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To find long-term forest experiment data, search repositories and research networks that match your study design, then check each record’s time coverage, methods, variables, documentation, access terms, and citation requirements before using it. ForestGEO, the USDA Forest Service Research Data Archive, USGS and Data.gov records, Forest Research, and the LTER data portal serve different purposes; a catalog entry is a lead to evaluate, not proof that data are downloadable or suitable for your analysis.
Where to find long-term forest experiment data
There is no single catalog that covers every forest experiment. Start with the kind of evidence you need—such as repeated tree censuses, experimental treatment outcomes, or a particular region—and follow the route that best fits. Confirm the current record, files, and terms directly with the relevant repository.
ForestGEO: standardized forest plot censuses
ForestGEO’s Explore Data page helps identify plots and data available through its portal. The page reports that 30 of 78 sites host data in the portal; this is a snapshot accessed in 2026, not a permanent inventory. Data for other plots may need to be requested from the plot’s principal investigator. ForestGEO’s overview page reports 84 sites in 29 countries, representing 7 million trees and 12,000 species; these network figures can change, so check the current overview.
ForestGEO offers resources including field and data protocols, a data model, data-entry software, and a guide. Site pages can help narrow candidates by ecological zone and number of censuses. The network’s shared protocols support cross-plot comparisons, but they do not establish that every site has the same variables, measurement history, or usable cadence.
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USDA Forest Service Research Data Archive: research data publications
The USDA Forest Service Research Data Archive publishes and preserves short- and long-term research data from Forest Service Research and Development, the Joint Fire Science Program, and the Aldo Leopold Wilderness Research Institute. Its collection includes data from Experimental Forests and Ranges. Each archived data publication includes at least one dataset, complete metadata, and researcher-provided supporting documentation; the data file may be hosted in another archive, so follow the record’s data link.
USGS and Data.gov: inspect individual catalog records
A useful example is the public USGS catalog record “Long-term Experimental Forest Growth and Drought Data.” The record describes a compilation of multi-decadal growth across eight U.S. experimental forests with replicated density treatments and a drought index. Growth is treatment-level annual basal area increment (BAI, mm²/year); drought severity is represented by the self-calibrated Palmer Drought Severity Index (scPDSI). The record lists John B. Bradford as contact, reports the dataset as public, and gives an update date of 2020-08-14. Its catalog entry was last checked on 2026-08-01; verify the current record and files before relying on them. These eight forests describe this compilation’s scope, not the total number of experimental forests.
Forest Research: identify UK long-term experiments
Forest Research’s long-term experiments project concerns conserving silviculture and genetics field experiments so they can be revisited for sustainable forest management questions. Its aims include maintaining sites and records, supporting collaboration, and advancing long-term forest science. Use the project page to identify relevant work; it is not itself a catalog of downloadable datasets.
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LTER: ecological data packages and citation guidance
The LTER data portal describes ecological data packages contributed by past and present network sites. It provides dataset DOIs to facilitate citation and advises users to review the data policy and consult metadata and providers to avoid misinterpretation. Check the current portal location, record metadata, and policy for the specific package.
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ForestGEO distinguishes between public data and records that require investigator approval. Follow the portal’s data-access workflow for the selected plot and data type:
- Choose a data type, then select a region and plot.
- Read the applicable terms and conditions before requesting or downloading data.
- Submit the request with a project description, planned analyses, and a description of the data needed.
- For non-public data, wait for the plot investigator to approve or reject the request. For public data, the portal says it sends login and download information automatically.
Do not assume a plot’s information is openly downloadable just because it appears in the portal. If essential methods or use conditions are unclear, contact the investigator or data provider before analysis.
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How to evaluate whether a forest dataset fits your research
Evaluate the record against the question you plan to answer. A long time span alone does not make a dataset appropriate: the design, sampling cadence, variables, and measurement methods must capture the process you want to study.
Check the study design and scale
Determine whether the record describes a manipulative experiment or observational monitoring. Check the treatment structure, forest type, geographic setting, and spatial scale. A treatment comparison and a record of natural change can support different inferences; neither should be treated as a substitute for the other.
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Find the start and end dates, identify missing periods, and confirm how often measurements were taken. ForestGEO’s digital resources page describes tree censuses every five years at its sites, with some sites also conducting specialized surveys. Verify the cadence for the particular plot. A five-year census may be inadequate for annual or event-scale questions unless paired with other data.
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Check variables, units, and methods
Confirm variable definitions, units, treatment levels, taxonomic conventions, and field protocols. Look for method changes over time, which can create discontinuities that resemble ecological change. For multi-site work, compare the actual protocols and available variables for every selected record rather than assuming a shared network protocol guarantees identical data.
Read metadata and supporting documentation
Read the full metadata, methods, and documentation before downloading or requesting data. The Forest Service archive says its data publications include complete metadata and researcher-provided documentation. LTER specifically warns that failing to consult metadata or data providers can lead to misinterpretation. Resolve unclear definitions and missing context with the responsible investigator or provider.
Confirm access and reuse conditions
Check whether files are public, require a request, or carry plot-specific terms. Access to a catalog page does not imply unrestricted reuse. Follow the record’s use conditions and obtain required approval before analysis or redistribution.
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Keep provenance and citation details
Retain the dataset title, authors or investigators, repository, version or update date, DOI or other persistent identifier, and the date you accessed it. Use the repository’s citation instructions; LTER provides dataset DOIs for citation. Keep these details with your analysis so that the exact data version can be identified later.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can you compare data from different forest plots?
Yes, when the records are comparable for the specific question—but not merely because both concern forests or come from the same network. ForestGEO’s shared protocols are designed to support comparisons, yet each plot’s variables, measurement history, cadence, and documentation still need review. Comparisons across other sources require the same scrutiny.
Assess candidate records along these dimensions:
- Geography and forest type: Are the sites ecologically relevant to the question, and is the geographic contrast intentional?
- Design: Are the records both experimental, both observational, or being compared across different designs for a defensible reason?
- Time coverage and interval: Do dates, gaps, and sampling cadence allow the same process or period to be compared?
- Variables and protocols: Do definitions, units, treatment levels, and measurement methods align, or can differences be handled transparently?
- Access and documentation: Can the records be used under their terms, and is there enough metadata to interpret them consistently?
No universal quality score establishes which repository or plot is best. Choose based on fit to the research question and explain any protocol or coverage differences that affect interpretation.
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