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Estimating Intermittent Individual Spawning Behavior via Disaggregating Group Data

Overview of attention for article published in Bulletin of Mathematical Biology, December 2017
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Title
Estimating Intermittent Individual Spawning Behavior via Disaggregating Group Data
Published in
Bulletin of Mathematical Biology, December 2017
DOI 10.1007/s11538-017-0379-x
Pubmed ID
Authors

Joel Nishimura, Rebecca Smith, Kathleen Jensen, Gerald Ankley, Karen Watanabe

Abstract

In order to understand fish biology and reproduction, it is important to know the fecundity patterns of individual fish, as frequently established by recording the output of mixed-sex groups of fish in a laboratory setting. However, for understanding individual reproductive health and modeling purposes it is important to estimate individual fecundity from group fecundity. We created a multistage method that disaggregates group-level data into estimates for individual-level clutch size and spawning interval distributions. The first stage of the method develops estimates of the daily spawning probability of fish. Daily spawning probabilities are then used to calculate the log likelihood of candidate distributions of clutch size. Selecting the best candidate distribution for clutch size allows for a Monte Carlo resampling of annotations of the original data which state how many fish spawned on which day. We verify this disaggregation technique by combining data from fathead minnow pairs, and checking that the disaggregation method reproduced the original clutch sizes and spawning intervals. This method will allow scientists to estimate individual clutch size and spawning interval distributions from group spawning data without specialized or elaborate experimental designs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 25%
Unknown 3 75%
Readers by discipline Count As %
Mathematics 1 25%
Business, Management and Accounting 1 25%
Unknown 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 April 2018.
All research outputs
#15,505,836
of 23,043,346 outputs
Outputs from Bulletin of Mathematical Biology
#727
of 1,104 outputs
Outputs of similar age
#267,190
of 440,030 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#22
of 27 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,104 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 440,030 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.