I'm a Research Economist at the USDA Forest Service, Southern Research Station, where I develop open-source software tools that make environmental and natural resource research more accessible and reproducible.
My work lives at the intersection of economics, ecology, and data science. I build tools that help researchers, land managers, and policymakers understand our forests better — from analyzing national forest inventories to projecting how land use will change under different climate scenarios. I was a key contributor to the USDA Forest Service 2020 RPA Assessment, which provides long-range strategic planning for America's renewable resources.
Education Ph.D. Applied Economics, Oregon State University
Location Research Triangle Park, NC
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High-performance Python library for Forest Inventory and Analysis (FIA) data. The nation's forest census monitors 300,000+ plots — pyfia makes this massive dataset accessible with Polars and DuckDB. Design-based estimation with proper variance calculations matching FIA EVALIDator exactly. |
Python implementation of the Forest Vegetation Simulator for the Southern variant. Simulates growth and yield of loblolly, shortleaf, longleaf, and slash pine. Used for timber harvest planning, carbon modeling, and forest management scenarios. |
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Create gridded spatial estimates from FIA plot data. Transforms discrete plot measurements into continuous maps of biomass, carbon density, and timber volume. Outputs to GeoTIFF and Zarr for seamless GIS integration. |
Natural language query agent for RPA land use projections. Ask questions like "How much forestland will Georgia lose by 2070?" and get data-backed answers. Built with LangChain and Claude for accessible policy analysis. |
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Community accessibility analysis bridging OpenStreetMap POI data and US Census demographics. Travel-time based metrics for understanding service access. Useful for urban planning, public health, and equity research. |
Convert ESRI geodatabases to open formats like GeoParquet. Handles multi-GB datasets with streaming and chunking. OGC compliant output with Rich progress tracking. |
Statistical methods for large-scale forest data analysis |
Projecting future scenarios under climate change |
Quantifying ecosystem service values |
Tools for wildfire and drought planning |
First-Author Publications
Mihiar, C., Brandeis, T., Bruck, S., Hass, J.L., Wentland, S., Mei, R. & Warziniack, T. Timber valuation from forestry microdata: Lessons from developing a pilot timber asset account for the US.
Develops a national timber asset account using FIA microdata to value standing timber stocks across the US.
Mihiar, C., Lewis, D.J. & Coulston, J.W. (2023). County-level land-use projections for the conterminous United States, 2020-2070, used in the 2020 RPA Assessment.
Official land-use projections for the 2020 RPA Assessment — six land-use categories across 3,000+ counties under multiple climate scenarios. [4 citations]
Mihiar, C. & Lewis, D.J. (2023). An empirical analysis of US land-use change under multiple climate change scenarios. Journal of the Agricultural and Applied Economics Association, 2(3), 597-611.
Climate effects on land use are smaller than socioeconomic drivers but regionally significant. [3 citations]
Mihiar, C. & Lewis, D.J. (2021). Climate, adaptation, and the value of forestland: A national Ricardian analysis of the United States. Land Economics, 97(4), 911-932.
Estimates how climate affects forest land values across the US, finding forests are already adapting to local conditions. Results suggest forestland values are more resilient to climate change than previously thought. [16 citations]
Co-Authored Publications
Zhang, Y., Li, W., Caldwell, P., Sebestyen, S.D., Tang, C., Toot, R., Mihiar, C., et al. (2025). Contemporary patterns of prescribed fire and its risks and benefits to water quantity and water quality over the conterminous United States. Environmental Research Letters, 20(12), 123002.
National-scale assessment of how prescribed fire affects water resources across the US.
Renwick, K.M., Woodall, C.W., Mihiar, C., Murray, L.T., Lewis, R., Beeson, P.C., et al. (2025). Evaluating the current status of agriculture-driven deforestation across jurisdictional scales in the United States using foundational, federal datasets. Environmental Research Letters, 20(7), 074002.
Quantifies agriculture-driven deforestation across US jurisdictions using federal datasets. [3 citations]
Kilgore, M.A., Frey, G.E., Snyder, S.A. & Mihiar, C. (2025). Factors influencing a forest landowner's choice of incentive program commitment length. Forest Policy and Economics, 177, 103513.
