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2.8
The Alert System
2.8.1
General approach
The alert system
used within this report is designed to draw attention to developing
population declines that may be of conservation concern. It also
identifies situations where long-term declines have reversed, leading
to an improvement in conservation status. It must be stressed that
the changes reported here are advisory and do not supersede the
agreed UK conservation listings (Gregory
et al. 2002; see PSoB
pages). They are based on similar criteria to The Population
Status of Birds in the UK, however, and so provide an indication
of likely changes at future revisions.
The system is
based on statistical analyses of the population trend data for individual
species. Alerts seek to identify rapid declines (>50%) and moderate
declines (>25% but <50%). These declines are measured over
a number of time-scales, depending on the availability of data -
the full length of the available time series, and the most recent
25 years, 10 years and 5 years for which change can be estimated.
The conservation emphasis is particularly on the longer periods,
but short-term changes help to separate declines that are continuing
- or accelerating - from those that have ceased or reversed.
The alerts are
calculated annually using standard automated procedures. Where species
are at the margin of two categories (e.g. a decline of about 25%)
they may fire alerts in some years but not others, or different
levels of alert in different years.
Data on some
species might be biased, owing to unrepresentative monitoring, or
imprecise, owing to small sample sizes. Because these data often
provide the only information that is available, our general approach
is to report all the alerts raised but to clearly flag up any deficiencies
in the data.
2.8.2
Smoothing population trends
Bird populations
show long-term changes that do not follow simple mathematical trajectories.
In addition to the long-term trends, unsmoothed population indices
also show short-term fluctuations resulting from a combination of
natural population variability and statistical error. We use smoothing
techniques that aim to extract the long-term pattern of population
change, without forcing it to follow any particular shape (such
as a straight line or a polynomial curve). These methods remove
most of the effects of short-term fluctuations (including any natural
year-to-year variability) so that the long-term trend is revealed
more clearly.
Technical
details available here
2.8.3
Years used for analysis
Once a smoothed
population trend has been calculated, change measures are calculated
from the ratio of the smoothed population indices for the two years
of interest. Population indices for the first and last years of
a smoothed time series are less reliable than the others, and so
we always drop them before calculating alerts. Because the latest
year is not included, the alerts are therefore less up-to-date than
they could be, but fewer false alarms are generated. The latest
year's data points do contribute to the smoothed curve and are dropped
only after the smoothing has taken place.
The time taken
to collate and analyse bird monitoring data is another factor affecting
the years that can be included in these analyses. Full analyses
of data sets are not usually all available until 12-15 months after
the end of a particular breeding season. This report was prepared
in 2004 when we had analyses of monitoring data up to 2003. As we
drop the final year of the smoothed time series, we report here
on change measures up to 2002.
Long-term changes
for most of the species included in this report are calculated from
joint Common Birds Census and Breeding Bird Survey data (CBC/BBS
indices). The CBC started on farmland in 1962 and on woodland in
1964. However, the early years of the CBC population indices are
strongly influenced by the effects of the unusually severe winters
of 1961/62 and 1962/63, as well as by developments in methodology
(Marchant et al.
1990). Therefore joint CBC/BBS indices have been calculated
using the data from 1966 onwards and population changes are calculated
back to 1967.
Data for other
schemes generally start as soon as the scheme had reached a sufficient
size to produce reliable results. The maximum periods available
from the main schemes contributing to this report are set out in
the table below.
2.8.4
Confidence limits and statistical testing
We show 90%
confidence limits for population change measures wherever possible.
Any decline where the confidence limits do not overlap zero (no
change) is regarded as statistically significant and will trigger
an alert if it is of sufficient magnitude. Note that, because we
are seeking to detect only declines, we are using a one-tailed test
- with a P value of 0.05. These confidence limits therefore do not
indicate whether increases are statistically significant.
The graphs of
population trends show 85% confidence limits because these allow
an approximate visual test of whether the difference between the
indices for any two given years is statistically significant: if
the indices for two given years are assumed independent and normally
distributed with standard errors of comparable size (standard errors
differing by a factor of up to about 2 are quite acceptable), then
to a good approximation the difference between the indices is significant
at the 5% level if there is no overlap in their 85% confidence intervals
(Buckland et al.
1992). This test is fairly robust, and the independence
assumption is reasonable if the years are some distance apart.
Technical
details available here
2.8.5
Data-deficient species
There is uncertainty
about the reliability of the results for some species, either because
data may be unrepresentative or because they are based on a very
small sample of plots. In these cases the cause of the uncertainty
is recorded in the comment column of the population change table.
Unrepresentative
data
In this report
we only present joint UK or England CBC/BBS trends if there was
no substantial or statistical difference between the trends from
the two schemes over the period when they ran in parallel. Thus
the trends are always considered representative of the region concerned.
In previous
reports representativeness was assessed using the criteria developed
by Gibbons et al.
(1993). Data from the 1988-91 Breeding Atlas were used to
compare the average abundance of a given species in 10-km squares
with and without CBC plots. If average abundance is higher in squares
without CBC plots, it is likely that much of the population is not
well sampled by the CBC. In past reports, CBC data for such species
were labelled as "unrepresentative". Where there are insufficient
data to undertake such calculations, expert opinion was used.
Sample
size
Sample size
is assessed from the average number of plots contributing to the
population indices for a given species in each year. A plot with
a zero count would be included provided that the species had been
recorded there in at least one year and that records for that plot
were available for at least two years. Plots where a species has
never been recorded do not enter the index calculations. These average
sample sizes are shown in column four (plots) of the population
change tables. For CBC, WBS and CES, a mean of between 10 and 19
plots is flagged as a small sample. For BBS indices for individual
countries a mean in the range 30-39 plots is flagged as a small
sample. UK BBS indices are only presented for samples of at least
40 plots.
2.8.6
Application to individual schemes
Currently the
full methodology outlined above is applied to the CBC/BBS and the
WBS trends. For the CES scheme and the Heronries census we present
annual indices with confidence limits and then fit a smoothed curve
through the annual index values. We do not currently have confidence
limits for this smoothed curve. Therefore all alert labels for CES
are shown in square brackets. There are no alerts for Grey Heron.
BBS started
in 1994 so only nine years' data (1994-2003) were available for
this report. This is not a long enough time series to apply the
smoothing methods and alerts framework outlined above. Therefore
we have simply calculated change measures between the first and
last years of the BBS time series based on the standard 'sites x
years' model that is used to produce the BBS indices each year.
Technical
details available here
Next - 2.9 Statistical methods used for
alerts
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