Michael O'Connell

Plantings of non-commercial trees are sometimes considered for the management of groundwater levels and dryland salinity in Western Australia. This is especially the case in low rainfall areas of the wheatbelt where the number of salinity management options available is limited. The purpose of this analysis is to provide insights into the impact of non-commercial trees on recharge and farm profits, and to draw conclusions and implications for researchers and extension personnel.

A whole farm bio-economic model (MIDAS) is used to assess the place of non-commercial trees in the wheatbelt farming system for a range of scenarios. Several factors are identified as important considerations in the decision to plant trees for recharge control. These include initial levels of recharge, opportunity cost of converting land from agricultural production to trees, and whether flexibility in the farm plan can be maintained so as to adapt to seasonal conditions and maximise profits.

The analysis suggests that small areas of non-commercial trees can be established without incurring large decreases in profit. However, such activities are unlikely to significantly impact on overall recharge levels. The costs associated with establishing enough trees to significantly impact on recharge will almost certainly lead to negative profits. Furthermore, it is suggested that the farms with the highest levels of recharge will be least able to afford even small areas of trees. The implications of these findings for researchers and extension personnel are discussed.

Dryland salinity threatens agricultural production on large areas of land in Western Australian (Ferdowsian et al 1996). The removal of native perennial vegetation and its replacement with annual crops and pastures has resulted in more water being added to the landscape than pre- clearing. As a consequence water tables are rising, bringing large amounts of salt to the soil surface (George et al 1996). Over time the soil becomes highly saline and hostile to many native and introduced plants. Salinity that has developed as a result of land clearing is referred to as secondary salinity, and is distinct from primary salinity (e.g. salt lakes) that existed prior to the clearing of the land. The effects of secondary salinity are not limited to agricultural production - rising saline groundwater threaten wetlands, forests, homesteads, towns, roads, railways and fresh water supplies (State Salinity Council 1998).

A range of strategies are available to help combat dryland salinity. These include using plants with high water use capacities such as trees, shrubs, perennial pastures, and long season annuals (e.g. George 1991, Lefroy and Scott 1994); and modifying the landscape to intercept and remove excess water by drainage or pumping (e.g. McFarlane and Cox 1990, McFarlane et al 1990). In higher rainfall areas some of the strategies employed to manage dryland salinity are able to contribute directly to farm profits. For example, Tasmanian Bluegums are a viable option on many farms in the Southwest of Western Australia (Eckersley 1994), while lucerne, a perennial pasture species, has been shown to be profitable on the South Coast (Bathgate and Pannell 2002).

In lower rainfall areas of the wheatbelt there are less options available to farmers for managing salinity. Attempts are being made to develop profitable strategies for these areas, such as oil mallees and dryland lucerne. However, these strategies are not suited to all situations and are still undergoing substantial research and development. For this reason, non-commercial trees remain one few strategies available to farmers in low rainfall areas of the wheatbelt.

The purpose of this analysis is to assess the impact of non-commercial trees on recharge and farm profits. A three to five year outlook was used. It is recognised that this time frame is too short to assess the long-term benefits of trees. However, from a farm management point of view the analysis is highly relevant, as it provides insights into the short–medium term financial implications that a farmer will face when considering planting trees. In particular, the analysis will provide information about:

• Opportunity costs of converting land from agricultural production to trees.
• The relative effectiveness of trees on different soil types.
• The likely trade off between farmers’ profit and non-profit objectives.
• The indirect costs of trees to the farm business.
• Likely patterns of adoption and farmer behaviour.

This information may prove valuable to researchers and extension personnel as an input to formulating research priorities and advice.

The Eastern Wheatbelt (Merredin) version of MIDAS (Model of an Integrated Dryland Agricultural System) was used in the analysis¹. MIDAS is a whole farm bio-economic model that selects profit maximising farm management strategies subject to resource, technical and environmental constraints. Optimal management strategies are derived using the linear programming technique. The model includes components for crops (cereals, legumes and canola), pastures, sheep, stubble, grain feeding, finance and machinery. The model is strongly based on soil types with each rotation on each soil type having its own production figures (Pannell and Bathgate 1991).

The Eastern Wheatbelt version of MIDAS was adapted to include non-commercial trees. The non-commercial trees are assumed to be mixed species grown in blocks. Establishment involves ripping and mounding the ground where each row of trees will be planted, and spraying for weeds in a two metre wide strip over each row four weeks prior to planting seedlings. The herbicides used are glyphosate and simazine. These chemicals are slightly antagonistic to one another, but can be tank mixed safely (Piper 1993). Rows of trees are five metres apart and there is a space of five metres between each tree in a row, i.e. 400 trees/ha (D. Bicknell, pers comm). The details of the costs of trees are outlined in Table 1.

