1. Improving
abundance
estimation by
combining capture-
recapture and
occupancy data
L. Blanc, E.
Marboutin, S. Gatti, F.
Zimmermann and O.
Gimenez

2. • Abundance and distribution: two key parameters often studied apart
Management and conservation

3. • Abundance and distribution: two key parameters often studied apart
• 2 issues in natural population:
Imperfect detection
Management and conservation

4. • Abundance and distribution: two key parameters often studied apart
• 2 issues in natural population:
Imperfect detection
Management and conservation
-> Capture-recapture data (CR data)

5. • Abundance and distribution: two key parameters often studied apart
• 2 issues in natural population:
Imperfect detection
great commitment of time and money
Management and conservation

6. • Abundance and distribution: two key parameters often studied apart
• 2 issues in natural population:
Imperfect detection
great commitment of time and money
Management and conservation
75 camera traps/2 months Price (€)
Staff (1 full-time worker for 1 year ~ 200 days) 112000
Accomodation and travel expenses 6700
Material 45000
Material extra (theft) 3500
TOTAL 163700

7. • Abundance and distribution: two key parameters often studied apart
• 2 issues in natural population:
Imperfect detection -> Capture-recapture data
great commitment of time and money -> Occupancy modelling
Management and conservation

8. Eurasian lynx

9. Lynx data
• Intensive monitoring :
– 2011: camera trapping
– 33 sites

10. Lynx data

11. Lynx data
5 m

12. Lynx data
• Intensive monitoring:
– 2011: camera trapping
– 33 sites
– 39 captures
– 9 individuals identified 14/32
sites

13. PhD: Persevere but Highly Depressed

14. • Cry for my mommy
• Pray for a miracle
PhD: Persevere but Highly Depressed

15. • Cry for my mommy
• Pray for a miracle
PhD: Persevere but Highly Depressed

16. • Cry for my mommy
• Pray for a miracle
« [Sample] size matters not, …
Look at me. Judge me by size, do
you?
May to force be with you ! »
PhD: Persevere but Highly Depressed

17. Lynx data
• Extensive monitoring:
– from 2009 to 2011
– 172 presence signs

18. Lynx data
• Intensive monitoring:
– 2011: camera trapping
– 33 sites
– 39 captures
– 9 individuals identified 14/32
sites
• Extensive monitoring:
– from 2009 to 2011
– 172 presence signs

19. WHY? HOW?
• Abundance and distribution = two distinct variables ?

20. WHY? HOW?
• Abundance and distribution = two distinct variables?
• Abundance and occupancy = linked variables = key concept

21. WHY? HOW?
• Abundance and distribution = two distinct variables?
• Abundance and occupancy = linked variables = key concept
• When a site is known to be occupied by a species, there is at least one
individual of this species on this site (N>=1)

22. WHY? HOW?
• Abundance and distribution = two distinct variables?
• Abundance and occupancy = linked variables = key concept
• When a site is known to be occupied by a species, there is at least one
individual of this species on this site (N>=1)
• Information on N if information on the occupancy

23. State process
Occupancy model (ψ)
ψ

24. State process
Occupancy model (ψ)
1-ψ

25. State process
Occupancy model (ψ)
Detection process
p
? ? ? ?
time
X

26. CR model (N)
State process

27. CR model (N)
State process
!
k)P(N
k

 k
e


28. CR model (N)
State process

 eNP )0(

29. CR model (N)
State process
-
10)P(N–10)P(N e

30. CR model (N)
State process
Detection process
p
? ? ? ?
time

31. State process
CR model (N) Occupancy model (ψ)
Detection process

32. State process
CR model (N) Occupancy model (ψ)
Detection process
Combined model
State process
ψ
ψ

33. State process
CR model (N) Occupancy model (ψ)
Detection process
Combined model
State process
-
10)P(N–10)P(N e

34. State process
CR model (N) Occupancy model (ψ)
Detection process
Combined model

 -
10)P(N–10)P(N e

35. 
 -
10)P(N–10)P(N e

36. Combined model

 -
1 e

37. Combined model

 -
1 e
)(~ PN

38. Combined model
)1log(  

 -
1 e
))1log((~ PN

39. State process
CR model (N) Occupancy model (ψ)
Detection process
Combined model
Detection process
State process

40. 0
5
10
15
20
25
30
35
40
45
50
Capture-recapture model Combined model
Abundance
Eurasian lynx abundance

41.  Limits
Closure assumption valid ? (territorial species)
Limits and Perspectives

42.  Limits
Closure assumption valid ? (territorial species)
False positives in presence data? (validation step)
Limits and Perspectives

43.  Limits
Closure assumption valid ? (territorial species)
False positives in presence data? (validation step)
N homogeneous Poisson random variable
Limits and Perspectives

44.  Limits
Closure assumption valid ? (territorial species)
False positives in presence data? (validation step)
N homogeneous Poisson random variable
 Perspectives
SECR model vs. standard CR model
Limits and Perspectives

45.  Individual data
+ most informative data
- Limited financial resources and data sampling jeopardy
Take-home message

46.  Individual data
+ most informative data
- Limited financial resources and data sampling jeopardy
 Presence-absence data
+ Affordable (citizen science programs) + Large scale surveys
- Less precise data
Take-home message

47.  Individual data
+ most informative data
- Limited financial resources and data sampling jeopardy
 Presence-absence data
+ Affordable (citizen science programs) + Large scale surveys
- Less precise data
 Combining data ()
small budget or targetting elusive territorial species
Surveys with two resolutions (count data/individual data and
presence-absence data)
Take-home message

48. Thanks for your attention
;-)
© Alain Laurent