Download clicking here - Blue Mountains World Heritage Institute

10/25/11
Australian case study: the Greater
Blue Mountains World Heritage Area
THINK.CHANGE.DO
Dr Daniel Ramp
Senior Lecturer
School of the Environment
Australian case study
Climate trends in Australia - Rainfall
1
10/25/11
Australian case study
Climate trends in Australia - Topography
•  99%
of
the
Australian
con2nent
<
1000
m
•  Limited
scope
for
al2tudinal
migra2on
as
climate
zones
shi<
Australian case study
Climate trends in Australia - Fire
•  Vegeta2on
in
all
but
we@est
areas
very
fire‐prone
•  5%
of
land
surface
burnt
each
year
(up
to
50%
in
north)
•  Future
fire
regimes
effected
by:
–  Temperature
–  Rainfall
–  Fuel
loads
(CO2)
•  Very
difficult
to
predict
2
10/25/11
Australian case study
Issues of scale
Australian case study
World Heritage site listings
•  Cultural
•  Australian Convict Sites (2010)
•  Royal Exhibition Building and Carlton Gardens (2004)
•  Sydney Opera House (2007)
•  Natural
•  Australian Fossil Mammal Sites (Riversleigh / Naracoorte) (1994)
•  Fraser Island (1992)
•  Gondwana Rainforests of Australia (1986)
•  Great Barrier Reef (1981)
•  Greater Blue Mountains Area (2000)
•  Heard and McDonald Islands (1997)
•  Lord Howe Island Group (1982)
•  Macquarie Island (1997)
•  Ningaloo Coast (2011)
•  Purnululu National Park (2003)
•  Shark Bay, Western Australia (1991)
•  Wet Tropics of Queensland (1988)
•  Mixed
•  Kakadu National Park (1981)
•  Tasmanian Wilderness (1982)
•  Uluru-Kata Tjuta National Park (1987)
•  Willandra Lakes Region (1981)
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Park management framework
Where
do
we
want
to
be?
Experience
Did
we
achieve
what
we
planned
and
should
we
change?
Management
Objec2ves
Management
and
Evalua2on
Park
Policy
How
to
translate
into
departmental
ac2on?
Outcomes
What
did
we
do
and
what
services
or
products
were
produced?
What
did
we
achieve?
Outputs
How
to
get
there?
How
do
we
go
about
it?
Research
Context
Planning
Inputs
What
do
we
need?
Management
Processes
Australian case study
Hierarchical adaptive management
Vision
Objec2ves
Biodiversity
objec2ves
Thresholds
of
poten2al
concern
Indicators
and
modelling
4
10/25/11
Ecological
condi2on
Australian case study
Measurement indicators and management intervention
Upper
and
lower
thresholds
(TPCs)
Time
Management
interven2on
2007‐2009
Managing
for
ecosystem
change
in
the
Greater
Blue
Mountains
World
Heritage
Area
ARC
LP0774833
5
10/25/11
What is the GBMWHA?
  GBMWHA
  1.03
million
hectares
  Land
tenure
What
do
we
  8
protected
areas
Where
is
it?
  have?
Na2ve
2tle
  Reserves
subject
to
claims
What
do
  Co‐management
What
are
the
strategy
plan
ecosystems
unknowns?
require?
  Adjacent
land
use
  Perimeter
approximately
5,000
km
What
impact
What
can
  Freehold,
protected
do
threats
areas
and
Crown
managers
do?
have?
reserves
ARC
LP0774833
Greater Blue Mountains World Heritage Area
Contrasting values
Bequest,
inspira2on,
spirituality
Biodiversity
Geodiversity
Scenic
and
aesthe2c
Research
and
educa2on
Water
catchment
GBMWHA
Values
Social
and
economic
Indigenous
values
Historic
values
Wilderness
Recrea2on
and
tourism
6
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Greater Blue Mountains World Heritage Area
Contrasting threatening processes
•  Invasive
species
–  Over
40
plants
–  15
animals
•  Fire
–  Days
with
high
fire
risk
–  Increase
in
frequency
and
size
(without
management)
•  Urban
expansion
•  Pollu2on
•  Fragmenta2on/habitat
loss
Greater Blue Mountains World Heritage Area
Climate trends for the GBMWHA
Parameter
Projec*ons
to
2050
Source
Temperature
•  Increase
in
mean
min
and
max
temperature
by
1
–
3oC
DECCW
2009
(A2)
CSIRO
2007
•  Increase
in
number
of
hot
days
over
35oC
•  More
hot
days/nights
and
fewer
cold
days/night,
CSIRO
2007
o
including
fewer
frost
days
below
0 C
Rainfall
•  No
change
in
autumn
•  10
–
20%
decrease
in
winter
rainfall.
