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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
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