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. 



This indicator should present no significant problems from the perspective of information management. 

 Based on the proposed methodology, data are collected at one-meter intervals. The values are written on 

 hard-copy datasheets and concurrently logged electronically in a surface unit attached to the CTD. (Note 

 that this process will vary with the method used. Other options include not using a deck unit and logging 

 data in the CTD itself for later uploading to a computer; or simply typing values from the hard-copy datasheet 

 directly into a computer spreadsheet). After sampling has been completed, data from the deck unit can be 

 uploaded to a computer and processed in a spreadsheet package. Processing would most likely consist of 

 plotting out dissolved oxygen with depth to view the profile. Data should be uploaded to a computer daily. 

 The user needs to pay particular attention to the memory size of the CTD or deck unit. Many instruments 

 may contain sufficient memory for only a few casts. To avoid data loss it is important that the data be 

 uploaded before the unit's memory is exhausted. The use of hard-copy datasheets provides a back-up in 

 case of the loss of electronic data. 



Guideline 6: Quality Assurance 



For accurate interpretation of indicator results, it is necessary to understand their degree of validity. A 

 quality assurance plan should outline the steps in collection and computation of data, and should identify 

 the data quality objectives for each step. It is important that means and methods to audit the quality of 

 each step are incorporated into the monitoring design. Standards of quality assurance for an indicator 

 must meet those of the targeted monitoring program. 



The importance of a well-designed quality assurance plan to any monitoring program cannot be overstated. 

 One important aspect of any proposed ecological indicator is the ability to validate the results. Several 

 methods are available to assure the quality of dissolved oxygen data collected in this example. The simplest 

 method is to obtain a concurrent measurement with a second instrument, preferably a different type than is 

 used for the primary measurement (e.g., using a DO meter rather than a CTD). This is most easily performed 

 at the surface, and can be accomplished by hanging both the CTD and the meter's probe over the side of 

 the boat and allowing them to come to equilibrium. The DO measurements can then be compared and, if 

 they agree within set specifications (e.g., 0.5 mg/L), the CTD is assumed to be functioning properly. The DO 

 meter should be air-calibrated immediately prior to use at each station. One could argue against the use of 

 an electronic instrument to check another electronic instrument, but it is unlikely that both would be out of 

 calibration in the same direction, to the same magnitude. An alternative method is to collect a water sample 

 for Winkler titration; however, this would not provide immediate feedback. One would not know that the data 

 were questionable until the sample is returned to the laboratory and it is too late to repeat the CTD cast. 

 Although Winkler titrations can be performed in the field, the rocking of the boat can lead to erroneous 

 titration. 



2-6 