Slightly
drier
winter
due
to
higher
temperatures
and
increased
evapora2on
DECCW
2009
•  5
–
10%
increase
in
spring
rainfall.
Slightly
drier
spring
due
to
higher
temperatures
and
increased
evapora2on
•  20
–
50%
increase
in
summer
rainfall.
We@er
summer
Evapotranspira*on
•  Increase
across
region
CSIRO
2007
Bushfire
•  Risk
likely
to
increase
across
region
CSIRO
2007
Sea
level
rise
•  Increase
40
cm
by
2050
and
90
cm
by
2100,
rela2ve
to
DECCW
2009
1990
sea
level
Atmospheric
CO2
•  Increase
IPCC
2007
7
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Greater Blue Mountains World Heritage Area
Project themes
Future
scenarios
Sta2s2cal
modelling
Species
distribu2ons
Endemism
Dispersal
Fire
regimes
Climate
change
Hotspots
Representa2on
Efficacy
Land
acquisi2on
Data
collec2on
Reserve
design
Diversity
Invasive
species
Decision
making
Surrogacy
Survey
efficiency
ARC
LP0774833
Adap2ve
management
Park
management
Risk
minimisa2on
Weeds
‐
Lantana
Carnivore
interac2ons
Collaborators
Greater Blue Mountains World Heritage Area
Collaborators
• 
Chief
inves2gators
– 
– 
– 
– 
– 
– 
– 
– 
– 
• 
Dr
Daniel
Ramp
(BEES,
UNSW)
Prof.
Richard
Kingsford
(BEES,
UNSW)
Dr
Shawn
Laffan
(BEES,
UNSW)
Dr
David
Warton
(Maths,
UNSW)
A/Prof.
John
Merson
(IES,
UNSW)
Prof.
Ross
Bradstock
(UoW)
A/Prof.
Robert
Mulley
(UWS)
Dr
Tony
Auld
(DECCW)
Dr
Rosalie
Chapple
(BMWHI)
Partners
–  NSW
Office
of
Environment
and
Heritage
–  NSW
Department
of
Primary
Industries
–  Hawkesbury‐Nepean
CMA
–  Blue
Mountains
City
Council
–  Blue
Mountains
World
Heritage
Ins2tute
• 
Research
staff
– 
– 
– 
– 
– 
• 
Daniel
Ramp
(Research
Fellow)
Evan
Webster
(Research
Assistant)
Erin
Roger
(Research
Assistant)
Tom
Colley
(Research
Assistant)
Kun
Zhang
(Post‐doc)
Research
students
– 
– 
– 
– 
– 
– 
– 
– 
– 
Fiona
Thomson
(PhD)
Gilad
Bino
(PhD)
Jack
Pascoe
(PhD)
Alex
Gold
(PhD)
Ian
Renner
(PhD)
Alex
Gold
(MPhil)
James
Mar2n
(MEM)
Melissa
Head
(Hons)
Leah
Shepherd
(Hons)
ARC LP0774833
8
10/25/11
Greater Blue Mountains World Heritage Area
Research examples on climate change
1.  Endangered
ecological
communi2es
– 
Upland
swamps
2.  Individual
species
and
community
composi2on
– 
Plants
in
the
family
Myrtaceae
3.  Vulnerability
within
sites
– 
Microrefugia
4.  Reserve
adequacy
– 
Communi2es
of
species
5.  Risk
to
ecosystem
services
– 
Catchment
water
yield
Greater Blue Mountains World Heritage Area
1. Upland swamps
•  Prominent
on
steep
valley
sides,
where
water
exits
the
ground
between
sandstone
and
claystone
rock
layers
•  Extent
varies
due
to
changes
in
rainfall/evapora2on
•  Porous
sandstone
layered
with
impermeable
ironstone
and
shale
belts
•  Water
flows
through
sandstone,
but
the
hard
ironstone
forces
it
to
the
surface
9
10/25/11
How might conditions change in the future?
Which swamps are likely to be susceptible?
How can mitigation strategies be optimised?
