Multi-method late-successional and old-growth (LSOG) forest mapping uncertainty for Maine's unorganized townships

This dataset quantifies the uncertainty in mapping late-successional and old-growth (LSOG) forest across the approximately 4.2 million hectares of Maine's unorganized townships, and tests whether LSOG is rapidly disappearing. Three to four independent, credible mapping methods are compared on a common 100 m grid: (M1) a reproduction of the Hagan et al. (2026) airborne-LiDAR canopy random forest, rebuilt from their public Zenodo deposit; (M2) a logistic model of the FIA field-structure LSOG class on Potapov (GEDI-calibrated) canopy height; (M3) a direct canopy-height threshold; and (M4) the FIA structural class imputed to every pixel via USFS TreeMap (2016, 2020, 2022). Version 1.2.0 additions. This version adds the materials behind the formal Ecosphere Comment on Hagan et al. (2026): (a) a cross-validated accuracy assessment (AUC) of each mapping approach on the original authors' own training plots, showing that high training accuracy does not transfer to agreement among independent maps; (b) an FIA design-based estimate of older forest with sampling-error confidence intervals, the unbiased ground reference the original analysis lacked, putting older forest at about 3.9 percent (3.3 to 4.6) and rising, including on private commercial timberland; (c) a threshold-sensitivity sweep and a 20-seed reproduction ensemble; (d) an ownership-resolved breakdown (private commercial versus public); (e) a hex-scale (8 km) summary of cross-method disagreement; and (f) the Comment manuscript and Supporting Information. Headline findings. Credible methods disagree by roughly 2.8 times on how much LSOG exists and on the location of most LSOG hectares, while agreeing closely on the rare, well-defined old-growth core. Protecting the top 5 to 20 percent of hectares by one map versus another overlaps on only 16 to 30 percent of the ground, so single-map patch-level prioritization for large expenditures is fragile. The design-based FIA estimate and TreeMap imputation both show older forest stable to increasing rather than rapidly declining; the apparent loss reported elsewhere is a gross harvest flux, not a net stock decline. Contents. Derived 100 m GeoTIFFs (reproduced Hagan class, v5.1-GEDI probability, TreeMap class, a per-cell method-consensus layer), summary tables (area by method, pairwise agreement, concordance, prioritization fragility, AUC by approach, design-based older-forest trend with CIs, ownership breakdown, and FIA validation), the analysis R scripts, quick-look figures, the Ecosphere Comment manuscript and Supporting Information, and a full methods-and-findings report (PDF). Privacy. No FIA plot coordinates are included; all products are derived rasters or aggregate summary tables. Caveats: the robust temporal signal is direction rather than precise rate; FIA stand age is modeled, so a structural large-tree domain is reported alongside the age domain; cross-validated intervals are best read as lower bounds because plots are spatially dispersed but not independent. See the README and report for full methods, provenance, and limitations. Version 1.12.0 additions. The cross-map comparison is refined to independent remote-sensing operationalizations only. (a) A three-map remote-sensing ensemble over Maine on a common 100 m grid: reproduced Hagan airborne-LiDAR (any-LSOG 21.9 percent), an FIA-structure class on Potapov GEDI-calibrated spaceborne canopy height (14.0 percent), and the ORNL/Bruening national old-growth stratum (36.1 percent); the three span a 2.6-fold range and agree on only 2.7 percent of flagged hectares, with the ORNL stratum spatially uncorrelated with the structure maps. The USFS TreeMap imputation is reclassified as a second FIA-anchored accounting, reported with the design-based estimate rather than as an independent map. (b) A design-based estimate of LSOG itself: integrated any-LSOG 14.1 percent (12.9 to 15.3) and strict four-axis true LSOG 3.1 percent (2.5 to 3.7) of Maine forestland, the airborne map exceeding even the inclusive ground estimate. (c) A balanced-model LSOG probability surface at 100 m, with a binary class calibrated to the design-based area to bound over-prediction. (d) A multi-objective support vector regression pilot tracing the Pareto front of total versus systematic (attenuation) error. Derived rasters, the three-map agreement layer, the ORNL stratum reprojected to the study grid, tables, R scripts, the updated Comment, and the companion manuscript are included. No FIA plot coordinates are included. Version 1.13.0. Final consolidated release. Adds: a rare-class remedy menu for the reproduced random forest (default vs class weighting vs balanced sub-sampling vs voting-threshold; old-growth detection 0.24 to 0.82, mapped old-growth area 1.0 to 2.3 percent); the definitive five-model LSOG probability map for Maine with across-model uncertainty and reference reserves (MNAP/TNC network, Baxter, Big Reed) over real state and county boundaries; design-based 95 percent confidence intervals for forest-type and ecoregion representation and for disturbance shares; a full robustness/stress-test matrix; and the copy-edited, sole-authored Comment, companion manuscript, and Maine Forest Products Council technical report. Authorship updated to Aaron R. Weiskittel.