreeding increase69–71.
Values of fe (15.41) and fa/fe (0.71) may suggest the frequent use of a small number of animals for breeding
may lead to the loss of genetic variability, which may be supported by the low number of ancestors (5) which
explains 50% of population’s gene pool. Still, founders’ genotypes are represented in the current population. e
unequal contribution of founders may be conrmed by the values of fg (11.85) and fa/fe (0.71) as one of the main
causes for the current genetic diversity loss. e dierence between fe and fa suggests bottlenecks, although not
sharply, may have reduced population’s genetic variability. e lower the fe/fa is, the greater impact bottlenecks
have on the population.
ese bottlenecks may be associated to a progressive increase in the occurrence of abnormalities and sus-
ceptibility to disease or stressful environmental situations. Such an increased susceptibility may derive from
the increase in the incidence of deleterious recessive mutations, which may potentially lead populations to
extinction72. Mutations that are only mildly deleterious are dicult to eliminate and are the principle cause of
inbreeding depression73. Furthermore, even if lethal and semi-lethal mutations disappear rapidly due to inbreed-
ing, the large costs of this process may aect population viability73.
For instance, infant mortality levels of in white-naped mangabeys in captivity of 37.2% with most deaths
occurring within the rst two months of life58, could potentially be ascribed to increased inbreeding levels
(around 25%) in primate captive populations among other factors74. However, theoretically, species that are
naturally inbred to some degree in the wild, should potentially show less of a deleterious eect when subjected
to inbreeding in captivity, which may somehow explain the low representativity of the loss of genetic diversity
derived from the occurrence of bottlenecks and genetic dri in the population under study (0.97%)74.
Additionally, the dierence between fg and fa (11) would suggest the eects of genetic dri on genetic diversity
may have been compensated by the higher value of fg. e dierence between fg and the number of founders (f)
(29) may be indicative of the loss of founder’s ospring, inbreeding increase at founder stages, or a combination of
both causes19,75. is could be justied by the absence of an intensive population breeding programme until 2000
when the EEP76 of this species was set19. Nevertheless, according to genetic theory, twenty unrelated individuals
may be enough to retain 97.5% of the wild gene diversity within the founder population72.
Long generation intervals found in primates may permit genetically self-sustainability with few founders.
In fact, this specic ex-situ programme may have eectively captured at least 90% of wild gene diversity for
100years since the captive population was established, as most of the EEPs and ESBs within EAZA institutions77,
Scientic Reports | (2021) 11:674 |
with levels of genetic diversity (95.78%) in the captive population progressively increasing since 2012 (93%)19.
Considering that intensive management for this captive population is relatively recent, the maintenance of such
high genetic diversity levels may depend on multiple simultaneous factors. For instance, not enough generations
may have passed since the decrease in the eectives comprising the wild population pushed the species to its
current endangered situation. Hence, generation number in captivity may not be enough to verify the magnitude
of genetic variability reduction8,78.
However, in the absence of conservation eorts, a substantial loss could be conrmed in the near future for
these primates. For instance, as reported by Jara etal.19, the number of founder genome equivalents was half the
number of founders in captive white-naped mangabeys in 2016, which was indicative of either lost descendants
of the original founders or that the original founders were inbred, or a combination of these factors.
In this context, the lower dierence between founder genome equivalent and number of founders in the
present study conrms special eorts may be being made on the preservation of descendants from the founder
population, as if the cause for such dierences may have been the fact that founder animals were inbred, these
values may have remained somehow stable. is supports the fact that the founder population of captive white-
naped mangabeys may have been highly genetically diverse and may have included individuals from a wide range
of geographic origins hence, the variability to be expected from wild populations’ sub-structuration may be well
represented79 as described for other captive populations of critically endangered species80.
Genetic diversity may be the basis for individuals’ resilience to the factors that extensively threat their wild
populations and the adverse eects of adaptation to captive breeding81. In this context, research seeking to
understand viability and resilience mechanisms in captive populations may bring about the development of
tools which may enable to evaluate genetic diversity levels indirectly. is in turn may help to fulll conserva-
tion purposes more eciently and practically, as the more diverse populations are, the more capable to adapt to
captivity environments they will be as well.
