Census of Dugongs in the Coastal Waters of the Northern Territory. Peter Bayliss. Conservation Commission of the Northern Territory, Box 38496, Winnellie P.O. ...
Aust. Wildl. Res., 1986, 13, 27-37
Factors affecting Aerial Surveys of Marine Fauna, and their Relationship to a Census of Dugongs in the Coastal Waters of the Northern Territory Peter Bayliss Conservation Commission of the Northern Territory, Box 38496, Winnellie P.O., N.T. 5789.
Abstract
Some factors that may affect the aerial counts of dugongs, dolphins and turtles were examined experimentally. Tidal influence did not affect the counts of dugongs or dolphins, but those of turtles increased around high tide. A combined doubling of survey altitude and transect width reduced observed density of all three classes of animals by 50%. The counts of four observers did not differ significantly,but further data counsel caution. Overcast weather depressed counts of dugongs and turtles. Dolphin counts were affected by water surface condition, counts being lowest in choppy seas. A mark-recapture model was used on tandem observations to derive correction factors for groups of animals missed on the surface of a transect. Observers missed between 33% and 75% of dugong groups on the surface, the probability of detection decreasing with increased survey altitude and transect width. A similar range and pattern of probabilities was found for dolphins and turtles. Dugongs were censused in the coastal waters of the Northern Territory between the Daly River and Millingimbi in December 1983, an area of 28 746 km2. Sampling intensity was 7.6%. A minimum population of 2953 & 530 (standard error) was estimated, an overall relative density of 0.11 2 0.02 kmP2. A theoretical correction for submerged dugongs not seen yielded a total population estimate of 38 000, an overall density of 1.46 k n r 2 . The distribution of dugongs in the survey area was patchy, the highest densities being associated with shallow coastal waters, sheltered bays, and large islands.
Introduction
The dugong, Dugong dugon (Miiller),is one of four extant species of sirenians in the world, and is included in the IUCN list of animals vulnerable to extinction because much of its IndoPacific range has been apparently reduced (Thornback and Jenkins 1982). The coastal waters of tropical Papua New Guinea and Australia contain most of the world's remaining dugongs (Marsh 1983).Although the exact status of dugongs in Australia is unknown, there is increasing concern about the effects of hunting and accidental kills by commercial fishing on their numbers. Similar concern is expressed for the green turtle Chelonia mydas (Linnaeus),the loggerhead turtle Caretta caretta (Linnaeus),the hawksbill turtle Eretmochelys imbrica (Linnaeus), and certain species of dolphins (e.g. the Irrawaddy river dolphin Orcella brevirostris). The only practicable means of determining relative distribution and abundance of dugongs over extensive and remote areas is by aerial survey (Heinsohn 1975, 1978; Heinsohn et al. 1976a; Ligon 1976; Anderson 1982; Marsh et al. 1984a). Unless some of the causes of bias in aerial census can be quantified the status of dugongs and other marine animals will remain controversial. Correction of visibility bias is essential if a more accurate estimate of numbers is required to allow sustained-yield management by Aboriginal people. Even if the objective is to monitor population trends by means of a relative index, sources of bias must be standardized. This is especially pertinent to dugongs, which have low recruitment rates (Marsh et al. 1984b) and are difficult to see on most surveys. 03 10-78331861010027$02.00
This paper describes an experiment in which some factors affecting the visibility of dugongs, dolphins and turtles on an aerial survey were examined. Those animals that could not be identified as a dugong or a dolphin were classed as 'unknowns'. We did not distinguish between the various species of dolphins and turtles because of the difficulties of identifying these from the air. A markrecapture model (Magnusson et al. 1978; Caughley and Grice 1982)was used on the observations of two pairs of tandem observers during the experiment to derive a correction factor (CF) for those animal groups that were missed on the surface of a transect. The results of the experiment were used to define a set of standardized survey variables for use in a broad-scale survey of dugongs in coastal waters of the Northern Territory. Counts of dugongs were multiplied by the appropriate CF to give a more accurate index of density and distribution in the survey area. Water clarity in the survey area was extremely poor, hence submerged dugongs were almost impossible to see. A model based on surfacing and diving times is tentatively proposed to account for the number of submerged dugongs. Methods and Analysis Experimental (i) Factors affecting visibility Animals were counted on 14 unequal-length transects (5-12 km) in Port Essington, Cobourg Peninsula. Two pairs of tandem observers, on either side of a Partenavia high-wing aircraft, counted on transects defined by fibreglass rods attached to artificial wing struts. Transects were spaced 2.5 km apart, and were flown at two survey combinations (272-m altitude and 400-m transect width per observer, and 136-m altitude and 200-m transect width per observer) during high and low tide. At each tide transects were flown first at the higher altitude and then the lower. This combination was