CHAPTER 6
FACTORS AFFECTING THE TRADITIONAL HARVEST OF THE DUGONG FISHERY AT MABUIAG
ISLAND IN 1997-99
This chapter provides information on the major biological, environmental, social, cultural and economic
factors that affected the pattern of hunting, hunting effort and harvest levels of dugong in Mabuiag Island
in 1997-99. 1 conclude that this information has potential to improve existing management arrangements if
it is integrated with the cultural and socio-economic perspectives of Torres Strait Islanders.
Towards a sustainable Indigenous fishery for dugongs in Torres Strait: a contribution of empirical data and process
Chapter 6 Factors Affecting Dugong H a ~ ~ t s 91
6.1 INTRODUCTION
There is increasing recognition that effective management of natural resources for sustainable use will
require an understanding of both human and biological systems. This is reflected in the increasing number
of studies across various disciplines aimed at gaining a better understanding of the interactions of human
behaviour and the resources they exploit, and how best to regulate this activity. Such studies have
included those in fisheries science, particularly in commercial fisheries (see Holland and Sutinen 1999;
Holland 2000; Hilborn and Walters 2001) and anthropology for subsistence practices such as hunting (see
Winterhaulder and Lu 1995; Fitzgibbon 1998) and fishing (Aswani 1998; Bird et a/. 2001). Whereas the
approaches vary according to the discipline, all studies emphasise the need for information about the
behavioural response of fishers or hunters to changes in stock or prey abundance.
In fisheries, there is growing acceptance that it is more effective to regulate 'how' people fish rather than
controlling 'how much' is caught. Historically, commercial fisheries have been managed numerically
through the use of quotas or other controls based on empirical information (see Hilbom and Walters
2001). However, there is growing recognition that the numerical approach of current resource economics
and marine biology which are based on linear relationships and states of equilibrium are of limited
effectiveness because they fail to account for the stochastic aspects of many fisheries (see Palsson
2000). Unpredictable changes in populations result primarily from complex changes in environmental
factors (e.g., dugongs, see Chapters 2 and 9) and compounds even further the level of uncertainty and
limits of scientific ecological knowledge (see Acheson ef a/. 2001).
For fisheries that are stochastic in nature, the growing tendency to regulate 'how' fishers catch fish is
reflected in the increasing number of fleet dynamics studies aimed at understanding the dynamic
responses of fishers to changes in stock size and management itself (Hilborn and Walters 2001). Fleet
dynamic models have been used to explore how the interaction of human and biological systems
influences the results of regulatory changes (Holland 2000). These models have been used to understand
the response of fishers in redistributing their fishing effort after closures, impacts on other fish stocks
andlor in other areas and the overall productivity of the fishery (Holland and Sutinen 1999; Holland 2000)
Anthropologists have adapted optimal foraging theory and population biology (e.g., population growth
rates of target species) to simulate the population dynamics of hunter-gatherers and their prey resources
(Winterhaulder and Lu 1997). Models have been used to examine how characteristics of individual
hunterlfishers foraging tactics and resource populations might impact on the sustainability of a prey
resource. In the context of my study, it is pertinent to note that 'the important question now is not which
traditional practices, as practised in the past, are sustainable, but rather which conditions cause people to
Chapter 6 Factors Affecting Dugong Harvests 92
conserve their resources and which conditions favour destruction andlor overexploitation of local
resources' (Schmink 1992).
According to Fitzpatrick-Nietschmann (1980), people in the Western Islands of Torres Strait became highly
specialised hunters because of their ability to adapt their subsistence techniques, scheduling and
strategies to coincide with temporal and spatial changes in the marine environment and its organisms. A
hunter's decisions to go hunting are likely to be based largely on the need for fresh meat for home
consumption or for other specific purposes, disposable income to pay for fuel and oil, available crew for
hunting and favourable weather conditions. However hunting success depends on a number of
environmental factors, the local distribution and abundance of dugongs and the skill of the hunter. In
Torres Strait, the social, cultural and economic significance of important traditional resources such as
dugongs and turtles plays a crucial role determining catch effort. Bird et a/. (2001) suggested that foraging
and the distribution of the products of hunting (green turtles) by Torres Strait Islanders do not conform to
predictions of maximisation of individual energetic return rates because maximisation of social and political
benefits are more important in shaping hunting and sharing decisions.
This chapter describes the major factors that affected the hunting pattern, hunting effort and harvest levels
of dugongs at Mabuiag Island during 1997-99. Knowledge of such factors should be central to the
development of more effective management plans. This information has potential to considerably improve
existing management arrangements for dugongs by enabling the integration of western scientific
knowledge and Torres Strait Islander cultural and socio-economic perspectives.
6.2 METHODS
6.2.1 Probability of Hunting*
Important variables influencing hunting activities were identified from the literature on dugong hunting in
Torres Strait (Nietschmann and Nietschmann 1981; Nietschmann 1984,1989; Eley 1988; Johannes and
MacFarlane 1991). These variables were used in the following statistical analyses of my data to explore
the relationships between the major determinants of dugong hunting by hunters based at Mabuiag Island
during 1997-99.
Statistical analyses in this section were performed with the assistance of Steve Delean.
Chapter 6 Factors Affecting Dugong Harvests 93
Data were obtained from my daily records of dugong hunting at Mabuiag lsland (755 days) between
October 1997 and October 1999 (see Chapters 4 and 5). Data for the eight months from March to October
were available for both 1998 and 1999 (598 days). The relationship between the following responses:
the daily probability that hunting occurred;
the total catch, given hunting occurred;
catch per unit effort (catch per month and catch per hunting hour); and
the proportion of females caught
was examined in terms of the various covariates listed below.
The covariates included in analyses were the categorical variables:
Month (8 levels): March to October
Year (2 levels): 1998 and 1999
Month in year (21 levels): January-December 1998, January, March-October 1999
Season (3 levels): South-East (SE), North-West (NW) doldrums and variable wind direction (data
from Island weather station, as data were limited for the North-West season, they were excluded
from analyses in the comparative period (March-October)
Minimum tide height (coded for4 levels): 0.5 m intervals in the range 0.5 - >1.6 m (Australian
National Tide Tables for Moa Island)
Maximum tide height (coded for4 levels): 0.5 m intervals in the range 0.5 - >2.6 m (Australian
National Tide Tables for Moa Island), and
Mean tide difference (coded for 5 levels): differences in 0.5 m intervals in the range 0.5 ->2.5
(Australian National Tide Tables for Moa lsland).
The continuous independent variables used in the analyses were:
lunar days (i.e., day I = new moon etc.);
wind velocity (data on wind direction from the Horn lsland weather station);
tide difference between maximum and minimum tidal height (to the nearest 0.1 m, during March 1
to October 30 in 1998 and 1999, Australian National Tide Tables for Moa Island); and
Chapter 6 Factors Affecting Dugong H ~ N ~ s ~ s 94
daily crayfish catch (kg) landed at Mabuiag Island (log transformed).
The data were modelled using generalised linear models (GLM) and generalised additive models (GAMs).
The GLMs allow the specification of the link function, which determines the relationship between the mean
and the linear predictor, and the variance function, which defines the relationship between the mean and
the variance. The link function used for the binary response 'probability of hunting occurring', and the
'proportion of females caught' was the logit [i.e., log (p I (1-p)], and the variance function was the binomial
distribution (i.e., logistic regression model). The link function used for the count response 'total number of
individuals caught', and the rate response 'catch per unit effort', was the log [i.e., log (y)], and the variance
function was the Poisson distribution (i.e., Poisson regression).