* Notes: Herbicides are applied to only 40% of the soil surface within an area sown to trees (i.e. a 2 metre wide strip in every 5 metres). Therefore, actual application rates for glyphosate and simazine are 1 and 4 L per hectare of sprayed ground. The cost of fencing will vary according to the shape and size of the plot being planted to trees, and if existing fencing can be utilised. A figure of $70 per hectare of trees is allowed for in this analysis. This is the approximate cost per hectare of fencing two sides of a 40 ha square block of trees (i.e. assume that the other two sides are contained by existing fences). The total cost of trees in the analysis was converted to an annuity payable over the lifetime of the trees (taken as 30 years). This is the same as the annual repayments if the money to plant the trees was borrowed and paid back over their lifetime.

Recharge values for trees, annual crops and pastures were also included in the model. To gain an appreciation of the relative amounts of recharge under different annual crops and pastures, the AgET Water Balance Calculator² was run using rainfall data from Merredin for the years 1954 to 1993. Data files that matched the physical and biological characteristics assumed in MIDAS were specifically created for the AgET model runs (P. Raper and D. Sawkins, pers comm). The recharge figures used for each soil type and species are outlined in Table 2.

The analysis involved forcing MIDAS to find an optimal solution where average recharge across the whole farm was restricted to certain levels. With this approach it was possible to examine the impact of imposing an environmental constraint (in this case recharge reductions) on tree area, optimal enterprise mix and whole farm profit.

The standard Eastern Wheatbelt version of MIDAS includes a mix of soil types considered to be representative of the Merredin Shire. In addition to the standard version, several sub versions of the model were created to allow different soil mixes to be examined. The soil mixes included can be described as a heavy land farm, a mixed quality light land farm, a good quality light land farm, and a poor quality light land farm (see Table 3). Total farm area for each soil mix was 2500 hectares. Availability of credit was also identified as an important factor in the ability of a farmer to plant trees. To account for this, each analysis was repeated with a range of overdraft limits imposed.

Each time non-commercial trees are planted on land that was previously used for agricultural production, profit that could have been generated from that land is forgone. The amount of profit forgone is termed the opportunity cost. Knowing the opportunity cost of different soil types is important, as it provides an indication of the impact on whole farm profit of converting agricultural land for conservation purposes. An indication of opportunity costs³ and annual recharge figures for each of the seven soil types represented in the Eastern Wheatbelt MIDAS is presented in Table 4.

From Table 4 it is evident that the soil types with the lowest opportunity cost are the acid sands ($25/ha/year) and the poorer quality heavy country ($40/ha/year). Ideally, any land converted for conservation purposes would consist of one of these soil types. To convert other land would incur a higher opportunity cost.

In this case the objective is to reduce recharge using non-commercial trees. The figures in Table 4 indicate that a large amount of recharge occurs under acid sands, but that very little occurs under the heavy country. Converting acid sands to non-commercial trees is likely to provide significant recharge abatement at relatively low opportunity cost. Similar levels of recharge abatement would also be possible on the good sandplain country, but would incur a much higher opportunity cost.

By contrast, although the opportunity cost of the poorer heavy country is low, converting this land to non-commercial trees is not expected to have any measurable impact on recharge levels. This has important implications for farmers considering planting trees for recharge control, in that it may be tempting to plant trees on land that is otherwise performing poorly (i.e. to minimise opportunity cost). However, from the data in Table 4, it is clear that this may not achieve the desired environmental objective of managing salinity.

Standard Eastern Wheatbelt MIDAS soil mix

Whole farm profit with different levels of recharge is shown in Figure 1. The profit maximising farm plan includes no trees and has a profit of about $60 000. Some minor reduction in recharge is possible without trees. This is achieved by substituting within the range of agricultural species already used, and is almost as profitable as the profit maximising farm plan. However the reduction in recharge made possible by this method is small and unlikely to result in salinity abatement.

In order to achieve further reductions in recharge, land must be planted to non-commercial trees. The most cost-effective way to achieve this is by planting on the acid sands. Taking this land out of production reduces profits, but by less than any other soil type. However there is a limit to the amount of acid sands available. If all acid sands have been planted to trees and a further reduction in recharge is required, then trees must be planted on the good sandplain. This results in large reductions in recharge, but comes at a high opportunity cost (Figure 1).

The trade off between profit and recharge for a heavy land and mixed quality light land farm are illustrated in Figure 2 (see Table 3 for soil areas). The results indicate that heavy and light land farms differ significantly in their ability to achieve cost effective salinity abatement using non-commercial trees. On farms with mostly heavy land, the ability to reduce recharge using trees is limited as recharge levels under crops and pastures are already relatively low. Taking land out of agricultural production for non-commercial trees leads to large reductions in profit without greatly changing recharge. By contrast, recharge levels on farms with a lot of light country are much higher under an annual crop and pasture system, hence there exists the capacity for some reduction in recharge using non-commercial trees.

Light land dominant farms will also differ significantly in their capacity to use non-commercial trees for recharge control depending on the quality of soil types. Figure 3 presents the trade off between profit and recharge for good and poor quality light land farms (see Table 3 for soil mix details). Both farms are able to reduce recharge to some extent without a large reduction in profit. This is achieved by substituting within the range of available annual crops and pastures.

