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Predicting Shifts in Australian Shrublands
with Changing Climates and Land Uses
John A. Ludwig
Stephen G. Marsden
should be sold (or moved) to avoid severe land degradation,
which can occur by keeping too many stock on the land
during drought.
Because Australian rainfall and its general vegetation
respond strongly to EN SO (Nicholls 1988, 1991), it is likely
that semiarid shrublands and woodlands will also respond
strongly to future climatic changes. It is predicted that over
the next thirty years, the semiarid rangelands of eastern
Australia could experience higher temperatures, higher
summer rainfalls (in fewer but more intense storms) and
lower winter rainfalls. The species composition of grasslands and shrub lands could significantly change in response
to these climatic shifts, for example, C4 grasses may increase in areas currently dominated by C3 grasses and
shrubs (Hattersley 1992).
Since its settlement by Europeans, the vegetation of
Australia has undergone many impacts and changes
(Saunders and others 1990). It is estimated that about 8% of
Australia's rangelands (some one-half million sq. km) have
undergone severe desertification (Dregne 1983), that is,'
areas showing signs of severe soil erosion such as gullies and
with vegetation in poor range condition. Eroded and degraded semiarid rangelands do not efficiently conserve re-
Abstract-Future changes in global climate and land use will
likely have severe impacts on the arid and semiarid shrublands of
Australia, and around the world. Current climate change models
are predicting shifts in the patterns of rainfall in the shrubland and
woodland regions of eastern Australia. Mean annual temperatures
are expected to rise by about 2 °C by 2050. Winter rainfall may
decrease, while summer rainfall may increase both in amount and
in intensity of local storms. The impact of these changing rainfall
patterns may be evident in subtle shifts in the balance between
shrubs and grasses at the landscape scale. The mode of action may
be through the way limited water and nutrient resources are
differentially conserved and utilized within these semiarid landscapes. Our flow-filter landscape model has been used to predict
changes in water, nutrient and productivity in a tall shrublandl
woodland system using climate change and land degradation scenarios. Simulation results indicate that even if land degradation
increases only slightly, that these impacts will be far greater than
those expected from changes in climate.
The arid and semiarid regions of Australia cover about 5.5
million sq. km (75% ofits land area; fig. 1). Except for the arid
sandy desert regions, the semiarid areas are used extensively as rangelands for grazing sheep and cattle (Harrington
and others 1984). These rangelands are drought-prone and
have a high risk of becoming desertified, that is, being
impacted by human activities and drought to become more
desert-like (Mabbutt 1978).
Global climate modellers have used the EI Nifio-Southern Oscillation (ENSO) phenomenon to predict rainfall likelihood in various regions of Australia (Hunt 1994). This
ability to easily predict rainfall likelihood has greatly improved through the development of software packages such
as "Australian Rainman" (Clewett and others 1994).
Pastoralists in semiarid rangelands can incorporate the
latest estimates ofthe Southern Oscillation Index (SOl) into
Rainman to obtain the probability of rainfall in the coming
season for their region (McKeon 1994). This helps them
minimize the risk of making an inappropriate management
decision, thus reducing economic risks and impacts on the
land (Muchow and Bellamy 1991). For example, if a drought
has started and the long-term forecast is for no rain, stock
In: Barrow, Jerry R.; McArthur, E. Durant; Sosebee, Ronald E.; Tausch
Robin J., comps. 1996. Proceedings: shrubland ecosystem dynamics in ~
changing environment; 1995 May 23-25; Las Cruces, NM. Gen. Tech. Rep.
INT-GTR-338. Ogden, UT: u.s. Department of Agriculture, Forest Service,
Intermountain Research Station.
The authors are Research Scientists in the National Rangelands Program,
CSIRO Division of Wildlife and Ecology, P.O. Box 84, Lyneham, Canberra,
AC.T. 2602 Australia.
D
Semi-Arid Zone
L':':':':/
Arid Zone
Figure 1-Arid and semiarid climatic zones of
Australia. Non-stippled areas are wetter tropical
and temperate zones (after Christie 1986).