The GAMs were used to examine nonlinear relationships among the continuous covariates and each
response. This was achieved by including smoothing tens. Model selection was based on Akaike's
Information Criterion (AIC), where the model selected for inference was the one that minimised the AIC
Criterion. This method selects a 'best approximating' model from a candidate set of considered models
(see Bumett and Anderson 1998). All means are presented k standard error unless otherwise stated, and
d.f. represents degrees of freedom for the various tests.
6.2.2 Catch Monitoring3
A subset of the data (639 days of recorded observations) used in the statistical analyses in Section 6.2.1
was used to explore various sub-sampling regimes with the aim of determining the most realistic and
pragmatic strategy for independently sampling the dugong catch to provide future estimates of catch rates.
My continuous records of dugong catches from Mabuiag Island collected for the period between 1 January
1998 through 31 October 1999 were used in the analyses (except for the period between 31 January 1999
and 1 March 1999).
To examine the outcome of various hypothetical sampling approaches, the data was sub-sampled and all
(635) possible outcomes recorded for five-day sampling periods (i.e., recorded catch from days 1-5, 2-6,
3-7. . . 635-639 resulting in 635 'samples'). All possible outcomes were then examined to provide data for
ten-day (31 0 samples), fifteen-day (201 samples) and twenty-day (153 samples) sampling periods. The
frequency of such samples containing 0, 1,2,3 dugongs etc was recorded.
3 Statistical analyses in this section were performed with the assistance of Dr Barry Goldman.
Chapter 6 Factors Affecting Dugong Harvests 95
My data was then compared with those available from the AFMN monitoring program CSlRO
(unpublished data, AFMA 1999) to examine the outcome of various sampling approaches. The sampling
regime of AFMA observers is based on a randomised frame survey, which aims to sample 120 days in a
year with between three and ten-days sampling on each island. The outcome of repeating samples with
various extensions of the sampling period was also investigated.
6.3 RESULTS
The following section reports the results of statistical analyses to examine the effects of various variables
on the probability of hunting.
6.3.1 Probability of Dugong Hunting
Excluding missing values, data for 553 days containing values for the various covariates were included in
the analyses examining the probability of hunting by the residents of Mabuiag Island. The mean probability
of dugong hunting was 0.59 t- s.e. 0.02 per day. The most complex GAM model examined included: the
main effects of month and year, and their interaction, season and the interaction between season and
year, the main effects of minimum tide, maximum tide and mean tidal difference and smooth terms in lunar
day, wind, tide difference, and log transformed cray catch (AIC = 709.3, d.f. = 56, Table 6.1). The most
parsimonious model included the main effects and interaction of month and year, a main effect of season,
a linear term for lunar day, a linear term for wind, and a linear term for the log transformed crayfish catch
(AIC = 685.59, d.f. 22) (Table 6.1).
The linear relationship between the probability of dugong hunting and lunar days resulted from the higher
probability of hunting immediately after the new moon (Figure 6.1). The probability of dugong hunting
decreased with increased crayfish catch (Figure 6.2) and was higher with low wind velocity (Figure 6.3).
There is strong evidence for differences of dugong hunting between months. This difference was not
consistent between years because of the lower probability of dugong hunting in the early months of 1998,
and the higher relative probability of dugong hunting in October 1998 (Figure 6.4). Overall the probability
of dugong hunting was higher in 1999 than 1998. The probability of hunting occurring was much greater in
the South-East season than the other three seasons, particularly when winds were variable (Figure 6.5).
6.3.2 Environmental and Temporal Factors Affecting Hunting
Given the complex and unpredictable tidal regime in Torres Strait, it is not surprising that there was no
significant effect of predicted tidal height (tide range difference, maximum tide and minimum tide) on the
probability of hunting. However, the significant effect of lunar day on hunting probability, with the highest
Chapter 6 Factors Affecting Dugong Harvests 96
probability of hunting (Figure 6.1) and CPUE per trip ( see Figure 6.8) occurring immediately after new
moon (and to a lesser extent at full moon) supports other findings (Eley 1988; Nietschmann 1989; Raven
1990; Johannes and MacFarlane 1991) that the preferred time for hunting is during spring tides.
There was considerable temporal variability in the hunting patterns for dugongs in 1998-99. Although the
probability of hunting was higher in 1999 than in 1998, the mean total catch per trip during March to
October was higher in 1998 (1.1 f s.e. 0.06) than in 1999 (0.93 + s.e. 0.06) (see Section 6.3.4.1). Higher
hunting effort in 1999 compared with 1998 is also reflected in the higher total catch during March-October
in 1999 (n = 160, see Table 6.4b) compared to 1998 (n = 155, see Table 6.4a). This variability was also
apparent in hunting activity in terns of number of hunters, total trips and total catch in various months
(Figure 6.6) in 1998 and 1999. As evident in Table 6.4, hunting activity was concentrated in the second
half of the year in 1998 but in the first half of the year in 1999 (Figure 6.6).
In 1998, most hunting trips were undertaken during the mornings or afternoons (85.2%, n = 75188) (Figure
6.7). However, in 1999 only 36% of trips were undertaken at these times (Figure 6.7). In 1999, over 50%
of hunting activity was undertaken at night compared to 1998 when only 7% of hunting trips occurred at
night (Figure 6.7). According to hunters, this was because of the greater abundance of dugongs on Orman
Reef in 1999 compared with 1998. Reef hunting using the fast pursuit method is potentially dangerous at
night, suggesting that hunting conditions were more favourable for hunting at night in 1999 compared with
1998. This explanation for the interannual variation is supported by the yearly variation in the number of
trips to Beka Reef, that part of Oman Reef furthest from Mabuiag Island (see Figure 5.1). There were no
trips in 1998. In contrast, 18 trips in 1999 suggesting that the hunters were willing to make this large
investment in fuel and time. There were very similar numbers of hunting trips to reefs within 20 km of
Mabuiag Island in 1998 and 1999 (see Table 5.3).
Chapter 6 Factors Affecting Dugong Harvests 97
Table 6.1. Summary of the results of the generalised additive models showing the main variables that affect the probability of hunting for dugongs by hunters based in Mabuiag in 1998-99 (the final model is bolded, see text for explanation of the AIC).
Model terms AIC Full model 709.31 Month + year + (month x year) + season + (season x year) + min. tide + m a . tide + mean tide
difference + lunar day* + wind direction* +mean tide difference* + log crayfish catch*
Step 1 705.5 Month + year + (month x year) + season + max. tide + mean tide difference + lunar day* +wind direction* + tide difference* + log crayfish catch*
Step 2 700.3 Month + year + (month x year) + season + m a . tide + mean tide difference + lunar day* +wind direction* + log crayfish catch*
Step 3 696.1 month + year + (month x year) + season + mean tide difference + lunar day* + wind direction* + log crayfish catch*
Step 5 692.6 month + year + (month x year) + season + mean tide difference + lunar day* + wind direction* + log crayfish catch*
Step 5 689.8 month + year + (month x year) + season + mean tide difference + lunar day* + wind direction* + log crayfish catch*
Step 6 687.7 month + year + (month x year) + season + mean tide difference + lunar day* + wind direction* + log crayfish catch*
Step 7 686.5 Month + year + (month x year) + season + mean tide difference + lunar day* + wind direction* +
log crayfish catch*
Step 8 685.6 Month +year + (month x year) + season + lunar day* +wind direction* + log crayfish catch*
denotes smooth terms in models
Chapter 6 Factors Affecting Dugong Harvests 98
Figure 6.1. The linear relationship between lunar day and the probability of dugong hunting in Mabuiag Island in 1998-99 evident from the generalised additive models. The solid line represents smooth spline, dashed lines represent approximate 95% confidence intervals.
Daily crayfish catch (log kg)
Figure 6.2. The linear relationship between daily crayfish catch and the probability of dugong hunting in Mabuiag Island in 1998-99 evident from the generalised additive models. The solid line represents smooth spline, dashed lines represent approximate 95% confidence intervals.
