| Abstract: |
| As diversity of fauna and flora in the landscape is disappearing with natural forests around the world, efforts to save biodiversity have increased over the years. Many man-managed systems (e.g. jungle rubber) are becoming increasingly important as biodiversity reservoirs.
Different mechanisms of ‘payment for environmental services’ or PES are being developed that aim to ‘reward’ local people for their contribution to conservation practice. The Rapid Agro-Biodiversity Appraisal or RABA (Kuncoro et al. 2006) approach was developed as an analytical framework to identify the information necessary for providers and beneficiaries of biodiversity protection in order to engage in environmental service agreements. While the approach deals well with the perspectives of both the sellers and the potential buyers of conservation services, the approach does not include a ‘rapid’ assessment of existing biodiversity in the target are. The assumption that biodiversity data for potential sites are available is not always correct and even when data is available, these tend to be outdates. As time, resources and expertise required for comprehensive inventory of flora and fauna are often limited; one often has to resort to short-cut checks, using selected indicators of biodiversity, for reasonably good indication of existing biodiversity.
The Quick Biodiversity Survey (QBS), under development, is a combination of quick inventories of plants, birds, beetles, bats, primates and mammals adapted for rapid checking of these ‘visible’ biodiversity. The plants and animal groups are surveyed in sample points, at every 100 metres along 1-2 km transects. Some biophysical measurements such as temperature of soil and air, soil pH, humidity, seasonal rainfall, distance from village and human population are also recorded. Generally, the field work takes about two weeks, followed by another two weeks of analysis and interpretation. The QBS method is currently under test in a range of agro-ecosystems in Indonesia. Further refinement and fine-tuning should be possible based on context and need. |
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