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Global Research journal of Natural Science  
& Technology (GRJNST)  
Volume: 04 - Issue 2 (2026), 2070  
ISSN P: 2790-7643 ISSN E: 2790-7651  
www.grjnst.net  
https://doi.org/10.53762/grjnst.04.02.21  
Integrating Genomic Tools with Conservation Biology: A Framework for Managing  
Genetic Erosion in Endangered Mammals of Pakistan  
Received: 30 December 2025. Accepted: 27 February 2026. Published: 24 April 2026  
Quratulain shaikh  
Assistant Professor Zoology  
Government College for Women, Khairpur, Sindh, Pakistan  
quratulain45203@gmail.com  
Rehana Aslam  
Assistant Professor Zoology  
Government College for Women, Khairpur, Sindh, Pakistan  
haniahadia127@gmail.com  
Hira Mazhar Ujan  
MS Zoology  
Shah Abdul Latif University Khairpur, Sindh, Pakistan  
hiramazhar997@gmail.com  
Sadaf Shafique  
Lecturer Zoology  
GGDC Gambat, Sindh, Pakistan  
sadafrajput444@gmail.com  
GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643  
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Abstract: This study examined the integration of genomic tools with conservation  
biology to address genetic erosion in endangered mammals of Pakistan. The research  
focused on key species including the snow leopard, Indus river dolphin, and markhor,  
which faced increasing threats from habitat fragmentation, inbreeding, and  
environmental change. A quantitative research design was applied, and a sample size of  
180 genetic specimens was analyzed using advanced genomic techniques such as DNA  
sequencing and single nucleotide polymorphism (SNP) analysis. The results indicated  
a moderate level of genetic diversity (mean = 3.21) alongside high inbreeding levels  
(mean = 4.05) and severe habitat fragmentation (mean = 4.18). Structural model  
findings showed that habitat fragmentation negatively affected genetic diversity (β = -  
0.42, p = 0.000), while inbreeding also exerted a significant negative effect (β = -0.39,  
p = 0.000). In contrast, genomic monitoring demonstrated a positive impact on genetic  
diversity (β = 0.36, p = 0.000), and conservation policy support also contributed  
positively (β = 0.31, p = 0.000). The study proposed an integrated framework  
combining genomic monitoring, habitat restoration, and policy interventions to enhance  
conservation effectiveness. The findings highlighted the importance of incorporating  
genomic data into conservation strategies to improve species resilience and reduce  
extinction risks. This research provided practical implications for policymakers,  
conservationists, and researchers aiming to preserve biodiversity and manage genetic  
erosion in endangered mammalian populations.  
Keywords: conservation biology, endangered mammals, genetic diversity, genomic tools,  
habitat fragmentation, Pakistan  
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Introduction  
The increasing rate at which the biodiversity is being destroyed has become one of the most  
urgent environmental problems in the world, with genetic erosion being an essential aspect of the  
species extinction. The genetic diversity is a crucial concept that allows species to adjust to  
environmental changes and ensure long-term viability of the population. Recent reports  
highlighted that genetic variability is highly reduced by lower effective population size,  
fragmented habitats, and anthropogenic impacts, contributing to a higher risk of extinction  
(Kardos et al., 2021; Kyriazis et al., 2022) . The development of next-generation sequencing and  
genome-wide analysis has radically changed the conservative methodology, which now allows  
focusing on identifying genetic bottlenecks and evolutionary forces affecting endangered species  
(Breed et al., 2019; Hohenlohe et al., 2021).  
The rise of conservation genomics was a shift in paradigm of classical genetic techniques to high-  
resolution analysis of genomic data. Genomic technologies, unlike previous methods which used  
only a small number of molecular markers, offered an in-depth view of thousands of loci  
throughout the genome, which improved the accuracy of conservation decision making. These  
instruments led to the discovery of concealed genetic variation, adaptive alleles, and population  
patterns of connectivity that are important to the survival of the species (Allendorf et al., 2013;  
Kardos et al., 2021). Genomic techniques allowed to define conservation units and to design  
strategies, including assisted gene flow and genetic rescue, in order to alleviate the negative  
consequences of inbreeding and genetic drift.  
A great number of mammalian species are present in Pakistan with some of them being  
endangered in the whole world e.g. the snow leopard, Indus river dolphin and the markhor. But  
these species were under growing threats of habitat degradation, poaching, climatic change, and  
human intrusion. The populations were fragmented and the quality of habitat was deteriorating  
which led to decreased gene flow and an increase in genetic isolation, thus, enhancing genetic  
erosion. It was hypothesized based on empirical data that small and isolated populations were  
especially susceptible to genomic erosion because genetic drift and the accumulation of harmful  
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mutations were amplified (Frankham, 2015; Hedrick and Garcia-Dorado, 2016). These issues  
underscored the necessity to incorporate sophisticated genomic tools in the conservation  
planning in Pakistan.  
International advances in conservation genomics, its application in developing nations, and in  
Pakistan have been minimal because of resource limitations, inadequate infrastructure and  
insufficient inter-disciplinary collaboration. Conservation programs still tended to be based on  
ecological observations, but did not include genetic data to enable them to deal with the long-  
term ecological risks. The combination of genomic technologies and conservation biology offered  
an excellent prospect of creating data-based, sustainable approaches to handle endangering  
mammalian groups and avoid irreversible genetic degradation.  
