Coordination Between the Forest Inventory and Analysis (FIA) Program and the National Agricultural Statistics Service (NASS) within the USDA
1.0 Introduction
The United States Department of Agriculture (USDA) houses a diverse array of agencies, each with specific mandates contributing to the nation's agriculture, forestry, and land management sectors. Among these are the Forest Inventory and Analysis (FIA) program, primarily managed by the USDA Forest Service, and the National Agricultural Statistics Service (NASS). The FIA program is tasked with monitoring the nation's forest resources 1, while NASS serves as the primary statistical agency for U.S. agriculture, providing comprehensive data on a wide range of farming and ranching activities.3
Effective coordination between these two entities is crucial for a holistic understanding of land use, resource management, and environmental conditions across the American landscape, where agricultural and forested lands often interface and interact. This report aims to describe the nature and extent of coordination between FIA and NASS, examining direct collaborative mechanisms, instances of indirect data integration, specific areas of joint interest, challenges encountered, and the potential benefits of enhanced collaboration. The analysis draws upon publicly available information regarding the missions, operations, and collaborative projects of both FIA and NASS.
2.0 Overview of the Forest Inventory and Analysis (FIA) Program
2.1 Mission and Scope
The Forest Inventory and Analysis (FIA) Program of the USDA Forest Service has a long-standing mission to "make and keep current a comprehensive inventory and analysis of the present and prospective conditions of and requirements for the renewable resources of the forest and rangelands of the US".2 Its core purpose is to measure and monitor key metrics related to the extent, condition, and trends of all forests in the United States.1 This involves the regular remeasurement of approximately 355,000 permanent inventory plots distributed across the nation, complemented by remote sensing applications.1 The program delivers a robust forest census, providing vital statistics, analyses, and reports crucial for long-term strategic planning, forecasting forest conditions, and understanding sustainability.1 The FIA program has been in continuous operation since 1930.2
2.2 Data Collected
FIA collects a consistent core set of ecological data at the plot level across all land uses and ownership categories.5 This includes detailed information such as tree quantity and species identification, downed woody materials, tree regeneration, forest type, ownership, site attributes, tree size, and overall tree condition.5 Data are also collected on land use and land cover characteristics for all plots, with some nonforest plots measured remotely using aerial imagery.5 The program is also expanding to include urban forest inventories and enhanced data on forest soils, carbon, and biomass.1
2.3 Partnerships and Collaborations
Partnerships are integral to FIA's operations, enabling the program to achieve its mission of collecting, analyzing, and reporting on America's forests.2 FIA collaborates extensively with state agencies, often through flexible contracting mechanisms and fiscal match requirements.1 These partnerships extend to personnel, funding, and expertise, with state cooperators comprising a significant portion of the FIA workforce.8 The program also engages in public-private partnerships for data collection on privately owned forestlands.1 Furthermore, FIA works with various research institutions, universities, and other federal agencies, such as NASA and the Department of the Interior, on specific projects and data applications like LANDFIRE, which uses FIA plot data for mapping vegetation, fuels, and fire regimes.2 The Society of American Foresters (SAF) recognizes the critical importance of FIA and supports its funding, staffing, and responsiveness to partner needs.1
3.0 Overview of the National Agricultural Statistics Service (NASS)
3.1 Mission and Scope
The National Agricultural Statistics Service (NASS) is the statistical agency of the USDA, with a mission to "provide timely, accurate, and useful statistics in service to U.S. agriculture".3 NASS serves as the official source of comprehensive, current information on farms, ranches, and the people who provide food, feed, and fiber to the nation and the world.3 Established with roots tracing back to 1863, NASS aims to provide equal market information to sellers and buyers, minimizing uncertainties and risks associated with agricultural production and marketing.4 The agency conducts over 400 surveys annually and the Census of Agriculture every five years.3
3.2 Data Collected
NASS collects, assembles, analyzes, and disseminates a vast array of data about U.S. agriculture.9 This includes statistics on:
●	Agricultural production and inventories (e.g., crops, livestock) 3
●	Farm labor, wages, income, and finances 3
●	Types and amounts of chemicals used 3
●	Conditions of specific crops, livestock trends, and rural development 3
●	Agricultural industries such as flour milling, ethanol, and cotton 3 The Census of Agriculture provides a complete count of U.S. farms and ranches and detailed information on land use, ownership, production practices, income, and operator characteristics.3 NASS also engages in ongoing research on survey design, sampling, and statistical methodologies, incorporating technologies like remote sensing.3
3.3 Partnerships and Collaborations
NASS collaborates with various entities to fulfill its mission. Historically, NASS has had a long history of cooperation and coordination with the USDA Extension Service (ES), formalized through Memoranda of Understanding (MOUs) aimed at enhancing the scientific collection and effective dissemination of agricultural statistics, as well as conducting educational programs.12 NASS also works with other USDA agencies, such as the Natural Resources Conservation Service (NRCS) on specific surveys like the Conservation Practice Adoption Motivations Survey (CPAMS).14 Data users include farmers, ranchers, policymakers, community planners, agribusinesses, researchers, and other federal and state agencies.3
4.0 Direct Coordination Mechanisms Between FIA and NASS
While distinct in their primary focus areas (forests for FIA, agriculture for NASS), certain overlaps and needs for coordinated data arise, particularly concerning land use at the agriculture-forestry interface.
