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    A new Cretaceous thyreophoran from Patagonia supports a South American lineage of armoured dinosaurs

    Dinosauria—Owen, 184225,Ornithischia—Seeley, 188726,Thyreophora—Nopcsa, 191527,Jakapil kaniukura gen. et sp. nov. (Figs. 1, 2, 3, 4, Suppl. Figs. 2, 3).Figure 1Holotype of Jakapil kaniukura (MPCA-PV-630), skull bones. (a) Skull bones in right lateral view (dashed contours based on Scelidosaurus10); (b) basisphenoid in left lateral view. af anterior foramen, btp basipterygoid process, bt basal tubera, cp cultriform process, df double foramen, ene external naris edge, jf jugal facet of the maxilla, Mx maxilla, mxe maxillary emargination, Pmx premaxilla, vc Vidian canal, vp ventral process.Full size imageFigure 2Holotype of Jakapil kaniukura (MPCA-PV-630), lower jaw bones. (a) left mandible in lateral view; (b) left mandible in lateral view, interpreted bone contours; (c) left mandible in medial view; (d) left mandible in medial view, interpreted bone contours; (e) right surangular in lateral view (mirrored); (f) transversal section of the posterior half of the left mandible, cranial view; (g) articular bone in occlusal view; (h) predentary bone in occlusal view. A angular, af adductor fossa, Ar articular, Ar (gl) glenoid fossa of the articular, ce coronoid eminence, D dentary, de dentary emargination, dfo dentary foramen, dmp dorsomedial process of the articular, dr dentary rugosities, hi subhorizontal inflection (dashed line), imf internal mandibular fenestra, lp lateral process of the predentary, mc Meckelian canal, Pa prearticular, Pd predentary, rp retroarticular process, S surangular, saf surangular facet for the glenoid articulation, safo surangular foramen (canal), Sp splenial, st surangular tubercle, sy mandibular symphysis, vmc ventral mandibular crest.Full size imageFigure 3Holotype of Jakapil kaniukura (MPCA-PV-630), teeth. Maxillary teeth in labial (a,b) and lingual (c,d); (d) highlight the wear facet) views; dentary teeth in lingual (e,g–j); (h,j) highlight the wear facets) and labial (f) views. dwf dentary tooth wear facet, me prominent mesial edge, mwf maxillary tooth wear facet.Full size imageFigure 4Holotype of Jakapil kaniukura (MPCA-PV-630), postcranial bones. Speculative silhouette showing preserved elements (a); osteoderm distribution is speculative and partial to show non-osteodermal elements); dorsal vertebra elements in dorsal (b), right lateral (c) and anterior (d,e) views; sacral vertebra in left lateral view (f); mid-caudal vertebra in left lateral view (g); fragment of the mid-shaft of a dorsal rib in posterior view (the enlarged, broken posterior edge is highlighted (h); expanded distal ends of two dorsal ribs (i); left scapula in lateral view (j); right scapula in lateral view (k); right coracoid in lateral view (l); left and right humeri in anterior view (m); probable right ulna in lateral view (n); metacarpals, non-ungual and ungual phalanx in dorsal views (o); left femur elements in anterior view (p); proximal end of the right fibula in lateral view (q); distal end of the left tibia in anterior view (r); ischial elements in side view (s); cervical osteoderms in dorsal view (t), flat scutes in dorsal view (u), spine-like osteoderm in side view (v) and ossicle in dorsal view (w). ac acromial crest, aco asymmetrical cervical osteoderm, alp anterolateral process, ap acromial process, at anterior trochanter, bb basal bone, ebr expanded broken rib edge, di diapophysis, dpc deltopectoral crest, ft fourth trochanter, gl glenoid, mc metacarpals, nc neural canal, ncs neurocentral suture, ph non-ungual phalanx, pp pubic peduncle, poz postzygapophyses, rug marginal rugosities, sb scapular blade, sc scute, tp transverse process, uph ungual phalanx.Full size imageEtymologyThe genus, Jakapil (Ja-Kapïl: shield bearer), comes from the ‘gananah iahish’, Puelchean or northern Tehuelchean language. The specific epithet, comprising kaniu (crest) and kura (stone), refers to the diagnostic ventral crest of the mandible, and comes from the Mapudungun language. These languages, currently spoken by more than 200,000 people, have been combined as a tribute to both of the coexisting native populations of North Patagonia, South America.HolotypeMPCA-PV-630 is a partial skeleton of a subadult individual (see Supplementary Information) that preserves fragments of some cranial bones (premaxilla, maxilla and basisphenoid), approximately 15 partial teeth and fragments, a nearly complete left lower jaw plus an isolated surangular, 12 partial vertebral elements, a complete dorsal rib and fifteen rib fragments, a partial coracoid, a nearly complete left