31
QT8S
sources and have low levels of annual net primary production (NPP) compared to similar but undegraded landscapes
(Ludwig and Marsden 1995).
The aim of this modelling study was to simulate the likely
impacts of climate change and land degradation on resource
conservation, species composition and NPP for the semiarid
rangelands of eastern Australia, and to compare the importance of these two scenarios relative to a natural or
undegraded tall shrublandlwoodland system.
across gentle slopes ofless than 1% (fig. 2). Runoff will flow
down these slopes unless it is captured by a patch. Runout
occurs from the landscape unit when runoff is not captured.
Semiarid Landscape Function _ _
Patchiness functions to concentrate and conserve limited
water and nutrient resources, hence increase plant production (Ludwig and others 1994). This resource concentration
effect is based on the theory that arid and semiarid lands
function as source-sink or runoff-runon systems (Noy-Meir
1973). Given limited resources, this theory predicts that
NPP will be higher in arid and semiarid environments if
water and nutrients are concentrated to form resource-rich,
productive patches than if such resources are uniformly
dispersed in low concentrations over the entire landscape.
Landscape studies have demonstrated that patchiness is
maintained by physical processes such as surface winds and
surface water flows which redistribute resources into patches
(Ludwig and Tongway 1995; Thiery and others 1995). For
example, patches capture runoff water which recharges soil
moisture stores, captured runoff sediments rebuild soil
nutrient pools and trapped wind-blown litter contributes to
soil organic carbon. Patches are maintained by biological
and chemical processes, for example, plants growing in the
patch utilize water and nutrients from the patch and then
through death and decay return organic carbon and nutrients to the patch.
Semiarid Tall Shrublands/
Woodlands
------------------------------
In the semiarid zones of eastern Australia, including parts
of Queensland, New South Wales, Victoria and South Australia (fig. 1), much of the upland vegetation is a mosaic
characterized by tall shrublands and woodlands dominated
by Acacia spp. and Eucalyptus spp. (Harrington and others
1984). Grasslands and riverine woodlands and forests occur
on floodplains and along creeks and rivers. The climate
varies from subtropical in Queensland to temperate in the
southern States. Upland soils are mainly hard setting massive red earths oflow fertility while lowland soils are cracking clays of moderate fertility.
Many of these semiarid landscapes in eastern Australia
are patchy, runoff-runon systems (Ludwig and Tongway
1995). For example, a common feature observed is where
thickets or patches of mulga (Acacia aneura) are interspersed with more open, grassy interpatches (Tongway and
Ludwig 1990). This patchiness also occurs as smaller scale
features such as logmounds-intermounds, or as grass clumpsinterclumps. In a top-view diagram, these patchy semiarid
landscapes appear as a number of discrete units dispersed
Simulation Models of Landscape
Function and Production
To quantify how runoff flows down, and possibly out of a
landscape, a "flow-filter" simulation model was developed
(Ludwig and others 1994). When the amount of rainfall (R)
exceeds the water infiltration rate (lR) or water storage
capacity (SC) of the soil then runoff (ROft) occurs within
interpatch areas (fig. 3). If not captured by patches, this ROff
will runout (ROut) of the system, that is, if the IR and SC of
the patch is exceeded then ROut occurs. Following a rainfall
event at time (t), the total ROut from a landscape is also a
function of the slope (S), area of interpatch (AI) and area of
patch (AP):
Top of Landscape
I
[I NTERPATCH)
ROu~ = f(R,IR,SC,S,AI,AP>t
1%
Another simulation model, SEESAW, was linked to the
flow-filter landscape model to estimate annual net plant
production (NPP) for the system. SEESAW was designed to
simulate the ecology and economics of semiarid woodlands
(Ludwig and others 1992, 1994). At time (t), a submodel
within SEESAW computes NPP as a function of plant
available moisture (PAM) and available nutrients (AN), and
as a function of temperature (TEMP):
ROff
SLOPE
ROff
Bottom of
Landscape
1-1-1ROut
ROut
NPPt = fiPAM,AN,TEMP)t
Another submodel, called WATDYN, computes PAM by
estimating soil water balance dynamics (Walker and
Langridge 1996).
