RII Track-2 FEC: Leveraging Intelligent Informatics and Smart Data for Improved Understanding of Northern Forest Ecosystem Resiliency (INSPIRES)

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Forests are an economically important and ecologically critical component of Northern rural working landscapes. Local and regional communities depend on the health of these forest ecosystems to support biodiversity, conservation, recreation, and a forest-based workforce. Forests are highly dynamic and diverse due to a wide variety of complex interacting factors, including changing environmental conditions, varying management objectives across federal, state and private land ownership, and natural disturbances. Despite advances in technology and acquisition of forest-related information, critical forest data remains highly variable, inconsistently available, and relatively coarse in scale. The INSPIRES project will build a digital framework to better assess, understand, and forecast complex forest changes. The integration of emerging computational, monitoring, remote sensing, and visualization technologies into a Digital Forest Big Data framework will provide comprehensive, near real-time spatial and temporal measurements of the forest at levels readily usable by scientists, land managers, and policy makers. This project will strengthen workforce development and broaden participation in science, particularly among students with diverse backgrounds and skills. The project will accomplish both its digital and educational aims by drawing from a broad array of established programs and disciplines, including data science, ecology, electrical engineering, computer programming, and communications. This effort will help support and sustain northern New England's unique forested landscape, which many rural communities rely on for their livelihoods. Faculty and students will collaborate on the development of a regional Complex Systems Research Institute that will facilitate ongoing analysis of forest ecosystem integrity and resilience from multiple scientific perspectives. Ultimately this Big Data Framework integrating advanced sensing and computing technologies, environmental informatics and analytics, ecological modeling, and quantitative reasoning skills would be applicable to other forested regions and ecosystems. Forests in New England represent the Northern Forest ecotone, which is a complex assemblage of transitional ecosystems that have a unique history of natural disturbance and human land use. In recent decades, societal demands on these forests and the ecosystem services they provide have continued to expand at a time when key stressors such as land use pressures, invasive pests, and extreme abiotic events are on the rise. Maintaining the value and integrity of the Northern Forest for the communities that depend on them requires a better understanding of how these interactive stressors affect this ecosystem. Thus, a new digital framework for harnessing Big Data is needed to assess and predict interactions under multiple alternative future response pathways. To address this grand challenge, faculty from the state universities of Maine, New Hampshire, and Vermont will collaborate on the development of a regional Complex Systems Research Institute that will facilitate analysis of forest ecosystem integrity and resilience from multiple scientific perspectives. Faculty and students will work across four research-integrated themes to develop a novel and flexible Digital Forest Big Data framework for effectively harnessing complex data streams from a variety of sources such as wireless sensors, remote sensing, and citizen science to enhance our fundamental understanding of Northern Forest ecosystems across multiple spatio-temporal scales. The project?s specific research themes are: (1) Advanced Sensing and Computing Technologies; (2) Environmental Informatics and Analytics; (3) Integrated Ecological Modeling; and (4) Quantitative Reasoning in Context. In particular, project participants will explore how to integrate the traditional ecological knowledge (TEK) of Wabanaki tribes and other available qualitative data with the primarily quantitative data typically employed to analyze and model ecosystems. The long-term goal is to extend this framework beyond the region, particularly to other ecosystems of high interest, including marine environments. Importantly, the effort will link with ongoing regional efforts to improve K-20 data literacy skills, while generating valuable new approaches for supporting natural resources-based economies and associated industries. The formation of a regional Complex Systems Research Institute will incorporate, extend, and sustain the strengths of all three EPSCoR jurisdictions by leveraging prior and ongoing efforts and expertise.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.