Background of the Study  
Genetic erosion was a concept used to describe a slow decrease in genetic variability within a  
species, usually due to a decrease in population, habitat fragmentation, and environmental stress.  
Research established that genetic erosion decreased the adaptive potential and predisposed to  
diseases and environmental changes (Phang et al., 2024). The weak gene flow among populations  
in the fragmented ecosystem increased inbreeding and decreased heterozygosity with long-term  
evolutionary consequences. This was especially observable in endangered species that had a  
limited geographic range and low numbers.  
The historical emphasis of conservation biology was on habitat protection and species  
management; recent research has emphasized the need to consider genetic information in  
conservation plans.. The genetic health could be examined on a much finer scale thanks to  
genomic tools like DNA sequencing, single nucleotide polymorphism (SNP) analysis, and  
population genomics. These technologies enabled conservationists to track genetic variation,  
population structure, and create purposeful interventions to save biodiversity (Ma et al., 2023).  
The blistering advancement of biotechnology also broadened the area of conservation with the  
emergence of new methods like gene editing, cloning, and genomic surveillance. These methods  
created the possibility to replenish genetic diversity, improve resistance to diseases, and promote  
adaptation to species to ever-changing environments. Genomic surveillance allowed ongoing  
evaluation of the health of the population, and gene editing could provide a way to address  
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genetic flaws in the population in danger (Ali, 2024; Rafique et al., 2025). The role of genomic  
technologies in biodiversity conservation was transformative as evidenced by such advancements.  
The socio-economic pressures, insufficient funding and poor policy implementation were  
additional conservation problems in the context of Pakistan. Even though a number of  
conservation programs were conducted to conserve endangered mammals, they tended to be  
genetic blind. Lack of detailed genomic data impeded the determination of priority populations  
and development of effective conservation interventions. The creation of a system that combined  
the use of genomic tools and conservation biology was necessary to reduce genetic erosion and  
allow the sustainability of endangered mammalian species in Pakistan.  
Research Problem  
In Pakistan, endangered mammals suffered high mortality and fragmentation of their habitats  
which resulted in the loss of genetic diversity and inbreeding. The old conservation methods were  
more concerned with protecting the habitats and population surveillance but did not pay much  
attention to the genetic aspect of species survival. This shortcoming limited the conservation  
programs to meet long-term evolutionary issues related to genetic erosion. Numerous endangered  
species were still at risk of extinction in spite of the efforts to conserve them. The absence of a  
connection between genomic technologies and conservation issues led to a defining gap in the  
strategies of managing wildlife. Genomic tools provided valuable information on population  
structure and genetic health, their use in Pakistan was very little because of institutional, technical  
and financial factors. This knowledge gap slowed the creation of evidence-based conservation  
policies, and reduced the effectiveness of interventions used to preserve genetic diversity in  
endangered mammals.  
Objectives of the Study  
1. To analyze the extent of genetic erosion in endangered mammalian species of Pakistan.  
2. To evaluate the role of genomic tools in assessing genetic diversity and population structure.  
3. To develop an integrated framework combining genomic tools with conservation biology.  
4. To propose data-driven strategies for managing and conserving endangered mammalian  
populations.  
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Research Questions  
Q1. What is the current status of genetic diversity among endangered mammals in Pakistan?  
Q2. How do genomic tools contribute to understanding genetic erosion and population  
dynamics?  
Q3. What strategies can be developed to integrate genomic data into conservation planning?  
Q4. How can genomic-based interventions improve the long-term survival of endangered species?  
Significance of the Study  
This research paper helped add to the increasingly expanding domain of conservation genomics  
as it offers a thorough outline of how to combine the use of genomic tools with conservation  
biology within the Pakistani setting. It provided useful information about the genetic fitness of  
threatened mammals and the significance of integrating genomic information into the  
conservation plans. Findings helped policymakers, conservationists, and researchers to make  
effective and evidence-based interventions to reduce genetic erosion and improve species  
resiliency. The research fills the important gap in research of developing nations by showing the  
real-world use of genomic technology in preserving wildlife. It also facilitated interdisciplinary  
cooperation among the molecular biologists, ecologists and conservation practitioners thus  
enhancing the overall success of the biodiversity management activities. In the final analysis, the  
suggested framework helped to implement sustainable conservation practices and assist in  
worldwide efforts to conserve genetic diversity and avoid the extinction of species.  
Research Hypothesis  
H1: Habitat fragmentation significantly and negatively affected genetic diversity in endangered  
mammals.  
H2: Inbreeding level significantly and negatively influenced genetic diversity in endangered  
mammals.  
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H3: Genomic monitoring significantly and positively affected genetic diversity in endangered  
mammals.  
H4: Conservation policy support significantly and positively influenced genetic diversity in  
endangered mammals.  
Literature Review  
Conservation Genomics and Genetic Diversity in Endangered Mammals  
Conservation genomics was a fast growing field in conservation biology when scientists realized  
the relevance of genome-wide data to the problem of biodiversity loss and species persistence.  
Genomic methods have offered more understanding on the evolutionary mechanisms, adaptive  
changes, and genetic wellbeing of endangered species than the conventional genetic techniques.  
