think climate. think change.
Department of Climate Change
Mark Howden - CSIRO Sustainable Ecosystems, Roger Jones - CSIRO Atmospheric Research
Australian Greenhouse Office - October 2001
There is considerable variance in the responses between different sites. Wongan Hills (WA) and Dalby (Qld) are chosen to represent two extremes of response. For Dalby in the year 2070, paddock scale yields (Fig 6a) are likely to increase with about a 85% chance of being greater than current yields and a mean increase of about 12%. Regional productivity shows similar patterns (Fig. 6b) whereas the regional value of production (Fig. 6c) is slightly damped due to decreases in grain nitrogen reducing price per ton. When translated into dollar
Fig. 6 Changes in a) yield, b) regional productivity (%), c) regional value of production (%) and d) change in value of production ($M) for Dalby in the year 2070.
Fig. 7 Changes in a) yield, b) regional productivity (%), c) regional value of production (%) and d) change in value of production ($M) for Wongan Hills in the year 2070.
values, (Fig. 6d) there is a large range of values (-50 to + 40 million) but with most values falling between -1 and +30 million and a mean of about $15M.
In contrast, Wongan Hills shows marked declines in yield (Fig. 7a) with only a small probability (9%) of a positive response, and a mean reduction of about 11%. Regional productivity is even more adversely affected (Fig. 7b) due to the assumed retirement of land from cropping with reductions in yield potential. There is a mean reduction of about 15% but with a 91% chance of reduction below current levels. Regional value of production shows a similar response (Fig 7c) which when translated into reductions in dollar value (Fig. 7d) indicates losses from current levels of between $20M and $300M per year with a mean of about $104M. There is a 50% chance of losses greater than $68M and only a 3% chance of maintaining current value of production from the region.
Results presented for the other eight regions (Figs 7 and 8) focus on two of the outcomes to restrict complexity of output. The eight sites are formed into a grouping of four types of response which are summarise in Table 2. Values for year 2030 are similar in direction but smaller than those for 2070.
Table 2 Category of impact, sites in each category and summary of impacts for Australian wheat yield in the year 2070. The numbers in parentheses indicate the current percent of the national yield originating in each region.
| Category | Sites | Impacts |
| Largely negative impacts | Wongan Hills (19), Geraldton (7), Katanning (12) | Mean regional productivity reduced by 3 to 15%, with a 52 to 90% chance of productivity being below current levels. Mean value of production reduced by $13 M to $104 M per year with a 52 to 97% chance of being below current levels. |
| Some risk of negative impacts but larger probability of positive impacts | Minnipa (15), Horsham (13) | Mean regional productivity increased by about 6% but with an 18-25% chance of being below current levels. Mean value of production increased by $10 M to $15 M per year with a 25 to 27% chance of being below current levels. |
| Generally beneficial impacts but small risk of negative impacts | Moree (7), Dubbo (12), Dalby (5) | Mean regional productivity increased by about 12% but with a 5 -14% chance of being below current levels. Mean value of production increased by $15 M to $24 M per year with a 13 to 14% chance of being below current levels. |
| Likelihood of largely beneficial impacts | Emerald (2), Wagga (9) | Mean regional productivity increased by about 9% to 13% but with an 0 - 8% chance of being below current levels. Mean value of production increased by $13 M to $24 M per year with a 1 to 4% chance of being below current levels. |
Fig 8 Changes in regional production (%) and value of production for the year 2070 for Geraldton (a,b), Katanning (c,d), Minnipa (e,f), Horsham (g,h) and Wagga (i,j).
Fig 9 Changes in regional production (%) and value of production for the year 2070 for Dubbo (a,b), Moree (c,d) and Emerald (e,f).
On a national basis, mean wheat production may increase in the year 2070 by 1.8% from current levels (Fig. 10a, Table 4) but there is a 34% probability that it could be below current levels. There is a marked skewness in the distribution, with positive responses being limited (to about 10%) but negative impacts down to about 25%. Slightly different responses occur for change in value of wheat production (Fig. 10b, Table 4) with a mean decrease in value of $35M and a 45% chance of value of production being lower than current levels. Again there is a skewed response with potential increases being limited to about $220M/year but decreases possible to about $800M/year although with low probability. Part of this long 'tail' of response is due to the assumptions of reduction in cropped area under significantly drier conditions, particularly for Geraldton, Wongan Hills and Minnipa, however, at a national level comparisons show this assumption makes only minor differences.
Fig. 10 Change in a) national production (%) and b) value of national wheat production ($M) for the year 2070 from current levels as a result of increase in CO2 and change in temperature and rainfall.