4.1 Memoranda of Understanding (MOUs)
Direct MOUs specifically between FIA and NASS are not prominently highlighted in the provided materials. However, NASS's approach to interagency collaboration is exemplified by its MOU with the Extension Service (ES).12 This MOU establishes a continuing working relationship to foster and enhance the scientific collection of statistics, effective dissemination of this information, and the conduct of educational programs for proper interpretation and use of agricultural statistics.13 Key aspects of the NASS-ES MOU include ES assisting NASS in data gathering (e.g., developing lists of farmers) and identifying new statistical needs, while NASS provides publications, information on methods, and survey assistance to ES.13 Such frameworks demonstrate a model for how NASS formalizes partnerships to achieve shared objectives, which could theoretically be applied to interactions with FIA if specific, ongoing collaborative needs were identified at a programmatic level.
4.2 Joint Projects and Surveys
Specific joint projects directly and equally co-led by FIA and NASS as primary partners are not extensively detailed. However, there are projects where data from one agency is crucial for a survey or analysis led by the other, or by a partner agency.
One notable area involves agroforestry data. The NASS Census of Agriculture (COA) has included questions about agroforestry practices.15 This data, collected by NASS, is then utilized by entities like the USDA National Agroforestry Center (NAC), which is a partnership between the USDA Forest Service and NRCS.17 The NAC uses NASS COA data to create maps and analyses depicting agroforestry extent and trends.15 For example, the 2017 and 2022 COA asked if farm operations practiced agroforestry, providing county-level numbers that the NAC uses for spatial visualization and trend analysis.15 This represents a significant point of data leverage, where NASS's broad agricultural data collection feeds directly into analyses relevant to forest-related practices.
NASS also conducts the National Agroforestry Survey as a cooperative effort with the USDA National Agroforestry Center.18 This survey collects more detailed information on specific agroforestry practices (windbreaks, silvopasture, riparian forest buffers, alley cropping, forest farming) than the general COA question.18 While FIA is not a direct partner in conducting this NASS survey, its parent agency, the Forest Service (via the NAC), is a key collaborator and user of the resulting data.
Another example is the Conservation Practice Adoption Motivations Survey (CPAMS), a joint project between NASS and the NRCS.14 While FIA is not a primary partner in CPAMS, the survey includes a forestry practices category.14 Significantly, the sample for the forestry respondents in CPAMS is determined by the USDA Forest Service using its area frame determination of wood or forest landowners.14 This indicates a direct, albeit specific, contribution from the Forest Service (FIA's parent agency) to a NASS-led survey effort, ensuring that the forestry component of CPAMS targets the appropriate population.
4.3 Data Sharing and Accessibility
Both FIA and NASS make their data publicly available, though with necessary confidentiality protections. FIA provides access to its data through online tools and fulfills spatial data requests, often under Material Transfer Agreements (MTAs) or Memorandums of Agreement (MOAs) when confidential data like plot coordinates are involved.8 NASS also provides extensive data access through its Quick Stats database, APIs, and reports, ensuring confidentiality of individual producer information.20
The USDA's Economic Research Service (ERS) utilizes data from both FIA and NASS for its Major Land Uses (MLU) series.11 This is a clear instance of data from both agencies being integrated by a third USDA entity for comprehensive national-level analysis. ERS uses USFS inventories for forest-use land estimates and NASS Census of Agriculture data for cropland and pasture/range estimates.11 This integration, though performed by ERS, implies a level of data compatibility and accessibility that allows for such combined analyses.
The development of platforms like the FIA Land Resources Explorer, which aims to provide user-friendly access to land area estimates from multiple sources (initially FIA data, with plans to incorporate other land resource monitoring products), points towards efforts to make complex land data more accessible.5 While not explicitly stated as a direct NASS-FIA collaboration, such initiatives could potentially incorporate NASS agricultural land use data in the future to provide a more complete picture.
5.0 Indirect Coordination and Data Integration
Beyond direct, formalized partnerships, considerable coordination occurs indirectly through the use of FIA and NASS data by other USDA agencies and in broader multi-agency initiatives. This often involves data integration for specific analytical purposes, such as land use accounting, climate change assessment, and specialized resource management.