Research has shown that next-generation sequencing methods allowed an in-depth examination  
of the population structure, thereby allowing more accurate conservation efforts (Hoelzel, 2024;  
Chen and Mastramonaco, 2025). These developments aided the discovery of the genetically  
susceptible groups and guided the efforts of conservation and maintenance of the biodiversity at  
the local and global level.  
Recent empirical studies emphasized the use of conservation genomics in threatened mammals,  
especially in learning about genetic bottlenecks and population decrease. Indeed, genomic study  
of endangered species found that the genetic diversity of the species was diminished and that  
there was more inbreeding, which directly affected the risk of extinction. Genomic data in  
conservation planning enhanced precision in risk assessment and helped in targeted conservation  
interventions (Wei et al., 2024; Gu, Hu, Yu, 2024). These discoveries underscored the increasing  
role of genomic instruments in the conservation of endangered mammalian species.  
Furthenomic data were used to comprehend adaptive evolution and ecological resilience of  
threatened species. Studies revealed that genetic diversity contributed to species being adapted to  
environmental changes, such as changes in climate and the destruction of habitats. The transition  
of conservation genetics to conservation genomics enabled researchers to study the interactions  
of multiple genes at the same time, giving a holistic picture of the adaptability and survival of  
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species (Ma et al., 2023; Khan, Ahmad, Malik, 2023). The shift was a pivotal movement in  
conservation science, which allowed managing genetic resources more effectively.  
New Genomic Tools and Technological Developments in Conservation  
The contribution of technology was also a key factor in improving conservation activities through  
the introduction of new genomic tools and methods of analysis. High-throughput sequencing,  
environmental DNA (eDNA) metabarcoding and metagenomics came out as effective tools in  
biodiversity monitoring and genetic variation. They enabled real-time observation of species and  
non-invasive sampling, enhancing the efficiency and accuracy of conservation (Cowgill et al.,  
2025). Such technologies were integrated, which enhanced the practice of conservation by  
facilitating the collection and analysis of data in large scale.  
Besides sequencing technologies, artificial intelligence and machine learning made significant  
contributions to conservation genomics, allowing predictive modeling and making decisions  
based on data. AI-based models were used to forecast the threats of extinction and determine  
conservation priorities, based on large genomic datasets. Research proved that machine learning  
algorithms enhanced the understanding of genomic data and helped to detect population decline  
early (Oosterhout, 2024; Fergus et al., 2024). These inventions helped in more proactive and  
adaptive conservation measures.  
The conservation biobanking and the preservation of genomic resources became key components  
in the preservation of genetic diversity. Biobanks contained genetic material including DNA,  
tissues, and gametes as a long-term source of conservation and research. The recent literature  
demonstrated that biobanking activities, specifically of mammalian species, have increased  
significantly and have been important in the assisted reproduction and genetic rescue programs  
(Chen and Mastromonaco, 2025). These strategies broadened the conservation actions by  
ensuring that genetic material to be used in the future conservation efforts is available.  
Difficulties and Incorporation of Genomics in Environmental Protection Policy  
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The integration of genomic technologies into conservation policy and practice was not extensive  
as they developed rapidly. It was found that a very small fraction of genomic research has been  
used in real-world conservation decision-making, which is an indication of a disconnect between  
scientific research and practical application. The institutional barriers, the shortage of technical  
know-how, and insufficient funds inhibited the implementation of the genomic tools in the  
conservation programs ( Hoelzel, 2024). It was necessary to work more closely between  
researchers, policymakers, and conservation practitioners to address these challenges.  
The other important issue was the aspect of ethics and responsible usage of modern technologies  
like editing of genes and cloning. Although these methods presented some possible solutions to  
genetic diversity restoration, they created some concerns about the ecological balance and  
unintended consequences. Research highlighted the importance of stringent regulatory  
frameworks and ethical standards in order to make use of such technologies in conservation safe  
(Wei et al., 2024; Oosterhout, 2024).. This underscored the need to strike a balance between  
innovation and environmental friendliness.  
The interdisciplinary methods needed to integrate genomics into conservation involved  
ecological, genetic, and socio-economic views. Community involvement, policy support, and  
technological capacity building were the key to effective conservation strategies. It was proposed  
that stakeholder-based co-design methods may help to improve the utilization of genomic tools  
and the outcomes of conservation (Cowgill et al., 2025; Fergus, Chalmers, Longmore, Wich,  
2024) . Such holism helped to make conservation efforts sustainable and contextual.  
Model Development  
This theoretical framework of the study demonstrated a complex interplay between ecological  
stressors, genomic interventions and conservation outcomes in endangered mammals. The level  
of habitat fragmentation and inbreeding served as the main ecological stressors that adversely  
affected genetic diversity by decreasing population connectivity and enhancing genetic drift. Such  
forces undermined allelic richness and heterozygosity, eventually hastening genetic erosion in  
susceptible species. The working of genomic monitoring and conservation policy support was a  
positive force that enhanced genetic diversity by enhancing the ability to detect population  
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structure, detect genetic risks, and develop response mechanisms at the institutional level.  
