canberrabirds

Pied Currawong: the facts on abundance trends from GBS data

To: "martin butterfield" <>
Subject: Pied Currawong: the facts on abundance trends from GBS data
From: "Philip Veerman" <>
Date: Sun, 30 Mar 2008 16:58:43 +1000
Martin,
 
Sorry you are wrong. My comments are correct but have a look at Appendix 8 of the book on page 121, which is as copied below. How is that consistent with your wrong accusation of my book being "without any measure of significance"? The many reviews of the GBS Report (see Appendix 9) do not mention a lack of statistical rigour therein.
 
The fact remains that applying analyses to the regressions of the species trends graphs is simply beyond the scope of the size of the book and the intended non-technical audience, not all of whom have studied statistics. Besides as the book clearly states bird populations did not start in 1981 nor finish in 2002. There is no practical reason to particularly assume that the trends for any one species would follow a linear trend of increase or decrease throughout that time. However in some aspects that still forms a useful model. The other point to be aware of is that many species, such as the Pied Currawong, the seasonal variations in abundance is far greater than the long term changes. When statistical models asses this, the perceive the seasonal variations as random, rather than regular and therefore do not show the trends as significant.
 
Extract follows (I hope it does not lose its formatting and comes through as a neat table).
 

The data shown in Figures: 4, 8, 23, 26, 28, 29 & 30 represent information that can be assessed with regression analysis. This method can calculate the line of best fit, which is included in these graphs (not Figure 23). It can also demonstrate how well they fit to this straight line. In each case the X & Y axes are as shown in the graph. The regression line is given by the standard formula of Y = a + bX. The values of a (intercept on Y where X = 0) and b (slope of the line), n (the sample size), f value from the Analysis of variance (ANOVA) table and the probability p significance of that f value are given, with a comment. High f values and low p values mean the regression line is a good fit to the data. Note that the p column includes powers of ten, so that 1.46, E-04 is 0.000146. Common practice gives p < 0.05 as significant.

Figure

Page

a

b

n

f

p

Significance

4

25

0.687

0.0094

20

22.974

1.46, E-04

High

8

26

-14.343

43.6632

294

8439.616

1.6, E-217

Huge

23

40

25.473

0.3877

1316

167.952

3.10, E-36

Huge

26

41

7.156

0.9778

294

2264.463

1.34, E-139

Huge

28

42

120.030

0.0070

21

11.148

0.0034

High

29

42

13.959

0.2071

21

90.967

1.12, E-08

Very high

30

43

82.665

-0.0025

21

1.406

0.2503

Not

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