Chapter 6 Factors Affecting Dugong Harvests 99
Wind velocity
Figure 6.3. The linear relationship between the probability of dugong hunting and wind velocity in Mabuiag Island in 1998-99 evident from the generalised additive models. The solid line represents smooth spline, dashed lines represent approximate 95% confidence intewals.
Month
Figure 6.4. The relative probability (k s.e) of dugong hunting in the months from March to October in 1998 and 1999.
Chapter 6 Factors Affecting Dugong Harvests 100
Season Season 1 = South East; 2 = North West; 3 = Doldrums; 4 =Variable wind direction Figure 6.5. The relative probability (k s.e) of dugong hunting and season in 1998-99.
During the South-East season (May to October) when hunting was most likely to occur, spring tides occur
at night. As noted above, spring tides were the preferred tides for hunting dugongs. In spite of this
preference, hunters in Mabuiag Island reported that hunting was usually limited to day trips in the South-
East season because the gusty wind conditions make travel in small dinghies dangerous and hunting very
difficult. This suggests that the weather conditions at night (when the preferred spring tides occur) in the
1999 South-East season were appropriate for night hunting. However, hunters also stated that hunting
during the day in the South-East season was favourable because the noise of windy conditions on waves
masked the noise of dinghies and their engines.
6.3.3 Interactions Between Dugong Hunting and the Commercial Crayfish Fishery
The tropical rock lobster or crayfish (Panulims omatus) is locally known as kayarr and has remained a
traditional food source for Islanders. Commercial fishing for crayfish commenced in 1957 and is now the
most important commercial fishing activity for Torres Strait Islanders. The fishery operates as a free diving
or hookah (compressed air pump) fishery with a seasonal ban on the use of hookah during October to
January (Pitcher et a/. 1997). Fishing occurs year round with a peak catches during March-August. Most
fishing activity occurs during neap tides when the currents are slower and the water is clearer (Pitcher et
a/. 1997). Although crayfish are found on most reefs in Torres Strait, the principal fishing grounds are near
Thursday Island and the Oman and Warrior Reefs. Oman Reef and Kuiki Pad (Jewis Reef) are important
fishing areas for crayfish (and dugong) for Mabuiag Islanders and also people from Badu and to a lesser
extent communities of St Pauls and Kubin on Moa Island (Pitcher et a/. 1997) (see Figure 5.1).
TcOl Trip El
(b) 1999
Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Month
Figure 6.6. The pattern of hunting activity of hunters based at Mabuiag Island in (a) 1998 and (b) 1999.
Chapter 6 Factors Affecting Dugong Harvests 102
(a) 1998 n = 97 drips
Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Month I BAMIPM El Niaht OAII Dav I
(a) 1999 n = 119 trips
Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Month
IBAMIPM =Night OAll Day I
AM=hunting trip initiated in the morning (0500-1200 hours); PM=hunting trip initiated in the afternoon (1300-1800 hours); Night=hunting trip undertaken 1800-0500 hours; All day=hunting trip undertaken 0500-1800 hours.
Figure 6.7. The thing of hunting trips undertaken by hunters based at Mabuiag Island in (a) 1998 and (b) 1999.
Chapter 6 Factors Affecting Dugong Harvests 103
In 1998, the abundance of crayfish combined with favourable diving conditions resulted in very high (9978
kg) and profitable ($351kg) catches of crayfish between March and June in Mabuiag. During the same
period in 1999, only 3171 kg were landed with a lower price of $281kg. Most dugong hunters generally
alternate between diving for crayfish during the neap tides and hunting dugongs during the spring tides.
According to hunters, the high number of dugongs caught in Mabuiag (n 117, Table 6.4b) during the
period March to June 1999 was the result of highly favourable weather conditions for hunting and the need
to 'feed theirfamilies'. The low abundance and price of crayfish required Islanders to supply the household
with dugong meat because of their limited disposable income to purchase store goods. This was
demonstrated by the negative relationship between the probability of dugong hunting and crayfish landings
in Mabuiag Island during my study period (Figure 6.1).
During the sampling period, hunters from Mabuiag reported that the sustained high level of fishing activity
in the Mabuiag and Badu areas regularly drove dugongs away from reefs. Increased participation of
Islanders diving for crayfish and the presence of freezer mother boats anchored at Orman Reef during
periods of crayfish abundance were said to cause dugongs to avoid nearby feeding areas during the day
and to have restricted them to feeding only at night or when boats have gone.
Although diving for crayfish takes place during neap tides while the preferred tide for dugong hunting was
spring tides (see Figures 6.1 and 6.8), hunters stated that dugongs are 'very clever' and remain wary
about returning to areas from which they have been disturbed. As discussed in Section 5.3.2, hunters
adapted to this situation by developing the reef hunting method, which uses spotlights to hunt dugongs at
night. With the increasing interest in diving for the more profitable live crayfish, which are caught at night,
there is concern amongst hunters that this will subject dugongs to disturbance by boats throughout the die1
cycle.
6.3.4 Factors Affecting Dugong Hunting Effort
The following sections report the results of statistical analyses used to examine the effects of various
variables on: (a) the total dugong catch per trip; (b) the dugong catch per hunting hour; and, (c) the sex of
the catch. I also report on the statistical analyses used to examine the selectivity by hunters for sex and
size of dugongs
6.3.4.1 Total dugong catch per trip
Data on dugong catches from 259 days were included in the statistical analyses. The mean total dugong
catch per trip was 1.005 k see. 0.05. The most complex GAM model examined included the main effects of
month and year, and their interaction, season and the interaction between season and year, and mean
Chapter 6 Factors Affecting Dugong H ~ N ~ S ~ S 104
tidal difference, minimum tidal height and maximum tidal height and smooth terms in lunar day, wind, tide
difference, and daily crayfish catch (Figure 6.8) (Table 6.2, AIC 206.6, d.f. = 56). Model selection
supported a more parsimonious model consisting of the main effects of year and season (Table 6.2, AIC =
157.55, d.f. 5). The results show that mean total dugong catch per trip was significantly higher in 1998
(1.1 + s.e 0.06) than 1999 (0.93 f s.e. 0.06). The mean total dugong catch per trip was also higher
during the doldrums (1.57 f s.e. 0.1 5) than in the South-East season (0.9 + see. 0.05) and the variable
seasons (1 f s.e. 0.08).
P 1 1 .- L .d
% O 0 P = 0 5 10 15 20 25 30 10 15 20 25 30 35 40 Y m 0 Lunar day Wind velocity
0.5 1.0 1.5 2.0 2.5 1 2 3 4 5
Tidal difference Mean tidal difference
Figure 6.8. The relationship between the total dugong catch per trip and (a) 'lunar day', (b) 'wind velocity', (c) 'tidal difference', and (d) 'mean tidal difference'. The solid lines represent smoothing spline fits, dashed lines represent approximate 95% confidence intervals.
6.3.4.2 Catch per hunting hour
A subset of the above data was used to examine the factors that influence dugong catch per hunting hour.
The subset included 197 days where the number of hours spent hunting was recorded and all covariate
information was available. Catch per hunting hour was calculated as the ratio of total number of individual
dugongs caught to the total number of hours spent hunting for each hunting trip. Model selection
supported the null model over any combination of the covariates: month, year, season and wind direction,
minimum tide height, maximum tide height and mean tide difference. There were no systematic
differences between months, seasons, years or any continuous variables in the rate of dugong catch per
hunting hour.
Chapter 6 Factors Affecting Dugong Harvests 105
Table 6.2. Summary of the results of the generalised additive models showing the main variables that affect the mean total dugong catch per trip of hunters based in Mabuiag Island hunting dugongs in 1998-99 the final model is bolded, see text for explanation of the AIC).
