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Standard Methods for Sampling North American Freshwater Fishes

Chapter 11: Statistical Analysis and Data Management

Michael C. Quist, Kimberly I. Bonvechio, and Micheal S. Allen

doi: https://doi.org/10.47886/9781934874103.ch11

Collecting fisheries data requires extensive time and financial commitments. Given this high level of investment by management agencies and individual biologists, data storage, summarization, and analysis should be a high priority to ensure that the integrity and accessibility of collected information are maximized over time. Arguably, the most important aspect of sampling is completing an appropriate and thorough analysis of collected data. Standard sampling procedures help ensure that data analysis and database management are appropriate and efficient, but even when data are collected using standardized methods, data structure will vary among species and systems making standardized analyses difficult and sometimes impossible. Different agencies may also have different database management needs and structures, which can influence how data are stored and later accessed for analysis. The purpose of this chapter is to provide an overview of data summarization and analysis techniques, sample-size estimators, and principles of database management. Whenever appropriate, we guide readers to more detailed sources of information because many of these topics have been discussed extensively in the fisheries literature.

Fisheries scientists typically collect large amounts of data during standard sampling surveys, and properly interpreting these data is necessary for making sound management decisions. Data analysis is often hierarchical in that some analyses focus on the estimation of simple summary statistics (e.g., mean, variance), while others rely on inferential statistical tests or modeling. Although fisheries data can be summarized using a variety of approaches, a few techniques have become standard in the profession, the most common of which are discussed in this chapter. Many texts are available on statistical techniques for fisheries data (e.g., Everhart et al. 1975; Jongman et al. 1995; Murphy and Willis 1996; Guy and Brown 2007), so these efforts are not reproduced in this chapter. Rather, we provide the most current references for analyzing fisheries data and encourage biologists to use these resources for more detailed presentations of analytical methods for fisheries data. In particular, we recommend Brown and Austen (1996) as a starting point for readers not familiar with the issues and idiosyncrasies of analyzing such data.