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Flocker
1.1
is
a software
to quantify and compare
statistical measures of group
size
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download:
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Briefly
This is a statistical toolset
designed to analyse group size data
while:
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differentiating between outsiders' view (group size)
versus insiders' view (crowding) measures;
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controlling for the ties among data points in the latter
case;
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handling biased distributions
correctly.
Theoretical
background, examples, and a description of statistical procedures are
found here:
Reiczigel et al. 2008.
Measures of sociality: two different views of group size. Animal Behaviour,
75,
715-721.
The software is free to
use and distribute for scientific and educational purposes. Please cite
the above article as a theoretical background of the statistical
procedures. |
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How to run
Runs under Windows. After download,
unzip the file and find a folder named 'Flocker 11'. Within this folder,
just run the file flocker11.exe. Do not remove the files from the
folder. In Vista, however, use the right button and then select
"run as administrator". No Mac version is available. |
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Some details
Many animals, including
humans, tend to live in groups, herds, flocks, bands, packs, parties, or
colonies (hereafter: groups) of conspecific individuals. The size of these
groups, as expressed by the number of participants, is an important aspect
of their social environment. Group size tend to be highly variable even
within the same species, thus we often need statistical measures to
quantify group size and statistical tests to compare these measures
between two or more samples. Unfortunately, group size measures are
notoriously hard to handle statistically since groups size values
typically exhibit an aggregated (right-skewed) distribution; most groups
are small, few are large, and a very few are very large. Statistical
measures of group size roughly fall into two categories.
1. Outsiders’ view of group
size
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Group size is the
number of individuals within a certain group;
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Mean group size,
i.e. the arithmetic mean of group sizes averaged across groups;
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Confidence interval of
mean group size;
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Median group size,
i.e. the median of group sizes calculated across groups;
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Confidence interval of
median group size.
2. Insiders’ view of group
size
As Jarman (1974) pointed
out, average individuals live in groups larger than the average – simply
because the groups smaller than average have fewer individuals than the
groups larger than average. (Except for an unrealistic case when all
groups are of equal size.) Therefore, when we wish to characterize a
typical (average) individual’s social environment, we should not apply the
outsiders’ view of group size. Reiczigel et al. (2008) proposed the
following measures:
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Crowding is the
number of individuals within a group (equals to group size: 1 for a
solitary individual, 2 for both individuals in a group of 2, etc.);
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Mean crowding, i.e.
the arithmetic mean of crowding values averaged across individuals
(this was called "Typical Group Size" in Jarman's terminology);
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Confidence interval of
mean crowding.
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Animal group size data tend to exhibit
aggregated (right-skewed) distributions, i.e. most groups are small, a few
are large, and a very few are very large. The distribution of rook colony
sizes in Normandy, 1999-2000 (smoothed). Mean colony size is 60 pairs. (Data from Debout, 2003)
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Though large colonies are rare, however,
they still incorporate a lot of individuals. Insiders' view
of the same data set as on the left: the distribution of individuals (pairs)
across colonies of different sizes. An average individual breeds in a
colony of 120 pairs, far larger than mean colony size.
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3. Statistical methods
Due to the aggregated (right-skewed)
distribution of group members among groups, the application of parametric
statistics would be misleading. Another problem arises due to the 'ties'
among data. Crowding data consist of non-independent values,
so-called ties, which show multiple and simultaneous changes in response
to a
single biological event. Say, all group members' crowding values increase
simultaneously whenever an individual joins the group. The papers by Reiczigel et
al. (2005, 2008) discuss the statistical problems associated with crowding
measures (calculating confidence intervals, 2-sample tests, etc.) and
Flocker1.1 provides a cost-free and user-friendly toolset to carry out
these calculations.
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This page is on-line since
Febr of 2008. Last updated on the
24th
of
April, 2010.
Maintained by
Lajos Rózsa.
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