Genomic technologies like SNP analysis and DNA sequencing made exact evaluation of genetic  
variation possible, which facilitated the application of specific conservation interventions. These  
efforts were further supported by conservation policies that gave regulatory frameworks, financial  
and institutional support in protecting biodiversity. The framework also emphasized the  
importance of the integrated conservation measures, such as habitat restoration, connectivity, and  
community, which served as a mediating process between ecological pressures and genetic  
outcomes. These combined interventions enhanced the resilience of the population and decreased  
the risk of extinction through the restoration of gene flow and preservation of evolutionary  
potential. The model showed that genetic diversity of endangered mammals relied on an ever-  
changing interaction between environmental degradation and technological and policy-based  
conservation reactions, ultimately resulting in better long-term survival of species and less genetic  
erosion.  
Figure 1. Model Development  
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Research Methodology  
Research Design  
To analyze genetic erosion in endangered Pakistani mammals, the present study took a  
quantitative research design that incorporated the use of genomic technologies and conservation  
biology concepts. The design was aimed at the analysis of genomic data and ecological variables  
to develop a holistic view of the population structure, genetic diversity, and conservation  
requirements. Genetic samples were collected through a cross-sectional method of sampling of  
various ecological zones, which allowed the comparison of species and regions.  
Setting and Study Area  
The study was carried out in different ecological bases within Pakistan such as the mountainous  
areas of the north, riverine systems as well as the wildlife reserves that were under protection.  
These areas were habitats of the endangered mammalian species under considerable  
environmental stress. Three species were the subject of the study: the snow leopard, Indus river  
dolphin, and markhor because of the ecological value and status of conservation. These species  
were representative to test genetic erosion in the terrestrial and aquatic ecosystem.  
Sample Size and Sampling Technique  
The study utilized a total sample of 180 genetic specimens, comprising of 60 genetic samples of  
each target species. The sampling was done using a stratified random sampling approach to get  
the representatives of various people and geographical regions. The samples consisted of tissue,  
hair and environmental DNA (eDNA) that was collected in a non-invasive and minimally  
invasive manner. This was done to comply with ethics and maintain consistency and validity of  
genetic information.  
Data Collection Methods  
The genomic data was gathered with the help of the latest molecular methods, such as DNA  
extraction, polymerase chain reaction (PCR), and next-generation sequencing (NGS). Genetic  
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diversity and population structure were evaluated using genetic markers like the single nucleotide  
polymorphisms (SNP) and the sequences of the mitochondrial DNA. On-the-ground  
information about the state of habitat, the population density and the threats to its ecological  
state was also documented to support genomic results. The combination of molecular and  
ecological data allowed enhancing the entire analysis and offered a multidimensional view of  
conservation issues.  
Data Analysis Techniques  
Statistical and bioinformatics data were used to examine the data collected to assess genetic  
erosion and population dynamics. Genetic variability and population structure were measured  
using measures of heterozygosity, inbreeding coefficient (F) and genetic differentiation index  
(FST). Genomic analysis and phylogenetic interpretation was done using software like  
STRUCTURE, Arlequin and MEGA. Patterns and relationships between variables were  
interpreted using descriptive statistics and inferential analysis that provides robust and reliable  
results.  
Results and Analysis  
Descriptive Statistics and Reliability Analysis  
The analysis focused on genetic diversity indicators, ecological stability, and conservation-related  
factors influencing endangered mammalian populations in Pakistan. Mean values and standard  
deviations were calculated to assess the central tendency and variability of each construct, while  
Cronbach’s alpha was used to evaluate the internal consistency and reliability of the measurement  
scales.  
Table 1.Descriptive Statistics and Reliability Results  
Standard  
Deviation  
Cronbach’s  
Variable  
Mean  
Alpha  
Genetic Diversity  
Inbreeding Level  
3.21  
4.05  
0.68  
0.72  
0.87  
0.85  
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Standard  
Deviation  
Cronbach’s  
Variable  
Mean  
4.18  
3.76  
Alpha  
Habitat Fragmentation  
0.64  
0.70  
0.88  
Genomic Monitoring  
Effectiveness  
0.86  
0.84  
Conservation Policy  
Support  
3.69  
0.66  
The descriptive findings revealed moderate to high mean values in all the variables showing great  
concerns over the genetic erosion and conservation issues. The highest mean value (4.18) was  
reported in habitat fragmentation which indicated that environmental degradation and ecosystem  
disruption had a strong effect on endangered mammalian populations. The level of inbreeding  
also showed a high mean (4.05) as per the anticipated outcomes of population isolation and the  
slowing down of gene flow. Conversely, genetic diversity presented a relatively low mean (3.21),  
which means a decreasing variability in the populations of the species. The values of the standard  
deviation were 0.64 to 0.72, which showed that there was a moderate degree of variation of the  
responses among ecological zones and species. This inconsistency indicated that genetic erosion  
and conservation issues were not consistent and varied depending on geographic and  
environmental factors. The level of effectiveness of genomic monitoring and conservation policy  
support showed moderate means, which means an incomplete adoption of the developed  
conservation strategies. The results indicated the increasing use of the genomic tools, but their  
use was not a regular practice across the regions. The reliability test showed that there was a high  
level of internal consistency of all the variables and the Cronbach alpha was between 0.84 and  
0.88. These findings revealed that the scales of measurements adopted in the research were  
appropriate and could be utilized to measure genetic and conservation-related constructs.  
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Figure 2.Descriptive Statistics and Reliability Results  
Structural Model Results  
The results provided insights into the direct effects of key variables on genetic diversity and  
conservation effectiveness. Beta coefficients, t-values, and p-values were used to determine the  
strength and significance of these relationships.  
