Pascal Polonik
@pascalpolonik.bsky.social
Postdoc at Stanford University’s Doerr School of Sustainability. Human-evironment interactions, climate, air quality, environmental equity, biking/transportation. Opinions my own.
We are crowd sourcing reductions in graduate admissions and hiring freezes across biomedical research and higher ed in response to pauses in NIH funding and EO’s. If you have information if you could add to this spreadsheet, it would be greatly appreciated!: docs.google.com/spreadsheets...
Graduate Reductions Across Biomedical Sciences (2025)
docs.google.com
February 24, 2025 at 7:35 PM
Many of these topics have been discussed previously, but we contextualize with tangible examples and suggest possible ways forward. This project has been a long time coming and was a huge learning experience for me. Many thanks to my coauthors/advisors for their help and patience.
February 12, 2025 at 8:41 PM
Many of these topics have been discussed previously, but we contextualize with tangible examples and suggest possible ways forward. This project has been a long time coming and was a huge learning experience for me. Many thanks to my coauthors/advisors for their help and patience.
Lastly, we argue that the mean climate is poorly represented when using fixed effects. We test a few examples of how mean climate could be better incorporated, but assuming adaptation yields entirely different projections. More work is necessary since this can completely change the interpretation
February 12, 2025 at 8:41 PM
Lastly, we argue that the mean climate is poorly represented when using fixed effects. We test a few examples of how mean climate could be better incorporated, but assuming adaptation yields entirely different projections. More work is necessary since this can completely change the interpretation
Depending on setup, we argue this may sometimes cancel out the benefit of using precip "as a control" for temp impacts. It's not always a huge effect, but it's worth keeping in mind! The impact of measurement error can be backed out if you know the error - precip impacts double in our GDP example
February 12, 2025 at 8:41 PM
Depending on setup, we argue this may sometimes cancel out the benefit of using precip "as a control" for temp impacts. It's not always a huge effect, but it's worth keeping in mind! The impact of measurement error can be backed out if you know the error - precip impacts double in our GDP example
We then set up an idealized multivariate model (with a known outcome) to demonstrate that uncertain variables can cause bias to estimated impacts of other (certain) variables. So, thanks to correlation, uncertain precip can cause bias in temp impact estimates even if temp is perfectly measured
February 12, 2025 at 8:41 PM
We then set up an idealized multivariate model (with a known outcome) to demonstrate that uncertain variables can cause bias to estimated impacts of other (certain) variables. So, thanks to correlation, uncertain precip can cause bias in temp impact estimates even if temp is perfectly measured
Relatedly, we discuss the role of aggregation to political boundaries. We point out that running the same model on different levels of aggregation yields very different results. Perhaps surprisingly, more granular estimates don't always yield higher impacts - for GDP it's the opposite!
February 12, 2025 at 8:41 PM
Relatedly, we discuss the role of aggregation to political boundaries. We point out that running the same model on different levels of aggregation yields very different results. Perhaps surprisingly, more granular estimates don't always yield higher impacts - for GDP it's the opposite!
We start by pointing out the different spatial scales of different environmental variables. That means we actually don't have great global datasets of precipitation (relative to temperature). Furthermore, surface measurement are declining and sparse in many parts of the world, which results in bias
February 12, 2025 at 8:41 PM
We start by pointing out the different spatial scales of different environmental variables. That means we actually don't have great global datasets of precipitation (relative to temperature). Furthermore, surface measurement are declining and sparse in many parts of the world, which results in bias
thanks for sharing, but I think you skipped an important part of the story, which is that they’re assuming - especially in the very optimistic scenario - a large amount of carbon capture to offset the continued extraction of fossil fuels. The required technology does not currently exist at scale.
February 12, 2025 at 6:55 PM
thanks for sharing, but I think you skipped an important part of the story, which is that they’re assuming - especially in the very optimistic scenario - a large amount of carbon capture to offset the continued extraction of fossil fuels. The required technology does not currently exist at scale.
Sources
www.aims.gov.au/sites/defaul...
www2.gbrmpa.gov.au/learn/threat...
amp.theguardian.com/environment/...
www.aims.gov.au/sites/defaul...
www2.gbrmpa.gov.au/learn/threat...
amp.theguardian.com/environment/...
www.aims.gov.au
November 22, 2024 at 1:21 AM