The document summarizes research on extinction dynamics in the Caribbean. It discusses how early equilibrium models of island biogeography have been challenged by disequilibrium dynamics seen in the Caribbean, including multiple waves of extinction. Several studies are highlighted that use fossil and genetic data to determine extinction timing for various bat and small mammal species. The arrival of humans in the Caribbean, through four migration waves, corresponded with many extinction events, though some pre-dated humans as well. A model is presented that aims to predict extinction risk factors at the species and island level, finding traits like body size as well as island characteristics influence survival. The talk concludes by discussing the importance of the findings for contemporary conservation efforts.

1. Dynamics of extinction and survival in the
Caribbean and the future of biodiversity
Liliana M. Dávalos
American Museum of Natural History
Comparative Biology Seminar Series
26 March 2018

2. What we do in the lab
The Dávalos Lab

3. A double mission
Biological
diversity
Evolution Extinctionincrease decrease

4. Come to my Columbia
University Seminar!
Tomorrow!
Biological
diversity
Evolution Extinctionincrease decrease

5. MacArthur & Wilson 1963 Evolution

6. Equilibrium dynamics
• Scaling of richness
• Stability
• Predictable

7. Disequilibrium
dynamics
• Under-scaling of richness
• Instability
• Unpredictable

8. Most tests = dynamics
from scaling
Morgan & Woods 1986 Biol. J.
Linnean Soc.
Scaling
Scaling (ancient)

9. Evolutionary dynamics Ricklefs & Bermingham 2001 Science
Scaling

10. Only two elements Ricklefs & Bermingham 2001 Science
Extinction
Colonization

11. (Some) Bats of the Caribbean
Rojas, Warsi, Dávalos 2016 Syst. Biol.
Tavares, Warsi, … Dávalos 2018 J. Biogeogr.

12. Data on Greater
Antillean bats
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.

13. Equilibrium, three
elements
Time before present (106 years)
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.
Which
scaling?

14. Equilibrium dynamics!
Time before present (106 years)
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.
Age λc μ γ λa
20 0.22 0.26 0.017 0.27
45 0.26 0.35 0.021 0.27

15. What about extinct
species?
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.

16. Fossils make a
difference
Age
Ma
λc μ γ λa
20 0.28 0.33 0.030 0.19
45 0.32 0.41 0.036 0.16
Age
Ma
λc μ γ λa
20 0.22 0.26 0.017 0.27
45 0.26 0.35 0.021 0.27
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.

17. 0 10 20 30 40
020406080
Numberofendemicspecies
01020304050
Numberofendemicspecies
Time (Ma)
Restoring richness takes
time
Valente, Etienne, Dávalos 2017 Nature Ecol. & Evol.

18. Highlights 20 Ma
• Equilibrium upended by
recent extinctions
• Fossils change rates of
colonization, not just
extinction
• Scaling, stable,
predictable
• Time to recovery long
Photo by Jon Flanders

19. Image by David Rini

21. What killed the mammals
of the Caribbean?
Deglaciation!
© Adrian Tejedor

22. Islands of the Caribbean:
The West Indies
Dávalos,& Turvey 2012 Bones, Clones, and Biomes

23. Dávalos & Russell 2012 Ecol. Evol.

24. But there were no dates Soto-Centeno & Steadman 2015 Sci. Rep.

25. Timing is everything Cooke, Dávalos et al. 2017 Annu. Rev. Ecol. Evol. Syst.

27. A hierarchical model
• Difference in dates
• Clustered by island
• Can be affected by
the type of dating or
remains
• Positive = after
humans

28. Large islands: Two
extinction waves
• Larger islands, some
pre-human extinctions
• Not all extinction
caused by humans
• Another cluster of
extinction after human
arrival
• Humans likely
responsible for
some losses
Cooke, Dávalos et al. 2017 Annu. Rev.
Ecol. Evol. Syst.