Four plant functional groups: ephemerals (forbs and
grasses), C3 grasses, C4 grasses, and shrubs, were included in
this simulation study. Plant processes modelled included
ROut
Figure 2-Top-view diagram of a typical semiarid landscape in eastern Australia, with patches separated by
open interpatch areas (after Ludwig and others 1994).
32
Table 1-lnputs and parameter values used to simulate three
scenarios for semiarid landscapes in eastern Australia.
R
!
Environmental inputs
and landscape values
Landscape:
Scale:
InterPatch
Patch
( InterGrove)
(Acacia Grove)
Precipitation at
Cobar, NSW
IR (mm/hr)
Patch
Interpatch
Soil Depth (cm)
Patch
Interpatch
Scenario
Degraded
system
Climate
change
Actual for
1962-94
Actual for
1962-94
+10% S*
-10%W
60
10
30
5
60
10
100
45
75
30
100
45
Natural
system
• S = summer (Dec-Feb); W = winter (Jun-Aug)
100 m
Figure 3--Cross section of a typical semiarid Acacia
shrubland/woodland landscape in eastern Australia.
The flow of resources is depicted following a rainfall
event (R) with runoff (Raft) occurring when the amount
and intenSity of the rainfall exceeds the infiltration rate
(IR) or the water storage capacity (SC) of the soil.
Resources not captured by the patch runout (ROut) of
the landscape system. Soils within patches are deeper,
thus have a greater SC, and also have a higher IR
(after Ludwig and others 1994).
landscape systems (Greene 1992). The climate change scenario assumed a 10% rise in mean summer rainfall (fewer
events and more intense) and a 10% drop in mean winter
rainfall, and included a two degree centigrade rise in mean
annual temperature.
Results -----------------Over the 31.5 year simulation run the natural semiarid
landscape had a NPP of about 330 kg/ha/yr (fig. 4). The
degraded landscape NPP only averaged about 160 kg/ha/yr,
probably because it lost more rainfall as ROut (about 135
mm/yr) compared to the other scenarios (about 75 mm/yr;
fig. 5). The impact of climate change was to increase NPP to
about 425 kg/ha/yr relative to the 330 kg/ha/yr for the
natural system.
growth, senescence, death, decay and consumption. Given
initial or starting biomass values for leaf, stem and root
components, annual NPP was _computed using a weekly
time-step for both patch and interpatch areas. However, the
WATDYN submodel used a daily time-step to compute soil
water dynamics by rainfall event within each rainy day.
Temperature and rainfall amount and intensity data used
to "drive" the simulations was based on a 31.5 yr record (midyear 1962 through 1994) collected from a Class A weather
station at Cobar, New South Wales. Cobar is located near the
centre of the semiarid tall shrublands/woodlands of eastern
Australia.
'i:'
«I
CD
>......
«I
.c
......
Climate Change and Rangeland
Degradation Scenarios --------
-
400
C)
~
For the simulations three scenarios were simulated: (1) an
undegraded or natural semiarid landscape, (2) a similar but
degraded landscape, and (3) a natural landscape being
impacted by climate change. We used a semiarid landscape
system offixed size, shape and patch structure (fig. 2). The
landscape unit was assumed to be a rectangular area of 1 ha
(10000 m 2 ) and having a uniform slope (S) of 1%. Patches
were dispersed regularly over the 1 ha area and occupied
?O% of the area. Undegraded semiarid woodland landscapes
~n eastern Australia typically have Acacia thickets occupyIng about 30% of the surface area (Tongway and Ludwig
1990).
Each of the three scenarios included parameter values
reflecting differences in rainfall and soil infiltration rates
(IR), and in soil depth which is related to soil water storage
capacity (SC) (table 1). Actual field measurements taken in
the semiarid woodlands of eastern Australia were used to
estimate the parameter values for natural and degraded
c
0
;::
300
CJ
:::s
'C
0L.