1. Upland swamps
Climate change and upland swamps
Higher
summer
rainfall
Rainfall
Drier
in
winter
and
spring
Drier
ground
Geomorphology
Physical
features
Hydrology
Biota
Weed
source
Erosion
Soil
organisms
affected
Less
infiltra2on
Some
plants
ok
Temperature
Al2tude
range
500
–
950
m
Lower
eleva2ons
first
Geomorphology
important
Fauna
impacted
More
frequent
Fire
More
intense
No
more
than
once
every
12
years
Peatland
burning
Erosion
Lower
water
table
10
10/25/11
1. Upland swamps
Benefits of modelling
•  Predic2on
–  A
model
can
iden2fy
unknown
areas
where
a
habitat
may
occur
•  Explana2on
–  A
model
can
help
to
explain
why
a
habitat
exists
where
it
does
(i.e.
how
it
responds
to
the
environment)
•  Projec2on
–  A
model
can
incorporate
different
climate
scenarios
to
predict
where
a
habitat
may
thrive
in
the
future
1. Upland swamps
Niche modelling
Upland
swamp
Niche
envelope
 
 
m
Te
all
inf
Ra
/
re
tu
ra
pe
 
Look
for
a
sta2s2cal
rela2onship
between
where
upland
swamps
exist
and
environmental
and
clima2c
variables
–
their
niche
Model
suggests
where
condi2ons
for
swamps
may
change
Provides
a
mechanism
for
assessing
risk
to
swamp
communi2es
11
10/25/11
Number
of
swamps
within
suitable
niche
1. Upland swamps
Swamps at risk
1600
1400
1469
1469
1398
1469
1368
1278
1211
1200
1288
35%
at
risk
956
1000
800
2000
600
2030
2050
400
200
0
B1
A1B
A1FI
IPCC
Scenario
1. Upland swamps
Web visualisation of simulations
12
10/25/11
2. Individual species
Family Myrtaceae – Key Outstanding Value
•  Contains
the
Eucalypts:
Eucalyptus,
Corymbia,
Angophora
(127
species)
•  29
genera,
293
species
•  Trees
or
shrubs
•  Most
diverse
family
in
the
region
2. Individual species
Endemism
•  Many
species
have
very
narrow
clima2c
and
geographic
ranges
–  53%
eucalypt
species
clima2c
ranges
<3oC
–  25%
span
<1oC
13
10/25/11
Species
distribu2on
modelling
2. Individual species
Species distributions
2050 medium emission scenario (A1B)
* 5% reduction in annual rainfall
* 1.5 degree rise in minimum temperature
* 2 degree rise in maximum temperature
Angophora bakeri
Angophora costata
2. Individual species
Climate change
  Current
condi2ons
  268
species
suitability
models
  200,000,000
data
points
  Computer
array
  2030
medium
emission
scenario
(A1B)
  2
%
reduc2on
in
annual
rainfall
  1
degree
rise
in
minimum
temperature
  0.6
degree
rise
in
maximum
temperature
  2050
medium
emission
scenario
(A1B)
  5
%
reduc2on
in
annual
rainfall
  1.5
degree
rise
in
minimum
temperature
  2
degree
rise
in
maximum
temperature
14
10/25/11
3. Microrefugia
Biodiversity corridors
•  Biodiversity
corridors
–  large
spa2al
areas
of
con2guous
habitat,
or
core
areas
–  connected
by
habitat
linkages
to
meet
their
natural
ecological
and
behavioural
requirements
•  Design
–  can
be
con2nuous
strips
of
land
or
'stepping
stones'
that
are
patches
of
suitable
habitat
–  providing
func2onal
linkages
between
core
protected
areas
s2mula2ng
or
allowing
species
migra2on
between
areas
Great
Eastern
Ranges
Ini2a2ve
•  A
response
to
mi2gate
the
impacts
of
climate
change,
and
other
threats
•  It
will
strengthen
conserva2on
management
and
connec2vity
of
natural
lands
along
the
great
eastern
ranges
conserva2on
corridor
15
10/25/11
3. Microrefugia
Refugia = resilience
•  Nature
of
biodiversity
is
dynamic
•  Protect
loca2ons
that
are
important
for
ongoing
ecological
and
evolu2onary
processes
•  Refugia
are
loca2ons
that
have
stable
and
unusual
climates
with
intrinsic
conserva2on
value
because
they
–  buffer
species
from
climate
variability
and
therefore
enhance
the
ability
of
species
to
persist
when
the
climate
is
unsuitable
elsewhere
–  foster
gene2c
isola2on
that
can
enhance
evolu2onary
processes;
and
–  enhance
the
diversity
of
environmental
condi2ons
and
thus
increase
the
poten2al
for
higher
biodiversity
A novel approach to quantify and locate microrefugia using topoclimate, climate stability, and
isolation from the matrix – Global Change Biology
3. Microrefugia
Macrorefugia
Macrorefugia
16
10/25/11
3. Microrefugia
How to map microrefugia
•  To
iden2fy
the
poten2al
loca2on
of
microrefugia
need
to
quan2fy
areas
that:
–  have
the
lowest
or
highest
temperatures
when
assessed
using
fine‐scale
topoclima2c
grids
–  have
rela2vely
stable
climates;
and
–  are
dis2nctly
different
from
the
climate
in
the
surrounding
area
3. Microrefugia
Fine scale topoclimate information
!
