Mapping genetic and taxonomic species diversity at regional and continental scales

Mapping genetic and taxonomic species diversity at regional and

continental scales

Shawn Laffan Sophie BickfordCSIRO

Centre for Plant Biodiversity Research

Species Diversity

• Conservation prioritisation• Evolution & dispersion

• These are geographic phenomena• multi-scaled• expensive to directly sample

• Need a source of data

Museum data

• Rich source of geocoded information• 6 million plant specimens in Australian

Herbaria• Australian Virtual Herbarium – approx. 40%

digitised in 2002• every specimen description has a

geographic coordinate or reference

• No true absence data• Variable sampling effort

Data set

• Genus Pultenaea• Eastern Australian species used

• 91 species• 3 clades used• Genetic similarity data for 49

species• Aggregated to 50 km resolution

• reduce effects of variable sampling effort & roadmap effect

• Lambert’s conic conformal projection

• 5799 samples (after aggregation)

Species richness

Genetic diversity

• Use of a taxonomy assumes it is reliable• but taxonomy is constantly revised• implies equal similarity between all species

• If we know the genetic similarity of species then we can soften the effects of taxonomy• number of base pairs in common• two sections of trnL-F and ndhF chloroplast genes

base pairs: 900 trnL-F, 674 ndhF• matrix of similarities

Genetic diversity

• We know where the species occur• we can therefore map genetic variation• useful for evolutionary history

• Explicitly spatial:• mean and coefficient of variation of genetic

similarity between all species within a local neighbourhood

• Implicitly spatial• agglomerative clustering with average genetic

similarity as similarity metric

Local genetic diversity, all species

Local genetic diversity, all species

Local genetic diversity by clade

Implicitly spatial

• Agglomerative clustering of cells• Allows for disjoint distributions

• Taxonomic similarity metric between two cells:• Jaccard distance

Shared presence divided by total number of species in two cells

a / (a + b + c)a Num species occurring in both

cellsb & c Num species occurring in only

one cell

Jac = 3 / (3 + 4 + 4) = 3 / 11= 0.27

ACT Brumbies• B. greganii• B. larkhamii• B. gitaeuii• B. mortlockii• B. rathboneii• B. gerardii• B. roffii

Australian Wallabies• B. greganii• B. larkhamii• R. flatleyii• B. mortlockii• W. tuqirii• R. sailorii• W. rogersii

Agglomerative clustering – linkage heuristic• Similarity of newly aggregated classes:

• Unweighted Pair-Group Method• UPGM-A

- average similarity of merged classes- common species counted more than once- “staircase” effect

• UPGM-R- recalculate similarity matrix from first level- each species counts only once in each merger

Similarity Similarity

Recalculated Linkage

Average Linkage

(little variation within clades 2, 3a & 3b)

What next?

• Cross-validation for genetic analyses• More sophisticated measures of genetic

similarity• able to cope with more diverse groups• mean & CofV not ideal measures for non-

symmetric distributions• Software distribution / web analysis

service• http://www.biodiverse.unsw.edu.au