It was probably one of the oddest riots in the history of the United States. In Erie, Pennsylvania during 1853. federal marshals were called to restore order during bloody uprisings. A mob of women, equipped with sledgehammers, was tearing up railroad rack to protest standardization of track width (Nesmith 1985). All across the United States, standardization of rail gauges was talking place to improve transportation across the country,but many people did not want consistency. Jobs moving freight from, a train running on one gauge of track to a train running on another gauge were plentiful at this time, and standardization would mean these jobs would disappear. Fortunately, for us today, the riots were quelled and standardization of railroad tack gauges went ahead. The magnificent transportation system of North America was aided by the standardization of rails, contributing to robust economies.
Standardization of industrial processes, languages, measurements, and data collection methods has been essential for world progress (Figure 1.1). Today , we are often unaware of the degree of standardization of the most basic elements of our society--from bolts and nuts where thread sizes are standard to computer components that can be used interchangeably to the standard sizes of photos we carry in our wallets or purses. Data collection and presentation are standardized in many disciplines, including medicine, meteorology, geology, and water chemistry. For example, our cholesterol, body temperature, and blood pressure are measured by standard medical tests and compared to averages calculated from the results of the same standard tests for many other people to determine if individuals are higher, lower, or average compared to the population in general. If these diagnostic tests were not standardized, it is unlikely that we would be able to evaluate eve the most basic data about our health. In fact, if standardization was not used in countless other facets of our society our lives would be much more difficult.
For data collection purposes, standardization means to collect data in one way so comparisons can be easily made. Although routine data collection has been standardized in many other disciplines, data from freshwater fish sampling across North America have not. Previously, most data collection has been standardized only at local, state, and provincial levels (Bonar and Hubert 2002).
Several years ago, when one of the authors (Bonar) was a biologist for a state agency, he was asked to compile as much data as he could about the state's warmwater fish communities to provide information to managers developing fishing regulations. These data had been collected by many biologists over time using different methods, including rotenone, electrofishing, gill netting, and hook-and-line sampling. Data were written carefully on detailed data sheets or in scribbled notes in a biologists's notebook. As you can imagine, these data were a nightmare to compile. However, they were even worse to interpret.
How could length-frequency distributions be compared among lakes if the methods used to catch the fish were dissimilar with differing efficiencies in sampling fish of various species and lengths? How could catch per unit effort (CPUE), a common index of population density, be compared when samples were collected one year using fyke nets and the next year by electrofishing? Ultimately, how could one compare if fish population were high, low, or average in growth, body condition, or abundance if there was no compilation of distributions of standard data to facilitate comparison?
Months were spent trying to interpret these data, and finally a body of comparable data gathered by similar methods was assimilated. However, much of the nonstandard data had to be discarded--data that had taken thousands of hours to collect but were essentially useless. If all data jhad been collected and recorded in a standard manner, whoch would have required very little extra work, all of these hours of survey effort would not have gone to naught and isights regardimng the fisheries would have been imporived by a larger number of samples.
|Title||An introduction to standardized sampling: chapter 1|
|Authors||Scott A. Bonar, Salvador Contreras-Balderas, Alison C. Iles|
|Publication Type||Book Chapter|
|Publication Subtype||Book Chapter|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Arizona Cooperative Fish and Wildlife Research Unit|