In this sense, a recent population viability analysis simulating dierent scenarios combining deterministic
and stochastic factors and their potential impact on the viability of wild isolated populations of white-naped
mangabey has suggested high levels of genetic diversity may be generally maintained under all assumptions
(> 90%)82. Hence, the subdivided populations could contribute to the conservation of genetic diversity, as shown
in wild fragmented populations of other nonhuman primates83–85.
e minimum Nei’s genetic distance between institution pairs, eective population size and Wright’s F statis-
tics conrmed a certain subdivision degree. A single institution (26) is at the top of the relationship cladogram
(Fig.5). is may base on the private character of the institution and on the frequent translocation of the ospring
born to other zoos, while no genetic material is received (from live animals or assisted reproduction).
Reproductive policies normally consider a small number of ancestors as the basis for subsequent generations,
which indirectly replicates the natural isolation patterns found for fragmented wild animal populations86. Table5
suggests the breeding strategy should aim at mating animals keeping relationship coecients (R) below 10%
to maintain the inbreeding below 1%, which may increase eective population size up to a minimum of 50 to
counteract the risk of extinction. Breeding animal selection should consider conservation criteria such asmean
kinship rankings (average relatedness value of an animal towards the current population) to reduce inbreeding
and genetic variability loss87.
Bearing this in mind, current pairing/transfer criteria focuses on ranking animals in the population con-
sidering their individual inbreeding coecients (F) and genetic conservation index (GCI). GCI88 measures the
proportion of genes of founder animaliin the pedigree of each particular individual in the population. GCI
is a measure of the representativity of founding population in the individuals, and acts as a measure of genetic
diversity in the range of the genetic pool of the base population. e highest score in the rank was given to the
model obtaining the most desirable value for each particular criterion. For instance, those individuals present-
ing the lowest inbreeding coecients may be ranked higher, while those animals presenting the highest genetic
conservation indexes will be ranked higher as well. en, the rest of positions in the rank were determined in
ascending or ascending order from the most desirable values to the lowest desirable ones, which are ranked
with the value of 1.
Aerwards, as aforementioned inbreeding and GCI dier in terms of which their most desirable values are
and what their magnitude is, a combined selection index (ICO) is developed following the premises in Van
Vleck89 to summarize the position in the rank for each of the two parameters. e combined index used (ICO)
was as follows;
where W1 is the weight for inbreeding coecient, W2 for GCI rank position. All criteria are given the same
relevance in the ICO, hence, no coecient was used, that is the proportion of 1:1 is followed. As a result, the
animals presenting greater ICO values are the ones presenting the highest levels of genetic diversity from the pool
of the founding population and having those founding genes from the least related animals. Conclusively, the
individual values for ICO and mean kinship rankings between pairs of individuals are considered to determine
which the most appropriate pairing/transfer candidates are.
is use of mean kinship, inbreeding and GCI values for best guiding of animal pairing is proposed to be
more attainable in zoo-kept intensive-managed populations than in other large housing facilities where social
structure and therefore mate choices cannot be accurately handled4. Such condition may translate into a more
successful genetic and demographic intensive management of biodiversity conservation43. Comparing genetic
diversity and structure between captive and wild populations using genomic markers would help to determine
ICO =Inbreeding coeﬃcient Position in the Rank
GCI position in the Rank
Scientic Reports | (2021) 11:674 |
the magnitude of the potentially occurring bias when using information from pedigrees and which of these two
alternatives may eventually more eective26,90.
White‑naped mangabey breeding‑management programme in captivity. Barcelona Zoo coor-
dinates the European Studbook (ESB) for the white-naped mangabey. is population breeding/management
programme registers the information in respect birth place, birth and death dates, average kinship (average
relatedness between an individual to all others in the population, including itself) and transfers of the individuals
that are housed in EAZA-member institutions.
rough the compilation of this information, a demographic and genetic assessment is regularly performed
to eectively manage the general status of the population. If derived results indicate a non-self-sustaining popu-
lation at a given time, more intensive management (i.e. increasing the rate of exchange of individuals between
zoos and planning matings carefully considering their diversity, inbreeding levels and relatedness) are proposed
for the ongoing population viability19.
