Accuracy and consistency in the aerial survey of kangaroos

5 Pages·1999·0.8 MB·English

by  S. C. Cairns

Accuracy and consistency in the aerial survey
of kangaroos
S. C. Cairns
Division of Zoology, School of Biological Sciences, University of New England, Armidale,
New South Wales 2351
ABSTRACT
Accuracy, or bias, is the closeness of a measured value to its true value. It can be of
secondary importance in relation to repeatability and precision in a sampling programme, but
where management decisions, such as the setting of kangaroo harvest quotas, are involved,
accuracy assumes a greater importance. Associated with this is the requirement that the
survey method used be consistent. If this is the case, as has been common practice, then
the negative, but consistent bias of standard fixed-wing aerial surveys of kangaroos can be
redressed through the use of correction factors. The correction factors currently used to
account for the negative bias in fixed-wing aerial surveys of kangaroos, which were derived
for red kangaroos, have not been found to be suitable for all species likely to be encountered
in surveys. This was confirmed by comparison of standard fixed-wing aerial survey Counts
with those obtained using helicopter line transect surveys. While the currently used correction
factors may be suitable for red kangaroos Macropus rufus, correction factors of at least
1.5 times these are probably required for eastern and western grey kangaroos M. giganteus
and M. fuliginws. The standard fixed-wing aerial survey method was found to be spatially
density independent and therefore consistent over seven survey blocks in Queensland. If
desired, this would allow the derivation of broad-scale correction factors for both red and
eastern grey kangaroos of 2.25 and 4.37, respectively. Currently used correction factors range
from 2.29 to 2.57.d epending on vegetation cover.
INTRODUCTION trajectory of a population over time as part
of~thep rocess of ensuring the population's
Critical to the management and conservation
well-being. If this is the case, then a survey
of large kangaroos is the effectiveness of
technique that is repeatable and relatively
the survey techniques used to monitor their
precise but produces a biased population
populations. This effectiveness is usually
index is usually adequate. However, if an
defined in terms of accuracy, repeatability and
estimate of the absolute density of a species
precision, with the relative importance of
is required, as is the case for the setting of
these three properties being determined
harvest quotas for the management of large
by the specific aims of the monitoring
kangaroos, then accuracy assumes greater
programme.
importance.
Accuracy, or bias, is defined as simply being A further characteristic of a survey technique
the closeness of a measured value to its true associated principally with accuracy is that
value (Krebs 1989). The transect-based survey of consistency. The relationship between the
techniques usually used to monitor kangaroo population density estimate, or an index
populations have been recognized as being produced by a particular survey technique,
negatively biased (Pollock and Kendall and the true population density can take a
1987; Southwell 1989). Repeatability can be number of forms (Caughley 1977; Southwell
defined as the closeness of repeated measure- 1989). For a survey technique to be consistent,
ments of the same item (Southwell 1989), or the relationship between the density estimate
as constancy of bias among samples (Pople or index produced by it and the actual
1999). A technique is generally repeatable population density must be linear and pass
if it is unaffected by the conditions under through the origin such that any proportional
which it is used. Precision is related to the change in the population density will be
random errors associated with the sampling reflected in the same proportional change
process and is influenced directly by sampling in the density estimate or index (Southwell
intensity (Southwell 1989). Precise estimates 1989).
have low coefficients of variation.
Consistency, like repeatability and precision,
Ordinarily, within the context of wildlife is generally more important than accuracy
monitoring programmes, repeatability and (Southwell 1989). Consistent but inaccurate
precision are considered to be relatively more (biased) counts produced by a particular
important than accuracy, particularly if the survey technique can provide useful popu-
aim of a sampling programme is to follow the lation estimates o r indices. If the relevant
Australian Zoologist 31(1) 275
information is available, these counts can be be attributed to doubt about the various ways
corrected for the inherent bias of the survey in which the baseline estimates of the true
densities
technique and estimates of the true population population were derived. Never-
density produced. theless, some of these studies (Short and
Bayliss 1985; Short and Hone 1988; Grice
THE CURRENT STATUS OF et al. 1990) did provide further weight to
FIXED-WING AERIAL SURVEYS the argument that the Caughley et al. (1976)
correction factors were not as generally
Aerial surveys of kangaroo populations using
applicable as first thought, particularly for
fured-wing aircraft were first conducted in the
grey kangaroos.
