i-Tree Pest Detection (IPED)
Urban areas are frequently the first site of introduction for exotic pests, where they remain undetected until populations are well established and have had harmful impacts on the health of host trees. Many communities routinely complete and update tree inventories, but often overlook pest invasions because pest detection tools are not part of the inventory process. There are also no processes in place for aggregating pest inventory data into a standardized form, which would allow communities to analyze pest trends that are otherwise difficult to detect across geographic or political boundaries.
The goal of the i-Tree Pest Detection Development Team is to develop, disseminate, implement, and establish an accepted, modern protocol for long-term national urban pest detection and monitoring
Benefits of Pest Detection
- Increase and broaden efforts to detect exotic pests.
- Increase awareness of the need for routine tree health assessments.
- Provide a standardized method for integrating pest detection with urban forest management.
- Improve opportunities to control pests while invasions are still manageable.
- Reduce unchecked movement of pests across geographic and political boundaries.
- Reduce costs for long-term tree management, removal, and replacement.
- Provide a tool for integrating pest detection with more innovative, technologically advanced tree inventory and assessment tools.
Pest Detection Integration in i-Tree
i-Tree was created to develop, disseminate, support and refine urban forest analysis tools and will be utilized as a platform for Pest Detection delivery. The release of i-Tree v5.0 includes the pest detection protocol as an optional module within the i-Tree Streets and Eco applications. See Vendor section below for information for Pest Detection external integration.
The Pest Detection module in i-Tree Streets and Eco provides:
- A portable, accessible and standardized method of observing a tree for possible insect or disease problems.
i-Tree Streets and Eco integrated field data collection and desktop reporting:
- Pest Reporting example
- Pest Report Menu
- Primary Pest Summary
- Primary Pest Details
- Pest Sign Symptom Overview
- Pest Sign Symptom Details
- Pest Review
- Pest Review (2)
Pest Detection Resources:
- Extensive user support through a Wiki online Pest Detection resources site, integration with established pest identification and reporting networks, and training.
- Online Pest Detection Key to further investigate symptom & sign combinations to help identify potential issues Pest Detection Key examples
- i-Tree Pest Detection Field Guide 38.7MB
- i-Tree Pest Detection Field Guide - Printer Friendly Version 2.81MB
- Pest Detection Field Data Entry Tip Sheet
- i-Tree Pest Tatum Guide
- Excel 2003 / Excel 2007 Pest Detection Workbook - Spreadsheets designed for the collection of pest detection protocol information.
- Pest and Host Matrix - The complete list of pests used by the pest detection protocol.
- Pest Detection Matrix - Signs and symptoms associated with the pests in the pest detection protocol.
Pest Detection Training
Four archived 60-minute online sessions offered by the Urban Natural Resources Institute (UNRI) focusing on the Pest Detection module.
- An Introduction to Pest Detection
- Project Planning & Set-up
- Pests, Signs & Symptoms
- Interpreting & Reporting Results
Pest Detection Future Developments
- A national database repository that will enable pest specialists to access regional pest data to query for pest detection anomalies and trends at multiple scales.
One goal is to make the Pest Detection Protocol accessible to vendors and other interested parties. XML is employed to accomplish this. Extensible Markup Language is similar to the language of the web, HTML (HyperText Markup Language). However, XML is designed to carry data and it is recommended by the World Wide Web Consortium. XML structures, stores, and transmits data. Refer to: w3schools.com website for more background on XML.
The Pest Detection (and i-Tree Streets) XML schema definitions provided below are geared towards software developers. They can use the XML schema to integrate Pest Detection data collection fields into their applications. Also, developers may wish to engineer their applications to output their related Pest and/or i-Tree Streets data in a format that adheres to the XML schemas specified here. This will provide straightforward compatibility between their application and i-Tree.
- Pest Detection XML Schema Definition - Standardized XML Schema for specifying Pest data in XML format.
- Dynamic Matrix Pest List - Source of the dynamically updated pest list for use by the pest detection XML Transformation Sheet.
- Pest Detection XML Transformation Sheet - Transformation file used to translate an XML file that adheres to Pest Detection XML Schema Definition into an HTML table format. This can be used to produce a web viewable version of the XML. Requires the Dynamic IPED Matrix Pest List
- Pest Detection XML Sample - A sample XML document that adheres to the Pest XML Schema Definition and utilizes the Pest XML Tranformation Sheet to produce a HTML viewable table based version of it.
- i-Tree Streets XML Schema Definition - Standardized XML Schema for specifying an i-Tree Streets inventory in XML form. Requires the Pest Detection XML Schema Definition
- i-Tree Streets XML Transformation Sheet - Transformation file used to translate an XML file that adheres to the i-Tree Streets XML Schema Definition into an HTML table format. This can be used to produce a web viewable version of the XML. Requires the Pest Detection XML Transformation Sheet
- i-Tree Streets XML Sample - A sample i-Tree Streets inventory in XML format that adheres to the i-Tree Streets XML Schema Definition and utilizes the i-Tree Streets XML Transformation Sheet to produce a HTML viewable table based version of it.
A project planning and development team is working to move this effort forward. Team subgroups are focusing on pest signs and symptoms, i-Tree integration and programming, pilot community involvement, research database development, and online resources. The team includes employees of several U.S. Department of Agriculture agencies, including the Animal and Plant Health Inspection Service, and the Forest Service Northern Research Station and the Northeastern Area State and Private Forestry's Urban and Community Forestry and Forest Health Protection Programs. Other team members represent the Society of Municipal Arborists, The Davey Institute, the University of Georgia Bugwood Network, Cornell University, National Plant Diagnostic Network, Purdue University, University of California, Davis, University of Florida, University of Maryland, University of Vermont and the Vermont Department of Forests, Parks, and Recreation. The USDA Forest Service manages the project planning team.