Model terms AIC Full model month + year + (month x year) + season + (season x year) + min. tide + m a . tide + mean tide 206.6 difference + lunar day* + wind direction* + tide difference* + log crayfish catch*
Step 1 month +year + (month x year) + season + m a , tide + min. tide + mean tide difference + lunar 198.5 day* +wind direction* + tide difference* + log crayfish catch*
Step 2 year + season + max. tide + min. tide + mean tide difference + lunar day* + wind direction* + log 181.29 crayfish catch*
Step 3 year + season + mean tide difference + min, tide + lunar day* + wind direction* + log crayfish 175.9 catch*
Step 5 year + mean tide difference + season + lunar day* + wind direction* + log crayfish catch* 170.9
Step 5 year + season + mean tide difference + lunar day* + wind direction* + log crayfish catch* 166.8
Step 6 year + season + mean tide difference + lunar day* + wind direction* + log crayfish catch* 162.8
Step 7 year + season + mean tide difference + lunar day* + wind direction* + log crayfish catch* 158.7
Step 8 year + season + mean tide difference + lunar day* + wind direction* + log crayfish catch* 155.53
Step 9 year + season + mean tide difference + lunar day* + wind direction*
Step 10 year + season + lunar day* +wind direction*
Step I I year + season + wind direction*
Step 12 year + season 157.5
* denotes smooth terms in models
6.3.4.3 Sex Ratio
The subset of data which included the 181 days where the sex ratio of dugongs caught was recorded, and
all covariate information was available was used for analyses for the proportion of females caught (i.e., the
ratio of number of females to total catch) using the global model above (Table 6.3, AIC = 237.76, d.f. =
32). Model selection supported a more parsimonious model for the data consisting of the main effects of
Chapter 6 Factors Affecting Dugong Hawests 106
year and month and their interaction (Table 6.3, AIC = 218.55, d.f. = 15). There was strong evidence for
temporal variation in the proportion of females in the catch between months and years (Figure 6.9). The
proportion of females in the catch was highest between September and October in 1998 and in June 1999
(Figure 6.9). There was no evidence for systematic variation between seasons, lunar day, wind, or tidal
differences. The sex composition of the dugong catch in the period March to October in 1998 and 1999 is
shown in Table 6.4.
Table 6.3. Summary of the results of generalised additive models showing the main variables that affect the proportion of females caught (i.e. ratio of number of females to total catch) by hunters based in Mabuiag Island hunting dugongs in 1998-99 the final model is bolded, see text for explanation of the AIC).
Model terms AIC Full model month +year + (month x year) + season + (season x year) + min. tide + max. tide + mean tide 237.8 difference + lunar day* + wind direction* + tide difference* + log crayfish catch*
Step 1 month +year + season + (month x year) + mean tide difference + lunar day* + wind direction* 232.3
Step 2 month + year + season + (month x year) + mean tide difference + lunar day* +wind direction* 228.5
Step 3 month +year + season + (month x year) + mean tide difference + lunar day* +wind direction* 226
Step 5 month + year + season + (month x year) + mean tide difference +wind direction* 225
Step 5 month + year + season + (month x year) + mean tide difference + wind direction* 222.2
Step 6 month + year + (month x year) + mean tide difference + wind direction*
Step 7 month + year + (month x year) + mean tide difference*
Step 8 month + year + (month x year)
'denotes smooth terms in models
Chapter 6 Factors Affecting Dugong Harvests 107
4 6 8 10 4 6 8 10
Month
Figure 6.9. Proportion of female dugongs in the catch from Mabuiag Island in different months over two years (1998 and 1999). Error bars represent approximate 95% confidence intervals.
6.3.4.4 Sex and Size Distributions of Dugongs Caught by Hunters
Evidence of selectivity for females and large-sized animals by individual huntets was examined (using sex
and size data for six hunters: A, B, C, D, E and F). The proportion of female dugongs caught (x2 = 5.8, d.f.
= 5, P = 0.326) and the size class of dugongs caught ( ~ 2 = 2.06, d.f. = 5, P = 0.85) were both independent
of hunter.
6.3.4.5 Hunter Selectivity
The Islander's taste preference for the meat of female dugongs, particularly pregnant animals was
reported by Haddon (1912) in the late 1890s and has since been widely noted (Nietschmann and
Nietschmann 1981; Raven 1990; Johannes and MacFarlane 1991; Ponte 1996).
I found that females comprised 66% (n = 801121) and 59% (n = 801135) of the catch for which sex was
known in 1998 and 1999, respectively. However, there was no evidence that more active and hence more
experienced hunters (assumed to be those who had caught more than 10 dugongs per year) favour
females or large-sized animals. Thus, there is little evidence that modern hunters could differentiate
between or target dugongs on the basis of sex, age or body condition.
Chapter 6 Factors Affecting Dugong Hawests 108
6.3.5 Total Dugong Catch
Catch rates recorded in Mabuiag Island in 1998 (Table 6.4a) and 1999 (Table 6.4b) were consistent with
the pattern of interannual variability reported in other studies. Similarly, temporal patterns in monthly catch
rates were not consistent across years (Table 6.4a-b). In 1998, most of the catch was taken in the latter
part of the year (Figure 6.6). In contrast, most of the catch in 1999 was taken in the first part of the year
(Figure 6.6). Although there was evidence that the mean monthly total dugong catchltrip was higher in
1998 than 1999, the total catch and the daily probability of hunting were higher in 1999 than 1998. This
suggested that overall, hunting effort was higher in 1999 than 1998. Further evidence of higher hunting
effort in 1999 were evident from the higher probability of hunting correlated with lower crayfish catch
landed at Mabuiag Island in 1999 (Section 6.3.3). There was increased hunting activity at night in 1999
compared with 1998 (Section 6.3.2). Anecdotal information indicated that weather conditions were more
favourable in 1998. This factor, combined with high local abundance of dugongs, resulted in higher
catches in 1999.
6.3.6 Catch Monitoring4
I recorded 639 days of observations at Mabuiag Island, during which a total of 303 dugongs was captured,
yielding an average of 0.575 dugong per day. The distribution of the dugong catch was noticeably non-
normal and represented a Poisson distribution with many days with zero catches (see Table 6.4).
Statistical analyses (see Section 6.2.2) demonstrated that several factors have statistically significant
associations with dugong catches. These included such parameters as month, season (as weather type)
and lunar period. On the basis of these analyses, the role of moon phase was further examined with the
conclusion that catch rates increased during full moon (and new moon) and decreased in the third quarter
(and first quarter) (Chi-square, P < 0.01). These results were then used to examine the effectiveness of
the sampling regime used by the AFMAlCSlRO monitoring program.
The 1999 data from the AFMAlCSlRO monitoring program where observers generally spent about two to
ten days on an island several times during the year are summarised in Table 6.5. For Mabuaig Island in
1999, AFMA monitoring observers sampled a total of 22 days in five trips with an average of 0.23 dugong
caught per day, much less than 0.58 dugong caught per day I observed. There are some notable
differences between the monitoring observers' data and those I obtained for the same period (Table 6.6).
The monitoring observer missed four dugongs out of a possible 13 and I missed one dugong out of a
possible three (but this is an observer bias, not a statistical sampling bias) (Table 6.6).
These analyses were done with the assistance of Dr Barry Goldman
Table 6.4 Monthly catch statistics and hunting CPUE* (number dugongsltrip) of dugongs landed at Mabuiag Island in (a) 1998 and (b) 1999.
(a) 1998
Chapter 6 Factors Affecting Dugong Harvests 110
(b) 1999
Chapter 6 Factors Affecting Dugong Harvests 111
0 1 2 3 4 5 6 7 8 9 1 0 > 1 0
# dugong per sample
Figure 6.10. Distribution of dugongs caught in the 635 samples of five-day intervals at Mabuiag Island during 1997-99.
