Search for: All records

Abstract The Unlearning Racism in Geosciences (URGE) program guides groups of geoscientists as they draft, implement, and assess anti‐racist policies and resources for their workplace. Some participating Geoscientists of Color (GoC) shared concerns about microaggression, tokenism, and power struggles within their groups. These reports led us to collect and analyze data that describe the experiences of GoC in URGE. The data are from five discussion groups and two surveys. Our analyses revealed that participating GoC want to continue working with White colleagues on anti‐racist work. GoC want White colleagues not to shy away from doing anti‐racist work. Instead, GoC want White colleagues (a) to create and adhere to robust behavioral codes of conduct, (b) to focus discussions on anti‐racism, (c) to act on anti‐racism initiatives, (d) not to prompt GoC to educate them or reveal trauma, and (e) to refrain from microaggressions and tokenism. These desired outcomes were achieved in some groups with varying degrees of success. Correcting a history of mistrust relating to racism and anti‐racism action is key to implementing and assessing effective anti‐racist policies and resources. This requires leadership support, following through on anti‐racism action, and deepening relationships between GoC and White colleagues. Future anti‐racist programs should spend a substantial amount of time on and demonstrate the importance of training participants how to discuss racism effectively and how to create and adhere to robust behavioral codes of conduct. Future programs should also explore developing a robust program‐wide code of conduct that includes a policy for reporting offenses. 

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg Soil Survey Laboratory MIR spectral library. Overall, MIR-based estimates of SOC%, with samples scanned on a secondary instrument, were excellent with the root mean square error ranging from 0.10 to 0.33% across the seven sites. In all but two instances, the same statistically significant (p < 0.10) management effect was found using both the lab-based SOC% and MIR estimated SOC% data. Despite some additional uncertainty, primarily in the form of bias, these results suggest that large existing MIR spectral libraries can be operationalized in other laboratories for successful carbon monitoring.