Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.https://pubs.er.usgs.gov/publication/ofr2020107

Using the Spinal Cord Injury Common Data Elements

International Spinal Cord Injury (SCI) Data Sets include core, basic, and extended data sets. To date, 13 data sets have been published on the Web site of the International Spinal Cord Injury Society (ISCoS; www.iscos.org.uk), and several more are forthcoming. The data sets are constituted of data elements, which may be appropriate to use in trials conducted to test novel therapeutic candidates including neuroprotective drugs, various cell types, and rehabilitative strategies and devices. The National Institute of Neurological Disorders and Stroke (NINDS), the National Institutes of Health (NIH), embarked on a Common Data Element (CDE) Project 5 years ago. The mission of the NINDS CDE Project is to develop data standards for clinical research. The NINDS CDE team has since developed variable names and database structures for the International SCI Data Sets (ie, the SCI CDEs; http://www.commondataelements.ninds.nih.gov/SCI.aspx). Dataset variable names and database structure are exemplified with the International SCI Core Data Set and the International SCI Cardiovascular Function Basic Data Set. The consistency of the data sets and the CDE format may improve the ability to transfer critical medical information electronically from one center to another. The goals of the SCI CDE initiative are to increase the efficiency and effectiveness of clinical research studies and clinical treatment, increase data quality, facilitate data sharing, and help educate new clinical investigators. Pilot testing the SCI CDEs is an important step to ensure the SCI CDE effort achieves its goals