200
a..
~
«I
E
100
"i:
...
Q.
CD
Z
0
Natural
System
Degraded
System
Figure ~Average yearly net plant production
(NPP) over a 31.5 year period (mid-1962-1994)
for a semiarid landscape for three scenarios:
natural, degraded and climate change.
33
Climate
Change
declined under the land degradation scenario, particularly
C4 grasses and ephemerals. Shrubs only declined slightly
under the degradation scenario compared to the natural
system and climate change scenarios.
150
"i:"
Discussion
<'
~ 100
--~
::l
oa:
E
Q)
......
50
en
>.
(f)
o
Climate
Change
Degraded
System
Natural
System
Figure 5-Mean annual loss of runoff after rains from
a semiarid landscape (ROut) for three scenarios: natural, degraded and climate change
A natural semiarid landscape in eastern Australia subjected to the impacts of climate change is likely to experience
a significant shift towards a dominance ofC4 grasses (fig. 6)
along with increased annual NPP. However, under climate
change other plant functional groups changed little compared to the natural system. All plant functional groups
250
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-
200
C)
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150
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:g
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------------------------------------
The likely impacts of land degradation are far greater
than those impacts expected from climate change based on
the modelling results of this study for semiarid regions of
eastern Australia. Land degradation can lead to the loss of
water and nutrients from a landscape. Since resources are
, already very limited in these landscapes, the result can be
significant declines in plant production, particularly for
grasses and forbs although perhaps less so for shrubs and
trees. A loss of small-scale patchiness due to land degradation can lead to a decline in the capacity of the landscape
system to capture resources (Tongway and Ludwig 1994).
This simulation study predicted a significant increase in
C4 grasses under the impacts of a climate change scenario.
This increase might be expected since C4 pathway plants
have a higher rate of photosynthesis for a given CO2 level
compared to plants with the C3 pathway under warmer
temperatures and higher light intensities (Solbrig and Orians
1977). Thus, a scenario of greater summer rainfall with
warmer temperatures will tend to favor C4 grasses relative
to C3 grasses (Hattersley 1992).
Patchiness appears to be a common natural phenomenon
in arid and semiarid landscapes around the world. It has
been documented by field studies in the semiarid tall
shrublandslwoodlands of eastern Australia (Ludwig and
Tongway 1995; Tongway and Ludwig 1990), in the savannas
ofthe Serengeti, East Africa (Belsky 1989), in the 'tiger bush'
of West Africa (Thiery and others 1995), in semiarid grasslands of Chihuahua, Mexico (Mop.tafia 1992) and in the
shrublands of Western Australia (Tongway and Ludwig
1993).
Many degraded rangeland areas can be rehabilitated by
restoring landscape patchiness and processes through appropriate rehabilitation treatments and land management
practices. One treatment known to effectively restoration
landscape processes is by constructing surface obstructions
to water flow (Tongway and Ludwig 1993). Tree and shrub
branches can be piled in clusters along contours to create
patches. These obstructions function to capture limited
water and nutrients flowing as runoff and blowing as dust
and litter about the landscape. These processes rebuild
patches natural to the system. These patches also provide
valuable habitats for plants and animals.
Further simulation studies are needed to substantiate the
findings of this study for other rangeland regions that have
different levels of degradation, and which have different
climate change scenarios. Where available, long-term rainfall amount and intensity and temperature data will be
used.
(/)
.Ll
2
.J::.
(J)
"<t
()
Climate
Change
Acknowledgments _ _ _ _ __
Figure 6-Yearly net primary production (NPP) for
four plant guilds averaged over a 31.5 year period
(mid-1962-1994) for a semiarid landscape system
and three scenarios: natural, degraded and climate
change.
We gratefully acknowledge David Tongway for his contributions to conceptual and model developments, and we
thank Brian Walker and Jenny Langridge for providing us
their WATDYN model.
34
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