Guideline 4: Logistics 



The logistical requirements of an indicator can be costly and time-consuming. Thiese requirements must 

 be evaluated to ensure the practicality of indicator implementation, and to plan for personnel, equipment, 

 training, and other needs. A logistics plan should be prepared that identifies requirements, as 

 appropriate, for field personnel and vehicles, training, travel, sampling instruments, sample transport, 

 analytical equipment, and laboratory facilities and personnel. The length of time required to collect, 

 analyze and report the data should be estimated and compared with the needs of the program. 



Monitoring progranns that utilize sediment sampling for the collection of benthic macroinvertebrates vary in 

 their logistic requirements depending on the spatial extent and temporal duration of the monitoring design. 

 All field operations conducted by EMAP-E were planned and implemented according to an approved logistics 

 plan that was prepared following guidelines established for EMAP (Baker and Merritt 1 990). Elements of the 

 logistics plan address major areas of project implementation, including project management, site access and 

 scheduling, safety and waste disposal, procurement and inventory control, training and data collection, and 

 the assessment of the operation upon completion. EMAP-E in the Lousianian Province was tasked with 

 sampling -1 50 stations that ranged hundreds of miles from Texas to Florida. The time frame was -2 months 

 during the summer. Because the success of EMAP-E depended on standardized sampling and processing, 

 all boat crews underwent rigorous training that covered boat operation, collection methods, and proper QA 

 procedures. A field operations manual was prepared each year to give detailed instructions to the field 

 teams on safety, operation of equipment, handling of samples, and quality assurance (Macauley 1991). A 

 logistics plan was prepared each year that gave a day-to-day account of locations to be sampled, personnel 

 assignments, and suggested hotels, boat ramps, and other necessary resources. In addition, a quality 

 assurance project plan was prepared to identify quality control guidelines for collection, handling, and shipping 

 of field samples as well as laboratory analytical methods (Heitmuller and Valente 1991). Table 3-3 lists the 

 logistical requirements to carry out sampling of benthos by the EMAP-E field teams; however, the magnitude 

 of equipment required by EMAP-E would not necessarily be appropriate for small-scale, localized monitoring 

 programs. 



EMAP-E set a goal of producing a statistical summary approximately 9 months after sampling concluded. 

 Collection and field processing of benthic samples was completed aboard the boat within a short time frame 

 {i.e., 1-2 hours). In the laboratory, processing of the samples was more tedious and, on average, it took 5-10 

 man-hours to process a sample, from the initial bench sieving to transfer of raw data from handwritten sheets 

 to an electronic file. The original development of the index from receiving the electronic data to publishing a 

 manuscript took on the order of several years. The application of the index, now that it has been finalized, is 

 relatively straightforward; the length of time from receipt of the data to calculating the index is on the order of 

 a few days. 



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. 



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