A recent study in @nature couldn't replicate drastic CO2 effects on coral reef #fish behaviour & empirically found no effect of #oceanacidification go.nature.com/3hK49UR
Our #metaanalysis of the past decade on this topic concurs ecoevorxiv.org/k9dby/
Breakdown thread👇
We demonstrate one of the most striking examples of the #DeclineEffect in #ecology to date, w/ reported effects of OA on fish behaviour all but disappearing over past decade
If you’ve never heard of the #DeclineEffect see: bit.ly/2EbZX2o
Qualitatively the number of studies reporting “strong” effects of #oceanacidification on fish behaviour have plummeted over time
Quantitatively effect size magnitudes (log response ratio) have declined from averages of 3-4 in early pioneering studies to 0.2–0.4 over past 5 years
While highly significant in early years, mean effect size magnitudes have been non-significant from zero for 4 of past 5 years
To check if this #DeclineEffect was due to increasing studies on cold-water species, we removed cold-water studies (b/c these species may be more tolerant to OA than tropical coral reef species)
Nope…
But maybe OA only has an effect when some type of cue or stimulus is involved – after all, the biggest effects are with predator cues!
Again, nope…
OK, so if it’s not biological, then what could it be? Could it be… #BIAS!? 😱
We first checked for methodological bias
Underpowered studies are prone to Type I error & can often detect strong effects when they don’t actually exist
Do studies showing super-strong effects have low sample sizes?
Yep...
We also found that over time, avg n & proportion of studies w/ n>30 have increased
This suggests that the number of fish used in experiments partly explains the #DeclineEffect, but some high-n studies show strong effects, so n is not everything…
OK, but lots of fields have underpowered studies – what’s the harm?
Are studies w/ super-strong effects more likely to be published in influential high IF journals & thus get more attention?
….😬😬
Like sample size, we also saw that the average IF of journals publishing papers decreased over time
Note the strong blip in IF for 2014 which was accompanied by a similar blip in mean effect size for that year!
Strong evidence for selective publishing
This study provides strong evidence that dramatic reports of OA affecting fish behaviour are probably exaggerated &, frankly, false
The strong effects appear linked w/ methodological bias, selective publication of outstanding effects, and other unexplained phenomena
We suggest that OA-fish behaviour studies be given more weight when n>30 fish per treatment
It is imperative that authors REPORT SAMPLE SIZE PRECISELY!!!!
A massively frustrating part of this study was trying to decipher n – 34% of studies didn’t report it adequately!!
Reviewers & editors can also help here by being skeptical & critical of manuscripts reporting outstanding effects, especially those w/ n<30
We also strongly suggest that unbiased results be published early and alongside studies showing strong effects
How can we do this?
PRE-REGISTRATION!
go.nature.com/3c2Q43v
It’s also important for null results to be published in high IF journals so they are given equal public weighting
A scary anecdote w/ this paper: it’s been desk rejected by 5 high IF journals that previously published those extreme OA effects, each taking >1 month to decide…
Researchers should also incorporate best practices for behavioural studies whenever possible
for example, use published methodological guidelines such as bit.ly/2RAUghe & use automated technologies for recording behaviour if possible
Finally, be critical! Especially of early findings w/ large effects
Scientists are good at predicting which studies are likely to replicate & which ones won’t (see go.nature.com/3mtsCRK) – apply that skepticism early!!
Does #oceanacidification affect marine animals?
In many instances, yeah...
But in light of our results & those of the non-replication @nature study (go.nature.com/3hK49UR ), direct effects of OA on fish behaviour are likely small
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