Dorcas gazelle abundance estimation in southern Morocco

Dorcas gazelle abundance
estimation in southern Morocco
T. Dieuleveut 1 & Y. Hingrat2
1 Emirate Center for Wildlife Propagation, BP 47, 33250 Missour, Morocco
2 RENECO for Wildlife Preservation, PO Box 61741, Abu Dhabi, United Arab Emirates
Context
• Numerous observations of Dorcas Gazelles during
Houbara Bustard fall counts in Tata region (Southern
Morocco) from 2010 to 2013
• Standardized protocol which allows density
estimations using distance sampling
Study area
Study area
• About 450 km²
• Plains between mountains
(Anti-Atlas & Bani)
• Mainly rocky area with
network of wadis
• Good cover of Acacia trees
Protocol
• Observation points (=point transect): 47 points spread on
a regular grid of 3*3 km
Protocol
• Observation points (=point transect)
• 2 observers per team considered as one “super-observer”
• Twenty minute circular observations in the morning and
evening using binoculars
• Locations of Gazelle observations taken as accurately as
possible (using GPS)
• The whole set points redone several times (between 2 & 5
times) during each count session
Preliminary data
Year
Total number of
Mean
Number of
circular observations
group size
groups
achieved
( SD*)
Mean
observation
distance in m
(SD*)
2010
230
36
2.3 (1.6)
916 (589)
2011
94
13
1.5 (0.7)
1120 (677)
2012
140
14
1.9 (1.4)
1194 (901)
2013
234
25
3 (1.4)
1062 (701)
Summary
698
88
2.3 (1.5)
1032 (686)
Distance sampling analyses
• Analysed taking in account the whole dataset to get a reliable
detection function
• Stratification to extract annual density estimates
Main distance sampling
assumptions to be met
Detection is perfect at low distances
p(0)=1
Distances are measured accurately
No responsive movement before detection
Main distance sampling
assumptions to be met
Distance sampling analyses
Distance sampling analyses
Year
Total number of
circular
Number of
observations
groups
achieved
Density
(CV)
95%
Abundance confidence
interval
2010
230
36
0.076 (24%)
32
20-51
2011
94
13
0.039 (33%)
16
9-31
2012
140
14
0.037 (41%)
16
7-34
2013
234
25
0.068 (20%)
29
22-49
Distance sampling analyses
Year
Total number of
circular
Number of
observations
groups
achieved
Density
(CV)
95%
Abundance confidence
interval
2010
230
36
0.076 (24%)
32
20-51
2011
94
13
0.039 (33%)
16
9-31
2012
140
14
0.037 (41%)
16
7-34
2013
234
25
0.068 (20%)
29
22-49
Problem of detectability
Is the first assumption met ?
• Setup of a mark-recapture distance sampling survey specially
dedicated to Gazelles in spring 2014
• Still two observers, but acting independently
• Each observation is then assigned:
Observer 1
obs1, obs2 or both observer
Both
Observer 2
Problem of detectability
Preliminary results
Year
2010
2013
2014
Total number of
Mean
Mean
circular
Number of
observation
group size
groups
observations
distance in m
( SD*)
achieved
(SD*)
230
36
2.3 (1.6)
916 (589)
234
25
3 (1.4)
1062 (701)
235
65
2.3 (1.0)
1513 (911)
Problem of detectability
Preliminary results
Gazelle spring
survey
Houbara
fall surveys
… But calculated densities are similar
Problem of detectability
Analyses mark-recapture distance sampling
(MRDS)
Number of observations
Total
Observer 1
Observer 2
Both observers
61
46
45
30
A single observer detects about 75% of the total observations
Problem of detectability
Analyses mark-recapture distance sampling
(MRDS)
Number of observations
Total
Observer 1
Observer 2
Both observers
61
46
45
30
Is this non-detectability function of the distance
of observation ?
Are the groups close to the point always
detected by both observer ?
Problem of detectability
Analyses mark-recapture distance sampling
(MRDS)
Number of observations
Total
Observer 1
Observer 2
Both observers
61
46
45
30
Percentage of groups missed by one observer
Problem of detectability
Analyses mark-recapture distance sampling
(MRDS)
Both observers
p(0)=0.99
One
observer
p(0)=0.93
Problem of detectability
Analyses mark-recapture distance sampling
(MRDS)
Conclusion
• Point transect distance sampling
reliable for Dorcas Gazelle
density estimation
• Could be efficient for
population monitoring if
performed at a greater extent
(both geographical and
temporal)
• The problem of detectability
should be kept in mind for
protocol designing and before
making density inferences
Aknowledgements
We are grateful to H.H. Sheikh Mohammed
bin Zayed Al Nahyan,
Nahyan, Crown Prince of Abu Dhabi
and Chairman of the International Fund for Houbara
Conservation (IFHC) and H.E. Mohammed Al
Bowardi Deputy Chairman of IFHC for their support.
support