Current Projects

The Cooperative Forestry Research Unit works with our members to identify research needs and gaps on a yearly basis. We collaborate with researchers at UMaine and beyond to help address applied research questions through a yearly request for proposal process. Awarded funds and projects are typically 2-3 years in length and focus on our main research categories: silviculture, forest health, growth and yield/remote sensing, and wildlife & biodiversity. You can find more information on the projects we’re currently supporting by exploring the categories below.

Maine Adaptive Silviculture Network

MASN or Maine Adaptive Silviculture Network was established in 2017 with the goal of creating operational scale (>20 acres) research areas where the effects of harvesting methods could be studied and followed over time. Data collected on MASN sites can help inform questions on:

  • Cost and efficiencies of different harvesting systems
  • Regeneration and site productivity
  • The effects of harvesting systems on wildlife
  • Remote sensing, testing Enhanced Forest Inventories

MASN sites are measured every 5-10 years and measurements include: overstory, saplings, regeneration and coarse woody debris. For more information, including data sets and research questions, you can view our ArcGIS StoryMap and reach out to cfru@maine.edu

Northern Conifer Silviculture Guide

Researcher: Laura Kenefic, Research Forester, USFS Northern Research Station

Conifer (softwood) dominated forests are common in the northeastern United States and they are highly valuable both economically and ecologically. The United States Forest Service (USFS) publishes silvicultural guides to help inform sustainable management of our nations forest and the Northern Conifer Silviculture Guide was outdated. More than two dozen experts collaborated to review available literature, unpublished experiment data and practitioner experience to co-produce and updated version of this guide.

The guide has been completed and is awaiting publication by the USFS.

Mixedwood Management: Silviculture for Hardwood–Softwood Mixtures in Maine

Researcher: Laura Kenefic, Research Forester, USFS Northern Research Station

Mixedwoods (hardwood–softwood mixtures) present management opportunities and challenges. While there has been a lot of research on boreal mixedwoods, there is less information about temperate mixedwoods like those in Maine. Previous research on mixedwood stands has shown potential for reduced susceptibility to insects and diseases as well as increased market flexibility, carbon sequestration, climate resiliency, and wildlife habitat diversity. While desired, these stands can be difficult to maintain or are inconsistent with landowner goals.

A diverse team of experts are working together to synthesize Forest Inventory and Analysis (FIA) and Maine Adaptive Silviculture Network (MASN) data to analyze trends in harvested and unharvested mixedwood stands. The analyzed data, along with input from experts and practitioners, will be used to create a silviculture management guide with forest-type-specific sections. The final guide will be sent to the USFS for review and publishing.

Silvicultural Systems for Adaptive Planted Spruce Forests (SSAPSF)

Researcher: Mike Premer, Assistant Professor of Forest Management, University of Maine

This project aims to assess differences in commodity production, aboveground C (carbon) sequestration and storage, and soil nutrient status, under a variety of silvicultural treatments in planted white spruce forests when compared with naturally regenerated forests. An experimental network of 12 new research installations established across Maine has been installed to collect baseline measurements of pre-treatment conditions, artificial and natural regeneration dynamics, and site variables. Collectively, this project provides the foundation for continued, long-term measurements and monitoring of causal mechanisms of spruce productivity. Findings from this work can be used to generate predictive, geo-referenced maps of potential vegetative productivity and limiting growth factors. These tools can be used by foresters and landowners to assess the biological, financial, and ecological viability of planted white spruce forests on a site-specific basis to meet a variety of objectives and goals.

Secrets in the CTRN: Causal factors of thinning response and transfer to adaptive management regimes in Maine spruce-fir forests

Researcher: Mike Premer, Assistant Professor of Forest Management, University of Maine

Secrets in the Commercial Thinning Research Network (CTRN), builds of decades of long-term data collected by the CFRU. CTRN follows the effects of timing and intensity of tree-thinning in Maine’s commercial forests. This project seeks build off existing data sets and newly collected isotope tree cores to better understand the influence of site conditions on thinning response, a current gap in our applied understanding of the CTRN. More information on this project and the Maine Forest Management Lab can be found on Mike’s website.

Harmonized MASN Inventory Database: Curate, Analyze and Model Inventory Datasets for MASN

Researcher: Libin Thaikkattil-Louis, University of Maine Fort Kent

Long-term research projects provide unique opportunities to ask and answer questions, especially in the context of forests which are long-lived and often take years or decades to fully respond to a stimulus. However, managing data associated with long-term research projects can prove quite difficult due to the number of different people conducting research and adding in new data. This project aims to build a database where all new data related to the MASN project can be organized, housed and easily shared with researchers and cooperators alike.

Spruce Budworm L2 monitoring program in Maine

Researcher: Angela Mech, Associate Professor of Forest Entomology, Spruce Budworm Lab Director, University of Maine

The Spruce Budworm Lab opened its doors in 2021 with support from the CFRU to monitor SBW populations. To predict SBW populations for the following year, tree branch samples are collected in the fall and submitted to the UMaine Spruce Budworm Lab. The Lab processes the branch samples and counts the overwintering stage of SBW, better known as an L2. L2 data is important for monitoring SBW activity and growing populations. Research has found that 7+ L2s per branch, per sample site, indicates that SBW populations have passed a threshold where natural enemies (parasites, pathogens, weather) can no longer keep populations low and stable. CFRU members help monitor spruce budworm populations across Maine and beyond. Population maps are regularly updated and can be found on sprucebudwormmaine.org.

