abare.gov.au

ABARE is collaborating with the ANU and New South Wales Government agencies and Catchment Management Authorities (CMAs) to develop and test a decision-support framework for prioritising catchment management investment options. This note provides a context for this work and a short description of the project.

Context

In response to increased concerns about sustainability, government expenditure on environmental and natural resource management programs in Australia has increased substantially since the early 1990s. For example, the Natural Heritage Trust (NHT) was allocated around $2.8 billion from 1996 to 2007, and the Caring for our Country initiative has been allocated $2.25 billion over five years from 2008.

This level of government expenditure, combined with public pressure to generate clear outcomes, raises the question of how funds should be allocated in order to achieve the greatest value for money and how to ensure the best outcomes are obtained for society. To date, however, it has been difficult to assess progress. On this point, the Australian National Audit Office (ANAO) stated:

The information reported in the Department of Agriculture, Forestry and Fisheries (DAFF) and NHT Annual Reports has been insufficient to make an informed judgement as to the progress of environmental programs towards outcomes; and

There is little evidence as yet that the programs are adequately achieving the anticipated national outcomes or giving sufficient attention to the ‘radically altered and degraded Australian landscape’ highlighted in the 1996 Australia: State of the Environment Report (State of the Environment Advisory Council 1996).

The ANAO reported documentation of the economic costs and benefits of different on-ground actions needs to be substantially improved and there is still little information as to what options are best for delivering value for money outcomes (ANAO 2007). The recently launched Caring for Our Country initiative will involve, ‘…a business approach to investment, clearly articulated outcomes and priorities and improved accountability’ (www.nrm.gov.au/funding/future.html ).

Assessing options

Ideally, the net value of all benefits and costs to society of proposed investments should be used to rank options. If all costs and benefits can be measured in dollar terms, then a social benefit-cost analysis (BCA) would provide a ranking of options against the criterion of maximising social welfare.

The main difficulty with BCA is that all costs and benefits need to be measurable in monetary terms. This is difficult because of the public good nature of most environmental services. Markets do not exist for services provided by the environment, so the monetary value of environmental goods and services is not observable. Also, some of these goods cannot be easily identified because of their non-use values. For example, people may derive satisfaction from knowing good quality environments exist or people may value having the option to use these goods in the future or preserve them for future generations. Native vegetation, for example, can provide a range of benefits including improved wildlife habitat, improved water quality, reduced salinity, control of land degradation and other ecosystem services (Lockwood, Walpole and Miles 2000; Productivity Commission 2004; Sinden 2005).

There are techniques available for estimating non-market values. However, identification and valuation of environmental goods is often complex, costly and time consuming and environmental project assessments are usually undertaken without directly estimating them (Hanley and Spash, 1993).

Alternatives to BCA have been developed which do not require monetary estimates of non-market values. If these non-monetary measures of non-market benefits are available, then it may be possible to determine which investments achieve different levels of these non-market values for the lowest net social cost. Decision-makers have to determine whether the non monetised environmental benefits justify the estimated costs. This type of analysis is referred to as cost effectiveness analysis (CEA) or threshold analysis. In some work multiple environmental benefits are quantified using a single metric such as an environmental benefits index (EBI). Such approaches are sometimes referred to as cost utility analysis (CUA). Examples of these different approaches include Tecle(1992); Davidson et al. (2006a); Davidson et al. (2006b); Hajkowicz 2007; Proctor 2005; Parkes et al. 2003; Hajkowicz and Collins, 2008.

In multi-criteria analysis (MCA) all the values of interest are quantified and aggregated using a set of weights. At one extreme this could be used to carry out a CEA or CUA and involve combining monetised and non-monetised values into a single overall index to provide a ranking of options.

This might also involve including biophysical models to capture interdependencies between the values. If the weights used are estimates of the prices or non-market values then such an analysis would be a BCA. At another extreme MCA can simply involve giving each option a score on a standard scale for each value of interest. These individual scores are then added up using a set of weights to give an overall score for each option. This can be very cheap and easy to implement but the usefulness of the results will depend on the problem being addressed.

Optimisation framework to support CMA investment decisions at a catchment scale

The ABARE, ANU, NSW Government collaboration is developing and piloting a decision-support framework for the assessment of different catchment management strategies to assist catchment management authorities in NSW to comply with the Natural Resources Commission (NRC) Standard for Quality NRM and enhance the allocation of limited investment funds (NRC 2005) (see the scoping report, Feb 2008, [= http://www.namoi.cma.nsw.gov.au/attachments/OptFramework.pdf] for more information).

An integrated biophysical and socioeconomic prioritisation framework is being developed that will support decisions by:

assisting CMAs to evaluate the environmental, social and economic tradeoffs resulting from a range of investment strategy options;

providing forecasts of the effects of management actions on environmental outcomes and contributions to achieving management targets at catchment and site/property scales; and

accounting for spatial heterogeneity of the landscape in which CMAs must attempt to optimise their investments in natural resource management.

The goal is to develop a framework that will enable CMAs to meet the standards set by the NSW Natural Resources Commission (NRC 2005). The standard calls for CMAs to:

use the best available knowledge to inform decisions in a structured and transparent manner; and

manage natural resource issues at the optimal spatial, temporal and institutional scales to maximise the effective contribution to broader goals, deliver integrated outcomes and prevent or minimise adverse consequences.

The components of the project are:

collaboration with CMAs to focus on their needs;

assembly of available biophysical data and models for use in spatial optimisation;

integrated non-market valuation; and

refinement of a spatial optimisation tool to incorporate the estimates of the non-market values.

