How to use SLF Dashboard
Spotted lanternfly (Lycorma delicatula; 'SLF') is an invasive Asian planthopper that was first discovered in the US in Berks County, PA in 2014. It feeds on many plant species and causes economic damage to vineyards, orchards, the hardwood industry, and more. This dashboard houses SLF resources from different sources in one location. These include web applications, management resources, and citizen science opportunities.
Main Categories
Applications on the dashboard are displayed by app type: Forecasts, Past-Spread, High-Risk-Areas, and Resources.
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These applications provide predictive models and tools to forecast the spread or phenology of SLF.
Examples include Growth Rate Forecast, Forecasted Hosts, and County Spread Forecast
Forecasts
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These applications contain historical data and visualization tools that show the past spread of SLF over time. Researchers can analyze past movements to identify trends and patterns.
Examples include lydemapr R package and U.S. Invasion Timeseries Maps
Past-Spread
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Applications in this category identify areas at high risk of spreading SLF.
Examples include High Risk Properties, Global Invasion Risk Map, and Transport Risk
High-Risk-Areas
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These applications include additional educational materials, management guides, and citizen science tools to support SLF awareness and control efforts. It's a valuable resource for researchers, land managers, and the general public.
Examples include Citizen Science Reporting Tool, Citizen Science Survey- New York, and Management Information
Resources
App Description
Each app contains a 'Description' button. Apps marked with the Temple 'T' logo includes sections such as the: Description, How to Use the App, Interpretation, Accuracy, Assumptions, and Citation. Apps that are not marked with the Temple 'T' logo are encouraged to view the app's website for more detailed information. To go back to the homepage, please click on the 'Back' Button, located above the app's image.
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This section outlines the purpose of the app and what it aims to achieve or display. It typically explains the main function or goal of the app, such as modeling, calculating, or visualizing specific data.
Description
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This section provides instructions on how to interact with the app's interface, including controls, menus, sliders, or other features. It explains the steps users need to take to customize or view the app’s outputs based on their interests or scenarios.
How to Use the App
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This section explains how to understand the app's outputs or results. It often highlights what the results mean in the context of the data being analyzed and provides insights into the significance of the displayed information.
Interpretation
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This section discusses the limitations or reliability of the results, including factors like the data sources, assumptions, or external conditions that may affect accuracy. It provides context for understanding potential errors or biases in the outputs.
Accuracy
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This section details the underlying assumptions or conditions that the app is based on. It may include the scope, data averaging, or other simplifications made during model development.
Assumptions
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This section provides the reference for the app or its data sources. It typically includes how users should cite the app in their work.