Fig. 11 Change in value of wheat exports ($M) for the year 2070 when compared with current levels as a result of increase in CO2 and change in temperature and rainfall as well as mid-range projections of population change and other industry consumption change.
Table 3 Minima, means and maxima of change in value of wheat exports ($M/year) for 2070 with global change included as well as three scenarios of population change (Trewin 2001).
| Minimum | Mean | Maximum | |
| Low | -1713 | -121 | 354 |
| Mid | -1761 | -164 | 313 |
| High | -1867 | -261 | 221 |
National productivity of wheat can be translated approximately to export value by deducting the assumed domestic consumption at the time and multiplying the remainder by the crop value. For the ABS mid-range population projection in combination with climate change, there is a high probability (72%) of a reduction in export income with a mean of a $164M reduction against current levels (Fig. 11). The skewed distribution of the national production response follows through here, with the increase in domestic consumption arising from population growth causing about a $124 M reduction in average annual exports. If increases in feed consumption by livestock occur, then this reduction in export income may increase by about another $200M/year and there is a difference between the high and low population scenarios of about $40M to $100M/year (Table 3). However, such changes are less than those arising from the possible impacts of CO2 increase and climate change evident in Figs 10a,b. For the high population growth scenario, there is an 89% probability of reductions in export income from current levels whilst for the low scenario, this probability is 62%.
Adaptation
When adaptations of changing varieties and changing planting windows (to take advantage of reduced frost risk) are simulated across the Australia wheat growing industry for the year 2070, there is a marked offsetting of the negative impacts of global change and an enhancement of the positive aspects (Table 4). National mean wheat production was 8.5% higher than current levels and there was only a 16% chance of it being below current levels (Fig 12a). Similarly for value of production, mean value is $61M above current value and there is a 29% probability that it will be below current values (Fig 12b). When the mid-range ABS population scenario is used in conjunction with global change, there is a 40% chance of being lower than current values with a mean value being $17M per year lower (Fig 12c). Part of the reductions in value of production and export is that decreased grain nitrogen content reduced mean grain price by $12/ton (7%).
Fig. 12 Change in a) national wheat production (%), b) value of production ($M) and c) value of exports ($M) for the year 2070 when adaptations are practiced.
When management is adapted to cope with climate change, whilst there remains a high probability of negative impacts in the WA and SA sites there is some significant amelioration of the adverse effects. For example, in Wongan Hills, there is a 39% chance of yields above current levels (Fig 13a) whereas this was only 3% with no adaptations used. Mean value of production is $45M higher than when no adaptations are used. In eastern Australia, adaptations result in consistently higher probability of positive outcomes in value of production. For example, in Dalby, adaptation adds a mean of $10M/year to value of wheat production (e.g Fig 13b). Investment in adaptive strategies appears to provide a large pay-off.
Fig. 13 Change in value of wheat production for a) Wongan Hills and b) Dalby for the year 2070 under CO2 and climate change when adaptations are practiced.
Fig. 14 Change in regional production (%) and value of production ($M) for the year 2030 compared with current levels for Wongan (a,b) and Dalby (c,d).
There are potential impacts of global change evident in the year 2030 scenarios. Regional grain production in Wongan Hills could reduce by a mean of -3% with only a moderate probability (about 35%) that it may be higher than current levels (Fig. 14a). Value of production may also fall by an average of $25M (Fig 14b) with only a small likelihood of increases (13%). In contrast, mean yields and value of production in Dalby could increase by 7% with only a small chance (7 - 13%) of being below current levels (Fig. 14c,d).
National grain production may be higher than current levels (Fig. 15, Table 4) with a mean of (3%). There is only a 12% chance of it being below current levels. Mean value of production (Fig. 16) may increase by about $19M/year with a 32% chance of being below current levels. However, as with the year 2070 scenarios, the skewed relationship gives positive outcomes limited to about $150M/year whilst the negative outcomes range to below $250M/year albeit with low probability. In contrast, value of wheat exports may fall (Fig. 17) by a mean of $82M for the ABS mid-range population scenario with a 91% chance of being below current levels. This is largely due to an increase in domestic consumption of wheat as a result of population growth which reduces exports on average by $63M/year. Under the alternative population scenarios, mean exports may fall by between $60 and $114M/year.
Fig. 15 Change in national production (%) for the year 2030 from current levels as a result of increase in CO2 and change in temperature and rainfall.
Fig. 16 Change in value of national wheat production ($M) in the year 2030 from current levels as a result of increase in CO2 and change in temperature and rainfall.
