An Exploratory Study of Cost-Benefit Analysis of Landscape Restoration

Owing to the increasing demand for restoration globally and limited resources available, there is a need for economic analysis of landscape restoration to help prioritize investment of the scarce resources. Cost-benefit analysis (CBA) is a commonly applied approach in the economic analysis of landscape restoration as well as for strategizing and prioritizing resource allocation. However, despite the growing number of studies and projects on restoration globally, studies on cost-benefit analysis of landscape restoration are relatively few. A systematic review of the cost-benefit analysis of landscape restoration was conducted to understand the extent and coverage of existing studies, as well as gaps. After a comprehensive search and filtering of the studies, 31 that met the various guidelines of CBA of landscape restoration were identified. These are distributed across different regions globally, with the majority of them in Sub-Saharan Africa and Asia. The CBA studies reviewed were conducted for different types of restoration options/strategies including; reforestation and afforestation, agroforestry, biofuel agroforestry, participatory forest management, establishment of woodlots, sustainable land management practices, natural regeneration, assisted natural regeneration, mangrove restoration, clearing of invasive alien species, and restoration of urban and buffer areas. A larger proportion of the studies focused on agroforestry, reforestation and afforestation. For some restoration options, all the studies conducted reported positive net present value (NPV); agroforestry (8), soil and water conservation (5), mangrove restoration (3) and alien vegetation clearing (3). However, for some of the restoration strategies, several studies reported negative NPV: in reforestation and afforestation, the number of studies that reported positive NPV (4) was equal to those that reported negative NPV (4). In terms of accounting for benefits accruing from restoration, majority of the studies accounted for the use values only (either direct use or indirect use or both), and only around 16% accounted for non-use values. This is because non-use values and some of the indirect use values are not easy to quantify since they do not have a market price. Accounting for the total economic value of a project is particularly useful for large-scale restoration initiatives where the benefits accrue to the broader public beyond the targeted stakeholders. Similarly, for cost components, relatively few studies accounted for the opportunity cost component. This is probably because it is often difficult to estimate this cost since it is not a direct cost and for some land uses the opportunity cost may be negligible, especially if the land is highly degraded. Further still, some restoration projects fail to account for maintenance and monitoring costs since they view restoration as a one-time cost activity, as opposed to a continuous activity where maintenance and monitoring costs are significant. Future costbenefit analysis studies ought to account for all the benefits and cost components attributable to restoration; otherwise, profitability of restoration projects could either be over- or understated. Similarly, lack of reliable data owing to poor data-keeping during the restoration period also affects CBA results. This requires data over several years, and most projects do not keep such records. Hence, even for ex-post CBA evaluations, a lot of predictions and assumptions are involved in data generation. Thus, there is need to adopt standardized methods of data prediction if the results are to be comparable across different restoration projects that would guide decisions in the allocation of funds. An ongoing project, ‘The Economics of Ecosystem Restoration (TEER)’ aims to “offer a reference point for the estimation of costs and benefits of future ER projects in all major biomes, based on information from comparable initiatives on which data are collected through a standardized framework”.

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DOI:

https://doi.org/10.5716/WP20014.PDF

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