1. Climate Change, Disease, and Amphibian Declines by Jason R. Rohr University of South Florida Department of Biology, SCA 110 4202 E. Fowler Ave. Tampa, FL 33620 jasonrohr@gmail.com

2. Climate Change, Amphibian Declines, and Bd Also evidence that Bd-related declines are linked to climate change (Pounds et al. 2006, Bosch et al. 2006)

3. Outline for Talk Does global climate change affect worldwide amphibian declines associated with chytrid fungal infections?

4. Enigmatic Amphibian Declines

5. Genus Atelopus

6. from La Marca et al. 2005. Biotropica 71 of 113 spp. presumed extinct, many of which were ostensibly caused by chytridiomycosis

7. Climate, Bd, and Conservation Planning If we understand the climatic factors that accelerate Bd spread, increase host susceptibility, or elevate pathogen virulence, we can identify present and future geographic locations that might have amphibians at risk of Bd-related declines Hence, we can better target areas that warrant monitoring and remediation

8. Tenuous Links Between Climate and Amphibian Declines Most of the evidence supporting climate change as a factor in Bd-related amphibian extinctions comes from a positive, but temporally confounded, multi- decade correlation between air temperature and extinctions in the toad genus Atelopus Rohr et al. 2008 PNAS

9. Need to Conduct Detrended Analyses? If there is a true relationship between climate and Bd-related extinctions, fluctuations around temporal trends in temperature and extinctions should also positively correlate There would many fewer non-causal explanations for this correlation than the multidecadal relationship between declines and temperature

10. Use the Atelopus database to simult- aneously test various climate-related hypotheses for amphibian declines, controlling for multidecadal correlations and the intrinsic spatiotemporal spread of Bd Objectives

11. Ultimate Hypothesis: ENSO Drives Amphibian Declines

12. ENSO: El Niño-Southern Oscillation Commonly referred to as simply El Niño is a global coupled ocean-atmosphere phenomenon –The Pacific ocean signatures, El Niño (warm and wet) and La Niña (cool and dry) are important temperature fluctuations in surface waters of the tropical Eastern Pacific Ocean –The atmospheric signature, the Southern Oscillation (SO) reflects the monthly or seasonal fluctuations in the air pressure Effects of El Niño in South America are direct and stronger than in North America

13. Proximal Hypotheses for Enigmatic/Bd-related Declines Spatiotemporal spread hypothesis: declines are caused by the introduction and spread of Bd, independent of climate (Bell et al. 2004, Lips et al. 2006) Climate-based hypotheses: –Chytrid-thermal-optimum hypothesis: Increased cloud cover, due to warmer oceanic temperatures, leads to temperature convergence on the optimum temperature for growth of Bd (Pounds et al. 2006, Bosch et al. 2006) –Mean-climate hypothesis: changes in mean temp. and/or moisture conditions affect the distributions of amphibians (Whitfield et al. 2007, Buckley & Jetz 2007) –Climate-variability hypothesis: temporal variability in temp. cause suboptimal host immunity facilitating declines (Raffel, Rohr, et al. 2006)

14. Climate-Variability Hypothesis Ectotherms: *seasonal changes in body temperature*

15. Climate Variability Hypothesis Hypothesis: unpredictable temperature shifts, which are increasing with GCC, benefit pathogens more than hosts. –faster metabolisms of parasites should allow them to acclimate more quickly to unpredictable temperature shifts, especially for ectothermic hosts –parasites have fewer cells and processes to adjust and generally withstand greater temperature extremes than hosts (Portner 2002) –owing to their shorter generation times, parasites should evolve more quickly than hosts to changes in climate

16. Climate Variability Hypothesis The categorically faster metabolisms, smaller size, and greater reproductive capabilities of parasites than hosts provides a general hypothesis for how global climate change will affect disease risk– unpredictable climate variability should increase disease.

17. Rohr et al. 2008 PNAS Is there Spatiotemporal Spread of Atelopus Extinctions?

18. Atelopus Extinctions Through Time Best fit curve Rohr et al. 2008 PNAS

19. How we controlled for the likely epidemic spread of the pathogen

20. Ultimate Hypothesis: ENSO Drives Amphibian Declines

21. La Niña Years? El Niño Years?

22. Ultimate Hypothesis: ENSO Rohr and Raffel 2010 PNAS

23. Must Control for Intrinsic Dynamics to Detect Extrinsic Factors! No significant ENSO signature if we don’t control for probable epidemic spread Hence, the availability of susceptible hosts appears the primary factor influencing epidemic spread followed secondarily by climateHence, the availability of susceptible hosts appears the primary factor influencing epidemic spread followed secondarily by climate

24. But What is the Proximate Explanation? What is it about El Nino years that is associated with amphibian extinctions?

25. Proximal Hypotheses for Enigmatic/Bd-related Declines Spatiotemporal spread hypothesis: declines are caused by the introduction and spread of Bd, independent of climate (Bell et al. 2004, Lips et al. 2006) Climate-based hypotheses: –Chytrid-thermal-optimum hypothesis: Increased cloud cover, due to warmer oceanic temperatures, leads to temperature convergence on the optimum temperature for growth of Bd (Pounds et al. 2006, Bosch et al. 2006) –Mean-climate hypothesis: changes in mean temp. and/or moisture conditions affect the distributions of amphibians (Whitfield et al. 2007, Buckley & Jetz 2007) –Climate-variability hypothesis: temporal variability in temp. cause suboptimal host immunity facilitating declines (Raffel, Rohr, et al. 2006)

26. Regional Predictors tested w/ and w/o a one year lag 1.Mean absolute value of monthly differences (AVMD) in temp. 2.Cloud cover x temp. (Pounds et al. 2006) 3.Cloud cover (Pounds et al. 2006) 4.Temperature-dependent Bd growth (Pounds et al. 2006) 5.Precip. x temp. (Whitfield et al. 2007) 6.Diurnal temp. range (DTR) 7.Frost freq. 8.Precip. 9.Temp. 10.Temp. max. 11.Temp. min. 12.Vapor press. 13.Wet day freq.