Table 6.5. Sampling by CSlRO from several islands in Torres Strait between 21 January 1999 and 20 November 1999 showing sampling effort and recorded dugong catch.
Community No. Total Average no. Min no. days* Max no. days* Total no. Average no. Trips Days daysltrip dugongs dugonglday
Badu Is. 8 56 5.75 2 9 9 0.20 Boigu Is. Coconut Is. Darnley Is. Dauan Is. Kubin Is. Mabuiag Is. Murray Is. Saibai Is. St Pauls Stephens Is. Warraber Is. Yam Is. Yorke Is.
* minimum and maximum number of sampling days in a trip
Chapter 6 Factors Affecting Dugong Harvests 112
# dugong per sample
Figure 6.11. Distribution of dugongs caught in 153 hypothetical samples of 20-day intervals at Mabuiag Island during 1997-99.
Table 6.6. Comparison of observations of dugong catches by an AFMA monitoring observer and this study at Mabuiag Island in 1999.
Date This Study AFMA Observer Difference 29/01/99 0 0
Not sampled Not sampled Not sampled
0 0 0 0 0 0 1 0 0 3 2 3
03/05/99 1 1 05/05/99 2 2 061071-99 0 0 07/07/99 0 Not recorded 08/07/99 1 0 1 09/07/99 0 0 10107/99 0 0
The data was then examined to investigate the effects of sampling at five-day and twenty-day intervals. In
order to do this, the entire sampling period divided into contiguous periods of five, ten, fifteen and twenty-
day periods. The five-day and twenty-day periods were used to examine the distribution of dugong
Chapter 6 Factors Affecting Dugong Harvests 113
catches. The five-day samples yielded an average of 2.38 dugongs per period. Similar to the
AFMAICSIRO data (Table 6.5) the distribution of five-day intervals was a markedly non-notmal
distribution, possibly Poisson (Figure 6.10). This non-normal distribution of catch is also evident from the
twenty-day sampling (Figure 6.1 1). Very few samples had means approaching the true mean of 2.38 (five-
day samples) or 9.77 (twenty-day samples). Most samples fell outside the range of the true mean plus or
minus 50% as shown in Table 6.7. This result was consistent even with twenty-day samples, although the
reliability increases with sample size (Table 6.7).
Table 6.7. Percentage frequency of samples resulting in observed mean values that are more than 50% outside the true value.
#days in sample period #o f sampling periods % outside mean * 50% 5 635 70
Table 6.8. Percentage frequency of samples resulting in observed mean values that are more than 50% outside the true value based on repetitive samples repeated after varying intervals.
# days in sample period # repeat periods # days between repeat % outside mean k 50% samples
10 2 100 58
The outcome of repeating samples rather than simply extending the sampling period was then
investigated (Table 6.8). Ten-day samples repeated every three months (100 days) or six months (200
days) yielded the same outcome while repeating ten-day samples every two-and-a-half months (75 days,
to phase shift the lunar cycle) worsened the outcome (Table 6.8). Repeating the ten-day sample three
times resulted in a noticeable improvement while taking three lots of fifteen-day samples, three months
apart resulted in only 22% falling outside the range of the true mean + 50% (Table 6.9).
To approximate a power test for the results in the last two best cases (three by ten-day and three by
fifteen-day samples), a hypothetical 95% confidence interval of a sample having the same mean as the
true mean was calculated (note that with the Poisson distribution this interval is proportional to, but
asymmetric about the mean). The frequency of observed samples falling outside this range was recorded
with the result that 31% of the three by ten-day samples and 15% of the three by fifteen-day samples were
outside the expected mean number of dugongs (Table 6.9). Thus, three lots of samples of fifteen days,
Chapter 6 Factors Affecting Dugong Harvests 114
each separated by three months yielded results that may be acceptable (i.e., a 85% chance of falling
within the 95% confidence interval of the true population mean).
Table 6.9. The results of the simulated three by fifteenday samples showing a considerable spread of results either side of the expected mean number of 21.2 dugongs.
6.4 DISCUSSION
- - . - - . .
An understanding of and capacity to predict the impact of human hunting or fishing behaviour on prey
populations is crucial for their effective sustainable management. Most approaches to understanding
human behaviour and its impact on populations of prey species are based on underlying assumptions of
maximising economic returns (see Aswani 1998; Hilborn and Walters 2001) or the nutritional status of an
(human) individual or minimising the time needed to acquire necessary nutritional requirements to ensure
(human) fitness (see Winterhaulder and Lu 1997; Fitzgibbon 1998). However, the socio-cultural
significance of dugongs means that the situation is even more complex than assumed for commercial
fisheries. Thus the decision by Torres Strait Islanders to hunt depends on a complex interaction of
environmental, ecological, social, cultural and economic factors.
6.4.1 Biophysical Factors Affecting Dugong Hunting
6.4. I. I Tides
#of dugongs
Frequency
Previous studies have described the importance of a knowledge of tides and their effects on the local
distribution and timing of dugong hunting in Torres Strait (Nietschmann 1984, 1989; Eley 1988; Raven
1990; Johannes and MacFarlane 1991). Johannes and MacFarlane (1991) described the highly complex,
pronounced (2 - 5 m spring tidal range) and unpredictable tidal regime in Torres Strait, which result from
an interaction between the mainly diurnal tides of the Indian Ocean and the generally semidiurnal tides in
the Coral Sea (see also Section 3.13). Tidal patterns also vary with moon phase and wind conditions and
prevailing currents, which are accentuated by local bathymetry (Johannes and MacFarlane 1991).
With maximum tidal ranges of up to 3.5 rn and dugong hunting in depths of up to 4 m, tidal stage exerts a
major influence on the accessibility of hunting areas, particularly those on top of reefs (Nietschmann
1989). Seasonal changes in tide, wind and weather in relation to shallow seagrass meadows cause
hunting conditions to vary throughout the year (Nietschmann 1989). Hunters believe that during high tides
<I0
5
12-13
10
18-19
10
10
2
14-15
15
20-21
11
11
5
16-17
13
22-23
16
24-25
6
26-27
12
28
6
29
5
30
3
31
2
32
1
>32
29
Chapter 6 Factors Affecting Dugong Harvests 115
dugongs move into inshore areas and the higher windward side of reef tops while at low tide they move
offshore to deeper water on the leeward side of reefs (Nietschmann and Nietschmann 1981; Johannes
and MacFarlane 1991).
Kiwai people on the PNG side of Torres Strait (Eley 1988) as well as Islanders from Boigu (Raven 1990)
and Mabuiag Islands (Nietschmann 1989) consider spring tides the best for hunting. During spring high
tides, dugongs are more abundant and accessible in shallow waters, particularly in intertidal seagrass
habitats (Johannes and MacFarlane 1991). According to previous studies (Nietschmann and Nietschmann
1981; Raven 1990; Johannes and MacFarlane 1991) the preferred time for dugong hunting was in the
North-West season when peak spring tides occurred during the day when it was less dangerous and
easier to hunt.
6.4.1.2 Hunting at night
Hunters based at Mabuiag Island in 1997-99 tended to hunt during the South-East season although spring
tides occurred during the day apparently because weather conditions made it dangerous to travel and hunt
at night. However, when presumably not constrained by weather conditions in 1999, over 50% of the
hunting trips from Mabuiag Island were undertaken on nighttime spring tides. In contrast only 7% of
hunting occurred at night in 1998.
