machine learning methods for analysis of the global fossil record

Machine learning methods foranalysis of the global fossil record

Lecture 1

Indrė Žliobaitė[email protected]

Photo credit: Kayle Reed

Biospheric dataFossil databases

Environment observation sensorsSatellite imaging data

Ecological and conservation data

Weather stations

https://www.atm.helsinki.fi/SMEAR/index.php/smear-ii

http://www.iucnredlist.org/

http://www.worldclim.org/methods1

https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MCD12C1_T1

What can be answered using machine learning

● Reconstructing how life was in the past and how life works in general

● Analyzing relations between organisms and environments,understanding biospheric change processes

● Analyzing why and how species evolve

● Understanding circumstances of early human evolution

Environment:TemperaturePrecipitationProductivitySeasonalityVegetation typeWoody cover...

Occurring animals:Species ASpecies BSpecies C...

Features of animals:Body massSlim legs?Sharp teeth?...

Why understanding the past?

Source: https://climate.nasa.gov/evidence/

Climate change

Source: https://climate.nasa.gov/evidence/

Extreme events

Reconstructing and analyzing climate over time

Fortelius et al 2002

Source: http://humanorigins.si.edu/evidence/human-family-tree

Circumstances of early human environments

Circumstances of early human environments

Image credits:Mauricio Anton

Source: https://www.nature.com/nature/journal/v507/n7492/full/507303a.html

Slide credit: Mikael Fortelius

Estimates for the past, the Turkana basin


Ecometric modeling makes quantitative analysis possible,complements qualitative insights with quantitative reasoning

Paleobiology and conservation:putting dead to work

● “The geologic record as anatural ecological andevolutionary laboratory”

Dietl and Flessa 2011

Source: Barnosky et al 2017

Source: Turkana Basin Institute

Seminar agenda and topics

To pass the seminar

● Short presentation of a research article

● Data analysis project + presentation

– Implement one method from the article and one modification

● Attendance

● Exam?

Organization

● Mondays: lectures or presentations

● Tuesdays: project consultations

– come to discuss your projects, for help in interpreting articles,accessing data, implementation and analysis

A fully funded PhD position is available at the University of Helsinki on computational methods for analysis of the global fossil record, ecological and climate data to better understand history of life, evolutionary processes and environmental change.

Apply via UH by October 31, 2017https://www.helsinki.fi/en/open-positions/doctoral-student-machine-learning-for-evolving-data

Master projects are welcome(contact me)

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Topics for machine learning

1) Chronofaunas

2) Ecometrics

3) Macroevolution

4) Phylogenetic regression

5) Phylogenetic trees

Chronofaunas:(mostly unsupervised learning)

Eronen et al 2009

tracking faunal communities over time


identifying chronofaunas

Bingahm and Mannila 2014


seriation - ranking of localities in time

Fortelius et al 2006 Puolamaki et al 2006

World today

Environment:TemperaturePrecipitationProductivitySeasonalityVegetation typeWoody cover...

Occurring animals:Species ASpecies BSpecies C...


Fossil sites1-5 million years old

Fossil sites20-30 million years old

......

......

Occurring animals:Species XSpecies YSpecies Z...


one observation/ learning instance

Ecometrics - analyzingecosystems of the present and the past

Estimates for the past, the Turkana basin


Age in MA Age in MA

Why animal traits predict climate?

http://www.vivo.colostate.edu/hbooks/pathphys/digestion/pregastric/horsepage.html

http://home.utah.edu/~u0230781/project/foresta/pages/moose_jpg.htm

https://www.etsy.com/au/listing/163309116/2-huge-genuine-moose-teeth-molars-alces

Grazing in open environments requires much more more tooth than browsing in a closed forest

http://www.vivo.colostate.edu/hbooks/

http://home.utah.edu/~u0230781/project/

https://www.etsy.com/au/listing/163309116

Features of animal teeth

Žliobaitė et al 2016

● Hypsodonty (HYP)

● Horizodonty (HOD)

● Presence of acute lophs (AL)

● Presence of obtuse lophs (OL)

● Structural fortification of cusps (SF)

● Occlusal topography (OT)

● Coronal cementum (CM)

Predicting climate from animal communities(concept drift, transfer learning)

Satellite observation data Model fit

Ecometrics:(mostly predictive modeling, transfer learning)

Liu et al 2012

predicting productivity of environment from animal teeth


Global regression, main traits

Advanced traits, focus on Africa

Ecometrics:(mostly predictive modeling, transfer learning)

Redescription minning –local relations between climate and dental traits

Galbrun et al in review

Galbrun et al in review

Macroevolution:(probabilistic modeling, maximum likelihood)

Analyzing tempo and mode of evolution

Voje 2016


Analyzing tempo and mode of evolution

Raia et al 2016


Estimating probabilities of occupancy

Foote 2016

Phylogenetic regression

Freckleton et al 2002 Felsenstein 1985

2017

Phylogeny - reconstructing the tree of life

Fitting phylogenetic trees

Baron et al 2017

Fossils and fossil databases

https://fineartamerica.com/featured/1846-richard-owen-and-moa-leg-fossil-paul-d-stewart.html

Richard Owen and MOA leg fossil, 1846

Wikimedia commons

Museums – catalogues – books – fossil databases

Recorded in global fossil databases, Including: taxonomic identification, fossil age, location, other characteristics

Imgage: http://www.helsinki.fi/science/now/ From Heck's Iconographic Encyclopedia (1851),http://users.dickinson.edu/~nicholsa/Romnat/fossils.htm

Sepkoski 1981

Fossils

Fossils are collected all over the world- depositional environment needs to be specialfor fossil preservation- dating / stratigraphy

Photo credit: Mikael Fortelius

Fossil data

Image: http://africanfossils.org/search

Described and catalogued- identification of species- measured traits- environmental context- 3D scans

NOW database (Helsinki)

http://www.helsinki.fi/science/now/

PDBD – Paleobiological database

https://paleobiodb.org

Slide credit: Laura Säilä

Fossil teeth

Slide credit: Laura Säilä

NOW database (Helsinki)

http://www.helsinki.fi/science/now/

machine learning methods for analysis of the global fossil record

Documents