114 » Technologies To Maintain Biological Diversity 



• the types, extent, locations, and effects of 

 human uses, the degree of dependence of 

 local inhabitants on these uses, and the pos- 

 sible alternatives for activities that are 

 harmful to the site; 



• the present and potential threats from 

 activities outside the immediate area of 

 concern; 



• the opportunities for making the site more 

 useful to local inhabitants; and 



• the best approach for law enforcement on 

 the site. 



Agency budgets and policies for management 

 planning often omit some of these surveys, con- 

 sidering them fundamental research rather than 

 pragmatic planning activities. For example, the 

 U.S. Bureau of Land Management's Resource 

 Management Plan process does not include col- 

 lection of detailed site data if no deleterious hu- 

 man impact or other problem is known. Biolo- 

 gists argue, however, that the problems cannot 

 be fully identified without the surveys. 



Historically, the specific plans to conserve 

 biological diversity were left to the area man- 

 ager to devise and implement. This approach 

 still prevails in many regions of the world. In 

 the United States, conflicts in land and water 

 management and the increasing need to justify 

 all management activities to a governing insti- 

 tution have resulted in specialized tools for 

 planning the conservation of biological re- 

 sources. Much of this development of planning 

 techniques has occurred in the Federal land 

 management agencies. 



Modeling 



A recent innovation in planning techniques 

 is the use of mathematical models. The models 

 are highly simplified versions of natural envi- 

 ronments. Biological data are used to develop 

 equations that represent assumptions about 

 cause-and-effect interactions between plant and 

 animal populations and their habitats. Numer- 

 ous equations interact, and the outcome pro- 

 jects responses of the biological resources to 

 different management options. The accuracy 

 of the projections depends on how well the 

 equations and the data reflect the situation in 

 the natural environment. 



Various kinds of wildlife-habitat models have 

 been used, and recently, the population simu- 

 lation models described earlier have begun to 

 be used widely. These population models pre- 

 dict how management activities would affect 

 population size, structure, and recovery rate. 

 They can describe, for example, the probable 

 size of a fish population before and at various 

 times after a specified fishing season. 



Wildlife-habitat models are built from natu- 

 ral history data on species distribution and 

 abundance in various habitats, from which 

 cause-and-effect relationships are deduced to 

 predict how wildlife populations will change 

 as a result of changed habitat conditions. Indi- 

 cator Species Models, for instance, focus on 

 one or a few species known to reflect broader 

 ecosystem qualities. Another example is the 

 Habitat Evaluation Procedure used by the U.S. 

 Fish and Wildlife Service to describe the re- 

 sponses of vegetation and, hence, wildlife habi- 

 tats to certain management options such as tim- 

 ber harvesting (75). 



Geographic Information System models also 

 account for the changes in vegetation or wild- 

 life habitats that result from different manage- 

 ment options, but the output is presented on 

 maps, which facilitates evaluation of cumula- 

 tive impacts by area. A complementary tech- 

 nique being developed by U.S. National Park 

 Service personnel, the Boundary Model, is in- 

 tended to assess not only management activi- 

 ties but also the effects of human actions out- 

 side the protected areas (69). 



Biologists warn that the accuracy of models 

 is constrained by the need to reduce complex, 

 often poorly understood interactions to assump- 

 tions simple enough to be represented with 

 mathematical equations. Often, data are too 

 limited to test all the assumptions. None of the 

 natural area models can predict all the possi- 

 ble ways that biological resources might re- 

 spond to habitat changes. Thus, models are best 

 used to make the assumptions and logic of sci- 

 entists, managers, and natural-area users ex- 

 plicit, so that final plans and management de- 

 cisions can be based on clear, thorough, and 

 objective understanding of all perspectives. 