29. Lesser Antilles: One
extinction wave
• Many smaller
mammals survived
human use
• Found in middens,
presumably eaten
• But could not recover
after European arrival
• Cats, rats, mice,
goats, introduced

30. Lessons from Marie
Galante
Stoetzel et al. 2016 Quat. Sci. Rev.

31. Many species lack
dates
• Some islands/clades
well studied
• Many missing
• Rodents & bats
• Even in Greater
Antilles
• Too few dates
• But we know one
thing…
Cooke, Dávalos et al. 2017 Annu. Rev.
Ecol. Evol. Syst.

32. Phylogeny!
• Some Caribbean
groups distinct
• e.g., Solenodon
• Others less distinct
• Some hutias &
Short-faced bats
• Not enough life history
Cooke, Dávalos et al. 2017 Annu. Rev.
Ecol. Evol. Syst.

33. A few traits
• Bat extinction
• Larger species
• Herbivores
• Non-bats
• Larger
• Smaller?!
Cooke, Dávalos et al. 2017 Annu. Rev.
Ecol. Evol. Syst.

34. Mammals of the Caribbean today
© Yomangani/Creative Commons © Eladio Fernandez
© Jon Flanders

35. Survivors are on the
brink of extinction
• Among bats
• 9 of 60 threatened
• 3 known from 1
cave each
• Among non-bats
• 8 of 12 threatened
• How to predict
extinction or
survival?
Illustration by Adrián Tejedor
Cooke, Dávalos et al. 2017 Annu. Rev.
Ecol. Evol. Syst.

36. Modeling extinction/
survival
In progress
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!
pecies-specific effects given by mu, and covariate coefficients
est the hypothesis that small and large mammals went extinct m
ed mammals or Goldilocks hypothesis. If the mass covariate is
en there are no covariates at this level.
ds 1 to k, island-specific intercepts are modeled in similar fashio
e independently distributed residuals, and thus require no phyl
the island intercepts are modeled as:
!. !"#. ℎ!"! = !. !"# ∗ !"#!! + !"#.
e various model parameters are summarized in Table 1.
ry of priors for Bayesian models. In the model building languag
, normal distributions have the precision tau or the inverse of th
ariation.
probability of survival given by pri such that:
!!~ !"#$%(!"!)
!"#$% !"! = !. !"# !"#$%#!! + !. !"# !"#$%&!
ariates observed at this level, equivalent to no sample-wide ef
troduced here thus:
$% !"! = !. !"# !"#$%#!! + !. !"# !"#$%&! + !. !"## ∗ !"##! +
istribution has no error associated with the observations, the e
ntercepts estimated for each of the cluster-specific effects. By
oid making the model unidentifiable by, for example, attempting
lar island across the entire sample. Additionally, the two sets o
ested.
es from 1 to j, the probability now becomes normally distributed
ng to the residuals. Each value of the tau_resid matrix is based on a pri
distribution based on the off-diagonals of the expected variance-covaria
ous trait evolving through Brownian motion on the phylogeny:
!"#_!"#$%[!:!,!:!]~ !"#$ℎ(!"#$[,], !)
distributions, the species intercepts can now be modeled as:
!. !"#. ℎ!"! = !". !. !"# + !. !"##! ∗ !"##! + !. !"##! ∗ !"##!
!
+ !ℎ!!
n of species-specific effects given by mu, and covariate coefficients for m
to test the hypothesis that small and large mammals went extinct more
-sized mammals or Goldilocks hypothesis. If the mass covariate is inclu
s, then there are no covariates at this level.
slands 1 to k, island-specific intercepts are modeled in similar fashion a
o have independently distributed residuals, and thus require no phylogen
ence the island intercepts are modeled as:
!. !"#. ℎ!"! = !. !"# ∗ !"#!! + !"#.

