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"https://w3id.org/sciencelive/o/terms/FORRT-Replication-Study", "https://w3id.org/sciencelive/o/terms/Reproduction-Replication-Study" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "Reproduction and independent replication in Colombia of the 87.9 % validation accuracy of the natural-regeneration random forest (Williams et al. 2024)" } ], "http://www.w3.org/2004/02/skos/core#related": [ { "@id": "http://www.wikidata.org/entity/Q11442890" }, { "@id": "http://www.wikidata.org/entity/Q115768950" }, { "@id": "http://www.wikidata.org/entity/Q199687" }, { "@id": "http://www.wikidata.org/entity/Q2140056" }, { "@id": "http://www.wikidata.org/entity/Q245748" }, { "@id": "http://www.wikidata.org/entity/Q3001793" }, { "@id": "http://www.wikidata.org/entity/Q5629401" }, { "@id": "http://www.wikidata.org/entity/Q739" } ], "https://w3id.org/sciencelive/o/terms/hasDeviationDescription": [ { "@value": "The authors' code is not public, so details the paper leaves open were chosen by us (all listed in docs/deviations.md): tree-cover threshold 30 %; forest 2018 = tree cover 2000 minus loss 2001-2018 from Hansen v1.13 (the authors used v1.6); forest density in a 1 km-radius disk; distance to forest capped at 25 km; R randomForest defaults reproduced in scikit-learn; our own mapping of ESA CCI classes to 11 classes; the climate principal components re-derived, because their loadings are not published.\nThe study covers Colombia only, with sample sizes scaled to Colombia's share of the regrowth patches. Predictors used only in the paper's model comparison were partly unavailable (WDPA August 2020, distance to water); they are not in the final model.\nAdditions not in the paper: spatially blocked, cross-country and forward-in-time validation, independent MapBiomas labels, calibration to the regrowth prevalence, land-use history, and full-resolution HEALPix aggregation." } ], "https://w3id.org/sciencelive/o/terms/hasDiscipline": [ { "@id": "http://www.wikidata.org/entity/Q2249329" } ], "https://w3id.org/sciencelive/o/terms/hasMethodologyDescription": [ { "@value": "Reproduction: the authors' 30 m continuous and binary maps (doi:10.5281/zenodo.7428804) were summed over Colombia (GADM 4.1) with exact WGS84 pixel areas, Mollweide areas and a nominal 0.09 ha per pixel, and compared with Supplementary Tables 3 and 4; Costa Rica was checked the same way.\nReplication: new Python code. A random forest (scikit-learn set to R randomForest defaults, 500 trees) with the paper's ten biophysical predictors rebuilt from open data: forest density in a 1 km disk and distance to forest from Hansen Global Forest Change v1.13 (tree cover at least 30 %), SoilGrids 2017 organic carbon density and pH (0-30 cm), WorldClim 2.1 bioclimatic principal components 1-4, ESA CCI land cover and RESOLVE 2017 biome; natural-regrowth labels from Fagan et al. (2022). Balanced training sample (39,522 points), independent balanced validation points, and prediction with 2018 forest and 2015 land cover on every 30 m pixel, aggregated conservatively to HEALPix on WGS84.\nValidation beyond the paper: random 5-fold cross-validation; spatially blocked 5-fold cross-validation with HEALPix cells of about 25 to 400 km (repeated with latitude/longitude squares); a model trained on a Neotropical sample excluding Colombia; independent labels from MapBiomas Colombia Collection 3, with a forward test (trained on 2000-2012 regrowth, tested on 2012-2024); area of applicability (Meyer and Pebesma 2021).\nRobustness checks: land cover from 1992 or 1999; variable selection with and without NPP, burned area and road density; gradient boosting; CHELSA climate; land-use history 1985-1999. Expected areas are also calibrated to the observed regrowth prevalence.\nCode: doi:10.5281/zenodo.23139192. Derived data: doi:10.5281/zenodo.23138775." } ], "https://w3id.org/sciencelive/o/terms/hasScopeDescription": [ { "@value": "The claim tested is the paper's reported validation accuracy (87.9 %) of its random-forest model of where natural regeneration occurs, and whether that accuracy describes the model where it is used: in places and periods not seen in training. The test is restricted to Colombia, one of the five countries holding 52 % of the estimated potential.\nIn scope: (1) whether the authors' published map reproduces Colombia's area figures in Supplementary Tables 3 and 4; (2) whether an independent implementation reaches the reported accuracy under the paper's validation design; (3) the accuracy under spatially blocked, cross-country and forward-in-time validation, with the paper's training labels and with independent labels; (4) the robustness checks suggested by The Unjournal's evaluators (doi:10.21428/d28e8e57.5411b150).\nOut of scope: the pantropical totals (215 Mha, 23.4 Gt C), the carbon estimates and the five-country share." } ], "https://w3id.org/sciencelive/o/terms/targetsClaim": [ { "@id": "https://w3id.org/sciencelive/np/RAit-NB6vnC7Fy4qSCK6H355AVXNgvkRLXftyHrATqm28" } ] } ] }, { "@id": "https://w3id.org/sciencelive/np/RAvmNqVLbETOORSoWE1WnelnJNtO0S97Z-16omQ65fhyg/provenance", "@graph": [ { "@id": "https://w3id.org/sciencelive/np/RAvmNqVLbETOORSoWE1WnelnJNtO0S97Z-16omQ65fhyg/assertion", "http://www.w3.org/ns/prov#wasAttributedTo": [ { "@id": "https://orcid.org/0000-0002-1784-2920" } ] } ] } ]