Livestock
Geo-­‐Wiki:
Maps
for
a
safer
and
more
equitable
livestock
sector
Timothy
Robinson,
Catherine
Pfeifer,
William
Wint,
Simon
Hay,
Thomas
van
Boeckel,
Giulia
Conchedda,
Giuseppina
Cinardi,
Jeroen
Dijkman,
Pierre
Gerber,
Theun
Vellinger,
Steffen
Fritz,
MarIna
Duerauer,
Gaëlle
Nicolas
and
Marius
Gilbert
Introduc7on
Global
demand
for
meat,
milk
and
eggs
is
driving
livestock
sector
growth
and
transforma7on.
Whilst
this
provides
many
economic
opportuni7es,
and
promises
to
provide
affordable
animal
source
foods
to
many
of
the
world’s
undernourished
poor,
it
comes
with
environmental,
social
and
public
health
risks
if
not
managed
carefully.
If
policymakers
are
to
guide
sector
growth
along
sustainable
routes,
par7cularly
in
the
developing
world,
they
will
require
sound
analyses,
based
on
reliable
data.
Materials
and
methods
In
a
recent
effort
to
bring
together
and
disseminate
spa7al
data
rela7ng
to
the
global
livestock
sector
the
Livestock
Geo-­‐Wiki
(hgp://www.livestock.geo-­‐wiki.org)
is
being
developed
by
a
group
of
interna7onal
organiza7ons
and
universi7es.
The
mainstay
of
the
wiki
is
a
set
of
recently
produced
global
livestock
maps
(Robinson
et
al.
2014).
With
livestock
produc7on
at
the
centre,
other
modules
under
development
relate
to
global
public
goods:
welfare,
environment
and
pubic
health.
Robinson
et
al.
(2014)
Mapping
the
global
distribu7on
of
livestock.
photo
credit:
ILRI/Chris
Jost
Global,
1
km
resolu7on
maps
of
livestock
densi7es
are
available
for
all
of
the
major
livestock
species,
and
are
already
being
downloaded
and
used
The
global
pig
map,
shown
to
the
lel,
was
recently
reported
by
Vox
to
be
among
the
38
maps
that
explain
the
world
economy.
hgp://www.vox.com/2014/8/26/6063749/
38-­‐maps-­‐that-­‐explain-­‐the-­‐global-­‐economy
The
livestock
distribu7on
maps
made
available
through
the
Livestock
Geo-­‐Wiki
are
an
essen7al
founda7on
for
much
important
environmental,
epidemiological
and
other
work
today.
These
maps
have
already
been
central
to
es7ma7ng
greenhouse
gas
emissions
from
the
livestock
sector,
for
example,
and
have
been
used
to
asses
the
risk
of
H7N9
(a
new
bird
flu
strain)
spreading
in
East
Asia
(based
on
a
boosted
regression
tree
model
that
includes
chicken
and
duck
densi7es
[Gilbert
et
al.
2014]).
Gilbert
et
al.
(2014)
Predic7ng
the
risk
of
avian
influenza
A
H7N9
infec7on
in
live-­‐
poultry
markets
across
Asia.
Nature
CommunicaIons
DOI:
10.1038/ncomms5116.
Timothy
Robinson
t.robinson@cgiar.org
●
P.O.
Box
30709-­‐00100
Nairobi
Kenya
●
+
254
20
422
3020
●
www.ilri.org
Acknowledgements:
This
work
is
being
funded
by
the
CGIAR
research
programmes
on
the
Humidtropics,
Climate
Change,
Agriculture
and
Food
Security
(CCAFS)
and
Livestock
and
Fish
This
document
is
licensed
for
use
under
a
Crea7ve
Commons
Agribu7on
–
Non
commercial-­‐Share
Alike
3.0
Unported
License
November
2014
Results
Research
into
use
H7N9
infec7on
risk
PLoS
ONE
9(5):
e96084.
doi:10.1371/
journal.pone.0096084.
Modules