5.1 USDA Economic Research Service (ERS) Land Use Statistics
The USDA ERS plays a pivotal role in integrating data from various sources, including FIA and NASS, to produce its comprehensive Major Land Uses (MLU) series.22 The MLU series, initiated in 1945, provides national and state-level estimates for all major land uses at approximately 5-year intervals, coinciding with the NASS Census of Agriculture.22
ERS develops its estimates by first accounting for cropland, urban areas, rural transportation, and rural parks/wilderness areas, largely based on census and administrative data.23 Subsequently, forest-use land and pasture/range estimates are developed. For forest-use land, ERS primarily relies on FIA's inventories of forested land.11 For cropland and permanent pasture/range, NASS data, particularly from the Census of Agriculture, are critical inputs.11 For instance, the total cropland estimate incorporates NASS Census data adjusted with NASS data on principal crops harvested.23 This systematic integration by ERS demonstrates how data from FIA (forest focus) and NASS (agriculture focus) are brought together to create a unified national picture of land allocation. This process inherently requires that the data, despite being collected for different primary purposes, possess sufficient compatibility and definitional clarity to be merged for broader analysis.
5.2 USDA National Agroforestry Center (NAC)
The USDA National Agroforestry Center (NAC), a partnership between the USDA Forest Service and the Natural Resources Conservation Service (NRCS), is a key user of NASS data for understanding and promoting agroforestry practices.17 Agroforestry intentionally integrates woody plants with crop and/or animal production systems, bridging the traditional domains of forestry and agriculture.15
The NAC extensively uses data from the NASS Census of Agriculture (COA) to map and analyze agroforestry adoption across the U.S..15 Since 2017, the COA has included a question asking farm operations if they practice any of five common agroforestry systems (windbreak, silvopasture, forest farming, alley cropping, riparian forest buffer).15 The NAC takes these county-level raw numbers from NASS and joins them with geospatial data to create thematic maps and reports, such as those detailing the number and percentage of farms practicing agroforestry by county and state.15 This allows for national-level trend analysis, as seen with the comparison of 2017 and 2022 COA data.15
Furthermore, NASS conducts the National Agroforestry Survey in cooperation with the NAC.18 This survey provides more detailed information on specific agroforestry practices than the general COA question and its findings are used to guide USDA policy and program development.18 This collaboration, with NASS collecting detailed agroforestry data that the Forest Service-partnered NAC then analyzes and disseminates, represents a significant indirect link between NASS's statistical capabilities and the Forest Service's interest in agroforestry.
5.3 USDA Climate Adaptation and Greenhouse Gas (GHG) Monitoring
Both FIA and NASS data are crucial inputs for USDA's efforts in climate adaptation and greenhouse gas (GHG) monitoring. The USDA's Climate Adaptation Plan highlights the need for robust data to assess climate risks and integrate adaptation into mission delivery.24
FIA data, through programs like the Resources Planning Act (RPA) Assessment, provide snapshots of current forest and rangeland conditions and projected climate impacts, forming the basis for understanding forest carbon stocks and fluxes.24 FIA data are authoritative for U.S. reporting of forest carbon to the United Nations Intergovernmental Panel on Climate Change (IPCC).11
NASS contributes by collecting data on agricultural practices, land management, and through surveys like the Agricultural Resource Management Survey (ARMS), which can inform assessments of GHG emissions from agriculture and the adoption of climate-smart practices.26 NASS is also modernizing its data collection to better support climate science, for example, by using Google Earth Engine to estimate crop impacts from extreme weather.24
The National Association of State Foresters (NASF) has emphasized the need for FIA to play an explicit role in the Measurement, Monitoring, Reporting, and Verification (MMRV) of forest carbon, potentially requiring enhanced data collection capabilities.25 While direct FIA-NASS integration for GHG reporting is not explicitly detailed as a current formalized system, the overarching USDA strategy for GHG MMRV in agriculture and forestry implies a need for data from both sectors.25 Efforts to improve the timeliness and integration of conservation data, involving ERS and NASS, also contribute to quantifying GHG benefits, many of which have climate adaptation co-benefits.24 The USDA Climate Hubs further facilitate the translation of scientific outcomes from agencies like the Forest Service (using FIA data) into usable tools, underscoring the importance of these foundational datasets for broader climate initiatives.24
5.4 LANDFIRE Project
The Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) is a multi-stakeholder project that produces geospatial data describing vegetation, land cover, wildland fuels, and fire regimes across all U.S. lands.2 FIA data is a critical input for LANDFIRE. Specifically, FIA plot data provides status and trends on the nation's forest lands across all ownerships and is used to develop and refine LANDFIRE products.2 For example, FIA data are used in mapping BioPhysical Settings (BpS), predicting tree canopy closure and height, and modeling existing vegetation types for LANDFIRE.2 While LANDFIRE is not a direct NASS collaboration, it demonstrates how FIA's comprehensive forest data serves as a foundational layer for broad-scale land management tools, which could potentially be integrated with agricultural land cover data (like NASS's Cropland Data Layer) for more comprehensive landscape assessments.
6.0 Specific Collaborative Areas and Data Intersections
Several specific domains highlight the intersection of FIA and NASS data and the potential or actualized collaboration, often facilitated by other USDA entities or driven by shared thematic interests.
6.1 Agroforestry Data
As previously discussed, agroforestry is a prime example of an area where NASS data collection directly supports Forest Service (and NRCS) objectives through the National Agroforestry Center (NAC).
