Summary 



Data collection activities for the indicator are described within the constraints imposed by the proposed 

 monitoring frameworl<. Considerable lead time is required to obtain permission to access sampling sites and 

 to obtain the required scientific collecting permits. Partnerships with local agencies can streamline collection 

 efforts. Various staffing options are presented to provide the required expertise; some safety training may be 

 necessary for crews. Equipment and supplies may have to be transported over harsh terrain. Validation of 

 fish identifications can be achieved by a competent local museum. 



Guideline 5: Information Management 



Management of information generated by an indicator, particularly in a long-term monitoring program, 

 can become a substantial issue. Requirements should be identified for data processing, analysis, storage, 

 and retrieval, and data documentation standards should be developed. Identified systems and standards 

 must be compatible with those of the program for which the indicator is intended and should meet the 

 interpretive needs of the program. Compatibility with other systems should also be considered, such as 

 the internet, established federal standards, geographic information systems, and systems maintained by 

 intended secondary data users. 



Performance Objectives 



1. Identify requirements for data processing, review, analysis, and storage, and demonstrate 

 compatibility with those capabilities available to the proposed monitoring program. 



2. Describe the metadata necessary for primary and secondary users to access the data, to 

 reproduce the results, or to use the data in other types of analytical and interpretive activities. 



There are important information management requirements and issues related to supporting the routine use 

 of the indicator within the proposed monitoring framework (Table 4-1 1 ). Experience with the MAHA study has 

 indicated that a fairly lengthy time period is required to complete review and validation of the measurement 

 data prior to their use in computing metric responses, scores, and the indicator value. This process may 

 inhibit the ability to achieve the desired reporting timeframe (9 months; Table 4-10). We anticipate this time 

 will be reduced as experience with the data is gained and automated routines are developed to facilitate 

 review and validation activities. 



The requirements for hardware and software (Table 4-11) were selected to be compatible with nearly all 

 potential participants in the proposed monitoring program. Some programming support may be needed to 

 develop the routines for computing metric responses, scores, and indicator values from validated measurement 

 data. Diaz-Ramos ef a/. (1 996) provide statistical algorithms needed to compute resource population estimates 

 in spreadsheet-compatible format. 



The critical data sets and metadata required to support the development of the indicator and its component 

 metrics (Table 4-1 1 ) are few in number and fairly straightforward. A critical component of archival activities 

 for the indicator is the incorporation of voucher specimens into a permanent museum collection. 



4-20 



