. Biodiversity indicators in national forest inventories. The incidence and intensity of both natu- ral and antliropogenic disturbance can pro- foundly influence forest structure and composition, and therefore affect the avail- abiUty of habitat for different groups of or- ganisms. Disturbances may be caused by small-scale processes such as the senes- cence and death of individual trees, or large- scale processes such as hurricanes or fire. Assessing disturbance can be difficult, how- ever; indicators of disturbance may need to be developed or adapted at the local level according to the charac
. Biodiversity indicators in national forest inventories. The incidence and intensity of both natu- ral and antliropogenic disturbance can pro- foundly influence forest structure and composition, and therefore affect the avail- abiUty of habitat for different groups of or- ganisms. Disturbances may be caused by small-scale processes such as the senes- cence and death of individual trees, or large- scale processes such as hurricanes or fire. Assessing disturbance can be difficult, how- ever; indicators of disturbance may need to be developed or adapted at the local level according to the characteristics of the site (Ramirez-Marcial, Gonzalez-Espinosa and Williams-Linera, 2001). Methods of assessment and analysis The data required for the biodiversity indi- cators considered here can largely be pro- vided through traditional forest inventory approaches, supported by the apphcation of remote sensing and geographic information system (GIS) technologies. In some cases, additional field survey techniques may be needed to inventory taxa not usually in- cluded in forest inventory. Careful attention needs to be paid to samphng design, strati- fication and survey methods both within forest inventory and in supplementary smd- ies (Dallmeier and Comiskey, 1998a; Bachmann, Kohl and Paivinen, 1998; Boyle and Boontawee, 1995;Vanclay, 1998). Re- mote-sensing images can provide a basis for stratifying field samphng efforts as well as for mapping distributions of species that are closely associated with distinctive veg- etation types. Although it may provide in- dications of ecosystem-level diversity as indicated by spatial distribution of differ- ent vegetation types, remote sensing can- not yet provide direct information on species-level diversity (Taimer, Kapos and Adams, 1998). Remote sensing and GIS can be used both to generate spatial data, for example on forest cover distribution, and to extrapolate the results of intensive ground studies. GIS can also be used to combine data
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