●	NASS Data Collection: The NASS Census of Agriculture (COA) has, since 2017, included a question about the adoption of agroforestry practices by farm operations.15 This provides county-level data on the number of farms engaging in practices like windbreaks, silvopasture, alley cropping, forest farming, or riparian forest buffers.15 NASS also conducts a more detailed National Agroforestry Survey in cooperation with the NAC, focusing specifically on these five practices.18
●	Forest Service/NAC Utilization: The NAC utilizes this NASS-collected data to produce maps, reports, and analyses on the extent and trends of agroforestry in the U.S..15 For example, the NAC published maps depicting agroforestry results from the 2017 COA and has updated these with 2022 COA data, allowing for trend analysis.15 This information is vital for understanding adoption rates, identifying areas for future promotion, and guiding policy and program development related to agroforestry.15 The collaboration here is clear: NASS leverages its extensive survey infrastructure to collect data relevant to practices that blend agriculture and forestry, and the Forest Service, through the NAC, is a primary beneficiary and analytical partner for this information.
6.2 Land Use and Land Cover (LULC) Data
Both FIA and NASS produce or contribute to critical LULC datasets, which are fundamental for understanding resource conditions, trends, and environmental impacts.
●	FIA's Role: FIA collects LULC data at all its inventory plots.5 It provides estimates of forest land by various classifications (owner, status, cover type) and is expanding efforts to monitor urban areas and land use change.5 FIA has developed tools like the FIA Land Resources Explorer to make LULC estimates more accessible, initially focusing on land use and planning to add land use change, land cover, and land cover change.5 FIA data distinguishes between land cover (physical features) and land use (socio-economic intent), recognizing that a recently harvested forest (changed cover) may still have a forest land use if regeneration is planned.5
●	NASS's Role: NASS produces the Cropland Data Layer (CDL), an annual, raster-based, crop-specific land cover data layer for the conterminous U.S..28 The CDL is derived using satellite imagery (e.g., Landsat, Sentinel-2) and is a key source for agricultural land cover information.29 The NASS Census of Agriculture also provides detailed data on agricultural land use on farms and ranches.11
●	Integration by ERS: As detailed earlier, the USDA ERS integrates FIA and NASS data for its Major Land Uses (MLU) series.11 FIA data informs forest land estimates, while NASS COA and crop production data inform cropland and pasture/range estimates.11 The distinct methodologies (FIA: field plots and remote sensing for all lands; NASS CDL: satellite-based for crop-specific cover; NASS COA: survey-based for farm operations) mean that direct fusion of these datasets can be complex. However, their complementary nature is essential for comprehensive LULC assessments, particularly at the national scale as performed by ERS.
6.3 Conservation Surveys (e.g., CPAMS)
The Conservation Practice Adoption Motivations Survey (CPAMS) is a joint project between NASS and the NRCS, designed to understand why landowners adopt (or do not adopt) various conservation practices.14 This survey has direct relevance to both agricultural and forested lands.
●	Survey Structure: CPAMS covers four categories: crop practices, confined livestock practices, grazing practices, and forestry practices.14
●	Forestry Component & Forest Service Involvement: For the forestry practices component of CPAMS (surveyed in 2024), the sample of respondents (forest landowners) is determined by the USDA Forest Service using its area frame.14 This is a specific instance where the Forest Service provides critical input into the sampling design of a NASS-led survey to ensure the forestry-related questions reach the target population. While FIA itself is not named as the direct Forest Service entity involved, the use of a "Forest Service area frame determination" points to the agency's expertise in identifying forest landowner populations, a capability closely aligned with FIA's comprehensive land inventory work. The data from CPAMS, including the forestry section, is intended to improve voluntary conservation programs and document the stewardship efforts of agricultural producers and forest land managers.14 This collaboration, even if indirect for FIA, ensures that conservation on forested lands is appropriately addressed within this significant NASS survey.
6.4 Climate Change and Greenhouse Gas (GHG) Inventory
The imperative to understand and mitigate climate change necessitates data from both the agricultural and forestry sectors.
●	FIA's Contribution: FIA data is fundamental for quantifying forest carbon stocks and fluxes, forming the basis of U.S. reporting for the forest sector under international agreements like the IPCC.11 The program is working to improve carbon and biomass estimates.1
●	NASS's Contribution: NASS collects data on agricultural land use, management practices, and livestock, which are essential for estimating GHG emissions from agriculture.24 Surveys like ARMS provide detailed economic and practice-level information relevant to climate impacts and mitigation.26 NASS is also enhancing its use of geospatial data and climate information systems to assess impacts of extreme weather on agricultural production.24
●	Need for Integrated Approaches: The National Association of State Foresters (NASF) has called for FIA to have a more explicit role in GHG MMRV, with dedicated funding.25 They also suggest the need for a single USDA-sponsored platform with user-friendly tools for forest and wood product carbon data, implying better integration of various data sources.25 While a fully integrated FIA-NASS GHG accounting system is not yet apparent, the USDA's broader climate strategy necessitates robust data from both agencies.24 The development of national-level conservation data platforms involving ERS and NASS, aimed at quantifying GHG benefits, points towards efforts to improve data integration for climate-related objectives.24 The challenge lies in harmonizing data collected with different methodologies and for different primary purposes to support comprehensive climate assessments.