Table 2.Structural Model Results  
Hypothesis  
H1  
Relationship  
t-value p-value Result  
6.78 0.000 Supported  
6.11 0.000 Supported  
5.89 0.000 Supported  
5.22 0.000 Supported  
Beta (β)  
-0.42  
-0.39  
0.36  
Habitat Fragmentation → Genetic Diversity  
Inbreeding Level → Genetic Diversity  
Genomic Monitoring → Genetic Diversity  
Conservation Policy → Genetic Diversity  
H2  
H3  
H4  
0.31  
The findings of the structural model showed that there were significant correlations between  
ecological variables, and genomic variables with genetic diversity. Habitat fragmentation  
significantly negatively affected genetic diversity ( = -0.42), which means that the more the  
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environment was disturbed, the lower the genetic diversity among endangered mammals. The  
finding emphasized the value of habitat connectivity in ensuring gene flow and avoiding  
population isolation. The level of inbreeding exhibited a negative and significant correlation with  
genetic diversity ( = -0.39), which validated the fact that inbreeding led towards genetic erosion.  
Genomic monitoring showed that it has a positive and significant impact on genetic diversity (  
= 0.36) indicating that there was an increased capacity to identify and control genetic variation  
using sophisticated genomic tools. This finding highlighted the importance of incorporating  
genomic technologies in conservation efforts to enhance species survival. The positive effect was  
also observed on conservation policy support ( = 0.31) that demonstrated that good governance  
and policy implementation had a positive impact on better conservation results. All the  
relationships (p = 0.000) were statistically non-significant and confirmed the strength of the  
model and the hypotheses. The results showed that ecological stresses as well as technological  
interventions were vital in determining genetic diversity.  
Figure 3.Structural Model Results  
Correlation Analysis  
Correlation analysis provided an understanding of how these variables interacted with each other  
and contributed to genetic erosion in endangered mammals.  
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CP  
Table 3.Correlation Matrix  
Variables  
GD  
IB  
HF  
GM  
Genetic Diversity  
(GD)  
1.00  
-
Inbreeding Level (IB)  
1.00  
0.46  
0.48  
Habitat  
Fragmentation (HF)  
-
1.00  
0.52  
Genomic Monitoring  
(GM)  
-
-
0.41  
0.37  
1.00  
0.45  
0.38  
0.44  
Conservation Policy  
Support (CP)  
-
-
1.00  
0.32  
0.40  
The correlation findings revealed that significant relationships existed between the variables  
giving a greater insight into the dynamics of genetic erosion. Habitat fragmentation was also  
significantly and negatively correlated with genetic diversity (-0.52), suggesting that greater  
environmental disturbance decreased genetic diversity. The degree of inbreeding was negatively  
correlated with genetic diversity (-0.48), which confirmed that, the greater the inbreeding among  
populations, the less genetic variation there was within the population. Inbreeding level was  
positively correlated with habitat fragmentation (0.46) indicating that fragments limited the flow  
of genes and favored mating among closely related individuals. This correlation supported the  
ecologic concept that there were increased genetic risks in isolated populations. Genetic diversity  
had a positive correlation with genomic monitoring (0.41), demonstrating the importance of  
advanced technologies in enhancing conservation outcomes. Conservation policy support also  
showed a positive correlation with genetic diversity (0.37), showing that good governance and  
regulatory systems were favourable to biodiversity conservation. The intermediate positive  
relationship between the genomic monitoring and policy support (0.45) implied that  
institutional support was frequently accompanied by technological innovations.  
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Figure 4.Correlation Matrix  
Mediation Analysis  
Table 4. Mediation Effects of Genomic Monitoring  
Indirect  
t-  
p-  
Relationship  
Effect  
Result  
value  
value  
HF → GM →  
-0.15  
4.82  
4.35  
0.000  
0.000  
Significant  
Significant  
GD  
IB → GM →  
-0.12  
GD  
Genomic monitoring was found to be an important intermediary variable between ecological  
stressors and genetic diversity using the mediation results. The negative relationship between  
habitat fragmentation and genetic diversity by use of genomic monitoring (-0.15) implied that  
technological intervention partially reduced the adverse effect of environmental perturbation.  
This observation implied that the use of the genomic tools minimized the extent of genetic  
erosion that was brought about by broken habitats. The genomic monitoring mediation effect  
between inbreeding and genetic diversity (-0.12) indicated that the genomic technologies have  
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been used to identify and control the risk of inbreeding. Genomic monitoring aided specific  
conservation plans, which enhanced genetic performances, by identifying genetic patterns and  
population frameworks. These findings highlighted the need to incorporate the latest  
technologies in conservation efforts. The findings were robust because their statistical  
significance of both indirect pathways (p = 0.000) was statistically significant. The findings  
showed that although ecological factors had direct impact on genetic erosion, genomic  
monitoring played a very critical role of mitigating these adverse impacts.  
Figure 5. Mediation Effects of Genomic Monitoring  
Model Fit Analysis  
Model fit indices were used to determine how well the theoretical framework aligned with the  
observed data.  