Understanding white pine’s responses to future environmental changes: Developing strategies to reduce damage caused by the white pine weevil

Researcher: Bill Livingston, Associate Professor of Forest Resources, University of Maine

White pine weevil (WPW) is the most serious insect pest of white pine in Maine. WPW feeding often kills the main stem of the tree, eventually leading to poor tree form. Despite this insect’s prevalence, little is known about how climactic differences across Eastern white pine’s (Pinus strobus L.) growing region impacts growth and survival of WPW. This study aims to connect environmental factors to weevil damage on white pine by utilizing FIA data for the region, as well as field studies conducted by the research team across the region. Ultimately, this project will create a model to predict occurrence and prevalence of WPW in Maine. Risk maps produced by the team will predict low hazard locations for weevil damage and may help inform where white pine regeneration and plantations may be best suited for establishment.

Maine High Resolution Land Cover and Forest Type Data for the State of Maine

Researcher: Kasey Legaard, Research Assistant Professor, Geospatial Analytics and Machine Learning, University of Maine

Good forest management relies on accurate understanding of our forests, especially their species composition. While determining a forest type on the ground is a simple process, high quality remotely sensed estimates of forest type are more difficult. Along with producing 1-meter resolution land cover maps consistent with NOAA’s Costal Change and Analysis Program (C-CAP), this project will also produce 5- or 10-meter forest type maps. Approximately 15 forest types will be represented and will cover the state of Maine. Robust estimates of species composition can help with carbon accounting, habitat management and stand delineation.

Refining the Acadian Model

Researcher: Ben Rice, Midgard Natural Resources

Growth and yield models are an important tool for foresters as they help to project forest growth into the future. The USFS maintains the Forest Vegetation Simulator (FVS) which is a growth and yield model that contains regional variants to help account for geographical differences in tree species and growth conditions. The Acadian variant was developed for the extent of the Acadian forest (northern Connecticut and New York through New Brunswick and Novia Scotia) in an effort to better estimate this unique forest within the northeastern US that was historically projected using the Northeast variant of FVS. This project is working to update equations used to estimate tree growth based on recent FIA data.

NAIP EFI: Investigating the use of new 3-D canopy surface model data from the National Agricultural Imagery Program for developing Enhanced Forest Inventories in Maine

Researcher: Tony Guay & David Sandilands, Remote Sensing Specialists, Wheatland Geospatial Laboratory, University of Maine

Enhanced Forest Inventories (EFIs) employ remotely sensed data, typically from Light Detection and Ranging (LiDAR), to estimate forest attributes such as volume or softwood percent. However, LiDAR is expensive to collect so this project aims to use the 3-D photo-based point cloud data from the National Agricultural Imagery Program (NAIP) to create EFIs. NAIP imagery and the associated point clouds are free, publicly accessible data sets which could make EFIs a more affordable option if they prove to be as accurate as the LiDAR-derived EFIs. This project will compare estimates from LiDAR-derived EFIs and NAIP-derived EFIs to test the accuracy of the NAIP-derived EFIs.

Using eDNA for biodiversity and rare species monitoring

Researcher: Noah Charney, Assistant Professor of Conservation Biology, University of Maine

Over the past decade, there has been exponential growth in the use of environmental DNA (eDNA) for biodiversity and rare species monitoring. In the coming years, landowners will be increasingly confronted with decisions around the use and interpretation of eDNA in forest management. As an emerging technology, there are many questions around potential limitations and pitfalls of this approach and prior to widespread application in any system, eDNA requires testing and validation. This study aims to establish protocols for using eDNA in Maine’s forested wetlands, to examine the potential for false positives and false negatives, and to synthesize the state of knowledge for managers.

Birds as indicators of forest management sustainability in Maine: an evaluation of past surveys and future assessment approaches

Researcher: Amber Roth, Associate Professor of Forest Wildlife Management, University of Maine

Line-transect bird surveys have been conducted on Maine Adaptive Silviculture Network sites since 2017, pre-and-post experimental harvest. These surveys have provided the CFRU with baseline data on species, but are labor intensive and provide brief snapshots in time when the birder is on site, typically once or twice a season. This project utilizes autonomous recording units (ARUs) to record bird vocalizations on MASN sites for post-processing analysis. This alternative survey approach requires less bird identification expertise and creates an opportunity for improved year-to-year consistency of species identification.

Movement Ecology of Wood Turtles (Glyptemys insculpta) in Maine’s Working Forests

Researcher: Matthew Chatfield, Assistant Professor of Evolution and Eco-Health, School of Biology and Ecology, University of Maine

The wood turtle (Glyptemys insculpta) is a Species of Greatest Conservation Need in the most recent version of the State’s Wildlife Action Plan and is currently listed on the U.S. Endangered Species Act. The working forests of northern Maine are thought to support relatively intact populations that may be critical to the long-term persistence of the species. The goal of this project is to provide a detailed understanding of movement patterns and habitat selection of wood turtles on Maine’s forestry lands. Conserving this species relies on cooperation between foresters and researchers to help create a well-informed and evidence-based approach to improve forest management practices for this species.