7.0 Challenges in Coordination and Data Integration
Despite instances of successful data sharing and indirect collaboration, several challenges impede deeper, more systematic coordination and data integration between FIA and NASS, and more broadly among federal LULC data producers.
7.1 Differences in Definitions, Methodologies, and Scope
FIA and NASS collect data tailored to their specific missions, leading to inherent differences:
●	Thematic Definitions: LULC classifications can vary significantly. For example, "forest" can be defined based on current vegetation cover (common in remote sensing products like some NASS might use for CDL context) or on land use intent (FIA's approach, where a harvested area intended for reforestation remains "forest land").5 Similarly, distinguishing between natural grasslands, managed pasture (relevant to NASS), and forest openings (relevant to FIA) using remote sensing alone can be difficult due to similar spectral properties; the distinction often lies in land use and management intent.29
●	Spatial Resolution and Scale: FIA relies on a systematic grid of permanent ground plots (approximately 1 plot per 2,400 hectares for base intensity) augmented by remote sensing 1, providing detailed ecological information at plot locations. NASS's CDL is a 30-meter raster product covering the conterminous U.S. annually, focused on crop types.28 The Census of Agriculture collects data at the farm operation level.11 Integrating these disparate data types and scales requires sophisticated analytical techniques.
●	Temporal Frequency: FIA aims for annual remeasurement of 20% of plots in each state (10% in the West) 1, leading to a 5 to 10-year cycle for full state remeasurement. NASS's CDL is annual, and the COA is every five years.3 Aligning these different temporal resolutions for change analysis can be complex.
●	Scope: FIA covers all forest lands regardless of ownership.1 NASS data primarily focuses on agricultural operations, farms, and ranches.3
These differences mean that simply overlaying datasets may not yield accurate or meaningful results without careful harmonization and understanding of each dataset's characteristics and limitations.29
7.2 Data Standardization and Interoperability
The lack of common data standards and system interoperability across USDA agencies, and more broadly among federal data producers, is a significant hurdle.29
●	Linking Variables: The absence of consistent "linking variables" makes it difficult to connect datasets from different sources for integrated analysis.30
●	Diverse Systems: State, local, and tribal governments, as well as different federal agencies, often have unique administrative and operational systems not designed for interoperability.30
●	MRLC Efforts: The Multi-Resolution Land Characteristics (MRLC) Consortium, which includes the Forest Service, has worked to improve consistency and reduce duplication in land cover mapping efforts.27 However, challenges remain in fully harmonizing thematic definitions, input data, and accuracy assessments across all federal LULC products.29 Strategies proposed by MRLC partners include developing multiresolution product suites, harmonizing thematic definitions with nested hierarchies, creating repositories of common imagery and training data, and establishing shared approaches for validation.29
7.3 Data Privacy and Confidentiality Concerns
Both FIA and NASS handle sensitive information that requires strict confidentiality.
●	FIA: Protects plot locations and landowner personally identifiable information.8 Data sharing often requires MTAs or MOAs.8
●	NASS: Legally mandated to protect the confidentiality of individual reports from farmers and ranchers; data are only published in aggregate form.14 The 2008 Farm Bill prohibited USDA from releasing producer information at an identifiable level, though aggregate analysis is permitted.30 These necessary protections, while crucial for maintaining respondent trust and data quality, can complicate data integration efforts, especially if record-level linkage is desired for specific research. Producers themselves may be wary of sharing data if they are unsure who will access it and how it will be used, or if they perceive too many data requests.20 Building trust through transparent data privacy rules and controls is essential.31
7.4 Institutional and Resource Constraints
●	Funding and Staffing: The FIA program, for example, is often described as funding- and labor-constrained. Expanding its functions (e.g., for enhanced carbon MMRV) without additional dedicated resources could exacerbate these issues.25
●	Misaligned Incentives: Data owners, particularly individual producers, may lack incentives to provide data if they do not see a clear return on investment or benefit from sharing it.30
●	Leadership and Governance: While USDA has a Chief Data Officer and data governance board, consistent leadership and sustained resources are needed across agencies to prioritize and manage data integration initiatives, especially through changes in political and agency leadership.30
●	Legal Authority Interpretation: Ambiguities in interpreting laws like the Privacy Act regarding secondary uses of administrative data can sometimes lead to a default position of not sharing data, even when permissible with appropriate safeguards.30
Addressing these challenges requires a concerted effort towards greater standardization, improved technological interoperability, clear governance for data sharing, and ensuring that data providers see value in their contributions. The development of integrated data platforms and user-friendly tools, as suggested by NASF for forest carbon data 25, could serve as a model for broader agriculture-forestry data integration.
8.0 Benefits and Opportunities of Enhanced Coordination
Enhanced coordination and data integration between FIA and NASS, as well as with other relevant USDA and federal programs, offer significant benefits and opportunities for improved resource management, policy development, and scientific understanding.
