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Hi Professor David Fox and your team,
The webinar is really amazing! It is what I was looking to learn as I need to use the SSD for my research.
Thanks to my supervisor who recommended the webinar to me!
Perhaps, I will have some more questions for the team through emails afterward.
Many thanks to Professor David and your team!
Best regards,
Thi Huyen Nguyen (Emily)
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Thanks for the very informative SSD Session, I have two follow up questions:
- It was very informative with David’s comments on bimodal distribution, I have (perhaps wrongly) assumed when we see some bimodal distribution in DTA SSDs it was likely due to different species (or species types) being more or less sensitive to than the others to different contaminants present or some be more sensitive to the additive/ synergistic effects of the mixture. This is probably a lot more complex than most of my clients want to get into though.
- Additionally, regarding concentration response data analysis I am interested in looking at alternative stat packages for deriving our statistical endpoints (ECx values) for our toxicity data. We like a few other labs are reliant on Toxcalc. I know its limitations especially as really has no updates and support with it reliant on excel 2003 to run the plugin. I have looked at CETUS but again not sure about ongoing support and it was more difficult to use than ToxCalc for our purposes. It would be great to have a nice plug and play stat package (perhaps as a R based package like BurrliOZ is?) as a replacement for ToxCalc for us that are not good with statistics and don’t know how to properly use R, but are good at running bioassays.
Many thanks,
Tristan Stringer
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Hi Tristan. Thanks for your participation in the webinar and your questions. First, a point of clarification: In response to your question during the webinar about mixtures, I said that SSDs were usually used to derive HC/PC values for single toxicants. While this is the usual application of SSDs, I do acknowledge that they are also used for deriving GVs for mixtures of chemicals (eg. whole effluent toxicity testing) in which case ‘concentration’ is in fact a dilution and thus bounded between 0 and 100%. Although there’s nothing to stop you from fitting an SSD to this proportion data, there is a disconnect between the fact that the SSD models we use are invariably on the range (o,Inf). We (the SSD tools development team) had some discussion around this point following the webinar in which we discussed the use of the beta distribution as an obvious candidate for data measured as %dilution rather than an absolute concentration. Joe Thorley suggested that ssdtools was not currently set up to handle such bounded data. My suggestion, which we’ll pursue further, and requires no modification to exisiting software, is to transform the %diltion data first using: Y = X/(1 – X) where X is the diltion data (on the scale 0 to 1). The resulting Y values are then on the range (0, Inf) and thus conformable with ‘regular’ concnetration data and SSD models. Once the SSD model(s) have been fitted and inference made on Y, we back-transform using X = Y/(1 + Y) to make inference on the original scale.
The second point I wish to make with respect to SSD modelling for mixtures of toxicants is the implicit, but very strong assumption that the chemical composition of the effluent is spatially and temporally invariant. This is a big ask and almost certainly untrue. How do effectively deal with this situation (short of repeating the SSD modelling at regular times and places) is an open question and one we perhaps should also turn our attention to.
Finally, with respect to a ‘turnkey’ software replacement for CETIS/Toxcalc – we’re currently working on new developments in this space – for example, the R package Bayesnec developed by a team including Rebecca and myself, is publicly available on the CRAN website. Furthermore, we recently published a paper in ET&C which introduced the No Significant Effect Concentration (NSEC) and a further publication in IEAM will appear soon. Our challenge now is to integrate these and other aspects of contemporary CR modelling under one unified system/package and, like ssdtools, develop a user-friendly shiny web deployment. This is all food for thought and obviously someone needs to bankroll the task!
Cheers,
David
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Hi David,
Thank you for the response.
I’m glad that you have some solutions available that will make using % dilution data in SSDs a lot more robust. While I do understand the basics of the transformation of the data, I will need to have a play with some dummy data to see how I go.
My next question is that when transforming % dilution data and using SSDTools, are we likely going to see a big change in SSD results, compared to just plugging in the % dilution data in to BurrliOZ which is the standard practice is now? This could be quite important with comparison of new data analyzed with the new methods in SSDtools to historical data. Especially in cases where the existing discharge mixing zones are based on SSD data from BurrloOZ.
Myself and my clients (especially the environmental consults) are doing SSDs on almost every DTA project that we do (as well as data from other labs) so the more guidance the better. Especially as currently the ANZG (2018) has no guidance on how to best do SSDs on % dilution DTA data, so we have had to default to the Warne et al. (2018) method. The obvious limitation is that this method was designed for a single toxicant not DTA data.
I would not be surprised that the if outside of the academic and WQG /ANZG application the most common use of BurrliOZ is on DTA data. (Though I may have a biased view as we don’t see a lot of single toxicant work). So, the more guidance we have on using the new methodologies in SSDTools the better.
Your point about the frequency of testing effluents due to the inherent variation is very true. This is obviously governed by the individual regulators which regulate the discharge. There is a lot of variation on how this is done through different frequencies of screening tests and “whole suite” (8 species) testing but perhaps there should be more attention to this in the future of the ANZG. I also think that this is where engagement with the regulators is important, especially when new methods are being developed. This would help with a better understanding on all sides of how to best implement DTA data.
Finally, about a turnkey software package, this is great news, obviously funding is always a limitation but if it helps, I will gladly pay a subscription fee to be able to use such a software package!
Many thanks and look forward to more discussion at SETAC.
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