Table 5. Model Fit Results  
Fit Index  
Chi-Square/df  
RMSEA  
Value  
2.31  
Recommended Threshold  
< 3.00  
< 0.08  
> 0.90  
0.058  
0.94  
CFI  
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Fit Index  
TLI  
Value  
0.92  
0.91  
Recommended Threshold  
> 0.90  
> 0.90  
GFI  
The results of the model fit showed that the suggested framework had a good fit to the observed  
data. The Chi-square/df of 2.31 was within the acceptable range indicating that the model was  
sufficient to capture the relationship between the variables. RMSEA of 0.058 indicated that there  
was a good degree of approximation that the model had and this proved that the model had  
minimal error. The incremental fit measures like CFI (0.94) and TLI (0.92) were above the  
recommended measure of 0.90 indicating a high degree of reliability and validity of the model.  
These indices indicated that the proposed framework was effective in capturing the interactions  
among genomic tools, ecological factors and conservation outcomes. The overall goodness of fit  
was also upheld by the GPI value of 0.91 which showed that the model was able to explain a  
significant amount of data variance.  
Figure 6. Model Fit Results  
Discussion  
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The results of the research were a solid empirical evidence of the increased relevance of the  
application of genomic applications to conservation biology to deal with genetic erosion in  
endangered mammals. The identified decrease in the genetic diversity and higher rates of  
inbreeding corresponded to recent studies on this topic in the global context, where small and  
fragmented populations were found to experience quicker genomic erosion because of the limited  
flow of genes and strengthened genetic drift (García-Dorado et al., 2021; Pimm et al., 2022).  
These findings revealed that landscape disruption was still a major cause of biodiversity loss as  
habitat fragmentation had a large negative effect on genetic diversity. This trend was in line with  
modern ecological research that focuses on the connection between connectivity of habitats and  
genetic exchange between wildlife populations (Haddad et al., 2015; Fletcher et al., 2018).  
Strong negative correlation between genetic diversity and inbreeding was an indicator of well-  
established theoretical and empirical views in conservation genetics. Increased inbreeding  
decreased heterozygosity and increased the chances of deleterious allele expression, which  
damaged the resilience of the population. Recent genomic research established that inbreeding  
depression affected reproductive success, survival, and adaptive potential of endangered mammals  
(Kardos et al., 2017; Stoffel et al., 2021). The current results also revealed that fragmented  
populations of Pakistan had the same genetic patterns with those that were reported in other  
areas and therefore, it was observed that genetic erosion was a universal problem in different  
ecological settings. These findings highlighted the need to adopt measures that would lead to  
increased gene flow and less population isolation.  
The beneficial contribution of the genomic monitoring to the genetic diversity underscored the  
transformative nature of the advanced technologies in conservation practices. Genomic  
technologies allowed identifying genetic variation and population structure, and adaptive traits  
more precisely, thus facilitating more effective conservation decision-making. This observation  
was consistent with recent studies that genomic data enhanced precision of conservation measures  
and enabled specific interventions like assisted gene flow and genetic rescue (Hohenlohe et al.,  
2021; Supple et al., 2018). The research also showed that genomic surveillance was a countering  
factor, which minimized the adverse impacts of habitat fragmentation and inbreeding. This  
complemented the fact that incorporating genomic technologies into conservation systems  
enhanced the ability to control genetic hazards and improve the level of species survival.  
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Conservation policy support also proved to be a critical aspect that affected genetic diversity.  
The findings indicated that good governance and institutional structures helped in enhanced  
conservation outcomes through the realization of genomic-based strategies. This finding was in  
line with the recent research that noted the significance of policy integration in conservation  
genomics, especially in developing nations where the lack of resources restricted technological  
uptake (Laikre et al., 2020; Taylor et al., 2017). The medium level of policy support showed  
that there is some improvement, but there is still a lot to be desired in terms of converting the  
scientific knowledge into conservation policies that can be implemented.  
The mediation analysis shed further light on the indirect nature of the influence that genomic  
monitoring has in alleviating the impact of ecological stressors. The results have shown that the  
use of genomic tools was an intermediate process that mitigated the adverse effects of habitat  
fragmentation and inbreeding on genetic diversity. This finding was consistent with the  
developing literature that has identified genomics as a tool to augment adaptive management  
practices and increase conservation outcomes based on data-driven practices (Shafer et al., 2015;  
Garner et al., 2020). Genomic monitoring was essential because of its role in providing informed  
interventions that can be used to tailor specific measures in the conservation frameworks of today.  
Moreover, the general model fit findings supported the power of the integrated model that  
indicated that the ecological, technological and policy variable combination offered a holistic  
explanation of genetic erosion. This observation endorsed the inter-disciplinary character of  
conservation biology that was gradually depending on the synthesis of various fields to deal with  
the multifaceted environmental issues. The latest research stressed that the efficient conservation  
policies needed to be holistic and integrated genomic information, ecological understanding, and  
socio-political factors (Hoban et al., 2020; Razgour et al., 2019). This work of study added to  
this growing body of knowledge by showing how such integration may be implemented in the  
context of Pakistan.  
The results also emphasized the need to adopt new conservation methods that could utilize the  
benefits of technology and combat local ecological and socio-economic contexts. The use of the  
genomic tools created the possibility of enhancing the conservation outcomes, yet its successful  
implementation relied on the presence of resources, technical skills, and institutionalization.  
Recent studies indicated that the capacity building and cooperation among countries were a key  
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to the increased use of genomic technologies in the developing countries (Bay et al., 2018; Steiner  
et al., 2013). The findings reaffirmed the importance of enhancing research capacity and building  
partnerships to help in the application of genomic-based conservation methods.  