Analyzes what drives forest landowner decisions on conservation incentive program enrollment duration. [2 citations]
Nehra, A., Baker, J.S., Caldwell, P.V., Martin, K.L., Warziniack, T.W., Manner, R.H., Mihiar, C., et al. (2025). The potential impact of forest loss on drinking water treatment costs in the southeastern US. Forest Policy and Economics, 179, 103603.
Estimates how forest loss could increase drinking water treatment costs across the Southeast. [1 citation]
Gc, S., Frey, G.E., Mihiar, C., Butler, B.J. & Brandeis, C. (2025). Quantifying the distribution of family forest ownership classifications for US federal income tax. Trees, Forests and People, 19, 100756.
Classifies family forest ownerships for federal income tax purposes and quantifies their distribution. [1 citation]
Lamica, A., Parajuli, R. & Mihiar, C. (2025). Forest-based employment in the Southern United States under climate change: Historical impacts and future projections. Forest Science, 71(3), 303-320.
Projects how climate change will affect forest-sector employment across the US South.
Murray, L.T., Woodall, C., Lister, A., Stockmann, K., Gu, H., Urbanski, S., Riley, K., Mihiar, C., et al. (2024). Quantifying greenhouse gas sources and sinks in managed forest systems. In: Hanson, W.L., Itle, C. & Edquist, K. (eds).
Comprehensive accounting of greenhouse gas fluxes in managed US forest systems. [13 citations]
Warziniack, T., Bagstad, K., Knowles, M., Mihiar, C., Nehra, A., Rhodes, C., et al. (2024). Natural capital accounting on forested lands in the United States: An application to the Colorado River Basin. Measuring and Accounting for Environmental Public Goods: A National Accounts Approach.
Applies natural capital accounting frameworks to value forest ecosystem services in the Colorado River Basin. [4 citations]
Caldwell, P.V., Martin, K.L., Vose, J.M., Baker, J.S., Warziniack, T.W., Costanza, J.K., Mihiar, C., et al. (2023). Forested watersheds provide the highest water quality among all land cover types, but the benefit of this ecosystem service depends on landscape context. Science of the Total Environment, 882, 163550.
Forests are critical for water quality, but value depends on surrounding land uses. [51 citations]
Riitters, K., Coulston, J.W., Mihiar, C., Brooks, E.B., Greenfield, E.J., Nelson, M.D., et al. (2023). Land resources. In: USDA Forest Service. Future of America's Forests and Rangelands: Forest Service 2020 Resources Planning Act Assessment.
Chapter on land resource trends and projections for the 2020 RPA Assessment. [6 citations]
Cavender-Bares, J., Nelson, E., Meireles, J.E., Lasky, J.R., Miteva, D.A., Mihiar, C., et al. (2022). The hidden value of trees: Quantifying the ecosystem services of tree lineages and their major threats across the contiguous US. PLOS Sustainability and Transformation, 1(4), e0000010.
Comprehensive assessment of tree ecosystem services across evolutionary lineages. [44 citations]
Bigelow, D.P., Lewis, D.J. & Mihiar, C. (2022). A major shift in U.S. land development avoids significant losses in forest and agricultural land. Environmental Research Letters, 17(2), 024007.
Documents how changing development patterns have reduced conversion of forest and farmland. [24 citations]
Mu, J.E., Mihiar, C., Lewis, D.J., Sleeter, B. & Abatzoglou, J.T. (2016). An empirical analysis of climate uncertainty and land-use transitions in the US Pacific and Mountain regions.
Examines how climate uncertainty affects land-use transition probabilities in the western US.
Conway-Gómez, K., Reibel, M. & Mihiar, C. (2014). A predictive model of yellow spotted river turtle (Podocnemis unifilis) encounter rates at basking sites in lowland eastern Bolivia. Applied Geography, 53, 332-340.
Spatial model predicting turtle encounter rates to inform conservation in Bolivian lowlands. [15 citations]
Building tools that empower researchers, policymakers, and communities to understand and protect our natural resources.