27. Results of Best Subset Model Selection results are similar using AIC

28. Can Monthly Temperature Variability Explain Atelopus Extinctions? Rohr and Raffel 2010 PNAS

29. Amphibian extinctions have often occurred in warmer years, at higher elevations, and during cooler seasons. Are monthly and daily variability in temperature also greater at these times and locations?

30. Do Warmer Years Have Greater Variability in Temperature? Rohr and Raffel 2010 PNAS

31. Do High Elevations Have Greater Variability in Temp.?

32. Do Cooler Months Have Greater Variability in Temp.? Rohr and Raffel 2010 PNAS

33. Results of Path Analysis El Niño 3.4 DTR R 2 =0.633 AVMD anomalies R 2 =0.567 Lag amphibian extinctions R 2 =0.674 P<0.001 0.675 P=0.002 0.673 P=0.044 -0.466 P<0.001 0.694 P<0.001 0.868 Rohr and Raffel 2010 PNAS

34. We Weren’t Convinced

35. Experimental Test Acclimated Cuban tree frogs to 15 or 25 ⁰ C for four weeks Challenged with Bd at start of week five Quantified survival and pathogen loads Acclimated Cuban tree frogs to 15 or 25 ⁰ C for four weeks Challenged with Bd at start of week five Quantified survival and pathogen loads 15 ⁰ C 25 ⁰ C 15 ⁰ C 25 ⁰ C

38. Does Temperature Variability Increase Bd Loads on Frogs? Raffel et al. in press Nature Climate Change Bd-induced mortality:Bd load: Temperature shifts increased Bd loads and Bd-induced mortality

39. Summary Availability of susceptible hosts appears to be the primary factor influencing the spread of BdAvailability of susceptible hosts appears to be the primary factor influencing the spread of Bd There is a strong ENSO signature to extinctions after controlling for epidemic spread Both field patterns of extinctions and manipulative experiments support the climate-variability hypothesis for amphibian extinctions

40. Conclusions Temperature, temperature variability, and Central Pacific El Niño events are increasing in tropical and subtropical regions because of climate change; thus, global climate change might be contributing to enigmatic amphibian declines, by increasing disease risk

41. Conclusions Elevated temperature variability might represent a common, but under-appreciated, link between climate change and both disease and biodiversity losses and might offer a general mechanism for why disease would increase with GCC.

42. Parte 4: MODELO CLIMÁTICO ECO FISIOLÓGICO para anfibios

43. Spea hammondi Fisher and Shaffer 1996

44. Bufo boreas Fisher and Shaffer 1996

45. Rana aurora (Bd induced?) Fisher and Shaffer 1996

46. Preparación de modelos Molde de Látex a partir de un espécimen de colección. Obtención de modelos de agar.

47. Experimento de campo 4 condiciones experimentales (factorial). HÚMEDO - SOMBRA (2 modelos) HÚMEDO -SOL (2 modelos) SECO - SOMBRA (2 modelos) SECO - SOL (2 modelos) Día

48. Experimento de campo Modelos conectados a data loggers. Reemplazo de modelos cada 3-4 hr. SECO SOL HÚMEDO SOL SECO SOMBRA HÚMEDO SOMBRA

49. T operativa y Pérdida de agua sol seco sombra húmedo Del Puerto Canyon; 12 march 2012; nublado; Annaxyrus boreas model

50. T ambiental y Pérdida de agua sol seco sombra seco sombra húmedo sol húmedo Tª sol Tª sombra Los Baños Cistern; 5 march 2012; soleado; metamórficos

51. Un sitio Extinct Un sitio persistente Pseudacris sierra

52. Species Calibrations for CA Frogs Spea hammondi Anaxyrus boreas*** Anaxyrus punctatus Rana sierrae*** Rana aurora Low sensitivity to Bd:Immune to Bd: Pseudacris sierra*** P. cadaverina* P. hypochondriaca Very sensitive to Bd: Hydric Loss Rates and Extinction, significant assoc:*,**,***

53. Preest and Pough, Funct Ecol 1989 Bufo americanus distancia recorrida en 10 minutos de la locomoción forzada

54. Víctor H. Luja lujastro@yahoo.comlujastro@yahoo.com Octavio Jiménez octavio.jimenez.robles@gmail.comoctavio.jimenez.robles@gmail.com Eric Curiel ecuriell@ucsc.eduecuriell@ucsc.edu

55. Desarrollando un MODELO CLIMÁTICO ECO FISIOLÓGICO para anfibios 1. Buscamos un modelo que explique mejor el límite de distribución de las especies. Buscamos encontrar el conjunto de tasas de pérdida de agua (y de temperatura) durante el día vs la noche que explique los límites más secos (el umbral de desecación) debajo del cual la especie no se encuentra mas. Este umbral que mejor ajusta está basado en las ubicaciones de todas las poblaciones a partir de 1970. 2. Este umbral hídrico de pérdida de agua es conceptualmente similar al h_r para las horas de restricción de actividad debido al calor. 3. Entonces, nosotros probaremos como se comporta este modelo para predecir la distribución actual de las extinciones (por ejemplo cambios en la pérdida hídrica del delta entre 1975–2010, debido al incremento en la intensidad de la sequía).