1960s (Frith 1964; Newsome 1965; Bailey
1971). Refinement of the survey technique and
A NEW APPROACH TO THE PROBLEM
the development of a set of correction factors
OF CORRECTION FACTORS
to overcome the negative bias inherent in the
counts obtained was undertaken by Caughley Mindful of the problems associated with
et al. (1976). They used an indirect regression the correction factors that were being used
method to develop these correction factors as part of the standard aerial survey method,
(Caughley et al. 1976). a new approach to surveying kangaroo
populations using a helicopter as the survey
Following the standardization of the survey
platform and the line transect method
technique and development of the correction
was developed by Clancy et al. (1997). The
factors, broad-scale aerial surveys of kangaroos
impetus for this had come from the success
began to be undertaken on a regular basis
that Southwell and Weaver (1993) and
throughout Australia in the late 1970s. These
Southwell (1994) obtained by using the line
surveys became an integral part of the
transect method in walked ground surveys of
kangaroo management programmes of New
kangaroo populations.
South Wales (Caughley et al. 1977; J. Caughley
el al. 1984), South Australia (Caughley and In a series of experiments conducted in
Grigg 1981; Cairns and Grigg 1993), Western Queensland, Clancy el al. (1997) were able to
Australia (Short el al. 1983) and, to a lesser demonstrate that for both red kangaroos and
extent, Queensland (Caughley and Grigg eastern grey kangaroos there was no difference
1982). The general approach and methods between the density estimates obtained using
used in these large-scale surveys are outlined helicopter line transect surveys and walked
in Caughley and Grigg (1981). line transect surveys. This, however, was not
the case for common wallaroos M. robustus for
While surveys using fixed-wing aircraft and
which helicopter line transect surveys under-
the correction factors derived by Caughley
estimated the density estimates of walked
et al. (1976) had been considered suitable
line transect surveys (Clancy et al. 1997). From
for deriving population estimates for the
the work conducted by Southwell and Weaver
red kangaroo Mncropzls mfiLs inhabiting open
(1993) and Southwell (1994), it could be
habitats, the accuracy of population estimates
assumed that helicopter line transect surveys
for other species using these correction factors
were similarly producing accurate estimates of
in more heterogeneous habitat had come
red and eastern grey kangaroo densities.
under some scrutiny (Barnes et al. 1986;
Hill et al. 1987). Also, a number of studies In further studies conducted in Queensland,
since Caughley el al. (1976) had proposed Pople et al. (1998a,b) compared standard
alternative, generally higher, correction factors fixed-wing aerial surveys with helicopter line
for eastern and western grey kangaroos M. transect surveys. These studies confirmed
giganteus and M. filiginosus (e.g., Short and the suspicion that the Caughley et al. (1976)
Bayliss 1985; Southwell et al. 1986; Short correction factors used to adjust standard
and Hone 1988; Grice et al. 1990). However, fixed-wing survey results were underestimating
the correction factors developed by Caughley densities of eastern grey kangaroos (Barnes
et al. (1976) continued to be used in relation et al. 1986; Hill et al. 1987; Clancy et a[.
to the standard fixed-wing method of aerial 1997). Correction factors derived by Pople et
survey, and the only real change to the al. (1998b) for red and eastern grey kangaroos
technique was the development of a tempera- in seven survey blocks ranging over the
ture correction factor that could be used in biogeographic areas of Queensland where
conjunction with the habitat correction factors these two species are relatively abundant are
(Bayliss and Giles 1985; Caughley 1989). given in Table 1.
That none of the correction factors derived Although derived for a number of survey
in more recent studies (see Table 4 in Pople blocks with varying vegetation cover, it was
et al. 1998a) replaced, in general use, those concluded by Pople et al. (1998b) that there
derived by Caughley el al. (1976) can probably was broad agreement between the proposed
276 Ausfralian Zoologist 31(1)
Tabb 1. Correction factors for the density estimates fmm a clear indication that correction factors
standard fixedwing aerial surveys on seven survey blocks double those that have been used are required
in Queensland based upon concurrent density estimates if reasonably accurate estimates of eastern
obtained fmm helicopter line transect surveys in the
grey kangaroo numbers are to be obtained.
same blocks. No correction factor has been derived for
red kangaroos in the Goondiwindi block because of a Also, although the data are limited (Short
very low and imprecise density estimate. Where they have and Bayliss 1985; Short and Hone 1988),
been given, the standard errors are those that have been this could also be the case for western grey
derived by using individual transect lines in blocks as
kangaroos.
replicates and treating the two survey methods as a form
of double sampling. (Data from Pople tt ol. 1998b).
CONSISTENCY
Eastern grey
If helicopter line transect surveys provide
Survey block Red kangaroos kangaroos
density estimates that can be assumed to
Longreach 1.67 "_ 0.37 10.18 -C- 9.14 be accurate (Clancy et al. 1997; Pople et al.
