bes/sfe talk 2014
DESCRIPTION
Talk on poit processes and distribution modelsTRANSCRIPT
A unified framework to combine disperate data types in species distribution modelling
A unified framework to combine disperate datatypes in species distribution modelling
Slides on Slideshare:http://www.slideshare.net/oharar/bessfe-talk-2014
Bob O’Hara1 Petr Keil 2 Walter Jetz2
1BiK-F, Biodiversity and Climate Change Research CentreFrankfurt am Main
GermanyTwitter: @bobohara
2Department of Ecology and Evolutionary BiologyYale University
New Haven, CT, USA
A unified framework to combine disperate data types in species distribution modelling
A ”Real” Curve
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A Curve
A unified framework to combine disperate data types in species distribution modelling
Approximated with a Discretised Curve
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A CurveDiscrete
A unified framework to combine disperate data types in species distribution modelling
Better: linear interpolation
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A CurveDiscreteInterpolated
A unified framework to combine disperate data types in species distribution modelling
With more points, the approximations improve
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A CurveDiscreteInterpolated
A unified framework to combine disperate data types in species distribution modelling
What does this have to do with distribution models?
A unified framework to combine disperate data types in species distribution modelling
What does this have to do with distribution models?
This is how SDMs see the world:
source: http://bit.ly/1l8sG7M
Map produced by Peter Blancher, Science and Technology Branch, Environment Canada, based on data from the
North American Breeding Bird Survey
A unified framework to combine disperate data types in species distribution modelling
DiscretionProjected maps look like this:
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A unified framework to combine disperate data types in species distribution modelling
Can we be less discrete?This might be better:
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A unified framework to combine disperate data types in species distribution modelling
Point Processes: Model
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Model of where individuals are Ahigher intensity means moreindividuals
A unified framework to combine disperate data types in species distribution modelling
Pointless Processes?
How do we use this approach?
A unified framework to combine disperate data types in species distribution modelling
Need to use talk about sausage
Lincolnshire Sausage! by Caro Wallis, https://www.flickr.com/photos/carowallis1/806455819
A unified framework to combine disperate data types in species distribution modelling
Point processes
Represent density by a surface, with intensity λ(s)Number in area A follows Poisson distribution with mean µ(A):
µ(A) =
∫Aλ(s)ds
Raw Blood Sausage by Carlos Lorenzo, https://www.flickr.com/photos/carlos lorenzo/447670758
A unified framework to combine disperate data types in species distribution modelling
Intense Models
Model the expected density through the intensity:
log(λ(s)) =∑
βjXj(s) + ν(s)
Xj(s) are covariates (also continuous in space)ν(s) is a residual spatial term
Gastrocast #91 by Neal Foley, https://www.flickr.com/photos/86571141@N00/345595467
A unified framework to combine disperate data types in species distribution modelling
Point Processes: Model
In practice, approximate the surface with triangles
A unified framework to combine disperate data types in species distribution modelling
How about the data?
Pig faces by Karen,
https://www.flickr.com/photos/unsureshot/167930176
Presence only points: thinnedpoint processAbundance: PoissonPresence/Absence: binomial,cloglog(large) areas:
Pr(n(A) > 0) = 1− e∫A eρ(ξ)dξ
A unified framework to combine disperate data types in species distribution modelling
Abundance to Presence
N ∼ Poisson(λ)
so
Pr(N > 0) = 1− Pr(N = 0) = 1− λ0exp(−λ)0!
= 1− exp(−λ)
or
cloglog(Pr(N > 0)) = log(λ)
i.e. we just use a GLM with a cloglog link function
A unified framework to combine disperate data types in species distribution modelling
Fitting models in PracticeNeed a sausage grinder
Fat Grinder by Danielle Harms,
https://www.flickr.com/photos/daniellemharms/5597688960
R + INLA
A unified framework to combine disperate data types in species distribution modelling
An Example
Data from MoL
Picus tridactylus by Biodiversity Heritage Library,
https://www.flickr.com/photos/biodivlibrary/9514435393
A unified framework to combine disperate data types in species distribution modelling
Data
eBird GBIF (not eBird)
BBS Expert Range
A unified framework to combine disperate data types in species distribution modelling
We run the model
Sausage machine by clement127, https://www.flickr.com/photos/clement127/15004844674
A unified framework to combine disperate data types in species distribution modelling
Predicted Distribution
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A unified framework to combine disperate data types in species distribution modelling
Predicted Distribution from Each Data Set
All Data
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eBird
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GBIF
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BBS
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A unified framework to combine disperate data types in species distribution modelling
We can make a better sausage
Combining data is betterDon’t lose positional informationBut still have to approximate a surface
Nakki by hugovk, https://www.flickr.com/photos/hugovk/27828598
A unified framework to combine disperate data types in species distribution modelling
We can make a better sausage
Great Marbling! by Gabriel Bucataru, https://www.flickr.com/photos/gabstero/4660842166