Increased adoption of best practices in ecological forecasting enables comparisons of forecastability across systems

2021 ◽  
Author(s):  
Abigail S. L. Lewis ◽  
Whitney M. Woelmer ◽  
Heather L. Wander ◽  
Dexter W. Howard ◽  
John W. Smith ◽  
...  
Keyword(s):  
Decision Support ◽  
Best Practices ◽  
Forecast Skill ◽  
Robust Analysis ◽  
Ecological Forecasting ◽  
Workflow Automation ◽  
Future Developments ◽  
Current State ◽  
Near Term ◽  
Over Time

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 ecological forecasting papers to understand the development and current state of near-term ecological forecasting literature and compare forecast skill across ecosystems and variables. Our results indicate 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, a number of 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 predictability across scales and variables. In this study, we found that forecast skill decreased in predictable patterns over 1–7 day forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in predictability, 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.

scholarly journals Workflow Automation in a Risk Management Framework for Pavement Maintenance Projects

2017 ◽  
Vol 12 (2) ◽  
pp. 155 ◽  
Author(s):  
Dan Bența ◽  
Lucia Rusu ◽  
Misu-Jan Manolescu
Keyword(s):  
Risk Management ◽  
Quality Control ◽  
Workflow Management ◽  
Process Automation ◽  
Management Framework ◽  
Pavement Maintenance ◽  
Workflow Automation ◽  
Road Pavement ◽  
Risk Management Framework ◽  
Solution Models

This paper presents a Workflow Management System (WfMS) for procurement process automation in road pavement maintenance and management. It fits information infrastructure for monitoring and maintenance of pavements and roads. Through the two roles of administrator and major users (builder and subcontractors), the solution models the entire process. This way, risks of exceeding allocated budget, time consuming tasks, overcoming deadline, and time consuming quality control, as main issues in risk management, are reduced and controlled.

Workflow Automation and Intelligent Control

2018 ◽  
pp. 149-195 ◽  
Author(s):  
Gustavo Carvajal ◽  
Marko Maucec ◽  
Stan Cullick
Keyword(s):  
Intelligent Control ◽  
Workflow Automation

Real-time Pore Pressure Modelling Workflow Automation

2017 ◽  
Author(s):  
A. Bartetzko ◽  
J.H. Figenschou ◽  
S. Schimschal ◽  
S. Wessling ◽  
T. Dahl
Keyword(s):  
Real Time ◽  
Pore Pressure ◽  
Workflow Automation

Workflow Automation for Cycling Systems

2019 ◽  
Vol 21 (4) ◽  
pp. 7-21 ◽  
Author(s):  
Hilary Oliver ◽  
Matthew Shin ◽  
David Matthews ◽  
Oliver Sanders ◽  
Sadie Bartholomew ◽  
...  
Keyword(s):  
Workflow Automation

Workflow automation for combined modeling of buildings and district energy systems

Energy ◽  
2016 ◽  
Vol 117 ◽  
pp. 478-484 ◽  
Author(s):  
Marcus Fuchs ◽  
Jens Teichmann ◽  
Moritz Lauster ◽  
Peter Remmen ◽  
Rita Streblow ◽  
...  
Keyword(s):  
Energy Systems ◽  
Workflow Automation ◽  
District Energy
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