Welcome to the Northeastern Forest Regeneration Data Network!
Comparemethods and find data from forest regeneration projects across the Northeast.
Use this Network to:
Discover projects that fit your criteria
Browse projects based on our assessment of their suitability for specific analyses
Compare standardized project metadata and methods
Learn more about this tool here
More information on how to use this tool here
Project Analysis Key
Project suitability for specified analysis:
Comparability of project metrics and sampling schema to FIA:
H
M
L
Welcome to the Northeastern Forest Regeneration Data Network!
The goal of this database is to improve the discovery of and access to research and monitoring projects related to tree regeneration in the Northeastern US.
We have provided detailed and structured metadata to more easily compare projects as well as an expert assessment if an individual project can be used for specific analyses.
This Network provides the forest ecology community with improved access to regeneration data across the Northeast. In doing so, it
improves the potential for data integration through methods documentation and analytical processes for comparing datasets across programs.
As such, larger scale and compiled datasets can be used to evaluate pertinent questions about forest regeneration in the region.
We are appreciative of the participation of many researchers, scientists, and managers who have provided information related to their project, and to
Harvard Forest and Hubbard Brook Ecosystem Study for making well-documented data public. We appreciate the long-term funding from the
U.S. Department of Agriculture, Forest Service State & Private Forestry, Vermont Agency of Natural Resources and the University of Vermont.
How To Use This Resource
Use the Northeastern Forest Regeneration Data Network to search or browse for projects and datasets related to tree regeneration.
To locate projects you can use the filter (bottom left of map) to select specific attributes or fields of interest or browse by the list of projects
in the table. Explore and compare the methodology and potential uses for each project.
Only those projects that match your criteria will be listed in the table.
Expanding the project gives you more information, including: primary contact person, description, a link to the detailed project metadata, and a link to the FEMC Data
Archive page where you can explore the project in more detail. To see all analyses that were considered, expand the seedling or sapling section using the plus symbol in the upper right of the column title.
For each project, we have provided expert assessment of:
Whether the project is comparable to the USDA Forest Service Forest Inventory and Analysis (FIA) program. We rated similarity at three levels: high, medium, and low.
H
M
L
Whether the project can be used for key assessments related to regeneration:
Refer to the methods section for more detailed information on how each of these analyses were evaluated.
The project methods page allows you to access and compare detailed metadata and methods for specific projects, and can be accessed by clicking on a specific project title, or by selecting “Compare Programs” (top left of the table of projects).
Either option will allow you to explore and compare standardized methodology and metadata.
Up to three projects can be shown at once by selecting projects to the right. A pdf version of the metadata can be downloaded.
To cite the Northeastern Forest Regeneration Data Network in general, we suggest:
The Northeastern Forest Regeneration Data Network (Version 1.0). 2020. Forest Ecosystem Monitoring Cooperative. Available at: https://vmc.w3.uvm.edu/vmcdevel/forest_regen.
We have provided citations for each project, to cite an individual dataset or project, please refer to the corresponding FEMC archive project information page.
Methodology used to develop the Northeastern Forest Regeneration Data Network
The initial inventory of projects related to tree regeneration, herbivory, and/or tree seed production were collated based on cooperator suggestions,
professional contacts, known datasets, and search engine queries. Any project or dataset was considered for inclusion if it measured or assessed tree seedlings,
tree saplings, browse presence/absence or intensity on the regeneration layer, or mature tree seed or flower production. We included any relevant resources that
may have a methodology that could be adapted to another project. This work represents a first round of dataset gathering, with the potential to add other appropriate
projects in the future.
We developed a methods assessment framework to systematically evaluate each project included in this effort. In this framework, we catalogued the metadata, methods,
and metrics collected. The assessment table was designed so it can be applied easily to additional programs and can accommodate a range of project types, but at the
same time allow for easy comparison of projects and data analysis. Using the results of this methods assessment framework, we then assessed whether each project was
comparable to FIA, and the level of suitability for using the project to analyze a subset of characteristics of seedlings and saplings.
