1. TESTING THE QUALITY OF THE FOSSIL RECORD THROUGH GEOLOGICAL TIME ALEXANDER M. DUNHILL [alex.dunhill@bristol.ac.uk] SCHOOL OF EARTH SCIENCES, UNIVERSITY OF BRISTOL, U.K. 1

2. THE INCOMPLETENESS OF THE FOSSIL RECORD Sepkoski (1984) Is our knowledge of the fossil record good enough to tackle macroevolutionary questions? 2

3. A BIASED FOSSIL RECORD... Raup (1972) Raup (1976) Biodiversity in the fossil record is significantly influenced by sampling bias. Most research focusing on geologically driven biases and subsequent collecting biases. 3

4. ...OR COMMON CAUSE & REDUNDANCY COMMON-CAUSE: geological and fossil records covary as both driven simultaneously by a common environmental agent. 4 REDUNDANCY: sampling and paleodiversity correlate as they are not independent signals. Benton et al. (2011) from Fröbisch (2008) Hannisdal (2011)Peters & Heim (2011)

5. SAMPLING PROXIES “...metric that represents collecting effort in some way... should represent some or all of the geological and human factors that can introduce error into interpretations of data from the fossil record.” Benton et al. (2011). Outcrop area e.g. Smith & McGowan (2005, 2007), Wall et al. (2009, 2011), Marx (2009), Uhen & Pyenson (2007) etc. Formation Counts e.g. Peters & Foote (2001, 2002), Butler et al. (2009), Barrett et al. (2009), Benson et al. (2010, 2011) etc. Wall et al. (2009) Peters & Foote (2001) 5

6. SAMPLING PROXY PROBLEMS Wall et al. (2009) Sampling proxies are largely untested. Global or continental scale studies. Arguably vague sampling proxies (e.g. global geological maps) and crude estimations of paleodiversity. 6

7. GIS & REMOTE SENSING PRECISE SMALL-SCALE CASE STUDIES 7

8. 8 POSTER T163. Geologic Timescale (Posters) Hall B, Poster booth no. 280 Wednesday 7 th November, 2-4pm, 4.30-6pm

9. OUTCROP AREA = rock area that is displayed on a geological map. EXPOSURE AREA = rock area that is visible at the Earth’s surface. 9 TESTING SAMPLING PROXIES OUTCROP vs EXPOSURE Dunhill (2011, 2012)

10. TESTING SAMPLING PROXIES OUTCROP vs EXPOSURE Dunhill (2011, 2012) 10 CALIFORNIA NEW YORK AUSTRALIAUK

11. TESTING SAMPLING PROXIES DIFFERENT ASPECTS OF SAMPLING DO NOT CORRELATE Triassic-Jurassic UK; Dunhill et al. in review Proxies for different aspects of sampling DO NOT consistently correlate. Sampling proxy precision deteriorates when scaling up data. Singular sampling proxies should NOT be used to correct diversity curves. 11

12. SAMPLING PROXIES & PALEODIVERSITY INCONSISTENT CORRELATIONS Lower Jurassic SW UK; Dunhill et al. (2012) Sampling proxies and paleodiversity show limited to no correlation in small-scale studies. 12

13. 13 Triassic-Jurassic UK; Dunhill et al. in review Sampling proxies and paleodiversity correlate in marine systems, but not in terrestrial systems. SAMPLING PROXIES & PALEODIVERSITY INCONSISTENT CORRELATIONS

14. ACCURACY OF SAMPLING PROXIES FACIES DEPENDENCE Facies and lithology effects are more pronounced than rock volume effects (Triassic-Jurassic UK; Dunhill et al., in review) 14

15. VALIDITY OF SAMPLING PROXIES NON-INDEPENDENCE & MULTIVARIATE MODELLING Triassic-Jurassic UK; Dunhill et al., in review 15 Sampling proxies can predict paleodiversity when included in multivariate models. Sampling and facies effects are non-independent in their influence on paleodiversity. Complexity of biasing factors confirms that singular sampling proxies (i.e. outcrop area) should not be used to correct the fossil record.

16. CONCLUSIONS 1. Sampling proxies representing rock volume are not good representations of amount of rock available for sampling. 2. Proxies for different aspects of sampling do not share a common pattern. 3. Sampling proxies and paleodiversity do not consistently correlate across: (i)Different geographical and stratigraphical scales. (ii)Different facies. (iii)Different lithologies. 4. Multivariate models better predict paleodiversity – complex. The use of a singular sampling proxy to identify and correct for bias in the fossil record is poorly supported. 16

17. ACKNOWLEDGEMENTS Michael Benton (Bristol) Richard Twitchett (Plymouth) Andrew Newell (BGS) Bjarte Hannisdal (Bergen) Manabu Sakamoto (Bristol) Graeme Lloyd (Oxford) Felix Marx (Otago) Phil Donoghue (Bristol) Emily Rayfield (Bristol) Marcello Ruta (Bristol) Alistair McGowan (Glasgow) alex.dunhill@bristol.ac.uk @AlexDunhill 17

18. Correlation between sampling proxies (for rock volume) and paleodiversity only correlate once facies effects are removed. Triassic UK; Dunhill et al., in press 18 ACCURACY OF SAMPLING PROXIES FACIES DEPENDENCE

19. SAMPLING PROXIES & PALEODIVERSITY WORKER EFFORT – BIAS OR BONANZA? Triassic UK; Dunhill et al., in press Triassic-Jurassic UK: Dunhill et al., in review Lower Jurassic SW UK; Dunhill et al. (2012) Worker effort consistently correlates closely with paleodiversity – likely reflects intense sampling of know fossiliferous formations. 19

20. VALIDITY OF SAMPLING PROXIES REDUNDANCY & ERRONEOUS DATA Triassic-Jurassic UK; Dunhill et al., in review Fossiliferous formation counts (PaleoDB) correlate with paleodiversity. Fossiliferous formation counts from PaleoDB are incomplete and suffer from synonymous and incorrectly spelled entries. 20

21. CORRELATION ≠ CAUSATION Proxies correlate well with generic diversity. Information transfer identifies directionality of causal relationships (Hannisdal 2011). Outcrop areaGenera FormationsGenera CollectionsGenera Outcrop area can be used to predict generic diversity. Phanerozoic UK; Dunhill et al., in prep. 21