Application And Issues Of CEA In Conservation

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Evaluating interventional programs that are and have been implemented are based mostly on ecological factors for success. For example, evaluating a conservation intervention programme based purely on species status (Salafsky and Margoluis, 1999). However, it is also important that investments in conservation should also be evaluated in order to decide which conservation options would provide the highest optimal conservation return on investment (Murdoch et al, 2007). Accounting for the efficiency of conservation options by measuring costs and the conservation outcome or return per unit of investment, can give a more accurate evaluation for a conservation option or programme (Carwarde et al, 2008). Therefore, efforts should be invested for the development of transparent tools that can thoroughly evaluate the efficiency of conservation programmes and interventions through scientific, objectively constructed methods such as CEA, which may provide an important role in the evaluation within conservation (Moran, Laycock and White, 2010).

Using CEA to evaluate conservation programmes can avoid the assumption that all species provide equal utility when compared to each other and resulting in the costs of certain conservation programmes and interventions being unable to correlate with its effectiveness. This lack of correlation can result in poor resource allocation and management, as implementing costly conservation programmes, plans and priorities may not be considered the most effective at meeting its conservation goals (Laycock et al, 2009).

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Laycock et al (2009), suggests that applying CEA by initially weighting species by their predetermined utility will dramatically affect the ranking of different conservation programmes especially those targeted for different species within Species Action Plans (SAP). It was found by Laycock et al (2009), that implementing vertebrate SAPs, specifically mammals and birds were very inefficient without accounting for weighting species by their utility. In contrast, once utility-based weighting was applied, vertebrates became to have some of the most efficient SAPs, due to the extra information or evidence being accounted for, such as larger home ranges than invertebrates in this specific case. In addition, a correlation between the cost of SAPs and the effectiveness of the SAPs meeting their targets were found. In the case of evaluating the cost-effectiveness of UK Biodiversity Action Plans, using this CEA model found that resource allocation was efficient, whereas not using this model found it inefficient (Laycock et al, 2009) showing vast contradictions between analysis methods. This can be a good example for how CEA can be used and applied in conservation. Although, the weighted efficiency values Laycock et al (2009) used in their study were just based on home ranges, it was also suggested that this can be expanded on and developed to produce a more accurate level of analysis by including more comprehensive ecological and social factors and possibly ecosystem good and ecosystem services within any weighting systems, to produce a CEA suitable for conservation.

It is argued that if conservation management options are continuing to be chosen based on just anecdotal evidence, personal experience and the lack of information of effectiveness, it will become increasingly more difficult to argue for conservation interventions within current economic development and measurements (Pullin and Knight, 2001). However, this would require a change in policy among some countries such as the UK, that would have to necessitate conservationists and conservation managers to keep accurate records of cost, such as the USA , as many currently do not do at the moment (Fairburn, Hughey and Cullen 2004). However just as policy changes in health care towards more evidence based treatments were implemented, no longer allowing medical professionals to prescribe medicines and treatments based on speculation and without in depth scientific knowledge of effectiveness, it is implied that the same should be applied to conservation policies. This would allow for more accurate calculations when monitoring and making decisions (Pullin and Knight, 2001). In addition, the appetite towards evidence-based policy to be used in environment and conservation sectors from other areas such as, CEA in the healthcare sector, is greatly increasing (Pullin and Knight, 2001; Holmes and Clark, 2008).

In order to implement the widespread use of CEA throughout conservation sectors, lessons can, again, be learnt from health care, regarding the methods involved. Pullin and Knight (2001) states that the methods involved may have to include: creating policy throughout the conservation sector for evidence based conservation options and interventions, using funding and investment as an incentive for the use of evidence based options, to develop methods of systematic reviewing, identifying any gaps in the scientific knowledge in order to prioritize the research that needs to be undertaken and, setting minimum standards of practice for conservation interventions, with reference to using the systematic reviewing methods that are developed to correlate with receiving funding, including the scientific justification of the effectiveness of any proposed intervention.

Issues of CEA in conservation can be argued that due to the complexity of biodiversity, the weighted status metric methods used can be limited in its value standard for creating a common outcome, by creating a relationship of proportionality when measuring between different species. This can obstruct the development of these metrics (Hockley, 2009). However, CEA and similar tools of analysis are always hindered by the need for a common outcome metric and therefore, this issue is not just exclusive to CEA in conservation (Laycock et al, 2009). To address this issue Hockley (2009) does suggest that more suitable weighting status metrics could be metrics that can be considered to be more“socially constructed”. For example, monetary valuation methods used in Cost Benefit Appraisals. However, to refute this, supplanting scientific objectivity with a more “socially constructed” measurement narrative can lead to considerable more uncertainty in defining evidence and methods or best practice involved and does not lend itself to the adaptive processes of creating and developing new policies (Moran, Laycock and White, 2009). As evaluating programmes and interventions, their stated aims/objectives and assigning weighted status to species can make it easier to develop these adaptive policies.


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