8.1 Improved Decision-Making for Land Management and Policy
A more integrated view of agricultural and forested landscapes can lead to better-informed decisions at multiple levels:
●	Holistic Landscape Management: Combining FIA's detailed forest ecological data with NASS's agricultural land use and practices data can provide a more complete picture of entire watersheds or regions. This is crucial for addressing issues that cross traditional sectoral boundaries, such as water quality, wildlife habitat connectivity, and the impacts of land use change at the wildland-agricultural interface.
●	Targeted Conservation Efforts: Understanding the spatial distribution of specific agricultural practices (from NASS) alongside forest conditions (from FIA) can help target conservation programs (like those administered by NRCS) more effectively. For example, identifying areas where certain farming practices might impact adjacent forest ecosystems, or where agroforestry could provide mutual benefits. The CPAMS survey, with its Forest Service input for the forestry sample, is a step in this direction.14
●	Evidence-Based Policy: Robust, integrated data strengthens the foundation for agricultural and forestry policies. For instance, policies related to climate change mitigation and adaptation (e.g., promoting carbon sequestration in both forests and agricultural soils) require comprehensive data from both sectors.24 Integrated data can also support more accurate economic analyses of different land management strategies.
8.2 Enhanced Resource Assessment and Monitoring
●	Comprehensive LULC Accounting: As demonstrated by the ERS Major Land Uses series, combining FIA and NASS data allows for a more complete accounting of national land resources.11 Improving the interoperability and harmonization of these datasets, as suggested by MRLC efforts 29, could lead to even more timely and detailed LULC products.
●	Agroforestry Potential: Better integration can refine assessments of current agroforestry adoption (using NASS COA and specific surveys 15) and identify areas with high potential for future implementation by combining agricultural land characteristics with data on adjacent forest resources or suitable tree species.
●	Climate Impact and Adaptation Monitoring: A unified approach to monitoring climate impacts on both agricultural and forest productivity, water resources, and ecosystem health would be invaluable. This includes tracking the effectiveness of adaptation strategies across different land types.
8.3 Streamlined Data Collection and Reduced Burden
●	Reduced Duplication: Coordinated data planning and sharing can help identify and reduce redundancies in data collection efforts across agencies.25 For example, ensuring that definitions and data collection protocols are harmonized where possible can prevent different agencies from collecting similar information in slightly different ways.
●	Lower Respondent Burden: For landowners and producers who might be asked to provide information to multiple USDA surveys, integrated data systems or coordinated survey efforts could potentially streamline requests and reduce the perceived burden.31
8.4 Advancing Scientific Research
●	New Research Frontiers: Integrated datasets can open up new avenues for research into complex ecological and socio-economic systems, such as the interactions between agricultural intensification, forest fragmentation, and biodiversity, or the landscape-level effects of climate change.
●	Improved Modeling Capabilities: More comprehensive and consistent data can improve the accuracy and predictive power of ecological, economic, and climate models used to forecast future conditions and evaluate policy scenarios. The use of FIA data in the LANDFIRE project is an example of how detailed inventory data supports landscape-scale modeling.2
8.5 Increased Transparency and Public Access to Information
●	Unified Data Platforms: Initiatives like the FIA Land Resources Explorer 5 or the proposed USDA-sponsored platform for forest carbon data 25 could be expanded to provide more integrated access to agriculture and forestry information, making it easier for a wider range of users (researchers, planners, public) to find and utilize relevant data.
●	Better Communication of National Trends: Coordinated reporting on key indicators for both agriculture and forestry can provide a clearer and more consistent message about the state of the nation's land resources and the effectiveness of management and conservation efforts.
Achieving these benefits requires overcoming the challenges outlined previously, including investing in data standardization, interoperability, and governance structures that facilitate collaboration while respecting the unique mandates and data confidentiality requirements of each agency.
9.0 Conclusion
The coordination between the USDA's Forest Inventory and Analysis (FIA) program and the National Agricultural Statistics Service (NASS) is multifaceted, characterized more by indirect data integration and project-specific collaborations than by overarching, systemic joint operations. Both agencies fulfill distinct, Congressionally mandated missions: FIA provides a comprehensive census of U.S. forests 1, while NASS delivers timely and accurate statistics for U.S. agriculture.3
Direct formal partnerships, such as dedicated MOUs solely between FIA and NASS, are not prominent. However, NASS's collaborative frameworks with other USDA entities, like the Extension Service 13, offer a model for structured cooperation. More evident are instances where data from one agency is leveraged by the other or by a partner agency for specific analytical purposes. The use of NASS Census of Agriculture data by the Forest Service-affiliated National Agroforestry Center to track agroforestry adoption is a key example.15 Similarly, the Forest Service provides input for the forestry sample in the NASS-NRCS Conservation Practice Adoption Motivations Survey.14
Significant indirect coordination occurs through the USDA Economic Research Service, which integrates FIA's forest data and NASS's agricultural data to produce the national Major Land Uses series.11 This highlights the complementary nature of their datasets for comprehensive land accounting. Furthermore, data from both FIA and NASS are crucial, albeit often separately utilized, for broader USDA initiatives related to climate change adaptation and greenhouse gas monitoring.24
Challenges to deeper integration persist, primarily stemming from differences in data collection methodologies, thematic definitions, spatial and temporal scales, and institutional focuses.29 Data privacy requirements 8 and resource constraints 25 also influence the extent of direct data merging.