scapula, a partial right scapula, two partial humeri, a possible partial right ulna, a complete and a partial metacarpal bone, three ischial and two femoral fragments, the distal end of a right tibia, the proximal end of a right fibula, three pedal phalanges, and more than forty osteoderms.Referred specimensMPCA-PV-371, two partial conical osteoderms.Locality and horizonUpper beds of the Candeleros Formation, early Late Cretaceous (Cenomanian, ~ 94–97 My, see16, and references therein), locality of Cerro Policía, Río Negro Province, North Patagonia, Argentina (Suppl. Fig. 1).DiagnosisJakapil differs from all other thyreophorans in having: a large, ventral crest on the posterior half of the lower jaw, which is composed of the dentary, the angular and the splenial (medially hidden by the crest); a dorsomedially directed process in the short retroarticular process; leaf-shaped tooth crowns with a prominent mesial edge on their labial surface; maxillary and dentary tooth crowns differ from each other in their apical contour, the former being pointed and strongly asymmetrical, and the latter slightly curved distally with a more rounded and less asymmetrical contour; elongated (articular surface almost or completely beyond the posterior centrum face) and slender (width of less than a half postzygapophyses length) postzygapophyses in dorsal vertebrae; a strongly reduced humerus relative to the femur (proximal humeral width smaller than distal femoral width, see Supplementary Information), with a deep proximal fossa distally delimited by a curved ridge; a very large fibula relative to the femur (anteroposterior length of the proximal end almost comparable to the distal width of the femur); flattened and thin disk-like postcranial osteoderms.Summarized descriptionA detailed description of the holotype is provided in the Supplementary Information. Jakapil is a small thyreophoran dinosaur (the subadult holotype is estimated to have been less than 1.5 m in body length and to have weighed 4.5–7 kg; see Supplementary Information, femoral description), with several novelties for a thyreophoran dinosaur.A short skull is suggested by the size of the skull and jaw bones, and the reduced number of dentary tooth positions (eleven), compared with most non-ankylosaurid thyreophorans28,29. The antorbital and mandibular fenestrae seem absent, as in ankylosaurs29 (Fig. 1a; the mandibular fenestra is also absent in Scelidosaurus10). Dentary and maxillary emarginations are present, as usual in ornithischians30 (Fig. 1a). The block-like basisphenoid is strongly similar to that of Scelidosaurus10, with Vidian canals opened posterodorsally to the basipterygoid processes, the basipterygoid processes lateroventrally projected (unlike the anteriorly directed processes of stegosaurs28 and ankylosaurs29), and a strong cultriform process (as in Lesothosaurus31, Thescelosaurus32 and probably Scelidosaurus10; Fig. 1b).Jakapil also bears the first predentary bone (Fig. 2a–d) with a plesiomorphic shape in a thyreophoran. It is subtriangular and quite similar to that of Lesothosaurus31, and externally it is ornamented by sulci and foramina, suggesting the presence of a keratinous beak. A beak is also supported in the edentulous and subtly ornamented preserved part of the premaxilla, as in derived thyreophorans28,29. The posterior half of the short lower jaw (Fig. 2a–f) is strongly dorsoventrally expanded, resembling the general shape of the heterodontosaurid33 and basal ceratopsian jaws34. This expansion is composed of a well-developed coronoid eminence (Fig. 2a–d, ce; similar to that in the stegosaur Huayangosaurus35 and most ankylosaurs36) and a large ventral crest at the dentary-angular contact that is unique among thyreophorans (Fig. 2a–d,f, vmc; resembling that of some ceratopsians, see SI). The dentary symphysis is slightly spout-shaped, as in most ornithischians37. Anteriorly, the dentary oral margin is subhorizontal in lateral view (Fig. 2a–d, D), unlike the strongly downturned line of most thyreophorans30,37. There is no evidence of a mandibular osteoderm as occurs in Scelidosaurus and ankylosaurs10. A surangular tubercle (Fig. 2a, st) adjacent to the glenoid fossa seems anteriorly continued by a subtly developed subhorizontal inflection of the anterior lamina (Fig. 2e, hi), in the position of the surangular ridge (synapomorphy of Thyreophora37), though the first is poorly developed. The glenoid fossa is roughly aligned with the tooth row in lateral view (Fig. 2a–d). The short retroarticular process bears a dorsomedially directed process resembling that of several theropods (Fig. 2g, dmp; see Discussion). This process is absent in all