17
10/25/11
3. Microrefugia
Wollemi region microrefugia
95th
percen*le
of
maximum
temperature
gradient
5th
percen*le
of
minimum
temperature
gradient
!
!
3. Microrefugia
Prioritisation and adequacy
•  Refugia
could
be
included
in
adequacy
assessments
•  Alloca2on
of
resources
for
ac2ons
need
to
be
op2mised
–  Tools
to
priori2se
values
spa2ally
are
very
useful
in
decision
making
–  Have
the
capacity
to
be
turned
into
simple
end‐
user
products
–  Can
incorporate
trigger
points
18
10/25/11
Macrorefugia
4. Community responses to climate change
Community aggregations
Incorporating climate refugia for faunal assemblages in assessments of protected
area adequacy – Journal of Biogeography
Macrorefugia
4. Community responses to climate change
Community responses
19
10/25/11
Macrorefugia
4. Community responses to climate change
Climate relationships among communities
Macrorefugia
4. Community responses to climate change
Stability in communities
20
10/25/11
Site
selec2on
across
NSW
targe2ng
10%
representa2on
of
11
mammal
assemblages
within
a
protected
area
network.
Colour
shading
represents
levels
of
irreplaceability
‎idenitfied by the
Marxan
so<ware
for
each
of
four
scenarios:
(a)
current
condi2ons
building
upon
exis2ng
protected
area
network;
(b)
current
condi2ons
without
exis2ng
network;
(c)
projected
condi2ons
for
2050
building
upon
exis2ng
network;
and
(d)
projected
condi2ons
for
2050
without
the
exis2ng
network.
Black
polygons
represent
the
exis2ng
protected
area
network.
Macrorefugia
4. Community responses to climate change
Representation of communities effected by change scenarios
21
10/25/11
Australian Case Study
What have we learned?
•  Science
can
inform
policy
within
sites
–  Can
priori2se
mi2ga2on/adapta2on
strategies
to
areas
of
most
risk/benefit
–  Can
op2mise
configura2on
of
protected
areas
and
priori2se
land
acquisi2on
for
specific
threats
–  Need
to
consider
range
of
outstanding
values
•  Problems
of
uptake
and
knowledge
transfer
s2ll
exist
–  Conflic2ng
values
in
mul2‐tenured
sites
–  Language
barriers
between
managers
and
scien2sts
–  Long
term
collabora2ons
lacking
22
10/25/11
3. Reserve Efficacy
Endemism
•  Endemism
in
the
Myrtaceae
–  To
compare
regional
and
na2onal
representa2on
of
plant
species
in
the
family
Myrtaceae
–  To
assess
spa2al
representa2on
of
plant
species
in
the
Myrtaceae
within
a
100
km
buffer
of
the
WHA
•  How
it
was
derived
–  Compared
regional
representa2on
to
na2onal
ranges
•  Species
range
–
10
km
cells
•  Species
weight
–  Sum
of
the
number
of
cells
in
the
GBMWHA
it
occurs
in,
divided
by
the
range
•  Weighted
endemism
–  Sum
of
the
species
weights
•  Corrected
weighted
endemism
–  Weighted
endemism
divided
by
the
number
of
species
3. Reserve Efficacy
Corrected weighted endemism
1
1
  20%
of
Myrtaceae
species
are
range‐restricted
to
0.9
the
GBMWHA
0.8
  The
GBMWHA
represents,
on
average,
20%
of
the
range
of
a
species
that
occurs
within
it
0.7
0.6
1
0.5
0.4
0.3
0.2
0.1
1
1
5
1
18
10
2
5
91
1
3
5
1
1
1
9
8
1
1
2
1
2
0
23
10/25/11
3. Reserve Efficacy
Spatially-explicit endemism
24