Transfer decisions are based on internal criteria such as lack of space for more individuals in a particular
location for welfare issues, existing heavy disputes among congeners sharing resources, desired phenotypic traits
and/or low reproduction performance within a captive herd.
Concerning exchanging rates, sixty-eight males and y-seven females have been subjected to transloca-
tion activities for improved pairing since 1994. In y-ve cases, this genetic exchange has been made through
assisted reproduction techniques by expert veterinarians instead of removing the animals from their living
emplacement for mating attending to animal welfare-related logistic and biological constraints (transport and
potential destabilization of social hierarchy in acceptor herd).
Data registries and software tools. e historical population comprises 298 animals (157 males and
141 females) born between January 1951 and January 2019. e current population comprised 120 white-naped
mangabeys (54 males and 66 females) which were born between September 1987 and January 2019 and are alive.
Only thirty-three animals (11%) were wild-born.
irty-four European Association of Zoos and Aquaria’s member zoos houses white-naped mangabeys and
compiles genealogical information for the commitment of this species conservation program’s goals19 (Fig.1). e
studbook was provided by the white-naped mangabey EEP coordinator. e registries consist of the individual
name and identication code, sire code, dam code, sex, birthdate (to know the temporal evolution or tendency
of some parameters), birthplace (captive-born or wild-born) and status (death or alive).
e demographic and genetic parameters of variability were evaluated using the ENDOG soware (v 4.8)91.
e analysis of the probabilities of genetic origin and ancestral contributions was carried out with the CFC
soware92, on all the data sets. Dendroscope 3 soware93 was used for the graphical representation of the den-
drogram based on Nei’s genetic distance between subpopulations.
New‑born annual increase and pedigree completeness index. New-born annual median number,
maximum and mean number of ospring per sire and dam were calculated. Pedigree completeness index (PCI),
which summarizes the percentage of known ancestors of each ascending generation, was evaluated as in Navas
etal.62 computing the maximum number of traced generations; the number of complete traced generations; the
number of complete equivalent generations (all known ancestors); and the quality of the genealogical informa-
tion of the pedigree were determined aer the calculation of the proportion of known parents through to great-
great-great-great-grandparents (rst to h generation inclusive).
Breeding animals, generation interval and mean age of parents at ospring’s birth. Genera-
tion intervals were computed as the mean age of parents at the birthdate of their ospring selected for breeding94
and the mean age of parents at ospring’s birth (selected for breeding or not), were calculated for each of the four
gametic pathways: sire to son, sire to daughter, dam to son and dam to daughter. ese parameters were obtained
from the birthdate for every animal together with those of its parents. Female/male ratio was considered the
relationship between total number of females and males in historical and current populations.
Identity by descent estimators and degree of non‑random mating. Individual inbreeding (F) was
computed according to Luo95. e average relatedness (ΔR) of each individual or the probability that an allele
randomly selected within the population belongs to a given animal, was obtained as proposed by Gutiérrez
etal.91. e individual rate of inbreeding (
for the number of complete equivalent generations was computed
according to Gutiérrez etal.96. e individual rate of coancestry (
for the number of complete equivalent
generations was computed as suggested by Cervantes etal.97. Mean inbreeding (F) per generation and average
relatedness (ΔR) were used to issue regression equations tting lineal, logarithmic and polynomic functions to
predict for the evolution of inbreeding and relatedness up to een generations onwards. Non-random mating
(α) was calculated as described by Caballero and Toro98. Genetic Conservation Index (GCI) or the eective
number of founder ancestors of each pedigree, was estimated as proposed by Alderson88.
Probabilities of gene origin, ancestral contributions and genetic diversity. e eective number
of founders (fe) or founders equally contributing that are expected to generate the same genetic diversity that in
the studied population, was computed as;
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where qk is the probability of gene origin of the founder and f the real number of founders75.
e minimum number of ancestors (fa), founders or not, necessary to explain the entire genetic constitution
of the population, was determined as;
where pk is the marginal contribution of an ancestor k, which means the contribution not explained yet by the
rest of ancestors99. Both parameters (fe and fa) can be used to summarise the loss of genetic variability because
of the non-proportional breeding animals’ contribution100.
e eective number of founder genomes (fg) or the number of equally contributing founders without founder
alleles loss that are expected to generate the same genetic diversity than in reference population (both parents
known), was obtained by calculating the inverse of twice the average coancestry98.