Despite these hurdles, the existing intersections and the clear benefits of a more holistic understanding of the nation's intertwined agricultural and forest landscapes point towards opportunities for enhanced coordination. Strengthening data standardization, fostering interoperable platforms, and clarifying data governance could unlock further synergies. Such improvements would lead to more robust decision-making for land management, more effective conservation strategies, particularly at the agriculture-forestry interface, and a more comprehensive scientific basis for addressing national challenges like climate change and sustainable resource use. The current coordination, while often indirect or facilitated by third parties, provides a foundation upon which more deliberate and integrated approaches can be built to maximize the value of the rich datasets produced by both FIA and NASS.
10.0 References
●	1 Forest Inventory and Analysis Program. (n.d.). eForester.org. Retrieved from https://www.eforester.org/Main/Issues_and_Advocacy/Statements/Forest_Inventory_and_Analysis_Program.aspx
●	2 LANDFIRE & Forest Inventory and Analysis (FIA). (n.d.). ArcGIS StoryMaps. Retrieved from https://storymaps.arcgis.com/stories/ce0c8da1d94a4bdcbd35f4cdf29f2a28
●	3 USDA - National Agricultural Statistics Service - About NASS - Career Opportunities. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/About_NASS/Opportunities/index.php 3
●	4 An Evolving Statistical Service for American Agriculture. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/About_NASS/pdf/evolving_nass.pdf 26
●	7 FIA Data Collection. (n.d.). Oregon State University - Institute for Natural Resources. Retrieved from https://inr.oregonstate.edu/forest-landscapes/fia-data-collection 7
●	6 FIA Database Description. (n.d.). CU ESIIL GitHub. Retrieved from https://cu-esiil.github.io/FCC24_Group_6/data-library/fia/
●	9 NASS Career Brochure 2025. (n.d.). NASS USDA. Retrieved from https://data.nass.usda.gov/About_NASS/Opportunities/NASS_Career_Brochure_2025.pdf 9
●	10 NASS Career Brochure May 2016. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/About_NASS/Opportunities/NASS_Career_Brochure_May_2016.pdf 10
●	25 NASF Comments on USDA_2023_0009_Final. (2023, November). National Association of State Foresters. Retrieved from https://www.stateforesters.org/wp-content/uploads/2023/11/NASF-Comments-USDA_2023_0009_Final.pdf
●	12 National Agricultural Statistics Service (NASS) Memorandum of Understanding. (n.d.). NIFA USDA. Retrieved from https://www.nifa.usda.gov/national-agricultural-statistics-service-nass-memorandum-understanding
●	13 NASS-MOU-30.pdf. (n.d.). NIFA USDA. Retrieved from https://www.nifa.usda.gov/sites/default/files/resource/NASS-MOU-30.pdf
●	28 USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL). (n.d.). Data.gov. Retrieved from https://catalog.data.gov/organization/352b4532-793d-4075-a03f-05b778a3c43a?harvest_source_title=USDA+JSON&res_format=HTML
●	20 Ag Data: Improving Productivity while Protecting Privacy. (2019, September). Food & Agricultural Policy Research Institute. Retrieved from https://foodandagpolicy.org/wp-content/uploads/sites/17/2019/09/2018-July-Ag-Data_Improving-Productivity-while-Protecting-Privacy.pdf
●	21 USDA National Agricultural Statistics Service Information. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/
●	15 County-level agroforestry reported in the 2017 U.S. Census of Agriculture. (n.d.). Ag Data Commons - NAL USDA. Retrieved from https://agdatacommons.nal.usda.gov/articles/dataset/County-level_agroforestry_reported_in_the_2017_U_S_Census_of_Agriculture/27010561
●	16 Census of Agriculture – Agroforestry Data. (n.d.). USDA Forest Service - National Agroforestry Center. Retrieved from https://www.fs.usda.gov/nac/maps-data/census-agriculture/index.php
●	11 Land Use and Land Cover Estimates for the United States. (n.d.). ERS USDA. Retrieved from https://www.ers.usda.gov/about-ers/partnerships/strengthening-statistics-through-the-icars/land-use-and-land-cover-estimates-for-the-united-states 11
●	5 FIA Land Resources Explorer. (n.d.). ArcGIS Experience. Retrieved from https://experience.arcgis.com/experience/ddb54b68e915431182d406f9778694cb
●	13 NASS-MOU-30.pdf. (n.d.). NIFA USDA. Retrieved from https://www.nifa.usda.gov/sites/default/files/resource/NASS-MOU-30.pdf 13
●	12 National Agricultural Statistics Service (NASS) Memorandum of Understanding. (n.d.). NIFA USDA. Retrieved from https://www.nifa.usda.gov/national-agricultural-statistics-service-nass-memorandum-understanding 12