other thyreophorans 9,10,35,36.The tooth crowns are leaf-shaped as in basal ornithischian and thyreophorans10,28,29,38 (Fig. 3). The tooth crowns are swollen labially at their base and lack both cingulum and ornamentation, unlike those of derived eurypodans28,29, heterodontosaurids33 and most neornithischians30,32. The mesial edge of the labial surface in the maxillary and dentary tooth crowns is prominent as in Scelidosaurus10, and ends distally in a denticle-like structure in Jakapil (Fig. 3, me). This prominent edge delimits anteriorly the wear facets of the dentary teeth. A striking difference with respect to most thyreophorans is that the maxillary and dentary tooth crowns are quite different (see Supplementary Information). The maxillary teeth (Fig. 3a–d) show seven/eight mesial and four distal denticles, a vertical apical denticle, and a straighter mesial denticle row (resembling those of non-ankylosaurid and non-stegosaurid thyreophorans10,35,36). The dentary teeth (Fig. 3e–j) bear seven mesial and five/six distal denticles, and a distally curved apical-most denticle. Also, the mesial denticle row is lingually recurved, as in Huayangosaurus35. Large, high-angled wear facets are present (Fig. 3d,h,j; dwf and mwf).The axial elements are similar to those of Scelidosaurus39 (Fig. 4). The posterior articular surface of an isolated cervical centrum is flattened and seems almost as wide as high. A large foramen is placed just posteroventral to the parapophysis. The dorsal centra are cylindrical and elongated, with subcircular articular surfaces, and are biconcave (Fig. 4c,e). The neural arch is low but the neural canal is larger (Fig. 4d,e, nc). A dorsal neurocentral suture is visible (Fig. 4c, ncs). The diapophyses are laterodorsally directed almost 40° from the horizontal (Fig. 4d, di), at a lower angle than in stegosaurs28 and most ankylosaurs29, unlike the horizontal processes of basal ornithischians38. The postzygapophyses are medially fused in a slender (width of less than a half postzygapophyses length) and strongly elongated posteriorly structure (Fig. 4b, poz; more than in some ankylosaurs, such as Euoplocephalus and Polacanthus; see40,41). An isolated mid-caudal vertebra shows an equidimensional centrum in lateral view, with concave, oval articular surfaces (Fig. 4g). Transverse processes are very small and button-like (Fig. 4g, tp). Postzygapophyses are medially fused and do not extend beyond the centrum edge (Fig. 4g, poz). Proximally, the cross-section of the dorsal ribs is T-shaped. The low curvature of the shaft suggests a wide torso, as occurs in Emausaurus42, Scelidosaurus39, and ankylosaurs29. Some rib fragments with expanded (though broken) posterior edges suggest the presence of intercostal bones (Fig. 4h, ebr), as in Scelidosaurus39, Huayangosaurus43,44, some ankylosaurids45 (and references therein) and some basal ornithopods46. Some ribs are distally expanded (Fig. 4i) like the anterior dorsal ribs of Scelidosaurus39 and Huayangosaurus43.Girdle and limb bones (see also Suppl. Figs. 2, 3) are mostly broken and with boreholes (probably due to bioerosion) at their ends. The scapular blade (Fig. 4j, sb) is elongated and parallel-sided, without distal expansion, an overall shape that resembles that of several theropods47, contrasting the distally expanded condition in most ornithischians30. A straight and parallel sided scapular blade is common in ankylosaurids29,40. The proximal scapular plate with a high acromial process (Fig. 4j,k, ap) is stegosaurian-like, and the lateral acromial crest (Fig. 4j,k, ac) is developed as in Huayangosaurus43. A low distinct ridge rises posterior to the glenoid fossa and represents the insertion site for the muscle triceps longus caudalis, as occur in ankylosaurids 40. The incomplete coracoid (Fig. 4l) is much shorter than the scapula, unlike that of ankylosaurs29,40, which bear a large coracoid. The coracoid and the scapula are not fused. The partial humeri (Fig. 3m) are strongly reduced in size, with overall limb proportions resembling those of basal ornithischians3,38 and several theropods47. A possible proximal end of the ulna (Fig. 4n) resembles that of other basal ornithischians, though more strongly laterally compressed. The anterolateral process is present (Fig. 4n, alp), and the olecranon process seems absent or poorly developed, as in Scutellosaurus9 and Scelidosaurus39. The ischia are poorly preserved (Fig. 4s). The pubic peduncle is separated from the iliac articulation, unlike the continuous cup-shaped structure of most ankylosaurs29. The shaft of the ischium is straight and parallel-edged, as in Scutellosaurus9 and Scelidosaurus39, and