Welcome to today's #GlobalScienceShow as part of #FUTURES2020

From now until 6pm GMT we have a new researcher every 20 minutes ready to share their work with you!

What's going on? Check out the schedule below for info on all presenters!

First up at 12.20pm is @JessieW_Palaeo

All presenters will post content to their Twitter account highlighted in the schedule above. We'll then retweet in the thread below!

You can also check out everything going on by following the hashtag #GlobalScienceshow
A strong opening to the day discussing fossils, climate and theres even A QUIZ.

If you know me, then you know I LOVE A QUIZ!!!

#FUTURES2020

https://t.co/jB6sEmP5H3
Here's a screenshot of Jessie's quiz, if you would like to try and match the pollen to the plant!

@JessieW_Palaeo #FUTURES2020
I am genuinely smiling so much. Penguins (and specifically Gentoo's) are my favourite animal.

It's so exciting that three new species of Gentoo penguins were recently discovered 🐧🐧🐧

#FUTURES2020

https://t.co/AFOqapN8oS
https://t.co/mYLWfzTX86
Underwater robots gliding through lakes in the dark sounds like it could be part of a horror movie

But in reality, these amazing machines could help us monitor bodies of water much more efficiently

https://t.co/5bqkx57HLj
https://t.co/mcOpfePFp5

More from Science

Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).

Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.


You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.

The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.

In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.

The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
Ever since @JesseJenkins and colleagues work on a zero carbon US and this work by @DrChrisClack and colleagues on incorporating DER, I've been having the following set of thoughts about how to reduce the risk of failure in a US clean energy buildout. Bottom line is much more DER.


Typically, when we see zero-carbon electricity coupled to electrification of transport and buildings, implicitly standing behind that is totally unprecedented buildout of the transmission system. The team from Princeton's modeling work has this in spades for example.

But that, more even than the new generation required, runs straight into a thicket/woodchipper of environmental laws and public objections that currently (and for the last 50y) limit new transmission in the US. We built most transmission prior to the advent of environmental law.

So what these studies are really (implicitly) saying is that NEPA, CEQA, ESA, §404 permitting, eminent domain law, etc, - and the public and democratic objections that drive them - will have to change in order to accommodate the necessary transmission buildout.

I live in a D supermajority state that has, for at least the last 20 years, been in the midst of a housing crisis that creates punishing impacts for people's lives in the here-and-now and is arguably mostly caused by the same issues that create the transmission bottlenecks.

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