Fig. 17 Change in value of wheat exports ($M) for the year 2030 when compared with current levels as a result of increase in CO2 and change in temperature and rainfall as well as mid-range projections of population change and other industry consumption change.
Table 4 Effect of climate change and CO2 increase for the years 2030 and 2070 on percent change in average production (currently 21.7Mt), value of production (currently $4.2 billion) and value of exports (currently $3.3 billion) assuming either current management practices or adapted management practices. The values in parentheses are the maximum and minimum values. These can be quite different from the average as they are the extreme 'tail' of the likely outcomes. The likelihood of these extremes can be assessed by looking at the respective probability graphs.
| Year 2030 | Year 2070 | ||
| Yield | - current - adapted |
3.1 (-9.1 to 10.1) 8.0 (-2.0 to 16.8) |
1.8 (-33.7 to 19.8) 8.5 (-32.8 to 29.0) |
| Value of production | - current - adapted |
0.4 (-7.4 to 4.0) 1.6 (-4.5 to 6.7) |
-0.8 (-29.8 to 9.1) 1.6 (-27.5 to 13.7) |
| Value of exports | - current - adapted |
-2.5 (-13.7 to 2.9) 0.0 (-8.8 to 7.3) |
-4.8 (-44.0 to 9.8) -0.6 (-41.0 to 16.5) |
Increases in atmospheric concentration of carbon dioxide and associated climate changes are likely to have significant effects on the Australian wheat industry, impacting on yields, regional productivity and values of wheat exports.
National impacts: year 2070
National grain production may increase slightly by the year 2070 as a net result of the beneficial effects of increased levels of CO2 and the often-negative impacts of climate changes. However, this result of a mean increase needs to be assessed against the one-in-three chance of reductions in national yield and that possible reductions in yield (25%) are greater than the possible increases (10%). When translated into value of national wheat production, there is a mean decrease in value of $35M and a 45% chance of value of production being lower than current levels. There is a skewed response with potential increases being limited to about $220M/year but decreases possible to about $800M/year although with low probability. The assumption that there is a reduction in area cropped with much drier conditions significantly increases the skewness of this distribution at regional levels (particularly the WA and SA sites) but makes little difference at the national level.
Regional impacts: year 2070
This national view increases in complexity when taken to the regions from which it is aggregated due to the markedly different regional climate changes in the year 2070. There exist four broad categories of regional response. For the cropping regions in West Australia, there is a high probability of decreases in regional wheat production (52 to 90%) and value of wheat production (52 to 97%). The decreases in value of the wheat produced are large (means of $13M to $104M/year for each region) and are likely to have major regional economic implications. Whilst this study focuses on wheat, impacts of similar relative magnitude are likely on other grain crops, oilseeds, forage crops and on other agricultural and horticultural activities found in similar regions of Australia (i.e. this excludes sugar cane). In contrast, there are also regions such as those around Emerald (Qld) and Wagga (NSW) in which there is calculated a very low probability of crop production/value being below current levels. In these regions, average value of production may increase by $13 M to $24 M/year.
There are two categories in the middle where there is calculated an increase in mean crop production and value, differentiated by the probability of these attributes being below current values. In one group (Minnipa, Horsham) the probability of regional crop value falling below current levels is about 25 to 27% whilst in the other group (Moree, Dubbo, Dalby), this is lower at 13 to 14%. In all cases, there is a negative 'tail' in the distribution which suggests that the downside risk is greater than the upside benefit.
Exports: year 2070
When the effects of CO2 increase and climate change are combined with increase in domestic consumption arising from population increase, there is a substantial decrease in the value of the crop available for export. For the ABS mid-range population projection for the year 2070 there is a high probability (72%) of a reduction in export income with a mean of a $164M reduction against current levels - the population growth component by itself causing about a $124 M reduction in average annual exports. The high population scenario decreases average export income by $261M/year with this reduction being about $121M for the low population scenario. If increases in feed consumption by livestock occur, then this reduction in export income may increase by about another $200M/year. The skewed distribution of the national production response follows through here, with only a 30% chance of increased value of exports in the mid-range population scenario (this is 11% and 39% for the high and low scenarios respectively. These results demonstrate the importance of dealing in an integrated way with scenarios for change. In this case, impacts of global change on wheat are magnified by relatively modest changes in consumption due to population growth. As noted before, these changes in the wheat industry are likely to be paralleled by changes in other primary industry sectors. The production from these cropping industries is in aggregate worth three times the value of wheat itself (Trewin 2001). In addition, there may be impacts on grazed livestock which produce product approximately five times the value of wheat.