e expected marginal contribution of each major ancestor j (the largest genetic contributing founders or
not) was computed as the expected genetic contribution independently of the rest of ancestors’ contribution99.
e contributions to inbreeding of nodal common ancestors (highest marginal genetic contributions) that
form inbreeding loops, were obtained according to Colleau and Sargolzaei101. An inbreeding loop exists when
the ancestor of an individual is that by both maternal and paternal pathway. Mean eective population sizes (
)102, was calculated as;
e number of equivalent subpopulations103 was assessed as the relationship between
mean eective population size considering the coancestry coecient and
that is the mean eective
population size considering the inbreeding coecient. Genetic diversity (GD) was calculated as75,104;
e GD loss (GDL) in the population since the founder generation was estimated as
. Considering the
dierent possible causes of this loss, GDL derived from the unequal contribution of founders was calculated as;
e dierence between GD and GD* is referred to genetic dri accumulated since the foundation of the
e eective number of non-founders (Nef) was calculated as proposed by Caballero and Toro98 to describe
the relationship between the eective number of founders and the number of equivalent genomes of founders.
Zoo relationships and breeding strategy. e relationships between zoos were evaluated using Wright’s
F statistics and Nei’s genetic distance. e Wright’s F statistics105 for each subpopulation (35) were calculated
according to Caballero and Toro106. Wright’s F statistics allow pairwise comparisons among subpopulations or
populations but those pairwise "distances" take account only of the data for the two populations concerned, not
all the data simultaneously. Still this provides relevant information in the context of pedigree evaluation as the
dierences between both parameters may account for the estimation bias that may occur. For this reason and to
quantify the degree to which populations diers from the entire pool of data using distance measures that make
biological assumptions, Nei’s distances were used as well. Nei’s genetic distance69 between subpopulations i and
j was computed as;
where Cij is the average pairwise coancestry between individuals of the subpopulations i and j, including all
Ni × Nj pairs. Cii and Cij are the average pairwise within subpopulations i and j, to assess interzoo relationships.
Aerward, a simulation was made to determine the maximum limit of relatedness coecient existing in
the population between mated animals to determine which matings maintained (
) in a generation equal or
ese levels of individual increase in inbreeding correspond to Ne = 50. Below these levels tness of a popu-
lation noteworthily decreases107. Relatedness coecient (ΔR) can be dened as the probability that two indi-
viduals share an allele because of common ancestry. Relatedness coecient (ΔR) of a pair of mating animals
is the potential inbreeding coecient of their potential ospring. is parameter ranges from 0 (unrelated) to
Scientic Reports | (2021) 11:674 |
1 (clones or identical twins). is denition excludes alleles that are shared because of belonging to the same
species or population.
Five mating groups were considered for the simulation. e average relatedness coecient between mated
animals was kept below 0.00%, 5.00%, 10.00%, 15.00% and 20.00% (greatest feasible limit considering all possible
mating among all 120 alive animals). e inbreeding coecient of the ospring for each mating was estimated as
one-half of the parental relationship coecient. e inbreeding rate96 was calculated by averaging the individual
inbreeding increase through;
where ti is the number of complete equivalent generations108 and Fi the inbreeding coecient of the individual i.
For each group, 17 random matings were selected, basing on the number of births in the last natural complete
year (2018: 17 births) and on the assumption of one baby per female42 using SPSS Inc.109. irty replicates were
evaluated within each group to calculate the average eective population size (Ne) as described by Gutiérrez
e datasets generated during and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Received: 20 June 2020; Accepted: 18 December 2020
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e authors would like to thank the collaboration of white-naped mangabey EEP for their work and support.
F.J.N.G. and J.V.D.B. designed and executed the study; M.T.A. provided the studbook information; C.I.P. sup-
ported the analyses for genetic diversity estimates; F.J.N.G. and C.I.P. performed the statistical analyses and
generated the gures and tables; F.J.N.G. and C.I.P. wrote the manuscript; and F.J.N.G., C.I.P., M.T.A., M.J.R.A.,
J.V.D.B. and J.A.D.G. participated in the discussion and editing of the article.
e authors declare no competing interests.
Scientic Reports | (2021) 11:674 |
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