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Research . 2016
License: CC BY
Data sources: OpenUCT
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Research . 2012
License: CC BY
Data sources: OpenUCT
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Test fishing analyses for Nightingale Island

Authors: Johnston, Susan J; Butterworth, Doug S; Brandão, Anabela; Muller, A;

Test fishing analyses for Nightingale Island

Abstract

Because there was no pre-OLIVA fishing in the month of January 2011, the simpler earlier approach of Johnston (2011) to analyse test fishing data by month to assess the OLIVA impact needs to be refined to be able to include data from January 2012. General Linear Models are used for this purpose; these have the additional advantage that they can take more data into account in adjusting for monthly patterns. These models also reveal a regional pattern in the OLIVA impact, which is least in the north and greatest in the southeast. There is some indication that the impact has decreased slightly over time, but the trend is not statistically significant. The best estimate obtained for the OLIVA impact is a decrease of about 50% (SE=5%) in abundance of lobsters above the size limit.

Country
South Africa
Related Organizations
Keywords

Nightingale Island, fishing analyses

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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