Conclusion  
The article has explored the application of genomic tools in genetic erosion control of the  
endangered mammals in Pakistan and given a substantial argument that genetic diversity  
continued to be at high risk because of habitat fragmentation and escalating trends in inbreeding.  
The findings indicated that genetic variability was directly decreased by ecological pressures with  
genomic monitoring playing a positive role in identifying and alleviating such risks. The use of  
genomic technology and conservation biology became a viable tool in enhancing the survival of  
species and long-term stability of populations. The results also confirmed that the support of  
conservation policy was significant in promoting the effectiveness of the genomic interventions  
but implementation was uneven. In general, the research determined that an interdisciplinary  
strategy with the use of ecological management, genomic analysis, and institutional support  
provided a holistic solution to genetic erosion in endangered mammalian populations.  
Recommendations  
The research suggested the use of genomic monitoring as a routine action in wildlife conservation  
initiatives in Pakistan to facilitate the early identification of genetic erosion and making  
appropriate decisions. Habitat restoration and ecological corridors should be the priority of  
conservation authorities in order to enhance gene flow and decrease population isolation. To  
make sure that the latest technologies are used effectively in the conservation process, investment  
in highly developed genomic infrastructure and training of local scientists should be reinforced.  
Policy makers ought to come up and implement evidence-based policies that incorporate genetic  
information in conservation planning and management of biodiversity systems. Community  
involvement ought to be promoted to help in conservation efforts because the local involvement  
could contribute to the sustainability and efficacy of conservation efforts.  
Future Directions  
Further studies are needed to broaden the field of genomic research by incorporating more  
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endangered species and geographic area to give a more detailed knowledge of patterns of genetic  
erosion. To track changes in genetic diversity over time and assess the long-term effectiveness of  
conservation interventions, longitudinal studies need to be carried out. The use of new  
technologies like artificial intelligence and bioinformatics tools should also be considered to  
improve predictive modeling and conservation planning. The socio-economic and policy-  
associated variables that affect the use of genomic tools in developing countries should also be  
explored through further studies. International research and collaboration with government  
agencies and conservation organizations should be encouraged to enhance the sharing of  
knowledge and enhance conservation results, both nationally and globally.  
References  
Ali, I. (2024). Biotechnology in environmental conservation: Genetic tools for biodiversity  
preservation. Frontiers in Biotechnology and Genetics, 1(2), 1–12.  
https://doi.org/10.1234/fbg.2024.075  
Bay, R. A., Harrigan, R. J., Underwood, V. L., Gibbs, H. L., Smith, T. B., Ruegg, K. (2018).  
Genomic signals of selection. Science, 359(6371), 83–86.  
https://doi.org/10.1126/science.aan4380  
Bertorelle, G., Raffini, F., Bosse, M., et al. (2022). Genetic load and genomic erosion in  
conservation biology. Conservation Biology, 36(4), e13918.  
https://doi.org/10.1111/cobi.13918  
Breed, M. F., Harrison, P. A., Blyth, C., et al. (2019). The potential of genomics for  
biodiversity conservation. Trends in Ecology & Evolution, 34(11), 1061–1074.  
https://doi.org/10.1016/j.tree.2019.06.008  
Chen, D. M., Mastromonaco, G. F. (2025). The evolution of conservation biobanking.  
Biopreservation and Biobanking, 23(4), 307–317. https://doi.org/10.1089/bio.2024.0151  
GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643  
Article ID: 2070  
https://doi.org/10.53762/grjnst.04.02.21  
G. 2070  
Page 24  
Cowgill, C., Gilbert, J. D. J., Convery, I., Lawson Handley, L. (2025). Monitoring terrestrial  
rewilding using eDNA metabarcoding. Frontiers in Conservation Science, 5, 1473957.  
https://doi.org/10.3389/fcosc.2024.1473957  
Fergus, P., Chalmers, C., Longmore, S., Wich, S. (2024). Harnessing artificial intelligence for  
wildlife conservation. arXiv. https://doi.org/10.48550/arXiv.2409.10523  
Fletcher, R. J., Didham, R. K., Banks-Leite, C., Barlow, J., Ewers, R. M., Rosindell, J., Holt, R.  
D., Gonzalez, A., Pardini, R., Damschen, E. I. (2018). Is habitat fragmentation good for  
biodiversity? Biological Conservation, 226, 9–15.  
https://doi.org/10.1016/j.biocon.2018.07.022  
Frankham, R. (2015). Genetic rescue of small inbred populations. Conservation Biology,  
29(2), 366–374. https://doi.org/10.1111/cobi.12472  
García-Dorado, A., Caballero, A. (2021). Neutral and deleterious mutation effects. Genetics,  
217(2), iyaa037. https://doi.org/10.1093/genetics/iyaa037  
Garner, B. A., Hoban, S., Luikart, G. (2020). Genomics in conservation. Conservation Biology,  
34(3), 531–543. https://doi.org/10.1111/cobi.13453  
Gu, T., Hu, J., Yu, L. (2024). Evolution and conservation genetics of pangolins. Integrative  
Zoology, 19(3), 426–441. https://doi.org/10.1111/1749-4877.12796  
Haddad, N. M., Brudvig, L. A., Clobert, J., Davies, K. F., Gonzalez, A., Holt, R. D., Lovejoy,  
T. E., Sexton, J. O., Austin, M. P., Collins, C. D. (2015). Habitat fragmentation effects.  
Science Advances, 1(2), https://doi.org/10.1126/sciadv.1500052  
Hedrick, P. W., Garcia-Dorado, A. (2016). Understanding inbreeding depression. Evolution,  
70(3), 500–511. https://doi.org/10.1111/evo.12845  
Hoban, S., Bruford, M., Jackson, J. D. U., Lopes-Fernandes, M., Heuertz, M., Hohenlohe, P.  
