Data-Driven Insights into Human–Gaur Conflicts: Spatiotemporal Trends and Risk Mapping Across Tamil Nadu, India
Abstract
Human–wildlife
conflict
(HWC)
is
one
of
the
most
pressing
conservation
challenges,
particularly
in
shared
landscapes
where
humans
and
wildlife
are
adversely
affected.
Despite
various
mitigation
efforts
globally,
frequency
HWC
continues
to
rise.
Among
conflict-prone
species,
Indian
gaur
(Bos
gaurus)
has
increasingly
been
involved
such
interactions
across
southern
India.
To
support
development
long-term
strategies
for
Human–Gaur
Conflict
(HGC),
we
conducted
a
comprehensive
study
using
data
collected
from
compensation
records
48
forest
divisions
Tamil
Nadu
between
2016
2024.
We
analyzed
spatial
temporal
trends,
predicted
risk
zones
ensemble
modeling,
identified
key
drivers
influencing
HGC.
Our
findings
reveal
that
intensity
was
highest
Nilgiri
division,
followed
by
Dharmapuri
Kodaikanal.
Crop
damage
predominant
type,
human
injuries,
with
incident
peaks
observed
during
December
March.
Elevation
emerged
as
influential
predictor
models,
clear
positive
correlation
showing
increased
rising
elevation.
The
model
also
18,335
km²
state
falls
under
zones,
accounting
approximately
14.1%
Nadu's
total
geographical
area.
This
provides
critical
insights
into
ecology
HGC
highlights
utility
predictive
modeling
identifying
high-risk
zones.
outcomes
can
inform
conservationists
managers
designing
implementing
proactive
measures,
especially
areas
have
high
likelihood
future
conflict.
Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown
Published: May 15, 2025
Language: Английский