the ppt of advanced ecological modeling lessons.

1. Climate variability in different
geographic scales and its impacts on
species temperature tolerance
Speaker: Eric Lai
Date:2019/10/28
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2. Outline
1. The scientific issue to focus on
2. A brief introduction to own project
3. Methods of the key paper
4. key paper's Results & Discussion
5. How to apply to own project
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3. The scientific issue to focus on
• Tropical mountain regions are among the most biodiverse ecosystems on
earth, with higher species richness than temperate mountains.
• Climate Variability Hypothesis (CVH) :
seasonal climatic variation increase with latitude, selecting for species with
broader thermal tolerance and higher dispersal capacities.
• Janzen (1967) extended the CVH to elevation gradients:
reduced seasonality produces greater thermal stratification along tropical
mountains, selecting for narrower species, and therefore limiting dispersal
across tropical elevation gradients.
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4. A brief introduction to own project
• A definitive test of the mechanisms linking climate variability and
tropical montane diversity has remained elusive.
• Elevational range size was negatively correlated with daily
temperature variation among gradients. (Chan et al, 2018)
• In addition to the different climate variability scales, under different
geographic scales, it may also influence the results.
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5. 5
Jiajinshan,
China
Zhongheng Highway,
Taiwan
Cameron Highlands,
Malaysia
All communities temperature tolerance range distribution
Three communities temperature tolerance range distribution

6. Questions
• Are the temperature tolerances of the populations of same
moths species in different geographical locations partially
overlapping and continuous?
• Does the temperature tolerance range of the moth adult
populations have significant differences in different regions?
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7. key paper
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10. The hypothesis in this study
• thermal complementarity and mean thermal breadth should
decrease along the mean annual temperature gradient, but
increase along the temperature seasonality gradient.
• the robustness of community resilience to species
extinctions should be the lowest in regions where
community thermal resilience is highest.
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11. Methods of the key paper
• species thermal optimum (μi)
• species thermal breadth (σi)
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12. • community thermal optimum (μcj)
• community thermal breadth (σcj)
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13. • Thermal complementarity CVj
• Mean thermal breadth μσj
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14. robustness of community thermal resilience
• geometrically declining function (out of the 1000 simulations)
• tolerance index, Thalf, j
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, 0 1
' 1 1
log 1 ( )
2
jhalf j b S
j j
r
T
S S a
  
 
     
0( )j
r
C r a a b    

15. key paper's Results
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MAT
MAT
MAT
MAT: Mean Annual Temperature

16. 16TS: Temperature Seasonality
Communitythermal
breadth
Thermal
complementarity
TSTS
TS

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18. Discussion
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tolerance thermal
complem-
entarity
mean thermal
breadth
community thermal
breadth
MAT + ─ ─ ─
TS _ + + +
thermal adaptation hypothesis
climatic variability hypothesis
communities in warm, less seasonal areas
are the most robust communities
p < 0.0001

19. To apply to own project
• Not only for single species thermal tolerance, but also will
calculate each regions of community thermal niche indices.
• Use tolerance index to check each communities thermal
resilience, and what factors influence it.
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20. Reference
• Arnan, X., Blüthgen, N., Molowny-Horas, R., & Retana, J. (2015).
Thermal characterization of european ant communities along
thermal gradients and its implications for community resilience
to temperature variability. Frontiers in Ecology and Evolution, 3,
138.
• Chan, W. P., Chen, I. C., Colwell, R. K., Liu, W. C., Huang, C. Y., & Shen,
S. F. (2016). Seasonal and daily climate variation have opposite
effects on species elevational range size. Science, 351(6280),
1437-1439.
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