Statistically-estimated tree composition for the northeastern United States at the time of Euro-American settlement
Christopher J. Paciorek, Simon J. Goring, Andrew L. Thurman, Charles, V. Cogbill, John W. Williams, David J. Mladenoff, Jody A. Peters, Jun Zhu,, Jason S. McLachlan

TL;DR
This paper introduces a high-resolution, statistically-estimated map of tree species composition in the northeastern US at Euro-American settlement time, derived from land survey records using a Bayesian model.
Contribution
It develops a novel Bayesian statistical methodology to produce a gridded, uncertainty-quantified map of historical tree composition from diverse land survey data sources.
Findings
Produced an 8 km resolution map of tree composition
Quantified uncertainty in the estimates
Integrated data from different survey types
Abstract
We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio) and midwestern (Indiana to Minnesota). Public Land Survey point data in the midwestern region (ca. 0.8-km resolution) are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
