Excellent!
04.03.2026 08:24
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Excellent!
Of course! I believe in the golden rule and I would be sad if people stopped talking about phytoplankton after 30 seconds.
I was once asked by a US immigration officer what I worked on. He tried to stop me soon after but that was clearly just him being polite. He really wanted to know about phytoplankton, I wasn't going to deny him.
Referendum proposal: governments must publish the DAGs underpinning all policy proposals.
Great - it's right up your alley! Would be fun to apply this to the spatiotemporal gradients and community data in the Baltic.
How does salinity affect growth?
@fryderheim.bsky.social & I developed a model to describe this, and he's parameterised it for >100 species. We can now model how salinity changes should affect population & community dynamics!
Check out his poster on Monday afternoon at #OSM26
We have many ideas for how to build on this, which we discuss in the preprint. I hope some of you will find inspiration for future projects in there!
Here's the link again:
www.biorxiv.org/content/10.6...
/end
This effort was led by Ting Lv, a then-Phd student who went from modelling satellite data to digging into experiments & field occurrences.
It was made possible by the excellent field data compilation & SDM work by our collaborators Fabio Benedetti, Dominic Eriksson, and @meikevogt.bsky.social.
8/n
Extrapolation will always be a concern. The future will see changes in environmental covariance. Species will evolve.
But my confidence in our ability to forecast responses to warming is now a little higher than before.
7/n
This is tremendously heartening!
Despite many sources of uncertainty and bias, there's still a reasonable match.
Even a single lab growth curve for a species is informative. And even a hundred occurrences lets SDMs learn something useful.
6/n
The growth niche width in the lab is positively associated with the occurrence niche width in the field. Occurrence niche width estimates are likely most reliable for unimodal curves, followed by monotonic and finally bimodal curves. The six bimodal curves (hollow squares) were therefore excluded from the regression.
Remarkably, there's even a modest association between the growth niche width and the occurrence niche width.
The latter is wider on average, possibly because our growth niche widths miss a lot of intraspecific variation.
5/n
Median growth temperature in the lab predicts median occurrence temperature in the field reasonably well across 39 marine phytoplankton species. The mean response (solid regression line) is close to the 1:1 line (dashed line). Median occurrence temperature estimates are likely most reliable for unimodal curves, followed by monotonic and finally bimodal curves. The six bimodal curves (hollow squares) were therefore excluded from the regression.
The 'median growth temperature' in the lab matches the 'median occurrence temperature' in the field reasonably well.
There's certainly scatter, especially at intermediate values. But the regression line is pretty close to 1:1.
4/n
The temperature-dependence of population growth rate estimated from lab experiments (top row) and of uncalibrated occurrence probability estimated from SDMs fitted to presence/pseudoabsence data (bottom row), for three marine phytoplankton species. These species are examples of the three shapes of occurrence probability curves that we manually classified curves into - monotonic, unimodal, and bimodal. We consider the few bimodal curves to be biologically unrealistic and exclude these species from our analyses. The vertical red lines show the median growth temperatures and median occurrence temperatures. The grey shaded regions indicated the growth niche widths and occurrence niche widths. For Trichodesmium erythraeum and Thalassiosira gravida, different growth curves (in black) correspond to different published experimental datasets, largely representing different strains. We overlay the envelope of the individual curves in blue and use this to calculate the indicated median growth temperature and growth niche width.
We compared thermal performance curves (TPCs) estimated from lab experiments and occurrence probability curves estimated with SDMs and a dataset of global occurrences.
We excluded a few occurrence curves that were bimodal, probably reflecting data/SDM limitations.
3/n
We need to forecast how warming will affect populations.
We use experiments or observations to model this. They have different pros & cons but have almost never been compared at scale - there are few taxa that we can both observe and experiment on easily.
We've now done this in phytoplankton.
2/n
New preprint out! 🌊🧪🌎 🧮➕📏
Temperature preferences estimated from lab experiments and species distribution models agree reasonably well!
This increases my confidence in our ability to forecast range shifts.
www.biorxiv.org/content/10.6...
1/n
Sian Henley and I have just had a NERC grant funded, looking at variation in Souther Ocean diatom traits under fluctuating light regimes. If you are a fearless experimentalist interested in working with us as a postdoc on this 3 year project, come chat with me at Ocean Sciences in Glasgow next week!
Department of Biological Sciences at the University of Bergen has a vacancy for a postdoctoral research fellow position within climate change ecology.
Work with @vvandvik.bsky.social and the @ipcc.bsky.social.
www.jobbnorge.no/en/available...
Screenshot of paper titled "Disentangling the effects of resource level and temperature dependence on the performance of fish in different guilds" with a first author named Bass Dye.
A paper on temperature effects on fish, written by Bass Dye. Nominative determinism strikes again!
(Interesting-looking paper too!)
"Flying squids [...] cover distances as long as 30 m above the surface of the water"
How have I never heard of these things?!
en.wikipedia.org/wiki/Japanes...
Phytoplankton empiricists: anyone have a good protocol (or reference) for treating fungal contamination in stock cultures without re-isolating? 2026 continues bringing all the icks...
This one, which shaped many of our lives:
www.newyorker.com/news/john-ca...
Alt link if that doesn't work: archive.ph/PtwWF
Done!
bsky.app/starter-pack...
bsky.app/starter-pack...
Thank you so much - that is very kind! All the best to you too.
My time in academia is at an end. I'm not sure what comes next, but what a privilege it's been getting to work with smart, idealistic, and kind people every day to understand our world a little better.
Happy to see our analysis on scaling up temperature x nutrient interactions from populations to communities published in Ecological Monographs @esajournals.bsky.social! 📈
How do temperature and resources interact to shape both population and community growth rates?
We have a model that makes predictions at both levels! And we test them with experimental data from the lab & field.
This one has been gestating for years and we're rather proud of it. Give it a read.
Looks like an exciting network!
There are so many interesting, important questions that we could address well with some more co-ordination.
Our data analysis guides for multiple stressor/driver research 🌊
@christinamcgraw.bsky.social
@sineadcollins.bsky.social
@mridulkthomas.bsky.social
@chrisecornwall.bsky.social
+ Peter Dillingham, Steeve Comeau, Sam Dupont
aslopubs.onlinelibrary.wiley.com/doi/10.1002/...