Improving the accuracy of aerial surveys for dugongs: implications

for management of Indigenous hunting

in Torres Strait Helene Marsh, Ken Pollock, Ivan Lawler and Matthew Alldredge

Basis for estimating sustainable anthropogenic removals

Potential biological removal (PBR) =

maximum number of animals not including natural mortalities that may be removed sustainably from a marine mammal population

PBR =

nmin * 0.5 r max* recovery factor

Parameters of PBRnmin 20th percentile of log-normal distribution

based on absolute population estimate < 4 years old

r max maximum rate of increase

RF between 0.1 and 1 depending on status of population

0.1 endangered species or stocks0.5 depleted or threatened stocks or stocks

of unknown status

Challenge: estimating the absolute size of a dugong population

The probability of detecting a group of dugongs is made up of a probability

that the area is sampled plus an availability process and a detection

process

P [animal detected] =

P[area sampled] *

P[animal available] *

P [ animal detected given it is available]

Chief source of variation is water turbidity which affects probability that a dugong is available: heterogeneous at fine temporal

and spatial scales

Estimation P [animal available]= pa

•Must be done external to survey with additional data

•Dugong models used to estimate depth at which dugongs visible in various turbidities and sea states.

•Dive profiles of 15 individually monitored dugongs recorded.

•Combination allows probability of dugongs being available for detection under various conditions of depth, turbidity and sea state to be estimated.

Dugong models fitted with timed depth recorders were raised from the bottom until they become visible from a helicopter at aerial survey height in water of varying turbidities and sea states

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A B D

C2 C1 C

Zone of non-availability

Dive profiles measured for 15 wild dugongs fitted with timed

depth recorders

~40,000 dives from 15 dugongs

AVAILABILITY PROBABILITIES FOR VARIOUS STRATA OF SURVEY DEPTHS,

TURBIDITIES AND SEA STATES

Water quality Depth range

Visibility of sea floor

Maxim depth models visible

Pa

(se)

Clear Shallow Clearly visible

All 1

Variable Variable Visible but unclear

2.44 m 0.652 (0.0452)

Clear >5m Not visible 4.32 m 0.462 (0.057)

Turbid Variable Not visible 1.23 m 0.474(0.0525)

Optimal survey sea state

Also developed for marginal survey sea state

ASSUMPTIONS FOR AVAILABILITY PROCESS ESTIMATION

• The depth at which dugong models became visible measured without error.

•The depth at which dugong models became visible was the same as for real dugongs.

•Depth profiles of individually monitored dugong are representative of the dugongs studied in the aerial survey

•Flight speed fast enough that the dugongs are only available for an “instant”.

MODELING PERCEPTION PROCESS

Estimate of P[animal detected given animal available] = pd

Done internal to the aerial survey using two independent observers and a mark recapture model

X11- no. detected by both observers

X10- no. detected by mid observer only

X01- no. detected by rear observer only

n1- no. detected by mid observer

n2- no. detected by rear observer

1112

2111

/ˆ

/ˆ

nXp

and

nXp

Seating arrangement in the aircraft

ASSUMPTIONS FOR DETECTABILITY PROCESS ESTIMATION

• Counts within the strip of 200 metres are measured accurately.

•There are no matching errors between the two observers so that the assignment to X11, X10, X01 are accurate

• Equal detection probabilities for all groups for each observer.

MODELING PERCEPTION PROCESS

Two Independent Observer Method

Generalizations using Program MARK

•Fits generalized Lincoln-Petersen models which allow for detection probability conditional on availability to vary by seat (mid or rear), side(port or starboard), and location of the survey.

•Uses AIC technique to pick the simplest adequate model

•Determines if detection probability conditional on availability is dependent on individual group covariates such as size of group, sea state, glare, distance class etc.

Example of Results using Program MARKProbability of a small group of available dugongs being detected by one Observer

= 0.72 (s.e. 0.0159)

Probability of a small group of available dugongs being detected by at least one Observer

= 0.92 (s.e. 0.0159)

Calculation of dugong population of Torres Strait

307

305 213

306

312

212

304

211210209208207206205204203202201

315

401

303

302

314

405

404

403

402

311

310

308

309

224223222221220219218217216215214

101

103

313

102

105104106

107108109

128

301

110

146

407

406

111

130

134

132

138

112

140

126

144

136

142

124

114

122

10

116

505

409408

120

501

410504

225

118

503502

4115041412

3061

3051

3

4

0

2A

1B

2B

1A

5

P [animal detected] =

P[area sampled] *

P[animal available] *

P [ animal detected given it is

available]N = 14106 + s.e. 2134

in December 2001

Crude estimates of current catch ~ 1000 dugong p.a.

 

 

Recovery Factor

rmax

=0.01

rmax

=0.02rmax

=0.03rmax

=0.04rmax

=0.05

0.5 31 61 92 123 154

1 62 122 184 246 308

N = 14106 + s.e. 2134

Nmin = 12297

PBR for Torres Strait

307

305 213

306

312

212

304

211210209208207206205204203202201

315

401

303

302

314

405

404

403

402

311

310

308

309

224223222221220219218217216215214

101

103

313

102

105104106

107108109

128

301

110

146

407

406

111

130

134

132

138

112

140

126

144

136

142

124

114

122

10

116

505

409408

120

501

410504

225

118

503502

4115041412

3061

3051

3

4

0

2A

1B

2B

1A

5

Conclusion

The 2001 aerial survey estimate of the absolute abundance of dugongs in the Torres Strait region indicates that the dugong harvest is far too high to be sustainable

Indigenous leaders agree with this assessment and a pushing for urgent management action