37. Modeling extinction/
survival
In progress
Spp. traits
Island characteristics
Mass is quadratic
Many island characteristics
can be added
Phylogenetic effect
!. !"#. ℎ!"! = !". !. !"# + !. !"##! ∗ !"##! + !. !"##! ∗ !"##!
!
pecies-specific effects given by mu, and covariate coefficients
est the hypothesis that small and large mammals went extinct m
ed mammals or Goldilocks hypothesis. If the mass covariate is
en there are no covariates at this level.
ds 1 to k, island-specific intercepts are modeled in similar fashio
e independently distributed residuals, and thus require no phyl
the island intercepts are modeled as:
!. !"#. ℎ!"! = !. !"# ∗ !"#!! + !"#.
e various model parameters are summarized in Table 1.
ry of priors for Bayesian models. In the model building languag
, normal distributions have the precision tau or the inverse of th
ariation.
probability of survival given by pri such that:
!!~ !"#$%(!"!)
!"#$% !"! = !. !"# !"#$%#!! + !. !"# !"#$%&!
ariates observed at this level, equivalent to no sample-wide ef
troduced here thus:
$% !"! = !. !"# !"#$%#!! + !. !"# !"#$%&! + !. !"## ∗ !"##! +
istribution has no error associated with the observations, the e
ntercepts estimated for each of the cluster-specific effects. By
oid making the model unidentifiable by, for example, attempting
lar island across the entire sample. Additionally, the two sets o
ested.
es from 1 to j, the probability now becomes normally distributed
ng to the residuals. Each value of the tau_resid matrix is based on a pri
distribution based on the off-diagonals of the expected variance-covaria
ous trait evolving through Brownian motion on the phylogeny:
!"#_!"#$%[!:!,!:!]~ !"#$ℎ(!"#$[,], !)
distributions, the species intercepts can now be modeled as:
!. !"#. ℎ!"! = !". !. !"# + !. !"##! ∗ !"##! + !. !"##! ∗ !"##!
!
+ !ℎ!!
n of species-specific effects given by mu, and covariate coefficients for m
to test the hypothesis that small and large mammals went extinct more
-sized mammals or Goldilocks hypothesis. If the mass covariate is inclu
s, then there are no covariates at this level.
slands 1 to k, island-specific intercepts are modeled in similar fashion a
o have independently distributed residuals, and thus require no phylogen
ence the island intercepts are modeled as:
!. !"#. ℎ!"! = !. !"# ∗ !"#!! + !"#.

38. Results species
• Species vary in
probability of survival
• Some appear doomed

39. Results islands
• Multiple islands were/
became extinction
traps

40. Results predictors
• Island area weakly
related to survival
• Elevation strong
predictor extinction
• Pattern of large and
small spp. correct!

41. A history of extinction Cooke, Dávalos et al. 2017 Annu. Rev. Ecol. Evol. Syst.

42. A history of people
• Humans arrived in four
waves
• First three waves
from New World
• Introduced dogs
and agriculture
• Last wave from Old
World
• Introduced
invasive spp.
©Theodor de Bry/National Library of Medicine

43. Larger mammals probably hunted early on
© Ghedoghedo Wilson 1989 J Field Archaeol.

44. Many extinction events recorded after arrival of Old World
invasive competitors/predators
Turvey et al. 2012 Mamm. Biol.

45. Agriculture likely important for certain species
© Adrian Tejedor ©Pierpont Morgan Library

46. Highlights
• Multiple causes of
extinction
• Some before humans
• Most after humans
• Small AND large
terrestrial species went
extinct
• not just hunting
• Agriculture maybe
important for bats, others
© Yomangani/Creative Commons

47. Why is this important? The world is made of islands

48. This is happening now Ray et al. 2015 Mongabay

49. What happens when the
frontier closes?
1869

50. Frontier closes, forest
vanishes
Stanton 2014 Biol. Cons.

51. The frontier
• Border between settled
land/ natural habitats
• Forest->property
• Final condition = no
forest
• Happened in other
regions
• Most of Andes hotspot
• Unfolding in most of
Amazonia Etter et al. 2006 J. Environ.
Manage.
Fractionforest

52. The Amazon frontier A general model
Fractionforest
beachhead
Time ->
mixed agriculture
properties
pastures!

53. The sixth extinction is
(partially) avoidable
• Equilibrium is real
• Habitat loss = extinction
• Fragmentation = extinction
• We have the tools to conserve
• Connect ecosystems
• ~30 years before Amazon
becomes pastures
• We are responsible for
evolution into the future

54. Thanks!