Abstract:
Biodiversity
in
Uzbekistan, encompassing deserts, steppes,
riparian forests, wetlands, and mountain
ecosystems, is increasingly threatened by
climate
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change, water scarcity, land
degradation, and unsustainable land use.
This study evaluates an integrated
conservation framework that combines
digital ecology tools (remote sensing, GIS,
artificial
intelligence,
and predictive
modeling) with nature-based solutions
(NbS),
including
habitat
restoration,
ecological corridors, wetland rehabilitation,
and community participation. Between 2022
and 2025, twelve pilot sites across five
ecological regions were monitored. Spatial
analysis identified 174 biodiversity hotspots,
38 critical habitats outside protected areas,
and 22 high-risk degradation zones. AI
assisted monitoring achieved 93% accuracy
across
45
target
species.
NbS
implementation resulted in a 28–44%
increase in vegetation cover, a 22%
improvement in soil moisture, and the
return of endangered species in 67% of restored sites. Predictive models indicate
that without intervention, 24% of habitats
may lose suitability by 2040, while
integrated digital-NbS strategies could
preserve over 80%. The results confirm that
combining digital technologies with NbS
provides an effective, scalable, and climate
resilient
approach
to
conservation in Uzbekistan.