Prior to the introduction of motorised dinghies, hunting at night was from hunting platfotms (see Figure
5.2), as the use of boats to hunt at night was considered dangerous (Raven 1990). Nietschmann (1984),
Raven (1990) and Ponte (1996) indicate that little dugong hunting from boats was undertaken at night in
the Western Islands during the periods of their research. Hunters reported to me that they developed 'reef
hunting' in the mid-1990s as a response to dugongs being displaced in main hunting areas such as Oman
Reef by increased boat traffic and crayfish diving activity during the day and their returning to feed during
the night (see Section 5.3.2). Increasingly, many Islanders are voicing their disapproval at 'reef' or 'night'
hunting, a hunting method apparently favoured by less skilled hunters. Some lslanders claim that 'reef or
'night' hunting is not a 'traditional' form of hunting because of the apparent ease that dugongs can be run
down in shallow areas after being startled with the use of spotlights. Without the advantage of spotlights,
moonlit nights or nights when there is fluorescence in the water were the most favourable for spotting
dugongs.
6.4.1.3 Effects of boats
Boating and fishing activity (which includes dugong hunting), particularly on Oman Reef may cause
temporal and spatial variability in dugong distribution and abundance as a result of dugongs avoiding such
disturbance. It is interesting to note that Boigu lslanders (during the late 1980s) recalled that their first
Chapter 6 Factors Affecting Dugong Harvests 116
perceptions of diminishing numbers of dugong was coincident with the widespread availability of motors
after World War II (Raven 1990), particularly in the 1970s (Johannes and MacFarlane 1991). Both
Johannes and MacFarlane (1991) and Harris and Nona (1997) reported a similar perception amongst
Islanders of diminished abundance of dugongs in the mid-1980~~ which was attributed to overhawesting or
migrations away from the area.
Disturbance by boats has been shown to affect the distribution of Florida manatees, sometimes resulting
in displacement of animals from large areas (Provancha and Provancha 1988; Buckingham 1990). Preen
(1992) reported that anecdotal evidence and a reciprocal pattern of distribution of dugongs and boats in
Moreton Bay suggested possible avoidance by dugongs in areas of high boat use. Concerns that in the
Hinchinbrook marina-based development in the Huchinbrook Channel potentially threaten dugongs and
compromises their habitat has resulted in management actions to restrict boating activity in key areas
(Preen 2001).
6.4.1.4 Distribution and abundance of dugongs
The distribution and abundance of dugongs has been long noted by the hunters in Torres Strait to be
highly variable. Consistent with the views of hunters, it is plausible that this variability is a large-scale
response of dugong to cues that indicate suitable food sources in other areas (see Johannes and
MacFarlane 1991; see Section 2.4.4). There is increasing evidence from aerial surveys in both
Queensland (Lawler et a/. 2001; Marsh and Lawler 2001a, 2000b; see Marsh et a/. 2002) and Western
Australia (Marsh et al. 1994; 2002) that large numbers of dugongs may commonly move considerable
distances. Satellite telemetry studies in Queensland (Marsh and Rathbun 1990; Preen 2001; Lawler et al.
2001; see Marsh et a/. 2002) and Western Australia (Holly et a/. 2001; see Marsh et a/. 2002; Gales and
Lawler unpublished data) show that individual dugongs may journey large distances making trips of up to
600 km within days (Preen 2001). As discussed in detail in Section 2.4.4, these movements may be in
response to changes in seagrass abundance as a result of extreme weather events. Halophila and
Halodule spp, the preferred food of dugongs, are highly variable both spatially and temporally (Kendrick ef
al. 1999; Thomas et al. 1999; see Section 2.4.3).
Anecdotal information of dugong movements from hunters is consistent with that from the scientific studies
discussed above. Hunters in Torres Strait reported that dugongs regularly move from one area to another
presumably in search of high food quality andlor abundance (Johannes and MacFarlane 1991). Hunters
interviewed in 1997-99 stated the period May to September is the 'best' time for hunting because of the
high local abundance of dugongs particularly at Oman Reef. Hunters said that dugongs 'move away' from
the area after October. This corresponds to the onset of the wet season in Torres Strait. Dugong herds in
Chapter 6 Factors Affecting Dugong Harvests 117
the Gulf of Carpentaria were also reported by Preen (cited in Aragones 1996) to disperse before and
during the wet season.
The temporal distribution of dugongs in Torres Strait is consistent with periods of high seagrass
productivity that occur when there is high water clarity (Walker ef al. 1999). Periods of high water clarity
are more likely to occur in the South-Easter season when hunters say the water is 'clean' as opposed to
the 'milky water' reported to occur during the North-West monsoon. The North-West monsoon is frequently
very stormy and the high dugong abundance near Mabuiag at this time may also be due to animals
seeking shelter inshore. Hunters also reported that dugongs move to the north-west side of Orman Reef
between Gariar and Beka Reefs during September to October to mate and to calve.
These movements may result from reduced biomass of high quality forage because of sustained high
grazing pressure over extended periods. The low abundance noted after October may reflect this
migration out of the usual hunting area in the Western Islands to other suitable habitat, which may
sometimes occur outside of the usual range of hunting activity. The recovery and regeneration of
Halophila and Halodule (Preen and Marsh 1995; Preen et a/. 1995; Mckenzie ef a/. 2000; see Section 2.4)
may be rapid enough to sustain large numbers of dugong. Experimental evidence indicates that the
recovery of H, ovalis and H. unine~is can occur within a couple of months to up to a year (Aragones and
Marsh 2000).
The above discussion suggests that the interannual variability long noted in the available catch estimates
of dugongs in Torres Strait (see Table 3.1) reflects historical patterns of dugong distribution and
abundance. Community perceptions in Boigu Island in the mid 1980s of poor hunting success (see Raven
1990; Johannes and MacFarlane 1991) were increasingly attributed to disregard for cultural practices
aimed at ensuring success. This period is coincident with the period of overharvesting in the late 1970s
and mid 1980s that resulted in the collapse of the artisanal dugong fishery in Daru (Hudson 1986).
Spiritual dissatisfaction with changing cultural practices was considered to result from lack of sharing of
dugong meat and skulls being thrown away (which are believed to send dugongs away) by hunters, which
caused dugong herds to be more dispersed. Other factors implicated included unfavourable weather
conditions, pollution, and disturbance from boat motors. Boigu Islanders believe that, although
populations of dugongs are known to vary at a local scale, dugongs always retum. The Boigu people
resolved to follow the cultural rules more closely and wait until conditions improved (Raven 1990). Reports
of animals vanishing for long periods of time but known to retum, is a view shared by the Inuit for many
marine mammals upon which they depend for subsistence (see Johannes ef a/. 2000).
6.4.2 The Catch
6.42.f Varjabiiity ha the annual catch
According to Nietschmann (1989), during the late 1970s hunting pressure was probably predicted by the
size of resident island communities, their food needs and social obligations as well as environmental
conditions, which affect dugong distribution and abundance and influence hunting success. Today, in
addition to these factors, socio-economic factors such as disposable income to pay for dinghies, motors
and fuel have also become increasingly important. These factors influence the observed high variability in
annual catch rates (see Table 3.1 and Figure 6.12).
The catch rate of dugongs is a key management issue in the Torres Strait region. As discussed above
several facbrs affect hunting pressure and the size of the annual catch in the Australian sector of the
Torres Strait Protected Zone. There have been various attempts to monitor the dugong in Be Australian
sector in Torres Strait (see Table 3.1). Catches have been monitored by AFMA using two independent
methods. Catches of dugong are recorded by: (1) schools in each community on a continuous basis (with
days when no recording has occurred, i.e., holidays, being noted) or (2) using a ca th frame survey with
rowing fisheries observers.
Mar May Jun Jul
Month
Figure 6.iZ. Comparison off %Re dugong catch from Mabuiag Island during 11977.78 (Nletschmann 1984) and 1B889.
