126 • Technologies To Maintain Biological Diversity 



Figure 5-4.— Representation of a Geographic 



Information System Function Overlaying Several 



Types of Environmental Data 



Human 

 settlements 



Animal 

 populations 



Vegetation 

 cover 



Water 

 resources 



Soil 

 types 



Base 



map 



SOURCE: United Nations Environmental Programme/Global Environment Mon- 

 itoring Systems. Global Resource Information Databases (Nairobi: 

 GEMS Publication, 1985). 



tion sponsoring the data collection. If the ob- 

 jective is to provide an overview of the status 

 and trends of biological diversity in large areas, 

 then remote sensing with sample surveys on 

 the ground for verification and analysis with 

 GIS may be the most cost-effective approach. 

 If the objective is to design a management plan 

 for a particular area, detailed field surveys are 

 necessary, but tools such as GIS may still prove 

 valuable. 



For implementation of resource develop- 

 ment, information on biological diversity at a 

 local, site-specific level is most important. Yet 

 this is the level at which the quality of biologi- 

 cal information is most variable. For some heav- 

 ily studied areas, detailed field inventories and 

 analyses of ecosystem interactions have been 

 completed, whereas for others, especially the 

 remote areas, often little detail of biological 

 diversity is known. Development of needed site- 

 specific diversity data is constrained by the 

 common attitude of land managers that diver- 

 sity assessment is fundamental research that 

 should be limited mainly to land areas where 

 research is the designated major use. This is 

 a problem even for agencies that are sensitive 

 to the issue of biological diversity, such as the 

 U.S. Fish and Wildlife Service. 



Coordination 



The quantity of biological data may increase 

 as information becomes easier to handle and 

 less costly to acquire and maintain. Linking 

 databases developed for different purposes can 

 greatly increase their utility and thus their cost- 

 effectiveness. Data incompatibility hinders 

 such linking, however, making it necessary to 

 reenter data manually at great cost, or more 

 often to forgo the improved analysis that linked 

 databases would allow. Data sharing in the 

 United States among and within Federal agen- 

 cies frequently is constrained by a lack of stand- 

 ards. For example, different agencies generally 

 use different terminology to define ecosystem 

 types. This problem also exists at the inter- 

 national level, especially where classification 

 schemes used to aggregate data are not stand- 

 ardized. 



