Guest Essay by Kip Hansen
The subject matter of the paper, examining the decline effect in the field of Ocean Acidification (OA), particularly in studies on the effects of OA on fish behavior, is itself interesting. I have written about OA and OA science many times here at WUWT.
There are two parts to this story about the decline effect. 1) The specific case of the decline effect in OA studies claimed in the Clements et al. paper. 2) The general case of the hypothesized causes of the decline effect in the sciences.
This essay will address the first issue: the decline effect in OA studies.
The decline effect in OA science:
As for the specific OA case, part of that story, featured in the Clements et al. paper, has been well-covered by Steve Milloy at JunkScience in his article “Climate fish scare turns out to be just a fish story”.
There are several obvious potential causes of a decline effect in a field. They are: publication bias, citation bias, methodological bias, and investigator effects.
As part of the review process of the new Clement et al. paper, each of those potential causes was investigated – and all but one were eliminated as a major cause. It is that last cause that I write about today.
The missing parts in Steve Milloy’s coverage are something that I have written about before and is left under-said Clements et al. (2022):
“….we additionally show that the large effect sizes and small within-group variances that have been reported in several previous studies are highly improbable. Together, our findings indicate that the reported effects of ocean acidification on the behaviour of coral reef fishes are not reproducible, suggesting that behavioural perturbations will not be a major consequence for coral reef fishes in high CO2 oceans.”
This was followed a year later with an article in Science:
This same Science article goes on to say:
“What few researchers know is that in August 2020, Clark and three others in the group took another, far bigger step: They asked three funders that together spent millions on Dixson’s and Munday’s work—the Australian Research Council (ARC), the U.S. National Science Foundation (NSF), and the U.S. National Institutes of Health (NIH)—to investigate possible fraud in 22 papers.”
“The request, which they shared with a Science reporter, rests on what they say is evidence of manipulation in publicly available raw data files for two papers, one published in Science, the other in Nature Climate Change, combined with remarkably large and “statistically impossible” effects from CO2 reported in many of the other papers. They also provided testimony from former members of the Dixson and Munday labs, some of whom monitored Dixson’s activities and concluded she made up data.“
NB: “Clark and three others in the group” in the above report are together the four authors of the decline effect paper under discussion in this essay.
Naturally, those funders asked to investigate cannot and will not discuss the matter until their investigations are completed and they are ready to issue a final report.
Clement et al. do not make accusations of fraud or any other scientific malfeasance in their latest paper but phrase their findings this way:
“It is important to note that the early studies published in 2009 to 2010 [8–10], and some subsequent papers from the same authors, have recently been questioned for their scientific validity . Indeed, these early studies have a large influence on the observed decline effect in our analysis. At the request of the editors, we thus explored the potential for investigator effects, as such effects have been reported to drive decline effects for the field of ecology and evolution in the past (e.g., fluctuating asymmetry )”.
When all papers authored or coauthored by at least one of the lead investigators of those early studies were removed from the dataset (n = 41 studies, 45%), the decline effect was no longer apparent from 2012 to 2019 (Fig 5). While conclusions regarding the potential roles of invalid data await further investigation , our results do suggest that investigator or lab group effects have contributed to the decline effect reported here.”
Citations [8-10] referred to in the text are as follows:
8. Munday PL, Dixson DL, Donelson JM, Jones GP, Pratchett MS, Devitsina GV, et al. Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proc Natl Acad Sci U S A. 2009; 106:1848–52. https://doi.org/10.1073/pnas.0809996106 PMID: 19188596
9. Dixson DL, Munday PL, Jones GP. Ocean acidification disrupts the innate ability of fish to detect predator olfactory cues. Ecol Lett. 2010; 13:68–75. https://doi.org/10.1111/j.1461-0248.2009.01400.x PMID: 19917053
10. Munday PL, Dixson DL, McCormick MI, Meekan M, Ferrari MCO, Chivers DP. Replenishment of fish populations is threatened by ocean acidification. Proc Natl Acad Sci U S A. 2010; 107:12930–4. https://doi.org/10.1073/pnas.1004519107 PMID: 20615968
31. Enserink M. Sea of doubts. Science. 2021; 372:560–5. https://doi.org/10.1126/science.372.6542.560 PMID: 33958459″
[the last paper cited as  is quoted in this essay above– kh]
The Bottom Line:
1. In the field of OA, nearly half (45%) of all studies suitable for use in the meta-study (or “systematic review”) of OA/fish behavior science were authored or co-authored by Philip Munday, DL Dixson, or other members of Munday’s or Dixson’s respective lab groups. (Note that Munday was Dixson’s PhD advisor.)
2. The three early papers from Munday and Dixson found very high effect levels on fish behavior from increased CO2/lowered ocean water pH and established expectations for a decade of subsequent follow-up research.
3. The Munday/Dixson early results led to wildly exaggerated adverse effects from OA being reported endlessly in the international media, and are still being used in climate reporting today, despite having failed replication and currently being investigated on suspicion of scientific malfeasance: fabrication, falsification, or other misconduct.
4. Refer to Jennifer Marohasy’s most recent post “Most Published Studies Exaggerated the Effects of Ocean Acidification – and Covid, Etc.” (or my earlier OA posts here at WUWT) for details on the other things OA research has gotten wrong.
5. This is a prime example of Investigator or Lab Group Effects; how a research field can be confused or corrupted when a research is confined to a handful of scientists related by shared authorship, working in the same lab, same working group, same department of the same agency, same academic department, or groups at several locations that all share data, methods and co-authorships. Labs, lab groups, academic departments and co-authors are extremely prone to sharing the same biases, political and world views, and tend towards enforced consensus building.
I will cover the other causes of the decline effect (and other ills of scientific research) in Part 2.
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The inevitable slight lowering of ocean surface water pH due to increasing atmospheric concentrations of CO2 may have some effect on something in ocean waters – for better or for worse. Properly done research by responsible scientists without axes to grind and agendas to push so far haven’t found any strong effects either way.
Bad science doesn’t always result in a decline effect situation. Sometimes it goes the other way. Bad results from prestigious sources start a field down path that leads to findings that are less and less grounded in reality until the field spins out of control. It can take decades for the science to correct itself.
The type of incestuous science exhibited in the OA/fish behavior field is found in many other fields as well. Sea level rise acceleration is one that comes to mind – centered at the Nerem’s CU-Boulder sea level group, which is closely associated with NASA’s satellite sea level altimetry group, and with the sea level group at Hawaii — these two prominent sources of SLR acceleration papers have led sea level research down a path to non-physical results – results that don’t show up in the Real World. The latest NOAA “2022 Sea Level Rise Technical Report” predicting a U.S. East Coast sea level rise of 1 foot by 2050 is a result of this.
Readers can supply other examples of fields, narrow and broad, that suffer from “Investigator effects” – fields in which the results depend chiefly on who is investigating, not on the realities of the physical world.
If not just leaving a general comment, please remember to state to whom you are speaking – for instance, if addressing me, please start your comment with something like “Kip, can you explain….?”
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