Chapter 6 Factors Affecting Dugong Harvests 119
There have been recent concerns that the current catch rate of dugongs in the Torres Strait Protected
Zone is not sustainable (Marsh 1996; Marsh et a/. 1997). However, because of the uncertainties in
assessing the status of the population (Marsh 1996; Marsh ef a/. 1997) and the apparent interannual
variability in catch rates, it is difficult to draw definitive conclusions (see also Section 10.3.1). While
acknowledging the inconsistency in catch monitoring methods used to obtain these estimates, there does
appear to be considerable variability in catch rates. For example, Nietschmann reported total annual
catches of 275 and 157 dugongs in the Westem lsland communities of Mabuiag, Badu and Kubin in 1977
and 1978, respectively (see Table 3.1). Johannes and MacFarlane (1991) reported a total catch of only 26
from the same islands between 1983 and 1985. Raven (1990) reported similarly low catch rates (total of
16 animals during September 1986 to January 1987) in Boigu lsland at a similar time (Table 3.1). The
magnitude of the annual catch rate monitored by AFMA since 1991 confirms this interannual variability
(Table 3.1), the reasons for which are not well understood. However, evidence from aerial surveys
conducted in 1987 and 1991 suggests that it is likely that large numbers of dugongs migrated into the
region in lthe period between surveys resulting in the high catches reported by AFMA in the subsequent
years (Marsh et a/. 1997; Marsh 1998; Marsh eta/. 2002).
6.4.2.2 Catch Selectivity
Although dugongs exhibit little sexual dimorphism, highly experienced hunters apparently use a variety of
clues to distinguish sex, pregnancy status and age. Clues include the positioning of the dugong within a
group, their evasiveness, the form of sediment plumes from feeding trails, grazing patterns, manner of
surfacing and diving and guttural sounds (Raven 1990; Johannes and MacFarlane 1991; Hams and Nona
1997). However, there is no conclusive evidence for selectivity by hunters and it is questionable whether
most contemporary hunters are able to be selective about their dugong catch (Raven 1990; Johannes and
MacFarlane 1991; Harris and Nona 1997). 1 was told that hunters who had caught male dugongs would
'cut' their dugong away from the main beach to avoid community scruitiny of a less prestigous catch (i.e.,
not a fat female animal). Data available from the 1970s and 1980s indicate that hunters at Mabuiag lsland
generally caught equal numbers of males and females (Nietschmann 1984) and Daru (Marsh 1986).
However, during the early 1990s, females comprised between 65% - 71% of the dugong catch from Boigu
and Mabuiag Islands (Johannes and MacFarlane 1991; Harris and Nona 1997). Female dugongs
comprised 66% and 59% of the catch from Mabuiag lsland in 1998 and 1999 respectively.
6.4.3 Catch Monitoring
This study has demonstrated that there are a number of factors that affect dugong hunting effort and
hunting success including local weather conditions, moon phase, environmental conditions, local
abundance of dugongs, socio-economic factors (i.e., cash income from crayfish catches) and the skill of
hunters (see above). Thus hunting effort is not normally distributed through time and not easy to predict
Chapter 6 Factors Affecting Dugong Harvests 120
accurately, factors which make it very difficult to obtain reliable estimates of total catch from sampling
(Section 6.3.6). Monitoring dugong catches in Torres Strait using sampling regimes is expensive,
logistically difficult and unreliable. Obtaining reliable catch estimates has also proven highly problematic.
My data indicate that even under the most ideal scenario (i.e., 15 days sampling, three times a year every
100 days) would yield only an 85% chance of falling within the 95% confidence interval of the 'actual'
catch (Table 6.9). This suggests that a program based on continuous monitoring rather than sampling
catch rates of dugong in Torres Strait is likely to be more reliable.
Councils at both Mabuiag and Badu Islands have regularly expressed a strong interest in direct community
participation in catch monitoring. They have been negotiating with AFMA to develop a locally based
community catch-monitoring program. The initiative to develop a catch-monitoring program at Badu Island
Council was originally instigated independently of AFMA (D. Jacobs, pers. comm., 2000).
With adequate funding and support, community-based catch monitoring can provide employment, training
and capacity building enabling community members to be more actively involved in the monitoring and
management of their dugong resources. Community-based monitoring has the advantage of potentially
providing more reliable catch rates than sampling because it provides total counts rather than estimates.
In addition, costs for travel and labour are considerably diminished because a community member can
record catches with less time and effort than roving monitoring observers. However, the success of this will
require an adequate level of ongoing support from AFMA to collate data and provide feedback to
communities (see Section 10.2.2). Technical support by AFMA staff for community-based catch monitoring
will enhance opportunities for AFMA to provide an important liaison between communities and AFMA on
traditional fisheries issues. The planned collaborative development of an appropriate community-
monitoring program for dugong and turtle by AFMA, communities and their councils has the potential to
produce reliable catch statistics. As discussed in Section 10.2.2, other anecdotal evidence (e.g., the
relative abundance of dugongs in hunting areas near communities) and additional information (e.g., how
many functional dinghies exist in the community) is important for assessing the status of the dugong
fishery can also be collected by community monitoring programs
6.4.4 Socio-Economic Effects on the Catch
Increasing demands for cash-based needs, limited employment opportunities other than those provided by
CDEP (a work for social security scheme, see Section 3.2) and few other alternatives to obtain a cash
income, force most Torres Strait Islander families to subsidise their cash income with subsistence fishing
or hunting activities (see Section 3.2). In an increasingly monetised economy with very low average
personal or family incomes, subsistence supplements of dugong or turtle meat are very important. As
many families who live on islands either own or have access to dinghies and outboard motors, they are
Chapter 6 Factors Affecting Dugong Harvests 121
likely to depend on hunting activities to provide fresh dugong and turtle meat, which is a preferred and
economical source of protein.
Socio-economic factors are important in several aspects of dugong hunting effort in Mabuiag Island. The
decision to hunt is dependent on factors such as disposable cash to purchase fuel or the opportunity to
earn additional income from other fishing activities such as diving for crayfish. In spite of the significance
of the cray fishery, there has been no formal study to assess its socio-economic importance to Torres
Strait Islanders. There is very little opportunity for employment in the outer islands (see Section 3.2). Thus,
the relatively nigh prices ($2&351kg in 1998-99) and often-large numbers of crayfish in the area provide
the most important source of income for some Islanders (Pitcher et a/. 1997). However, the opportunity to
earn such income has been very limited since 1999 because of very low crayfish numbers in the Torres
Strait region (Tony Kingston, AFMA, pers. comm. 2001). However, the high numbers of dugongs in areas
close to the Mabuiag community has allowed some people to supplement their households with dugong
meat (see Section 6.3.3).
Evidence that hunting effort for dugong increases when there are few opportunities to earn cash income
from crayfish (see Figure 6.2) has significant implications in light of the extremely poor catches of crayfish
in the Torres Strait region since 1999 (Tony Kingston, AFMA, pers. comm. 2001). Such a situation poses a
potential threat to the sustainability of the dugong fishery especially if periods of poor crayfish catches
coincide with episodes of seagrass dieback which reduce the fecundity of dugongs (see Chapters 7 and
9). Alternatively, as most hunters use income generated from crayfish for hunting activities, increased
cash incomes (from crayfish or other sources) may also pose potential risks to the sustainability of the
dugong fishery by enabling improved capacity to buy better or additional dinghies that can be used for
hunting.
Increased hunting effort may also result from increased migration by Islanders back to communities in
Torres Strait. As noted in Section 3.2, improved transport between the mainland and Island communities
allows Islanders the flexibility to take advantage of employment or other opportunities such as the ability to
participate in fisheries activities (for example, the previously very lucrative cray fishery) in Torres Strait. As
conditions, particularly for housing and employment, continue to improve in major communities such as
Badu or those in the Inner Islands and the Cape York Peninsula, increased (human) populations
pressures may result in increased hunting pressure and thus increased risks of over-harvest, particularly
under conditions of high local dugong abundance described below. However, there is no evidence of this
happening yet (see Section 6.4.5).
