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Abstract The harmful effects of mining waste on human and ecosystem health make reclamation of former mine sites an environmental management priority. However, field-based monitoring of reclamation requires significant investments of time, labor, and money. Remote sensing offers a less expensive alternative to field-based monitoring, but work is still needed to determine which metrics can be reliably estimated using remote sensing techniques. This study uses remote sensing to examine over 20 years of reclamation efforts at Tar Creek Superfund Site and to assess revegetation after site restoration. Using the Normalized Difference Vegetation Index (NDVI), we quantify key factors affecting vegetation recovery and stability after reclamation across 123 surface mining waste cleanup locations within Tar Creek. Leveraging long-term imagery from Landsat and high-resolution PlanetScope imagery, we combine time series analysis of vegetation regrowth and landcover change detection for a comprehensive picture of recovery at each site. Across all reclamation sites, the average recovery duration was 3.5 years, and average recovery rate was 0.1 NDVI year−1. After vegetative growth had plateaued, reclaimed sites had an average NDVI of 0.70. All reclamation areas were converted from majority barren landcover to vegetated landcover classes after reclamation, and vegetative stability at reclamation sites was high (70% of reclaimed area saw continuous vegetative cover from 2017 to 2023). These results demonstrate a strong potential for multi-method remote sensing techniques in tracking and explaining vegetation recovery after reclamation and represent a cost-effective approach for real-time monitoring of reclamation progress and outcomes.

Optimizing soil—crop—landscape occurrence is essential for sustainable intensification and food security, but little work has been done to evaluate these parameters on Tribal lands. The objective of this study was to develop first ever high-resolution crop suitability maps and compare two established crop suitability models for their ability to optimize soil resource management of the Quapaw Tribal lands. We built on previously developed continuous soil properties maps for 22,880 ha of Quapaw Tribal lands that used a digital elevation model and a fuzzy-logic based data mining approach to calculate and evaluate the Dideriksen and Storie crop suitability indices. Suitability index results were evaluated against observed yield (n ≥ 130,000) within the study area. Results showed that the observed yield was positively correlated with the Storie suitability index (Spearman rho = 0.16, p < 0.01), but not the Dideriksen index, suggesting the Storie index is more appropriate than the Dideriksen for modeling crop suitability in this area. Additionally, very little (

Mutations in RanBP2 (also known as Nup358), one of the main components of the cytoplasmic filaments of the nuclear pore complex, contribute to the overproduction of acute necrotizing encephalopathy (ANE1)-associated cytokines. Here we report that RanBP2 represses the translation of the interleukin 6 (IL6) mRNA, which encodes a cytokine that is aberrantly up-regulated in ANE1. Our data indicates that soon after its production, the IL6 messenger ribonucleoprotein (mRNP) recruits Argonautes bound to let-7 microRNA. After this mRNP is exported to the cytosol, RanBP2 sumoylates mRNP-associated Argonautes, thereby stabilizing them and enforcing mRNA silencing. Collectively, these results support a model whereby RanBP2 promotes an mRNP remodelling event that is critical for the miRNA-mediated suppression of clinically relevant mRNAs, such as IL6.