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Spatial Distribution Predicted Observed Evaluating & Using General Theories in Ecology Ethan P. White (@ethanwhite) with Xiao Xiao, Daniel J. McGlinn, & Katherine M. Thibault 15745 sites 8802 species 4 major taxa 50 million individuals Code: github.com/weecology Data: weecology.org/data Grants: weecology.org/grants Twitter: @ethanwhite Blog: jabberwocky.weecology.org MaxEnt models General tests of general theory General theories Using general theories to model diversity Theory Diversity Patterns Birds General ecological theories explain a broad array of ecological patterns They facilitate research and management at the scale of climate and land use change To evaluate general theories rigorously it is necessary to use large amounts of data (to get general results) and multiple predictions (to determine if the theory is right, or just lucky) We evaluate the Maximum Entropy Theory of Ecology and use it to model diversity at continental scales. Use all available dataUse all available predictions Body Size & Resource Use Predicted Observed Commonness & Rarity Predicted Observed Predicted Observed Maximum Entropy models describe the most likely state of a system that satisfies a set on constraints. Good models for complicated systems without dominant processes (e.g., toddlers and ecology) This MaxEnt model captures commonness and rarity across the globe and diversity of life. When pushed to predict multiple patterns the model produces decidedly mixed results. ( , | 0 , 0 , 0 , 0 ¿ =1 0 ∙Π ( | , 0 , 0 ) = 0 0 Specify a joint distribution Maximize entropy Subject to constraints We practice open science Predict Rarity Extrapolate across scales Model diversity Environment Richness & Abundance Harte et al. (2009) Ecology Letters Acknowledgements Poster Harte Lab CAREER Award Weecology Predic ted Predic ted log(Ar ea) log(# of Species) Predicted # of Rare Species Observed # of Rare Species

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Evaluating & Using General Theories in Ecology Ethan P. White (@ ethanwhite ) with Xiao Xiao , Daniel J. McGlinn , & Katherine M. Thibault. General tests of general theory. General theories. General ecological theories explain a broad array of ecological patterns - PowerPoint PPT Presentation

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Page 1: Spatial Distribution

SpatialDistribution

Predicted

Obs

erve

d

Evaluating & Using General Theories in EcologyEthan P. White (@ethanwhite) with Xiao Xiao, Daniel J. McGlinn, & Katherine M. Thibault

15745 sites8802 species4 major taxa50 million individuals

Code: github.com/weecology Data: weecology.org/data Grants: weecology.org/grants Twitter: @ethanwhiteBlog: jabberwocky.weecology.org

MaxEnt models

General tests of general theoryGeneral theories

Using general theories to model diversity

Theory

Diversity Patterns

0.0

0.2

0.4

0.6

-10

0

10

20

Birds

• General ecological theories explain a broad array of ecological patterns

• They facilitate research and management at the scale of climate and land use change

• To evaluate general theories rigorously it is necessary to use large amounts of data (to get general results) and multiple predictions (to determine if the theory is right, or just lucky)

• We evaluate the Maximum Entropy Theory of Ecology and use it to model diversity at continental scales.

Use all available data Use all available predictions

Body Size &Resource Use

Predicted

Obs

erve

d

Commonness& Rarity

Predicted

Obs

erve

d

Predicted

Obs

erve

d

Maximum Entropy models describe the most likely state of a system that satisfies a set on constraints.

Good models for complicated systems without dominant processes (e.g., toddlers and ecology)

This MaxEnt model captures commonness and rarity across the globe and diversity of life.

When pushed to predict multiple patterns the model produces decidedly mixed results.

𝑅 (𝑛 ,𝜀|𝑆0 ,𝑁0 ,𝐸0 , 𝐴0¿

∑𝑛=1

𝑁0

𝑛 ∙ Π (𝑛|𝐴 ,𝑛0 , 𝐴0 )=𝑁 0𝐴𝐴0

Specify a joint distribution

Maximize entropy

Subject to constraints

We practice open science

Predict Rarity

Extrapolate across scales

Model diversity

Environment

Richness & Abundance

Harte et al. (2009)Ecology Letters

Acknowledgements

Poster

HarteLab

CAREERAward

Weecology Predicted

Pred

icte

d

log(Area)

log(

# of

Spe

cies

)

Predicted # of Rare Species

Obs

erve

d #

of R

are

Spec

ies