replicated twice over three consecutive days, resulting in four tidal sessions. Each tidal session took 3 h. During the experiment (4-6 December 1983) high tide occurred in the morning and low tide during mid-afternoon. Extremely bad glare associated with low sun angles in the early morning was avoided. Counts were continuously recorded for every 5 km of transect (called a unit). During a 7-s pause between units, each observer ranked glare on a five-point scale (proportion of transect blotted out), and one observer recorded other weather-related factors that may have affected visibility. These were percentage cloud cover (an index of general light condition), an index of water surface condition on a five-point scale (very choppy to glass smooth), and an index of water clarity on a five-point scale (very turbid to crystal clear). The effects on visibility of uncontrolled weather-related factors were analysed by stepwise multiple regression, where observed density per transect is the dependent variable, and the indices of the weather-related factors averaged over the whole transect were the independent variables. The effects on visibility of those factors that were balanced in the experimental design (observer, animal class, tide, and survey combination) were analysed by ANOVA after counts were transformed to densities (per square kilometre) because of varying transect lengths. Transects are not treated as a blocking factor (Zar 1974) in this analysis but as replicates; each transect combination was replicated twice because of the low numbers of observations. All factors are fixed and the F-ratio denominator is the error mean square. The analysis is an approximation because the replicates were counts on systematically spaced transects of unequal length. Because the distribution of transect counts may be non-normal (too many zeros), and some factors may influence counts in a multiplicative manner (Eberhardt 1978),transect densities were transformed to natural logarithms after adding 1 and the data re-analysed.
(ii) The mark-recapture model The details of the model are outlined in Appendix 1. Each pair of tandem observers counted animal groups independently in their transect. Observers recorded the position of each animal group within the transect and their behaviour (submerged, diving, floating on the surface, etc.). The CFS derived for each observer and animal class apply only to groups on the surface of the transect. Broad-scale Scanning Survey of Dugongs between the Daly River and Millingimbi The coastal seas between the Daly River and Millingimbi (including Melville and Bathurst Is; see Fig. 1) were surveyed between 10 and 30 December 1983. The survey was conducted towards the end of the dry season; hence the heavy rain and storm activity of the early wet were avoided. Tides were neap,
Aerial Survey of Marine Fauna
resulting in clearer water between tidal changeover than at spring tides. Surveys were standardized to the range of weather conditions encountered during the experiment. Severe glare associated with a low or midday sun was avoided.
Fig. 1. Survey areas, showing the survey blocks (1-9) and transects. AS, Apsley Strait; BI, Bathurst I.; CI, Crocker I.; CP, Cobourg Peninsula; D, Darwin; J, Jabiru; Ma, Maningrida; Mi, Milligimbi; MI, Melville I.; PE, Port Essington; PI, Peron I.; SB, Snake Bay; VG, Van Diemen Gulf; YB, Yananti Bay.
All transects were flown at 136 m (450 ft) altitude and at 185 km h-' (100 knots). Two observers, one on either side of the Partenavia, each scanned a transect 200 m in width. The counts were multiplied by the appropriate CF to account for those dugongs missed on the surface. The survey area was divided into nine blocks and each was sampled intensively (Table 1).Block 8 is Port Essington, and the population estimate was calculated from the results of the experiment. Transects were placed perpendicular to the general direction of the coastline to aid navigation. Hence they were aligned either north-south or east-west, and were systematically spaced 5 km apart (Fig. 1). In the absence of an Omega navigation system, the end and start Table 1. Areas of the survey blocks and sampling intensities
Block No.
Area (km2)
Sampling intensity (%)
-
Total area 28 746
Area (km2)
Block No.
-
Sampling intensity (%)
--
Overall sampling fraction 7.6%
of transects offshore were located by time and aircraft speed. Islands were used to correct position, and in general most transects from sea to land were accurately placed and took the expected amount of flying time. Counts were recorded continuously for every 5-km unit of transect, and indices of weather were recorded during a 7-s pause. This aspect of the design was used to produce a relative density and distribution map. For the purposes of calculating numbers of dugongs per block, the corrected unit counts were pooled and the data analysed on a transect basis. The area covered in the pause was excluded from all analyses. Because transects were variable in length, the Ratio Method (Jolly 1969)was used to estimate density, population
P. Bayliss
size, and their associated standard errors. The formula is summarized in Appendix 2. Because the sampling intensity was very high (a mean sampling rate of 9.6% per block) any statistical bias resulting from this method is considered inconsequential (Caughley and Grigg 1981).
Table 2. Analysis of variance of transect densities of all classes of animals as affected by survey variables NS
not significant; *P