For each project, we assessed how easily it could be compared or integrated with FIA data. For each project, we ranked compatibility as
Low, Medium, or High. High compatibility was assigned if there were permanent plots that were assessed over multiple inventories and if
there were similar metrics to those in the FIA program. Medium compatibility was assigned if there was some similarity in metrics
assessed or if the project could be compared with one aspect of FIA data – for example, if the project only assessed eastern hemlock
regeneration, the project would only be compatible with FIA data for that one species. Low compatibility was assigned if the
data collected was not comparable to specific FIA data, but could be compared generally.
For each project we assessed whether there was sufficient information to analyze seedling or sapling:
biomass
browse impact
density
mortality
relationship with overstory trees
species composition
effects of treatment or management
For each one of these analyses, we evaluated if the project had sufficient information based on the required data needed for that analysis.
Analysis
Required metrics
Density
Species, count, plot size
Species Composition
Tallies by species
Mortality
Status (i.e. live and dead stems) or tracking of individual trees over time
Biomass
Diameter, height
Browse Impacts
Browse assessments
Change over time
Data collected at two or more distinct points in time
Effects of treatment or management
Data per treatment or management
Relationship with overstory trees
Overstory tree data collected in the same locations as regeneration data
If there was sufficient information for the specified analysis, the project was assigned ‘suitable’. If the project contained some of the information
required for the specified analysis, it was assigned ‘partially suitable’. This may mean that to complete the specified analysis, modeling or assumptions may be needed.
If the project did not contain the information needed for the specified analysis, it was assigned ‘unsuitable’.
Methodology used to develop the Northeastern Forest Regeneration Data Network
The initial inventory of projects related to tree regeneration, browse, and/or tree seed production were collated based on cooperator suggestions,
professional contacts, known datasets, and search engine queries. Any project or dataset was considered for inclusion if it had a component of tree seedlings,
tree saplings, browse presence/absence or intensity on the regeneration layer, or mature tree seed or flower production. We wanted to remain inclusive to all
relevant resources that may have a methodology that could be adapted to another project. This work is a first round of dataset gathering, leaving many other
appropriate projects to be added in a second version.
We developed a methods assessment framework to systematically evaluate each project included in this effort. In this framework,
we catalogued the metadata, methods, and metrics collected. The assessment table was designed so it can be applied easily to additional
programs and can accommodate a range of project types, but at the same time allow for easy comparison of projects and data analysis.
For each project, we assessed how easily it could be compared or integrated with FIA data. For each project, we ranked compatibility as
Low, Medium, or High. High compatibility was assigned if there were permanent plots that were assessed over multiple inventories and if
there were similar metrics to those in the FIA program. Medium compatibility was assigned if there was some similarity in metrics
assessed or if the project could be compared with one aspect of FIA data – for example, if the project only assessed eastern hemlock
regeneration, the project would only be compatible with FIA data for that one species. Low compatibility was assigned if the
data collected was not comparable to specific FIA data, but could be compared generally.
For each project we assessed whether there was sufficient information to analyze seedling or sapling:
biomass
browse impact
density
mortality
relationship with overstory trees
species composition
effects of treatment or management
For each one of these analyses, we evaluated if the project had sufficient information based on the required data needed for that analysis.
Analysis
Required Metrics
Density
Species, count, plot size
Species Composition
Tallies by species
Mortality
Status (i.e. live and dead stems) or tracking of individual trees over time
Biomass
Diameter, height
Browse Impacts
Browse assessments
Change over time
Data collected at two or more distinct points in time
Effects of treatment or management
Data per treatment or management
Relationship with overstory trees
Overstory tree data collected in the same locations as regeneration data
If there was sufficient information for the specified analysis, the project was assigned ‘suitable’. If the project contained some of the information
required for the specified analysis, it was assigned ‘partially suitable’. This may mean that to complete the specified analysis, modeling or assumptions may be needed.
If the project did not contain the information needed for the specified analysis, it was assigned ‘unsuitable’.