Further on this: Martin wrote:
"The main thing
that can be said about the long term trend for Pied Currawong abundance in the
GBS results is that there is no trend. The values of the correlation
coefficients for linear and polynomial trends for 21 and 26 year results for the
species range from just over 0.1 to nearly 0.3. These are well below the
values that would indicate a trend significantly different to
zero.
The facts are that the trends are obvious and strong. There
are two trends occurring and they need to be teased apart and seen separately,
especially because the biological impacts are different. We should be more
concerned about the biological impacts than the statistics. It is during the
summer that the PC is a major predator of other birds' nesting and during the
winter that the PC spreads seeds of woody weeds. We need to see the GBS data in
context. There are plenty on long standing bird surveys around the world that
are not continuous and only comprise summer or winter counts. If we did that,
then the results would be very different.
I have just done a regression analysis for the first 21 years of GBS data. Bearing in mind that the
analysis of the GBS does not exist beyond the first 21 years. Although
I discounted the odd months out of year 1 and 21 because of the split, in that
the survey started in July and ended in June). Winter includes June, July and
August and Summer includes December, January and February. Therefore each
analysis includes 63 data points. The analysis of variance from the
regression is also presented (below).
Just imagine that we did a GBS in only summer or winter. Two
separate regression analyses for these data show: for winter, a probability
value (significance of the ANOVA regression F test) of 2.0769E-05 in other
words, the chance that the observed decrease is due to chance factors is
0.000020769. Likewise for summer a probability value of 3.59055 E-14
in other words, the chance that the observed increase is due to chance factors
is 0.0000000000000359055. Normally biologists accept as reasonable evidence,
anything less than 0.05 (meaning 95% probability). These two trends are way off
the scale for any suggestion of no trend! Yet Martin says no trends,
just on the simple basis of missing that the two trends are running in opposite
ways (an increase and a decrease). The possibility of damage done to the
GBS and COG's data by such incompetent analysis and comment is of great concern.
It is simply the fact that summer abundance has increased to a
similar margin as winter numbers have decreased that appear to confuse those not
clear in the biological meaning of the results or capacity of the survey).
It was not by accident that I chose this species as one of the three to present
the full graph of abundance by month throughout the 21 years of the GBS (on page
90).
SUMMARY OUTPUT |
Of regression analysis of Pied Currawong Winter values of
A |
|
|
|
|
|
|
|
|
|
|
|
|
Regression Statistics |
|
|
|
|
|
|
|
Multiple R |
0.508654885 |
|
|
|
|
|
|
|
R Square |
0.258729792 |
|
|
|
|
|
|
|
Adjusted R Square |
0.246577822 |
|
|
|
|
|
|
|
Standard Error |
1.426770386 |
|
|
|
|
|
|
|
Observations |
63 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ANOVA |
|
|
|
|
|
|
|
|
|
df |
SS |
MS |
F |
Significance F |
|
|
|
Regression |
1 |
43.34189562 |
43.3419 |
21.29118 |
2.0769E-05 |
|
|
|
Residual |
61 |
124.1760978 |
2.035674 |
|
|
|
|
|
Total |
62 |
167.5179934 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
Intercept |
7.934359474 |
0.363835294 |
21.80756 |
1.71E-30 |
7.206825636 |
8.661893313 |
7.206825636 |
8.661893313 |
X Variable 1 |
-0.04561298 |
0.009885272 |
-4.61424 |
2.08E-05 |
-0.06537981 |
-0.025846155 |
-0.06537981 |
-0.025846155 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
SUMMARY OUTPUT |
Of regression analysis of Pied Currawong Summer values of
A |
|
|
|
|
|
|
|
|
|
|
|
|
Regression Statistics |
|
|
|
|
|
|
|
Multiple R |
0.782564696 |
|
|
|
|
|
|
|
R Square |
0.612407504 |
|
|
|
|
|
|
|
Adjusted R Square |
0.606053528 |
|
|
|
|
|
|
|
Standard Error |
0.337899565 |
|
|
|
|
|
|
|
Observations |
63 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ANOVA |
|
|
|
|
|
|
|
|
|
df |
SS |
MS |
F |
Significance F |
|
|
|
Regression |
1 |
11.00449822 |
11.0045 |
96.38179 |
3.59055E-14 |
|
|
|
Residual |
61 |
6.964743096 |
0.114176 |
|
|
|
|
|
Total |
62 |
17.96924131 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
Intercept |
1.479013121 |
0.086166484 |
17.1646 |
4.95E-25 |
1.306712539 |
1.651313703 |
1.306712539 |
1.651313703 |
X Variable 1 |
0.022983684 |
0.002341112 |
9.817423 |
3.59E-14 |
0.01830234 |
0.027665027 |
0.01830234 |
0.027665027 |
Also Martin wrote: I have attached a
graph showing A values by week (months are difficult since the weeks don't
all start and finish at the bginning/end of months) for 21 years and later
years. This clearly shows a flattening of the seasonal distribution in
the recent past with more birds in the warmer months and less in the colder
months. There has been previous correspondence on this list (last year
some time) about the reduced frequency of the huge flocks seen (particularly
in the Weston area) in the early years of the Survey.
As for "months are
difficult since the weeks don't all start and finish at the beginning/end of
months". What a non issue! Weeks and months are arbitrary human constructs and
dividing lines. (Indeed none of the weeks and months start on the same day apart
from on 1 January but it doesn't matter one iota). In contrast days and
seasons are real. However collecting data by week happens to be convenient to
our brains, our lifestyles and constraints of designing and printing a
chart. The arrangement of the GBS Calendar was a brilliant way to approach the
problem, invented by Henry Nix and it and the connection of weeks and months are
fully explained in the GBS Report.
Looking at the graph presented by weeks tells us
almost nothing more that looking at the graph presented by months. It simply
provides more data points. Each with a smaller sample size, thus increasing the
importance of random sample error for the rarer species. Thus weeks makes it
harder to provide the information in a graph and certainly much harder to
describe in narrative. Believe me, having written all the text I did for the
GBS Report it would have been much more difficult to describe every
change in terms of week numbers rather than months, because everyone understands
months.
Lastly, not only has there "been previous correspondence on this
list ... about the reduced frequency of the huge flocks seen ... in the
early years of the Survey. True but I point out that
this has been fully described in the GBS Report and the results Martin has now
provided since Year 21 are simply a continuation of the same trend that I
described therein (which is hardly surprising).
Philip
|