Datasets and code to create figures and conduct statistical analysis for paper in final revisions/published at Earth's Future (Paper #2025EF006463)..csv spreadsheet shows CMIP6 models (only those downscaled as part of STAR-ESDM used in the NCA5) assessed in the manuscript and the years when each of the historical + ssp585 scenarios global-mean 2-m air temperature anomalies reach various Global Warming Levels-- further methods outlined in Methods section of the manuscript.conus_heat_data.zip contains zipped netcdf (nc) files used to create figures and conduct statistical analysis. Zipped files can be unzipped (total directory size when unzipped is ~116Gb).Link to Github where ipynb files contain Python code to create figures and run analysis of data:Figure_1 creates maps shown in Figure 1Figure_2 creates violion plots shown in Figure 2Figure_3_4_5 has two versions (35C and 39C)- the 35C version creates the subplot/figure panels for the 35C threshold, and the 39C version creates the subplot/figure panels for the 39C threshold.environment_conus_heat.yml file contains modules needed to create a conda environment to run the Python code.

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This package contains replication files for all results in "Latent Heterogeneity in the Marginal Propensity to Consume," by Daniel Lewis, Davide Melcangi, and Laura Pilossoph, to be published in the Review of Economic Studies.

This package contains replication files for all results in "Latent Heterogeneity in the Marginal Propensity to Consume," by Daniel Lewis, Davide Melcangi, and Laura Pilossoph, to be published in the Review of Economic Studies.

Protein was isolated from human stool from individual living with Parkinson's disease (PD), inflammatory bowel disease (IBD), or neurologically healthy controls (NHC) samples using MSD lysis buffer (MSD; R60TX-3), 1 tablet complete protease inhibitor (Roche) and 5 mm stainless steel bead (Qiagen). After solids were removed by separating protein supernatant, protein concentration was determined via BCA Protein Assay Kit (Pierce), according to manufacturer instruction. Duplicates of stool (25ul) were diluted 1:1 and used to quantify chemokine and cytokines via U-PLEX custom pro-inflammatory human panel (Eotaxin, Eotaxin-3, IFN-γ, IL-1β, IL-6, IL-8, CCL22 (MDC), TNF-α (MSD#; K15067M-1) and R-PLEX human ferritin (MSD#; F21ADA-3) on the Quickplex MSD instrument, according to the manufacturer’s protocol.

Protein was isolated from human stool from individual living with Parkinson's disease (PD), inflammatory bowel disease (IBD), or neurologically healthy controls (NHC) samples using MSD lysis buffer (MSD; R60TX-3), 1 tablet complete protease inhibitor (Roche) and 5 mm stainless steel bead (Qiagen). After solids were removed by separating protein supernatant, protein concentration was determined via BCA Protein Assay Kit (Pierce), according to manufacturer instruction. Duplicates of stool (25ul) were diluted 1:1 and used to quantify chemokine and cytokines via U-PLEX custom pro-inflammatory human panel (Eotaxin, Eotaxin-3, IFN-γ, IL-1β, IL-6, IL-8, CCL22 (MDC), TNF-α (MSD#; K15067M-1) and R-PLEX human ferritin (MSD#; F21ADA-3) on the Quickplex MSD instrument, according to the manufacturer’s protocol.

Duplicates of plasma from individuals living with Parkinson's disease (PD), inflammatory bowel disease (IBD), or neurologically healthy controls (NHC) (25ul) were diluted 1:1 and used to quantify chemokine and cytokines via U-PLEX custom pro-inflammatory human panel (Eotaxin, Eotaxin-3, IFN-γ, IL-1β, IL-6, IL-8, CCL22 (MDC), TNF-α (MSD#; K15067M-1) and R-PLEX human ferritin (MSD#; F21ADA-3) on the Quickplex MSD instrument, according to the manufacturer’s protocol.

Duplicates of plasma from individuals living with Parkinson's disease (PD), inflammatory bowel disease (IBD), or neurologically healthy controls (NHC) (25ul) were diluted 1:1 and used to quantify chemokine and cytokines via U-PLEX custom pro-inflammatory human panel (Eotaxin, Eotaxin-3, IFN-γ, IL-1β, IL-6, IL-8, CCL22 (MDC), TNF-α (MSD#; K15067M-1) and R-PLEX human ferritin (MSD#; F21ADA-3) on the Quickplex MSD instrument, according to the manufacturer’s protocol.

Multi-species sensory networks, where different species prioritize different sensory modalities and then use heterospecific information in a likely non-cooperative fashion, may allow animals to improve foraging over large areas for cryptic prey. We test this hypothesis in procellariiform seabirds that forage in mixed flocks, where both prey odors and visual cues provided by other foraging hetero- and con-specifics might improve success rates. Using agent-based models, we explored the impact of social strategies on olfactory foraging for Antarctic krill (Euphausia superba). Our results suggest that social foraging enables species with different sensory adaptations to achieve similar success rates. Additionally, our results indicate that foraging is more successful in mixed-species rather than single-species flocks, where individuals can monitor the activity of other birds that are using different sensory foraging strategies than themselves to find prey. These results suggest that sensory-based foraging networks may be more critical to their survival than previously assumed. Finally, we show that success rates decrease at low population densities. As seabird populations continue to decline, understanding and preserving these social foraging networks may be essential for their conservation and ecological success. Overall, our study provides insights into the critical role of multi-species sensory networks for foraging success, wherein different species have different sensory adaptations for locating prey. While we used empirical anatomical and behavioral data specific to procellariiforms to inform our models, our approach and results may have broader implications for other species as well.