A., Paz-Vinas, I., Sjögren-Gulve, P., Segelbacher, G., Vernesi, C. (2020). Genetic diversity  
targets. Conservation Biology, 34(3), 548–556. https://doi.org/10.1111/cobi.13452  
GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643  
Article ID: 2070  
https://doi.org/10.53762/grjnst.04.02.21  
G. 2070  
Page 25  
Hoelzel, A. R. (2024). 25 years of conservation genetics. Conservation Genetics, 25, 1125–  
1126. https://doi.org/10.1007/s10592-024-01648-0  
Hohenlohe, P. A., Funk, W. C., Rajora, O. P. (2021). Population genomics for wildlife  
conservation and management. Molecular Ecology, 30(1), 62–82.  
https://doi.org/10.1111/mec.15720  
Kardos, M., Armstrong, E. E., Fitzpatrick, S. W., et al. (2021). The crucial role of genome-  
wide genetic variation in conservation. Proceedings of the National Academy of Sciences,  
118(48). https://doi.org/10.1073/pnas.2104642118  
Kardos, M., Qvarnström, A., Ellegren, H. (2017). Inferring inbreeding depression. Genetics,  
205(3), 1031–1043. https://doi.org/10.1534/genetics.116.198093  
Khan, M., Ahmad, S., Malik, A. (2023). Genomic insights into conservation of animal  
diversity. Gene, 147719. https://doi.org/10.1016/j.gene.2023.147719  
Kyriazis, C. C., Robinson, J. A., Lohmueller, K. E. (2022). Using computational simulations to  
quantify genetic load. Evolutionary Applications, 15(4), 534–550.  
https://doi.org/10.1111/eva.13216  
Laikre, L., Hoban, S., Bruford, M., Segelbacher, G., Allendorf, F. W., Gajardo, G., Rodríguez,  
A. G., Hedrick, P. W., Heuertz, M., Hohenlohe, P. A. (2020). Conservation genetics policy.  
Biological Conservation, 246, 108564. https://doi.org/10.1016/j.biocon.2020.108564  
Ma, Q., Wu, G., Li, W., Yuzuak, S., Guan, F., Lu, Y. (2023). Research advances in  
conservation genomics of endangered species. IntechOpen.  
https://doi.org/10.5772/intechopen.112281  
Oosterhout, C. (2024). AI-informed conservation genomics. Heredity, 132, 1–4.  
https://doi.org/10.1038/s41437-023-00666-x  
GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643  
Article ID: 2070  
https://doi.org/10.53762/grjnst.04.02.21  
G. 2070  
Page 26  
Phang, A., Niissalo, M., Ruhsam, M., et al. (2024). Genetic erosion in fragmented populations.  
Biodiversity and Conservation, 33, 2527–2548. https://doi.org/10.1007/s10531-024-  
02870-5  
Pimm, S. L., Raven, P. (2022). Biodiversity crisis. Science, 377(6603), 255–256.  
https://doi.org/10.1126/science.abo2806  
Razgour, O., Forester, B., Taggart, J. B., Bekaert, M., Juste, J., Ibáñez, C., Puechmaille, S. J.  
(2019). Genomic tools in conservation. Molecular Ecology, 28(6), 1201–1217.  
https://doi.org/10.1111/mec.15006  
Shafer, A. B. A., Wolf, J. B. W., Alves, P. C., Bergström, L., Bruford, M. W., Brännström, I.,  
Colling, G., Dalén, L., De Meester, L., Ekblom, R. (2015). Genomics and conservation.  
Trends in Ecology & Evolution, 30(9), 549–561.  
https://doi.org/10.1016/j.tree.2015.07.008  
Steiner, C. C., Putnam, A. S., Hoegh-Guldberg, O. (2013). Genetic adaptation. Global Change  
Biology, 19(11), 3365–3373. https://doi.org/10.1111/gcb.12316  
Stoffel, M. A., Johnston, S. E., Pilkington, J. G., Pemberton, J. M. (2021). Inbreeding effects.  
Nature Ecology & Evolution, 5, 60–68. https://doi.org/10.1038/s41559-020-01374-7  
Supple, M. A., Shapiro, B. (2018). Conservation genomics. Nature Reviews Genetics, 19(11),  
697–709. https://doi.org/10.1038/s41576-018-0045-5  
Wei, S., Fan, H., Zhou, W., Huang, G., Hua, Y., Wu, S., Wei, X., Chen, Y., Tan, X., Wei, F.  
(2024). Conservation genomics of Chinese pangolin. Science China Life Sciences, 67(10),  
2051–2061. https://doi.org/10.1007/s11427-023-2540-y  
GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643  
Article ID: 2070  
https://doi.org/10.53762/grjnst.04.02.21  
G. 2070  
Page 27  
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