Comprehensive framework for assessing and optimizing existing research networks.

Area of Science:

• Ecological research infrastructure
• Conservation science
• Environmental monitoring networks

Background:

• Conservation and ecological research rely on networks of research sites, but many developed opportunistically, limiting regional conservation insights.
• Existing networks may not systematically represent diverse environmental conditions, hindering comprehensive regional analysis.

Purpose of the Study:

• To develop and demonstrate a framework for evaluating the representativeness of existing ecological research networks.
• To create an approach for prioritizing sites for strategic expansion to optimize conservation impact and scientific inference.

Main Methods:

• Developed a framework assessing environmental representativeness, geographic coverage, and scientific inference adequacy.
• Applied the framework to the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN).
• Ranked candidate sites for expansion based on their potential to improve network performance.

Main Results:

• The EFRN effectively represents high-biomass forests nationally (82% of forest biomass well-represented).
• Significant gaps in coverage exist in regions like Texas, Florida, the Rocky Mountains, and the West Coast, limiting regional inferences.
• Adding top-ranked expansion sites can significantly improve national coverage of underrepresented areas.

Conclusions:

• A quantitative framework can guide strategic decision-making for optimizing conservation and monitoring networks.
• Balancing local and global priorities is crucial when expanding networks, as regional improvements may not always yield national benefits.
• This approach offers a scalable solution for enhancing the impact of limited monitoring resources in ecological research worldwide.