In Torres Strait, contemporary hunting technology requires access to a cash income, yet principles of
reciprocity and sharing ethics of traditional resources such as dugong meat still underpin the customary
Chapter 6 Factors Affecting Dugong Harvests 122
economic base (see Section 5.3.7). As monetary exchange for dugongs is illegal (see Marsh eta/. 2002):
hunters are required to outlay the expensive costs of hunting but are expected to share their catch freely.
Given the above situation, considerable tensions are generated within the community and may
substantially increase hunting effort because individual hunters can now store dugong meat in freezers
and avoid sharing their catch. Management strategies that incorporate community values of catch sharing
with innovative and more acceptable ways of sharing the monetary costs of hunting within the community
may be effective in managing the catch rate of dugongs.
The high cultural significance of dugongs and the strong sense of 'Ailan Kastom'to do things according to
'Ailan Pasin' (lsland way) provide an opportunity to develop community acceptable hunting and sharing
protocols that can be formally incorporated into management plans. Protocols that incorporate 'Ailan
Kasfom' and 'Ailan Pasin' would provide a culturally appropriate platform to address other specific
management issues such as hunting technologies and methods (for example the use of spotlights in reef
hunting, see Section 5.3.2) and whether dugong catches should be exported outside of Torres Strait. The
potential impact of the export of dugong meat from Torres Strait to friends and family members who live on
the mainland has caused debate amongst Islanders and their leaders as to whether this practice should
be allowed to continue. As discussed further in Sections 5.3.6 and Chapter 10, such considerations pose
an important management issue for Torres Strait Islanders.
Even today an amalgam of modem and pre-contact technologies is used to hunt dugongs. Because
modern technology is invariably more efficient than traditional technologies, wildlife can be more efficiently
caught. However, the key question is whether the use of such technology impacts on sustainability
(Altman ef a/. 1995).
6.4.5 Human populations, hunting and the distribution and abundance of dugongs
The work of the Nietschmanns provided important insights into the major determinants of hunting pressure
at Mabuiag Island in the late 1970s (Nietshcmann 1984, 1989; Nietschmann and Nietschmann 1981)
(Section 6.4.2.1) but did not include details of how many hunters were active at this time. Based on the
fact that the size of the community at Mabuiag Island has remained relatively stable (Table 3.3) and
assuming a stable sex ratio and age structure, the number of potential hunters (i.e., adult males > 25
years old) in the 1970s is likely to be similar to that in 1996, i.e., n = 35 adult males (Section 5.3.1).
Although hunting was undoubtedly an important activity for many, if not most men, in the Mabuiag
community, hunting pressure in the 1970's was apparently constrained by hunting strategies that were
highly selective for large adult dugongs that are difficult to catch (thus with an emphasis on the quality
rather than the quantity of the catch) and a closer observance of social and cultural norms that
Chapter 6 Factors Affecting Dugong Harvests 123
discouraged taking more than enough to share within kin networks (Nietschmann 1984, 1989;
Nietschmann and Nietschmann 1981).
The pattern of hunting by hunters (discussed Section 5.3.1) at Mabuiag Island in 1997-99 during
conditions of high dugong abundance close to communities (and favourable weather and tidal conditions
for hunting) can result in dramatic increases in hunting pressure. As discussed in Chapter 10, high local
dugong abundance can occur when dugongs move to inshore seagrass habitats (close to communities)
which can result, in partfrom, dieback of deeperwater seagrass areas (see Section 10.3.1). When such
situations occur (as widely reported in the Inner Islands and some Cape York communities in 2001), many
men who do not normally hunt participate in large-scale hunting. Excessive catches (reported by
community members) can result in local depletion because such hunting occurs at a time when the
dugong population in the region is reduced (because animals move away from the area in search of better
food conditions).
At Mabuiag Island in 1997-99, except under conditions of high local dugong abundance, only a few
hunters generally determine hunting pressure. Under the conditions of a stable (relative small) community
population and a dispersed dugong distribution, the catch rate of dugong is probably sustainable. While a
large increase in the size of the Mabuiag community is unlikely at least in the short to mid-term future, this
may not be the case in othercommunities. In major communities with large populations such as those of
Badu Island, the Inner Islands and the Northern Pensinsula Area, there is potential for excessive hunting
pressure that may result in unsustainable harvest rates and local depletions when large numbers of
dugongs occur in accessible inshore areas.
As discussed above, hunting success is now constrained not only by high costs for fuel and boat
maintenance but also the weather and the location and abundance of dugongs. Social obligations to share
their catch compound the high costs of hunting and influence the decision to hunt by some hunters. The
combined impact of these factors on the sustainability of the dugong fishery is likely to constrain rather
than increase catch rates. However, a sustained practice that extends hunting to potentially key areas
such as 'source' areas or those used by dugongs for breeding has the potential to have a significant
impact on the sustainability of the dugong fishery in Torres Strait. Similarly, potential increases in the
population of major communities with access to high local abundance of dugongs, particularly at times of
seagrass dieback, poses significant potential risks to over-harvesting.
6.5 SUMMARY
Today, the sustainable use of dugongs in Torres Strait has global significance because the area supports
the largest remaining population of a threatened species for which most populations outside of Australia
Chapter 6 Factors Affecting Dugong Hawests 1 24
are either severely depleted or almost extinct (see Marsh et a/. 2002). There is the potential for tension
between dugong conservation and the cultural rights of Islanders. This tension is a considerable but
important challenge for all stakeholders, particularly Torres Strait Islanders, government management
agencies and all those concerned with conselvation of this ecologically and culturally important resource.
The main results of this chapter are summarised as follows:
This study supports other reports (Marsh 1996; Marsh ef a/. 1997) that indicate that the magnitude of
annual catches of dugongs in Torres Strait is very variable.
This study has shown that the magnitude of the dugong catch in Torres Strait is likely to be dependent
on a number of factors which affect the temporal and spatial nature of hunting effort and success.
These factors include local weather conditions, seasons, moon phase, environmental conditions, local
abundance of dugongs in hunting areas (presumably linked to the condition of seagrass beds), socio-
economic factors and to lesser extent the skill of hunters.
Most hunting was undertaken during the South-East season (May to October) and locations of
hunting were determined by local weather conditions. Hunters tended to hunt further away when
conditions were calmer.
Most hunting occurred at new and to a lesser extent full moon on the spring tides.
The local distribution and abundance of dugongs were the most important factors influencing hunting
effort and success. The distribution and abundance of dugongs is presumably linked to the conditions
of seagrass beds, which may be impacted by stochastic environmental events that cause dieback
(see Chapter 8).
Socio-economic factors such as the opportunity to earn additional cash income from crayfish also
influences the decision to hunt dugong by Torres Strait Islanders. When there is less opportunity to
eam cash, men tended to support their families by hunting more. However, access to increased
income may also improve the capacity of some hunters to hunt more.
Increased hunting pressure as a result of population growth of major communities such as Badu, in
the Inner Islands and the Northem Peninsula Area also poses potential risks to overhawesting
especially during periods of high local abundance of dugongs in inshore waters (which coincide with
dieback in deepwater seagrass areas).
Chapter 6 Factors Affecting Dugong Harvests 125
Obtaining catch estimates from sampling is likely to be unreliable. A community-based monitoring
program would provide a cost-effective means of gathering more reliable catch estimates. Moreover,
such an initiative would increase the capacity of the local community to be more actively involved in
monitoring and research, potentially an important component of community based-management
plans.
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