1. Predicting Life History Traits for All Fishes: Proof of Concept and Next Steps
Rainer Froese
GEOMAR
Presentation at the FishBase Symposium
1 September 2015, Los Baños, Philippines

2. FishBase Data Content

3. Predicting LWR for All Fishes

4. Bayesian Inference on LWR
FishBase contains Phylogeny and body shape for all species
For species without published LWR estimates, LWRs of close relatives with same body shape are used for Bayesian predictions
This results in LWR predictions for all species of fish, with indication of uncertainty
Whenever new LWRs are entered, these predictions are updated (confidence limits become narrower)

5. FishBase Data Content

8. Proof of Concept
228 LWR published in JAI 31 were compared against Bayesian predictions:
69% point estimates fell within predicted range
85% were not significantly different
Most of the significantly different LWRs were actually questionable (small number of specimens, narrow length range, inclusion of early juveniles, other problems)
Thanks to Rudy Reyes for compilation of data and provision of example

9. Change in Body Shape between Juveniles and Adults
17 cm
Alectis indica
Solution: Estimate separate LWR
for juveniles and adults!
> 1 m

10. Improving Science
LWR studies submitted to JAI or ACTA are now routinely compared against predictions in FishBase
Significantly different LWR estimates are subjected to extra scrutiny
For example, if indeed body shape changes substantially during adult life (b > 3.5 or < 2.5), that should be visible when comparing photos of juveniles and adults

11. Bayesian Prediction of Growth
Growth is essentially described by two parameters, asymptotic length (L∞), and how fast that length is approached (K)
Phylogeny, maximum length, body shape, environmental temperature and activity level will be used to predict growth parameters for all species

12. Asymptotic length and maximum length are highly correlated
1:1

13. Influence of Temperature

14. Influence of Habitat or Life Style

15. Understanding Growth Space
tropical
pelagic
eel-like
bony fish
cold water
demersal
hagfish
subtropical
pelagic
fusiform
bony fish

16. Next steps Publish the “proof of concept” for LWR
Finalize and publish Bayesian growth
Predict mortality
Predict generation time
Predict resilience (intrinsic rate of population growth)

17. Big Question?
If we know growth for all fish, what “big question” shall be answered:
Do bony fish grow faster than sharks?
Do freshwater fish grow faster than marine fish?
Other big questions????

18. Thank You

19. Abstract
Predicting life history traits for all fishes: proof of concept and next steps
For 25 years we have compiled in FishBase key life history traits such as maximum size, growth, longevity, mortality, maturity, fecundity, or diet composition. The compilation reflects what is known, such as maximum length for most species, but mortality for only a few hundred species. Users of these data face three questions: 1) If many estimates of a trait are available for a species, which one shall be used or how shall all estimates be summarized? 2) If only one estimate is available, how representative is it? 3) If no estimate is available, what is the best guess? A rigorous statistical procedure to answer these questions is Bayesian inference, which has recently become practical through new software and fast computers. This technique allows the inclusion of related information, such as correlated traits or estimates from close relatives or previous general knowledge about the trait. We have already applied it to length-weight relationships (LWR), where body shape and LWR of close relatives was used to predict LWR for species without estimates. A meta-analysis showed that these predictions were, in most cases, not significantly different from subsequently published LWR estimates. We are now applying the technique to the prediction of growth parameters, based on maximum size, body shape, temperature, activity level, and estimates for close relatives. First results look very promising. Over the next three years, we plan to apply the approach also to maturity and mortality, aiming at the prediction of the intrinsic rate of population increase (= resilience) for all species of fishes.