Adaptation
Investment in developing adaptation strategies could be highly effective. When adaptations of changing varieties and changing planting windows are simulated across the Australia wheat growing industry for the year 2070, there is a marked offsetting of the negative impacts of global change (particularly in the WA sites) and an enhancement of the positive aspects (particularly in eastern Australia). Use of these readily implemented adaptation strategies changes the mean value of national production from a reduction of $35M/year to a gain of $61M/year - a difference of $96M. Similarly, in terms of export values adaptation changes the reduction in export value under the mid-range population scenario from a mean reduction of $124M/year to a reduction of only $17M/year - a difference of $107M. Furthermore, when adaptation is practiced, the likelihood of the value of production or exports being below current values falls by 29% and 40% respectively compared with 45 and 72% when no adaptation was practiced. In individual regions, adaptation could be worth $10M to $45M per year in increased mean regional wheat production when compared with the scenario where management remains the same as currently practiced.
Economic analyses
It is certain that the grain prices assumed in this report will vary by the years 2030 and 2070 due to highly uncertain changes in both global supply (from CO2, climate, technological and land use change and degradation) and demand (population growth, consumption per head and new uses e.g. biofuels) hence we have used these prices for comparative purposes only, within the framework of this study. However, studies of possible climate change impacts on global supply and demand (e.g. Rosenzweig and Parry 1994) suggest only relatively minor changes in prices due to similar changes in both factors. Hence on this basis, the assumptions regarding prices in this report don't seem unreasonable in the first instance. In contrast, the costs of inputs to production seem likely to increase substantially due to increasing costs of energy, technological and other inputs. It is feasible to expand the current study to assess the effects of such changes in costs as well as other assumptions about grain price and domestic consumption trends and international supply/demand ratios.
Impacts by year 2030
Changes to the wheat industry are not limited to the long-term future as there are potential impacts of global change evident in the year 2030 scenarios. Whilst mean regional grain production in Wongan Hills could reduce by a mean of only 3% there is a 65% probability that it will be below current levels. Value of production in that region may also fall by an average of $25M with only a small likelihood of increases (13%). In contrast, mean yields and value of production in Dalby could increase by 7% with only a small chance (7 - 13%) of being below current levels.
National average value of grain production in 2030 may be slightly higher than current levels ($19M/year) but there is a 32% chance of it falling below current levels due to climate change effects. As with the year 2070 scenarios, the skewed probability distribution gives positive outcomes limited to about $150M/year whilst the negative outcomes range to below $250M/year albeit with low probability. In contrast, value of wheat exports may fall by a mean of $82M for the ABS mid-range population scenario with a 91% chance of being below current levels. This fall in value is largely due to a rapid increase in domestic consumption of wheat as a result of population growth which reduces exports on average by $63M/year. Under the alternative population scenarios, mean exports may fall by between $60 and $114M/year for the low and high scenarios respectively.
Additional uncertainties
The results in this study are highly reliant on the simulation model used in the generation of the yield probability distributions and on the representativeness of the parameterisation used in the simulations. The model used (I-Wheat) has been validated for the CO2 response and effectively represents the changes likely within the range of CO2 concentrations used here. Similarly, the model has been tested in a wide range of environments which broadly cover those conditions simulated in the climate change scenarios. The model has also been tested against regional statistical yield data and performs well. However, the model does not incorporate possible changes in pest and disease incidence, changes in the frequency or severity of El Nino/La Nina events (although these could be encompassed in the mean changes in rainfall and temperature used) nor changes in resource status (ie soil condition) which may have trends due to climate change or to other factors such as ongoing soil salinisation. Climate change in particular may affect soil erosion risk and salinisation risk, but these remain to be studied.
Dryland salinity in particular is a potentially major factor not included in this study. Projections of trends suggest that a significant part of the cropping area of West Australia, NSW and Victoria may be affected, potentially reducing national grain production markedly. As noted before, such changes in addition to alterations in potential yield due to global change and increases in domestic consumption can have major consequences on value of exports.
It is feasible that technological changes may be sufficient to offset any reductions in yield arising from global change. For example, productivity increases from genetically modified organisms have been widely touted. However, experience to date in the USA indicates that when these varieties are used commercially, there is only marginal improvement in yields or in use of pesticides. An alternative offsetting factor may be to further develop the residue management and seasonal forecasting capability that exists currently to offset some of the risks of production loss in a more challenging climate. Development of varieties which increase grain nitrogen concentration to offset the effects of CO2 increase may also be a useful R&D direction.
We would like to thank Peter Whetton (CSIRO Atmospheric Research) and Brian Keating (CSIRO Sustainable Ecosystems) for reviewing the draft manuscript.
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