If further reductions in recharge are desired then non-commercial trees must be planted (in the absence of alternative options). On poorer quality light farms, devoting land to non-commercial trees soon results in negative profits. This is because initial profit levels are relatively low. Consequently, non-commercial trees are unlikely to be viable on farms dominated by poor quality light country. This leaves us with a serious conundrum – the farms that are probably contributing the most to the salinity problem are least able to afford adopting non-commercial trees for salinity management.

Farms dominated by good quality light country will be better placed to reduce recharge than poor quality light farms, however the opportunity cost of good light land is high and profits will rapidly decline as more area is planted to non-commercial trees.

The establishment and opportunity costs of non-commercial trees have already been examined. In addition to these costs, the decision to devote financial resources to planting trees will reduce the ability of the farm manager to respond to changing production and price conditions. For example, tight finances may make it difficult to adjust the area of farm cropped from year to year (e.g. insufficient funds to cover cost of an increase in herbicide and fertiliser requirement). As a result, it may not be possible to adapt quickly enough to take advantage of good seasons and minimise risks in poor seasons. This will result in forgone income due to a lack of flexibility.

Consideration of this "flexibility cost" is particularly important, but often overlooked. Farm income in the Eastern Wheatbelt is very unevenly distributed over time, with approximately 50% of long-term income received in less than 2 out of 10 years (R. Kingwell, pers comm). The ability to maximise returns in good years and minimise risks in poor years depends upon tactical changes in response to seasonal conditions. However, if financial resources have been devoted to growing non-commercial trees, the ability to make tactical changes may be restricted.

While MIDAS does not account for seasonal production and price variability, this analysis can provide insights into the impact on farm profit of having inadequate levels of finance. The results presented in Figure 4 demonstrate the importance of credit availability for maintaining farm profits when a recharge constraint is imposed (results are for a mixed quality light land farm). In the case where the overdraft limit is $125 000, profits begin to decline rapidly as recharge is reduced. This is primarily because there are insufficient funds available to put in as much crop as would otherwise be optimal. In contrast, where the overdraft limit is $175 000, there are adequate funds to put in enough trees to reduce recharge, and to maintain crop area at optimal levels. As a result, a relatively large reduction in recharge is achieved with only a small decline in profit.

The results of this study indicate that although non-commercial trees may be used to reduce recharge, achieving significant reductions by this method will result in large profit losses to farmers. Recent research in Western Australia suggests that in many areas of the state, trees would have to influence as much as 70-80% of water catchment areas to achieve reductions in water tables and salinity control (George et al 1999). Plantings of non-commercial trees on such a scale would make farms unprofitable. On the other hand, smaller plantings used in conjunction with other (preferably more profitable) salinity control measures may be attractive for farmers to adopt, especially if they fulfill non-profit objectives relating to stewardship of the land (e.g. tree planting for aesthetics or wildlife corridors).

Non-commercial trees have the potential to contribute to salinity abatement in low rainfall areas of the wheatbelt through reducing recharge levels and, in some cases, drawing down groundwater levels. However, it is not economically feasible for farmers to rely on non-commercial trees as the only means for managing salinity because the area of plantation required will result in farms becoming unprofitable. Therefore it is vital that economically viable salinity management options be developed for the areas such as the Eastern Wheatbelt.

In particular, the following points need to be kept in mind by researchers and extension personnel when formulating research priorities and advice:

• The opportunity costs of land provide an indication of the impact on farm profits of converting different soil types from agricultural production to non-commercial trees. Soil types with lower opportunity costs are to be preferred, providing that planting trees on these soil types will indeed have the desired impact on recharge and salinity abatement. In some cases, land with a low opportunity cost may not be suitable for tree planting (e.g. poor quality heavy country where the initial recharge under an agricultural system is low).
• It is probable that the farms that are contributing the most to a salinity problem (i.e. farms dominated by poor quality sandy soils) will be unable to afford even small areas of trees. The research and development of viable alternatives for poor quality sands is a high priority.
• The costs incurred from planting trees may restrict the flexibility to make tactical changes in the farm plan in response to seasonal production and price variability. This would threaten the ability to maintain long term income at desired levels.

In using an outlook of 3-5 years, this study has focused on the short–medium term financial implications of non-commercial trees. It is recognised that such an approach ignores the long-term benefits of trees – something that may be perceived as a weakness of this analysis. However, the results of the study suggest that if a farmer were to plant enough non-commercial trees to manage salinity, the negative impact on profits in the short term would result in bankruptcy well before the long-term benefits began to be realised.

Paul Raper and Doug Sawkins created the data files for the AgET Water Balance Calculator and provided helpful comments on using the model. Thanks to David Bicknell, Ruhi Ferdowsian and Ross Kingwell for helpful discussions, and to Andrew Bathgate and David Pannell for suggestions on the application of MIDAS for analysing salinity management strategies.

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