. Biodiversity indicators in national forest inventories. 7 000 6 GOO 5 000 4 000 S 3000 2 000 1 000. 4 5 6 Spatial integrity class'' 8 9 10 â 1 = lowest or most fragmented. 10 = core forest in large expanses. Forest area of Belize by spatial integrity class - statistical summary processes of interest and about the uncer- tainty surrounding these relationships. A variety of different frameworks are available for the development and imple- mentation of biodiversity indicators. Al- though some of these (notably the pressure-state-response framework) are now in widespread use, future research is
. Biodiversity indicators in national forest inventories. 7 000 6 GOO 5 000 4 000 S 3000 2 000 1 000. 4 5 6 Spatial integrity class'' 8 9 10 â 1 = lowest or most fragmented. 10 = core forest in large expanses. Forest area of Belize by spatial integrity class - statistical summary processes of interest and about the uncer- tainty surrounding these relationships. A variety of different frameworks are available for the development and imple- mentation of biodiversity indicators. Al- though some of these (notably the pressure-state-response framework) are now in widespread use, future research is likely to produce more refined methods of structuring and organizing indicators. In particular, there is a need to develop practi- cal tools that can assist in the development and application of biodiversity indicators, based on such frameworks. The provision of such tools, together with a programme of capacity building, would help increase the use of indicators among decision- makers and would improve the quality' of environmental monitoring. To date, despite the international effprt focusing on indica- tor development, such indicators have only rarely been implemented in a practical way to inform policy development or manage- ment interventions. The eight general indicators for forest biodiversity identified in this article are consistent with those developed by criteria and indicators processes but are amenable to practical implementation at the local level. It may be necessary to adapt each of these indicators to local circumstances and forest characteristics. Methodologies for assessing these variables are available and could be implemented at relatively low cost through integration with standard forest in- ventory approaches. Aggregating information collected at the local scale for the purposes of national-level assessment and reporting to international processes and conventions can be achieved by summarizing data in categorical forms and combining them in relation to fo
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