Browsing by Author "Hammond, Nicholas W."

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    A Decade of Cave Drip Hydrographs Shows Spatial and Temporal Variability in Epikarst Storage and Recharge to Appalachian Karst Systems
    Groce-Wright, Nigel C.; Benton, Joshua R.; Hammond, Nicholas W.; Schreiber, Madeline E. (MDPI, 2022-07-25)
    We conducted recession analyses on cave drip hydrographs from a 10-year record (2008–2018) of three drip monitoring stations within James Cave (Pulaski County, VA, USA) to examine differences in hydrologic characteristics of the epikarst and quantify the storage volume of the epikarst feeding the drips. We used two recession analysis methods (correlation and matching strip) to calculate recession coefficients for multiple hydrographs at each site. Results show subtle differences between the three drip sites, suggestive of spatial heterogeneity in permeability and storage in the overlying epikarst. Storage volume calculations show that during the recharge season, up to 95% of recharge through the epikarst to the cave occurs through rapid pathways (i.e., fractures), and 5% of recharge occurs through diffuse pathways (i.e., pores). However, during the recession period, recharge through rapid pathways in the epikarst decreases and occurs predominantly through diffuse flow. Combined, these results underscore the importance of documenting spatial and temporal characterization of drip rates and other recharge inputs into karst systems.
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    Increased adoption of best practices in ecological forecasting enables comparisons of forecastability
    Lewis, Abigail S. L.; Woelmer, Whitney M.; Wander, Heather L.; Howard, Dexter W.; Smith, John W.; McClure, Ryan P.; Lofton, Mary E.; Hammond, Nicholas W.; Corrigan, Rachel S.; Thomas, R. Quinn; Carey, Cayelan C. (Wiley, 2021-12-14)
    Near-term iterative forecasting is a powerful tool for ecological decision support and has the potential to transform our understanding of ecological predictability. However, to this point, there has been no cross-ecosystem analysis of near-term ecological forecasts, making it difficult to synthesize diverse research efforts and prioritize future developments for this emerging field. In this study, we analyzed 178 near-term (≤10-yr forecast horizon) ecological forecasting papers to understand the development and current state of near-term ecological forecasting literature and to compare forecast accuracy across scales and variables. Our results indicated that near-term ecological forecasting is widespread and growing: forecasts have been produced for sites on all seven continents and the rate of forecast publication is increasing over time. As forecast production has accelerated, some best practices have been proposed and application of these best practices is increasing. In particular, data publication, forecast archiving, and workflow automation have all increased significantly over time. However, adoption of proposed best practices remains low overall: for example, despite the fact that uncertainty is often cited as an essential component of an ecological forecast, only 45% of papers included uncertainty in their forecast outputs. As the use of these proposed best practices increases, near-term ecological forecasting has the potential to make significant contributions to our understanding of forecastability across scales and variables. In this study, we found that forecastability (defined here as realized forecast accuracy) decreased in predictable patterns over 1–7 d forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in forecastability, while more distantly related variables (i.e., pollen and evapotranspiration) exhibited significantly different patterns. Increasing use of proposed best practices in ecological forecasting will allow us to examine the forecastability of additional variables and timescales in the future, providing a robust analysis of the fundamental predictability of ecological variables.