Dead useful: methods for quantifying baseline variability in stranding rates to improve the ecological value of the strandings record as a monitoring tool

Research output: Contribution to journalArticle

Abstract

The ecological value of the stranding record is often challenged due to the complexity in quantifying the biases associated with multiple components of the stranding process. There are biological, physical and social aspects that complicate the interpretation of stranding data particularly at a population level. We show how examination of baseline variability in the historical stranding record can provide useful insights into temporal trends and facilitate the detection of unusual variability in stranding rates. Seasonal variability was examined using harbour porpoise strandings between 1992 and 2014 on the east coast of Scotland. Generalized Additive Mixed modelling revealed a strong seasonal pattern, with numbers increasing from February towards a peak in April. Profiling seasonality this way facilitates detection of unusual variations in stranding frequencies and permits for any change in the incidence of strandings to be quantified by evaluation of the normalized model residuals. Consequently, this model can be used to identify unusual mortality events, and quantify the degree to which they deviate from baseline. With this study we demonstrate that a described baseline in strandings allows the detection of abnormalities at an early stage and can be used as a regional framework of reference for monitoring. This methodology provides means to quantify and partition the variability associated with strandings data and is a useful first step towards improving the stranding record as a management resource.
Original languageEnglish
Pages (from-to)1205 - 1209
Number of pages5
JournalJournal of the Marine Biological Association of the United Kingdom
Volume98
Issue number5
Early online date11 May 2017
DOIs
Publication statusFirst published - 11 May 2017

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stranding
monitoring
porpoise
method
rate
seasonality
resource management
harbor
mortality
methodology
coast

Keywords

  • Cetaceans
  • Generalized Additive Mixed Model
  • Harbour porpoise
  • Monitoring
  • Scotland
  • Stranding process
  • Strandings
  • Unusual Mortality Event

Cite this

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title = "Dead useful: methods for quantifying baseline variability in stranding rates to improve the ecological value of the strandings record as a monitoring tool",
abstract = "The ecological value of the stranding record is often challenged due to the complexity in quantifying the biases associated with multiple components of the stranding process. There are biological, physical and social aspects that complicate the interpretation of stranding data particularly at a population level. We show how examination of baseline variability in the historical stranding record can provide useful insights into temporal trends and facilitate the detection of unusual variability in stranding rates. Seasonal variability was examined using harbour porpoise strandings between 1992 and 2014 on the east coast of Scotland. Generalized Additive Mixed modelling revealed a strong seasonal pattern, with numbers increasing from February towards a peak in April. Profiling seasonality this way facilitates detection of unusual variations in stranding frequencies and permits for any change in the incidence of strandings to be quantified by evaluation of the normalized model residuals. Consequently, this model can be used to identify unusual mortality events, and quantify the degree to which they deviate from baseline. With this study we demonstrate that a described baseline in strandings allows the detection of abnormalities at an early stage and can be used as a regional framework of reference for monitoring. This methodology provides means to quantify and partition the variability associated with strandings data and is a useful first step towards improving the stranding record as a management resource.",
keywords = "Cetaceans, Generalized Additive Mixed Model, Harbour porpoise, Monitoring, Scotland, Stranding process, Strandings, Unusual Mortality Event",
author = "{ten Doeschate}, MTI and AC Brownlow and NJ Davison and PM Thompson",
year = "2017",
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language = "English",
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AU - ten Doeschate, MTI

AU - Brownlow, AC

AU - Davison, NJ

AU - Thompson, PM

PY - 2017/5/11

Y1 - 2017/5/11

N2 - The ecological value of the stranding record is often challenged due to the complexity in quantifying the biases associated with multiple components of the stranding process. There are biological, physical and social aspects that complicate the interpretation of stranding data particularly at a population level. We show how examination of baseline variability in the historical stranding record can provide useful insights into temporal trends and facilitate the detection of unusual variability in stranding rates. Seasonal variability was examined using harbour porpoise strandings between 1992 and 2014 on the east coast of Scotland. Generalized Additive Mixed modelling revealed a strong seasonal pattern, with numbers increasing from February towards a peak in April. Profiling seasonality this way facilitates detection of unusual variations in stranding frequencies and permits for any change in the incidence of strandings to be quantified by evaluation of the normalized model residuals. Consequently, this model can be used to identify unusual mortality events, and quantify the degree to which they deviate from baseline. With this study we demonstrate that a described baseline in strandings allows the detection of abnormalities at an early stage and can be used as a regional framework of reference for monitoring. This methodology provides means to quantify and partition the variability associated with strandings data and is a useful first step towards improving the stranding record as a management resource.

AB - The ecological value of the stranding record is often challenged due to the complexity in quantifying the biases associated with multiple components of the stranding process. There are biological, physical and social aspects that complicate the interpretation of stranding data particularly at a population level. We show how examination of baseline variability in the historical stranding record can provide useful insights into temporal trends and facilitate the detection of unusual variability in stranding rates. Seasonal variability was examined using harbour porpoise strandings between 1992 and 2014 on the east coast of Scotland. Generalized Additive Mixed modelling revealed a strong seasonal pattern, with numbers increasing from February towards a peak in April. Profiling seasonality this way facilitates detection of unusual variations in stranding frequencies and permits for any change in the incidence of strandings to be quantified by evaluation of the normalized model residuals. Consequently, this model can be used to identify unusual mortality events, and quantify the degree to which they deviate from baseline. With this study we demonstrate that a described baseline in strandings allows the detection of abnormalities at an early stage and can be used as a regional framework of reference for monitoring. This methodology provides means to quantify and partition the variability associated with strandings data and is a useful first step towards improving the stranding record as a management resource.

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KW - Unusual Mortality Event

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