The spatial optimisation tool, MOSAIC, developed by ABARE, is used for exploring options. MOSAIC is being used to identify the wide range of trade-offs that could be generated by different levels of investment and cost-effective configurations of management changes. The trade-offs are estimated at the catchment level based on the set of relationships among biophysical values market values and non-market values that are embedded in the tool (see chapter 4 in the scoping report). For example, monetary losses in farm revenues are included in management options that remove land from cultivation. MOSAIC can also include the estimated benefits of improved water quality, carbon sequestration and biodiversity. When estimates of the monetary values of these environmental benefits are available these can be included in order to carry out a BCA of the available investment options.

The tool makes full use of available spatial information and the MOSAIC optimisation process accounts for the complex set of relationships among land and water characteristics - land cover, slope, soil and water quality – management changes and the environmental outcomes by using currently available biophysical models.

The stated preference survey technique, choice modelling (CM) is being used to assess community preferences for environmental improvements and estimate the non-market values (Mazur and Bennett 2008a) [=http://www.crawford.anu.edu.au/research_units/eerh/pdf/EERH_R_no1.pdf]). A survey instrument has been developed with expert regional CMA input and it has been tested with focus groups (Mazur and Bennett 2008b [= http://www.crawford.anu.edu.au/research_units/eerh/pdf/EERH%20RR2.pdf]). The answers to the survey questions enable researchers to estimate the value attached to a range of levels of environmental improvements.across large areas of NSW.

The case study regions include large parts of the Namoi, Lachlan, and Hawkesbury-Nepean CMAs. Posters giving background for the survey respondents are available here [links/thumbnails at top of page]. Focus group meetings and expert CMA input were completed in the first half of 2008 and surveys of CMA residents, Sydney residents and residents of an additional rural community are underway in July 2008. Analysis results will be available in September 2008 and these will be combined with the MOSAIC framework with initial results by December 2008.

Next steps

The results of this project will be available early in 2009 to inform the process of prioritising investments in NSW. The framework aims to:

incorporate measures of target variables and indicators of change;

apply across different types of natural resource investment;

include biophysical and monetary measures;

include market and non-market values in dollar values;

be useful to non-expert staff; and

be used readily both to rank options and to evaluate post investment outcomes.

These reflect the requirements of the NRC Standard also mirror the key requirements as set out by the ANAO for a prioritisation framework suitable for ranking options and evaluating the value-for-money of natural resource and environmental investments. Thus this project will contribute to a better understanding of how to prioritise options and assess the extent to which value-for-money is being achieved.

References

Australian National Audit Office, 2007, Commonwealth natural resource management and environment programs. Audit Report No. 36. Australian National Audit Office, Canberra

Davidson, A, Lawson, K, Kokic, P, Elliston, L, Nossal, K, Beare, S and Fisher, BS, 2006a, Native Vegetation Management on Broadacre Farms in New South Wales: Impacts on Productivity and Returns, ABARE eReport 06.3, Canberra.

Davidson, A, Beare, S, Gooday, P, Kokic, P, Lawson, K and Elliston, L, 2006b, Native Vegetation: Public Conservation on Private Land – Cost of Forgone Rangelands: Development in Southern and Western Queensland, ABARE Research Report 06.13, Canberra, September.

Hajkowicz, S, 2007, Allocating scarce financial resources across regions for environmental management in Queensland, Australia., Ecological Economics Volume 61, Issues 2-3, 1 March 2007, Pages 208-216.

Hajkowicz, S and Collins, K, 2008, Quantifying the Benefits of Natural Resource Management, CSIRO Draft Discussion Paper to the Australian Department of the Environment, Water, Heritage and the Arts, April

Hanley, N and Spash, CL, 1993, Cost-Benefit Analysis and the Environment, Edward Elgar Publishing Limited, UK.

Mazur, K and Bennett, J 2008a, Choice modelling in the development of natural resource management strategies in NSW, Environmental Economics Research Hub Research Report number 1, February. Accessed: http://www.crawford.anu.edu.au/research_units/eerh/pdf/EERH_R_no1.pdf

Mazur, K and Bennett, J 2008b, Using focus groups to design a choice modelling questionnaire for estimating natural resource management benefits in NSW, Environmental Economics Research Hub Research Report number 2, March. Accessed: http://www.crawford.anu.edu.au/research_units/eerh/pdf/EERH%20RR2.pdf

Natural Resources Commission, 2005, Recommendations: Statewide Standards and Targets, Natural Resources Council, Sydney.

Parkes, D, Newell, G and Cheal, D, 2003, Assessing the quality of native vegetation: the ‘habitat hectares’ approach. Ecological Management and Restoration. Vol 4 Supplement February

Proctor, W, 2005, MCDA and stakeholder participation: valuing forest resources. In Getzner, M, Spash, C and Stagl, S, Alternatives for environmental valuation, Abingdon :Routledge: 134-158.

Productivity Commission 2004, Impacts of Native Vegetation and Biodiversity Regulations, Report no. 29, Melbourne.

Sinden, JA, 2005, Conservation of native woodland by farmers in Moree Plains Shire, New South Wales, Australian Forestry, vol. 68, no. 1, pp. 65–72.

State of the Environment Advisory Council, 1996, Australia: State of the Environment, An Independent Report Presented to the Commonwealth Minister for the Environment. Accessed: http://www.environment.gov.au/soe/1996/publications/report/index.html

Tecle, A, 1992. Selecting a multicriterion decision making technique for watershed resources management, Water Resources Bulletin 28:1, pp.129-140.