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"Project 70.1"--Cover. ; "November 1959." ; "Operation Hardtack, April-October 1958"--Cover. ; "WT-1721 ; AEC Category: Instruments ; Military Category: 28"--Cover." ; Mode of access: Internet.

Aerial surveys of feral pigs in the Goondiwindi region of Queensland showed an overall observed
density of about 1 per square kilometree. On mature wheat crops in October, up to four feral pigs per
square kilometre were seen amidst substantial crop damage. Emus were less abundant and seen more
evenly over all habitats at an average of 0.3 per square kilometre. Factors affecting sightability are
discussed.

Observed densities of emus, Dromaius novaehollandiae, estimated from aerial surveys were compared with
results of a drive count in 1985 and 1986. The study area was mostly open shrubland. True density of emus
was 2.56 per km2 in 1985 and 1.15 per km2 in 1986. Aerial survey estimates were 66 and47% oftrue density in
the two years, respectively, and the weighted average was 60%. Over the limited range tested ofeach variable,
observed density was not significantly affected by temperature, cloud cover or time of day.

During October and November this year, an extensive dugong aerial survey was undertaken along the Northern Territory (NT) coast. The survey was part of an offset program developed by the NT Government through the Department of Land Resource Management (DLRM) Flora and Fauna Division with funds provided by the Ichthys LNG Project. The offset program "the abundance and distribution of dugongs in the Northern Territory" had a primary objective to assess the distribution and abundance of dugongs across the NT in a robust manner.

Some factors which affect the aerial counts of dugongs and sea turtles were examined experimentally.
There was no significant difference in the observed density of dugongs when survey height was doubled
from 137 m to 274 m with an accompanying doubling of transect width on either side of the aircraft
from 200 m to 400 m. In contrast, a significantly higher density of turtles was observed at the lower
heightharrower transect width. The higher level of glare on the exposed side of the aircraft, the time
of day and the time from high tide made no significant difference to the observed densities of dugongs
or turtles. The survey crew included a tandem team of two observers on each side of the aircraft,
who reported their uncolluded observations into separate tracks of a two-track tape recording system.
This allowed the reports of tandem observers to be compared in order to assess observer reliability.
Overall, observers missed over 40% of dugong groups and over 80% of turtles visible within the
transect including groups of more than 10 dugongs. The chance of observers missing a group of
dugongs was independent of group size. There was little disagreement between tandem observers about
the identification of animals, or the position of animals in the water column. However, observers
differed markedly in their categorisation of dugong behaviour and in their counts of animals
(particularly dugong calves) in larger groups.

Mark–recapture and line-transect sampling procedures both provide estimators for visibility bias in aerial surveys, and have coexisted in the literature for decades. Mark–recapture estimators of abundance tend to be negatively biased in this context as a result of unmodelled heterogeneity. Line-transect sampling can also be negatively biased if detection probability on the line is less than 1.0. Numerous papers have described hybrid approaches using mark–recapture and line transect methods but there have been some subtle but important differences that may not be apparent to the practitioner. We have used wild horse survey data collected in south-eastern Australia and some imaginary data to highlight these subtle differences. We demonstrate the advantage of using the hybrid approach, which uses the strengths of both mark–recapture and line-transect procedures by fitting a detection function (with p(0) = 1) to the line-transect data to estimate the shape of the detection function, and uses a separate detection function for the mark–recapture data to estimate the intercept (p(0)).

Altitude and flight speed affect detection probability and they typically vary during the course of most aerial surveys. We demonstrate how these sources of variation can be accommodated with covariates in a line-transect analysis using data from a pronghorn (Antilocapra americana) survey in Wyoming and a survey of Antarctic ice seals (Lobodon carcinophaga, Leptonychotes weddellii, Hydrurga leptonyx, Ommatophoca rossii). We also show how the likelihood for binned distance data can be modified to allow for variation in altitude. As an alternative, we develop an estimator for aerial line-transect sampling based on vertical angles rather than distance. With a small simulation study, we show that our estimators are unbiased and are preferable to using biased estimators based on fixed-distance intervals derived from average altitude.

Density estimates are seldom examined against actual population size, hence the ability of estimators to correct for bias is unknown. Studies that compare techniques are difficult to interpret because of the uncertainty of adherence to their respective assumptions. Factors influencing detection probability, estimators that correct for bias, the validity of their assumptions and how these relate to true density are important considerations for selecting suitable methods. Here we contrasted five estimates of feral goat (Capra hircus) densities obtained from aerial surveys (strip counts, Petersen, stratified Petersen, Chao, Alho) against known densities derived from total counts. After correcting for recounting, the Alho and stratified Petersen estimators applied to helicopter surveys were the most accurate (bias = 0.08 and –0.09 respectively), which suggests that estimates were improved by correcting individual observations according to the characteristics of each observation. An approach using modified Horvitz–Thompson equations for unequal-sized units is described and is recommended to allow for this. Both the Chao (bias = 0.35) and Petersen (bias = 0.22) estimators were positively biased, which is likely to be a consequence of averaging detection probability across all observations. Helicopter survey using capture–recapture with multiple observers is recommended for estimating the density of wildlife populations. However, adjustment for the factors that influence detection probability is required.

Experimental aerial and ground censuses of waterbirds were conducted on three small, isolated bodies
of water on the New England tablelands of New South Wales. The flying height at which sightability was
optimized for the most common species was 30 m. Aerial and ground counts were significantly
correlated for most species on the three watar bodies. Black swan, swamphen, coots, musk ducks and
maned ducks were counted in equivalent or greater numbers from the air than from the ground on at
least one water body. Other species were counted in lower numbers from the air than from the ground. A
fairly high precision in the aerial-ground relationship for the most abundant species indicates that aerial
survey can be a useful procedure for obtaining indices or estimates of the population sizes of these
species. However, differences in sightability between species and between types of water body indicate
that indices should be used and interpreted with caution. Other bird species from a variety of habitat
types which are also amenable to aerial survey are discussed, and some recommendations for aerial
surveys of birds are provided.

The accuracy and precision of eight line transect estimators and one strip transect estimator were
examined by helicopter aerial survey. Carcasses of feral pigs were counted in an area of treeless
floodplain and Eucalyptus woodland. The ratio and Cox's methods, Fourier series, exponential power
series, half-normal, exponential polynomial, negative exponential, hermite polynomial and hazard rate
estimators gave accurate estimates. Using the survey method described, most estimators were of similar
accuracy and precision, but the Fourier series estimator was the most accurate.