Skip to main content
NC State Home
CNR Internal Resources

Research in Focus: June 2026 Funding Highlights

August 11, 2026
Lightbulb Icon Image - College of Natural Resources Internal Resources NC State University

Faculty in the College of Natural Resources are advancing innovation through cutting-edge research that addresses critical environmental and natural resources challenges.

Each month, faculty secure funding from federal and state agencies as well as nongovernmental organizations, supporting initiatives in ecological restoration, biodiversity conservation and more.

This report highlights the grants awarded in June 2026, showcasing projects that advance scientific understanding and deliver real-world solutions.

Click on the projects listed below to learn more:

Advancing Software Capacity for the Statistical Analysis of AI-processed Ecological Data

  • PI: Jeffrey Doser
  • Direct Sponsor Name: National Science Foundation
  • Awarded Amount: $431,987 

Abstract: Automated sensors (e.g., camera traps, acoustic recording units) in tandem with artificial intelligence (AI) classification algorithms have revolutionized the ability to generate insights into wildlife and plant species across space and time. However, there exists no software to fit state-of-the-art statistical models required to account for the complexities of remote sensing data and AI classification errors. Without open-source software to fit these models, ecologists resort to using simpler frameworks that are at best drastically inefficient and at worst lead to inaccurate conclusions and misinformed policy and management recommendations. To address this crucial gap, we propose updating a set of three R packages (unmarked, spOccupancy and spAbundance) collectively called the Ecoverse with new functionality and workflows. Building on the existing Ecoverse codebase, we will develop functionality for three new model classes that enable researchers to estimate abundance and distributions of wildlife and plant communities while uniquely addressing complexities from ecological sensor data processed with AI. New false positive occupancy and abundance models will account for inherent false positive errors that arise from AI classification algorithms, improving the reliability of ecological inferences for individual species and multi-species communities. New coupled classification models will allow users to more efficiently estimate species distributions and abundance by directly incorporating the continuous output from AI classification algorithms. Functionality for continuous-time occupancy models will provide the ability to answer questions about species interactions and diel activity patterns that are not possible with standard models implemented in discrete time. Given the barriers many novice software users face when performing complex data analyses, we will then create comprehensive Ecoverse workflows from data preparation to statistical analysis interpretation for data processed with three common AI platforms: BirdNet, SonoBat and Wildlife Insights.

Quantifying and Partitioning Uncertainty in the Artificial Intelligence/Machine Learning (AI/ML) Models

  • PI: Chris Jones
  • Direct Sponsor Name: U.S. Department of Energy
  • Awarded Amount: $8,800

Abstract: I will pursue research in uncertainty quantification and partitioning with application to machine learning and AI models, specifically zoonotic disease risk models, through the DGRP fellowship. The focus of this work will be on leveraging existing techniques and methods in uncertainty analysis to apply to models being developed at PNNL.

Evaluation of Lampshade Traps for Spotted Lanternfly Detection and Population Monitoring in the Carolinas

  • PI: Kelly Oten
  • Direct Sponsor Name: Animal and Plant Health Inspection Service
  • Awarded Amount: $28,487 

Abstract: Spotted lanternfly is a destructive invasive pest found rapidly spreading and recently detected in South and North Carolina. This project implements a novel trap type to detect this pest in new areas across the Carolinas. 

Grower Considerations for Spotted Lanternfly in Fraser Fir Plantations

  • PI: Kelly Oten
  • Direct Sponsor Name: Animal and Plant Health Inspection Service
  • Awarded Amount: $73,892 

Abstract: This project will assess the risks associated with the presence of spotted lanternfly in and around Fraser fir plantations in western North Carolina. Surveys for preferred spotted lanternfly host trees in field edges and measurements of field edge gaps will be conducted in the mountains of North Carolina. Five to 10 surveys will be conducted, Locations will be based on participation by growers, but efforts will focus on Caldwell, Ashe and Avery Counties. Feeding trials and pesticide trials will be conducted in Wake County, North Carolina. Field-collected egg masses with be hatched in enclosures with access to Fraser fir and tree-of-heaven seedlings. Mortality of spotted lanternfly nymphs and seedlings will be monitored. A second trial of Fraser fir seedlings treated with common prophylactic pesticide treatments will be conducted to evaluate their effectiveness against spotted lanternfly. Lampshade trapping on wooden posts will be conducted at three infested sites in Forsyth County to determine movement of spotted lanternfly into and across empty fields seeking egg laying substrate.

Advancing Biological Control and Breeding EAB-Resistant Ash to Safeguard North Carolina Forests

  • PI: Kelly Oten
  • Direct Sponsor Name: Animal and Plant Health Inspection Service
  • Awarded Amount: $163,913 

Abstract: The long-term goal of our project is to advance biological control in the south and cultivate EAB-resistant ash nursery stock.

Elm Zigzag Sawfly Management

  • PI: Kelly Oten
  • Direct Sponsor Name: Animal and Plant Health Inspection Service
  • Awarded Amount: $100,312 

Abstract: North Carolina State University will conduct targeted research to improve mitigation tools and reduce spread risks of the invasive elm zigzag sawfly (Aproceros leucopoda). This project focuses on testing systemic insecticides in nursery production systems, evaluating pest impacts on pupal development in treated soil and collecting data to inform pesticide residual guidance for long-term management. This work directly supports Goals 4 and 6 of the PPA 7721 Implementation Plan.

An Improved Understanding of the Interplay Between Bedrock Properties and Forest Resilience in the Rocky Mountains

  • PI: Matthias Sprenger
  • Direct Sponsor Name: Lawrence Berkeley National Laboratory – University of California, Berkeley
  • Awarded Amount: $89,053 

Abstract: The Watershed Function SFA at Lawrence Berkeley National Laboratory aims to understand how ecosystems adapt to meteorological and environmental stressors based on their inherent traits, thereby simplifying the complexity of mountainous landscapes into key principles that guide ecosystem responses to disturbance. There remains a critical knowledge gap as to how disturbance-induced trait redistribution, following drought, insect infestation, or forest management, impacts ecosystem structure, hydrology and biogeochemical cycling.

Research Focus Area 1 (RFA1) of the project aims to understand how ongoing temperature-driven changes in water-energy balance across elevations impact watershed hydrological, ecological and biogeochemical functions. RFA1 seeks to identify mechanisms and trait-to-function relationships that explain functional responses and resilience to recent past disturbances. One focus is on the interplay between bedrock properties and forest resilience (RFA 1.2), which uses a combination of tree core sampling, remote sensing and biogeochemical and microbial sampling to understand spatial and temporal variation of forest health in response to drought.

Micro-Grafted Disease-Resistant Fraser Fir

  • PI: Justin Whitehill
  • Direct Sponsor Name: North Carolina Department of Agriculture, New and Emerging Crops Program
  • Awarded Amount: $100,000 

Abstract: We plan to request funds to accelerate tissue culture efforts of momi fir for use in commercialization of grafted PRR resistant Fraser fir.