Visualizing and Exploring Zooplankton Spatio-Temporal Variability

The distribution and abundance of zooplankton vary over time and space in response to physical and biological drivers operating at different temporal (e.g. seasonal, interannual and decadal) and spatial (e.g. local, regional, global) scales. As a result, zooplankton is often described as having patc...

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Bibliographic Details
Published inZooplankton Ecology pp. 192 - 224
Main Authors O’Brien, Todd D., Oakes, Stephanie A.
Format Book Chapter
LanguageEnglish
Published CRC Press 2021
Edition1
Subjects
Trend Slopes
TW
Longer Time Windows
Cpr
Seasonal Cycle
Zooplankton Variable
Cpr Survey
Annual Anomaly
AMO Index
Compare Time Series
Climatological Average
Satellite Chlorophyll
Copepod Abundance
Total Diatoms
Total Copepod
Interannual Variability
Whisker Plot
Time Series Variables
Atlantic Multi-decadal Oscillation
Anomaly Plot
Sea Surface Temperature Data Set
Time Series
Area D1
Climate Oscillations
PDO Index
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Summary:The distribution and abundance of zooplankton vary over time and space in response to physical and biological drivers operating at different temporal (e.g. seasonal, interannual and decadal) and spatial (e.g. local, regional, global) scales. As a result, zooplankton is often described as having patchy distributions and boom-or-bust abundance cycles. Zooplankton data are collected with different frequencies (e.g. sub-weekly to once-per-season), sampling methods (e.g. nets, pumps, and optical systems), and measurement techniques ranging from total biomass to microscope-based taxonomic identification and enumeration. The resulting time series data are often complex and require data usage and application caveats, as do the advanced statistics used for their analysis. Whether one is a statistics and programming expert, or a student analyzing data with a spreadsheet, the first step in any analysis should be to explore the data with basic visual and statistical techniques. This chapter introduces some simple techniques for visualizing zooplankton variability, patterns, and trends over time and space. Examples include time series with limited temporal and spatial coverage to multiple-site regional studies that require combining and comparing data with different sampling methods and sampling frequencies.
ISBN:1138496456
9780367620561
0367620561
9781138496453
DOI:10.1201/9781351021821-11