CHAPTER 6 FACTORS AFFECTING THE … 6 Factors Affecting Dugong Harvests 92 conserve their resources...

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.


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.


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


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).


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 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


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.


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.


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.


(a) 1998 n = 97 drips


Month I BAMIPM El Niaht OAII Dav I

(a) 1999 n = 119 trips


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.


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.


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 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


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


(b) 1999


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


# 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


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,


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


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


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


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.


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


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


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


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


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).


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.

CHAPTER 6 FACTORS AFFECTING THE … 6 Factors Affecting Dugong Harvests 92 conserve their resources...

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