USGS ScienceSearch

USGS · 70274748

Converting non-standard data to standardized data

Abstract

Fishery biologists spend considerable effort over multiple years collecting data on fish population and community status using a particular sampling method or set of methods. However, new (and often more effective) sampling methods and technologies are continuously being developed. To incorporate these new sampling techniques, fishery biologists need a means for converting fish sampling data collected using old methods so that they can be compared with data collected using new sampling methods. Similarly, fishery biologists often need a means to compare fish sampling data collected using the same method over time (e.g., from year to year) and space (e.g., between sample sites). If fish abundance, species presence, or richness are estimated using an unbiased statistical estimator (e.g., occupancy estimation, capture-recapture estimation), the estimates can be validly compared even if the fish sample data were collected with different methods. However, if unbiased statistical estimators were not used, biologists need methods for adjusting fish sampling data collected using different methods or using the same method collected under different sampling conditions. In this chapter, we describe and provide examples of statistical techniques for converting nonstandard fish sampling data to American Fisheries Society (AFS) standardized data and for making comparisons of fish sampling data collected at different times or at different locations. We define standard fish sampling data as data collected using the standardized fish sampling methods described throughout this book. Any other sampling methods and associated data are thus defined as nonstandard. Before delving into the details of the techniques that can be used to convert data, we describe the nature of fish sample data, their uses, and their limitations.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

James T. Peterson, Derrick T. de Kerckhove, Henrique C. Giacomini, Craig Paukert. 2024. Converting non-standard data to standardized data. https://doi.org/10.47886/9781934874769.ch16

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Loma salmonae and related species

Loma salmonae is a microsporidium that infects Pacific salmon and causes a gill inflammatory syndrome known as microsporidial gill disease of salmon. This disease has been mostly associated with netpen-farmed Chinook salmon ( Oncorhynchus tshawytscha ) in British Columbia, Canada. Clinical, diagnostic, pathological aspects of disease, as well as approaches for disease avoidance in salmon aquaculture are discussed. A laboratory infection model in rainbow trout was used to determine life cycle-stages, transmission dynamics, pathophysiology, influence of temperature, and to test therapeutics applicable to aquaculture. This experimental model has been informative on various approaches of disease control, including the development of a promising vaccine. In addition to improving fish health in salmon farming in North America, this L. salmonae model will be applicable to other microsporidial diseases that may be encountered in emerging aquaculture regions.

Book chapter

Cumulative effects of multiple stressors on marine mammals: Elephant seals as a model system

Noise exposure is a potential stressor for free-ranging marine mammals and is often studied in the absence of other environmental factors. Here, a multi-investigator, interdisciplinary effort was undertaken to examine the response of elephant seals to multiple stressors. An integrated physiological and ecological approach was taken, including immunology, stress physiology, toxicology, animal behavior, population biology, and life history theory, to examine the cumulative effects of exposure to multiple stressors in elephant seals. While we measured the response of individual animals, a population response can be predicted by incorporating these results into the long-term data on elephant seal demographics.

Book chapter

When is a parasite a problem?

A parasite’s perceived societal impact depends on the disease it causes and the perception of the affected host species. For instance, doctors and veterinarians have a mission to treat parasites that infect humans or that impact host species that have some utilitarian or aesthetic value for society. Marine scientists have different concerns than doctors. Although the number of parasites that marine scientists should be concerned about may vary, only 13% of parasites and 6% of host–parasite links might be considered “problematic” in a kelp forest food web. With regard to the many threats to marine ecosystems, these percentages suggest that most parasites and infectious diseases are inconsequential. A related issue is the common expectation that parasites and the impacts that they cause are increasing under stress as ocean environments across the globe degrade. Yet, reports of disease have not increased due to human impacts on the marine environment, where the factors that influence parasitism are more complex. Thus, the expectation that marine parasites create problems, and that the diseases they cause are getting worse, is more likely the exception than the rule.

Book chapter