Windorah 3.14 9.50
1998a), then the relationship between these
Blackall 2.63 ? 0.44 5.02 -C 1.05
Charleville 3.09 5.09 z 1.27 estimates and those derived from standard
*
Bollon 1.75 3.99 1.20 fixed-wing aerial surveys of the same areas can
Roma 0.74 3.41 f* 0.68 be used to assess whether or not the fixed-
Goondiwindi - 7.56 1.89
wing method is consistent. Figure 1 shows the
relationships between red and eastern grey
correction factors for red kangaroos (Table 1) kangaroo densities derived using standard
and those derived by Caughley el al. (1976). fixed-wing aerial surveys and helicopter Line
The correction factors that had been derived transect for seven survey blocks in Queensland
by Caughley ct al. (1976) ranged from 2.29 to (Pople et al. 1998b).
2.53, depending upon the type of habitat.
Linear regressions fitted to the data in
In the case of eastern grey kangaroos, the Figure 1 were found to be significant (red
correction factors derived by Pople et al. kangaroo: rP = 0.90; tr = 5.86, P < 0.01;
(1998b) for the seven survey blocks (Table 1) eastern grey kangaroos: r2 = 0.85; t5 = 5.34,
were between 1.5 times and 4 times the P < 0.01), but with intercepts not significantly
general correction factors derived by Caughley &fferent from zero (red kangaroos: 4 = 0.51,
et al. (1976). Despite the broad range of P > 0.50; eastern grey kangaroos: t5 = 0.56,
these correction factors, the details of which P > 0.50). This therefore allowed the fitting
are discussed by Pople et al. (1998b), there is of the simpler model of a linear regression
Helicopter line transect density (km-')
Fipn 1. The relationships between kangaroo densities derived from standard 200
m fixed-wing strip transect surveys and helicopter line transect survey for red
kangaroos (0)a nd eastern grey kangaroos (0)T.h e linear regressions passing through
the origin are confirmation that the standard 200 m fixed-wing.strip transect method
of aerial survey is consistent. (Data fmm Pople et nl. 1998b).
June 1999 Australian Zoologist 31(1) 277
through the origin to these data. Fitting such correction factor derived this way would
a model shows that the standard fixed-wing he 4.37, which is slightly less than twice
aerial survey method is consistent (Southwell the Caughley et al. (1976) correction factors.
1989). The two regressions of this form shown An alternative would be to derive and use
in Figure 1 are y = 0.445~fo r red kangaroos separate regional correction factors such as
and y = 0.229~f or eastern grey kangaroos, those shown in Table 1. This would be
where y is the fixed-wing aerial survey density appropriate if the linear regression between
estimate and x is the helicopter line transect fixed-wing aerial survey density estimates and
density estimate. helicopter line transect density estimates, such
as those shown in Figure 1, failed to conform
The fitting of linear regressions to the data
to the normal error model because of regional
shown in Elgure 1 assumes that the relation-
differences in bias due to, say, the influence
ships between the fixed-wing aerial survey
of habitat.
density estimates and helicopter line transect
density estimates were spatially density Kangaroo densities differ on a regional
independent. To ensure that this was the basis. Despite this, the different densities of
case, the linear form of the power relationship red and eastern grey kangaroos in the seven
+
(log y = log a b log x) was also fitted survey blocks used by Pople et al. (1998b) did
to the data and the regression coefficient not influence the overall relationship between
(h) tested against a null model of one. A fixed-wing aerial survey density estimates and
full explanation of this model is given in helicopter line transect density estimates.
Pople (1999). For both red and eastern grey Hence, the standard fixed-wing aerial survey
kangaroos, the regression coefficients were method could be considered to be spatially
found not to he significantly different from density independent and therefore consistent.
one (red kangaroos: t, = 0.84, P > 0.50; However, because populations rarely remain
eastern grey kangaroos: t5 = 2.07, P > 0.05), static, there is a possibility that the relation-
thus confirming that the relationships between ship between fixed-wing aerial survey density
fixed-wing aerial survey density estimates and estimates and the true population density
helicopter line transect density estimates were could he temporally density dependent. The
in fact density independent and consistent. likelihood of there being temporal density
dependence between fixed-wing aerial survey
DISCUSSION
density estimates has been examined by Pople
It appears from recent experimental work (1999) in relation to repeatability.
(Pople et al. 1998a,h) that, although the
correction factors developed by Caughley ACKNOWLEDGEMENTS
et al. (1976) remain acceptable for estimating
The writing of this paper benefited greatly
red kangaroo numbers, they are not suitable
from discussions with Tony Pople.
for eastern grey kangaroos nor, perhaps,
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