●	14 Conservation Practice Adoption Motivations Survey (CPAMS). (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/CPAM/index.php 14
●	29 Current Status of U.S. Federal Land Use and Land Cover Products. (2024, May). USGS Publications. Retrieved from https://pubs.usgs.gov/publication/cir1549/full 27
●	22 Major Land Uses Documentation. (n.d.). ERS USDA. Retrieved from https://www.ers.usda.gov/data-products/major-land-uses/documentation
●	17 National Agroforestry Center. (n.d.). USDA Forest Service. Retrieved from https://www.fs.usda.gov/nac/
●	18 National Agroforestry Survey. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/Agroforestry/index.php
●	21 NASS Homepage. (n.d.). NASS USDA. Retrieved from https://www.nass.usda.gov/ (Used for general NASS info)
●	19 USDA Moves to Gain Better Understanding of Forest and Grazing Conservation Practices. (n.d.). NRCS USDA News. Retrieved from https://www.nrcs.usda.gov/news/usda-moves-to-gain-better-understanding-of-forest-and-grazing-conservation-practices
●	31 Driving Farm Profitability Through Farmer-Centered Data Approaches. (n.d.). Food & Agricultural Policy Research Institute. Retrieved from https://foodandagpolicy.org/driving-farm-profitability-through-farmer-centered-data-approaches/
●	30 Modernizing Agriculture Data Infrastructure to Improve Economic and Ecological Outcomes. (n.d.). Data Foundation. Retrieved from https://datafoundation.org/news/data-sharing/151/151-Modernizing-Agriculture-Data-Infrastructure-to-Improve-Economic-and-Ecological-Outcomes
●	3 NASS mission, roles, responsibilities, and data collected. (2025, March 3). NASS USDA. Source: https://www.nass.usda.gov/About_NASS/Opportunities/index.php
●	26 NASS history, mission, and data collection evolution. (2005, July). NASS USDA. Source: https://www.nass.usda.gov/About_NASS/pdf/evolving_nass.pdf
●	2 FIA mission and partnerships, particularly LANDFIRE project details. (n.d.). ArcGIS StoryMaps. Source: https://storymaps.arcgis.com/stories/ce0c8da1d94a4bdcbd35f4cdf29f2a28
●	7 FIA data collection methods and partnerships. (2025). Oregon State University - Institute for Natural Resources. Source: https://inr.oregonstate.edu/forest-landscapes/fia-data-collection
●	9 NASS roles, data collected, and types of users of NASS data. (2025, February). NASS USDA. Source: https://data.nass.usda.gov/About_NASS/Opportunities/NASS_Career_Brochure_2025.pdf
●	24 USDA 2024-2027 Climate Adaptation Plan. (n.d.). Sustainability.gov. Source: https://www.sustainability.gov/pdfs/usda-2024-cap.pdf
●	25 NASF comments on USDA strategy, focusing on FIA data use and potential for collaboration with agricultural data (NASS). (2023, August 11). National Association of State Foresters. Source: https://www.stateforesters.org/wp-content/uploads/2023/11/NASF-Comments-USDA_2023_0009_Final.pdf
●	8 FIA 2022 Business Report. (2023, December). USDA Forest Service. Source: https://www.fs.usda.gov/sites/default/files/fs_media/fs_document/FIA-2022-Business-Report.pdf
●	23 ERS information on land use and land cover estimates, detailing how data from FIA and NASS are used and potentially integrated. (n.d.). ERS USDA. Source: https://www.ers.usda.gov/about-ers/partnerships/strengthening-statistics-through-the-icars/land-use-and-land-cover-estimates-for-the-united-states/
●	16 Forest Service National Agroforestry Center use of NASS Census of Agriculture data for agroforestry mapping and analysis. (n.d.). USDA Forest Service - National Agroforestry Center. Source: https://www.fs.usda.gov/nac/maps-data/census-agriculture/index.php
●	5 FIA Land Resources Explorer details, looking for data sources and any mention of NASS data integration or collaboration. (n.d.). ArcGIS Experience Builder. Source: https://experience.arcgis.com/experience/ddb54b68e915431182d406f9778694cb
●	14 Details on the Conservation Practice Adoption Motivations Survey (CPAMS), specifically the forestry practices category, and any mentioned involvement of the Forest Service or FIA definitions/data. (2025, May 30). NASS USDA. Source: https://www.nass.usda.gov/Surveys/Guide_to_NASS_Surveys/CPAM/index.php
●	29 Challenges and strategies for integrating federal land use and land cover products, particularly those relevant to agencies like USDA Forest Service (FIA) and NASS. (2025, January 14). USGS Publications. Source: https://pubs.usgs.gov/publication/cir1549/full
●	5 FIA Land Resources Explorer: purpose, data sources, and any integration or mention of NASS agricultural data for land use and land cover analysis. (n.d.). ArcGIS Experience Builder. Source: https://experience.arcgis.com/experience/ddb54b68e915431182d406f9778694cb
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