This csv contains spatio-temporal predictions for the year of white-nose syndrome/Pseudogymnoascus destructans in support of the manuscript "Gaussian process forecasts Pseudogymnoascus destructans will cover coterminous United States by 2030." Gaussian process models were fitted to monitoring data on the spread of white-nose syndrome in North America from 2007-2022. These models are used to make predictions on a fine spatial grid, giving a forecast (and hindcast) of the spread of white-nose syndrome at any location. The code relies on the GRTS grid for model prediction, which is publicly accessible at https://doi.org/10.5066/p9o75ydv.

For estimating the distribution of the target human dose for magnitude of effect M and human incidence I (abbreviated “HDMI”) in the Approximate Probabilistic Analysis (APROBA) software tool, using the default assumptions in APROBA (primary analysis) and specific case adjustments (sensitivity analyses): 1) Confidence limits of the HDMI components that were input in APROBA for each analysis, and the confidence limits for the estimated HDMI distributions that were output, along with some supplementary calculations on the outputs. Also included for each analysis are the percents contribution of the HDMI components to HDMI uncertainty. 2) Results of Bayesian model averaging dose-response analysis of incidence of nasal lesions in the lateral wall at level II, used for the sensitivity analysis in which dose-response modeling was used to determine the point of departure. 3) Parameters of the HDMI distribution for varying values of human incidence I. This dataset is associated with the following publication: Blessinger, T., A. Davis, W. Chiu, J. Stanek, G. Woodall, J. Gift, K. Thayer, and D. Bussard. Application of a Unified Probabilistic Framework to the Dose-Response Assessment of Acrolein. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 143: 105953, (2020).

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Washington, United States Of America. The time period coverage is from 503 to -30 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.