distally tapers as in stegosaurs28. The preserved femoral pieces (Fig. 4p) resemble those of basal ornithischians38,39. The bases of both the broken anterior and fourth trochanters (Fig. 4p, at, ft) are large, suggesting large elements; the fourth trochanter is proximally placed on the femoral shaft (near the height of the base of the anterior trochanter); and the distal end of the femur is slightly curved posteriorly. The proximal end of the right fibula (Fig. 4q) is much larger than that of all other thyreophorans (compared with both the femoral and tibial distal ends) and bears a large anterior curved crest. The block-like non-ungual phalanges and a bluntly pointed hoof-like ungual (Fig. 4o, ph, uph) are similar to those of Scelidosaurus39.At least five osteoderm types are preserved in the holotype of Jakapil. The cervical elements are composed of an external, low-crested scute (Fig. 4t, sc) over a fused, smooth bone base (Fig. 4t, bb), as in Scelidosaurus48 and several ankylosaurs2,49. A probable cervical element is also composed of a concave base of smooth bone fused to a high, asymmetrical osteoderm (Fig. 4t, aco). The bases of these dermal elements present strong rugosities at one edge, suggesting a sutural contact between (Fig. 4t, rug), as in Scelidosaurus48 and some ankylosaurs (such as Pinacosaurus and Scolosaurus40,49,50). Scute-like post-cervical osteoderms (Fig. 4u) are strongly flattened, disk-shaped, and suboval with a very low crest, resembling those of few ankylosaurs such as Gastonia and Gargoyleosaurus51 (‘body osteoderms’ sensu Kinneer et al.52; see also49). Only one scute shows a high triangular cross-section like those of Scelidosaurus48. Also present are a few conical, spike-like osteoderms with deep concave bases (Fig. 4v), and many flat, disk-shaped, minute (7–10 mm) ossicles without crests (Fig. 4w).PhylogenyThe phylogenetic analysis using the matrix of Soto-Acuña et al.5 recovers Jakapil within Thyreophora, as the sister taxon of Ankylosauria (Fig. 5). The branch support for the basal thyreophorans is considerably lower than that obtained by Soto-Acuña et al.5, although the support of Stegosauria and some less inclusive eurypodan clades is slightly better (ceratopsians and pachycephalosaurs also show a lower support). The Jakapil autapomorphies in this analysis are: ventrally orientated basipterygoid processes (char. 134; shared with Agilisaurus, Hypsilophodon, Zalmoxes, Tenontosaurus, Dryosaurus, Liaoceratops, Yamaceratops, Leptoceratops, Bagaceratops and Protoceratops); lateral orientation of the basipterygoid process articular facet (char. 136; shared with Homalocephale, Prenocephale, Stegoceras and Yinlong); a straight dentary tooth row in lateral view (char. 166; shared with the ornithischians Lesothosaurus, Eocursor, Scutellosaurus, Pinacosaurus, Euoplocephalus, heterodontosaurids and neornithischians); the presence of a ventral flange on the dentary (char. 170; shared with Psittacosaurus, Yamaceratops and Protoceratops); a well-developed coronoid process (char. 174; shared with heterodontosaurids and neornithischians); a surangular length of more than 50% the mandibular length (char. 183; shared with Stegoceras, Psittacosaurus, Yinlong, Chaoyangsaurus and Hualianceratops); less than 15 dentary teeth (char. 204; shared with heterodontosaurids, Gasparinisaura, Hypsilophodon, Wannanosaurus, Tenontosaurus, Dryosaurus and ceratopsians); apicobasally tall and blade-like cheek teeth crowns (char. 205; shared with Laquintasaura, Psittacosaurus, Yinlong, Chaoyangsaurus and Hualianceratops). Alternative phylogenetic analyses using the data matrices of Maidment et al.4, Norman6 and Wiersma and Irmis8 recover Jakapil as the sister taxon of Eurypoda (Stegosauria + Ankylosauria) and as a basal ankylosaur, respectively (see Supplementary Information). Being recovered either as an ankylosauromorph or a stem-eurypodan, Jakapil is closely related to Scelidosaurus in all analyses. Detailed phylogenetic results and discussion are provided in the Supplementary Information.Figure 5Time-calibrated strict consensus of 26,784 most parsimonious trees (L = 1267) with the Soto-Acuña et al.5 matrix. CI 0.359, RI: 0.708. Branch supports are figured (Bremer/bootstrap). Record ages references are listed in the Supplementary Information (Suppl. Fig. 4).Full size image More

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    Invasion stages help resolve Darwin’s naturalization conundrum

    Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.This is a summary of: Omer, A. et al. The role of phylogenetic relatedness on alien plant success depends on the stage of invasion. Nat. Plants https://doi.org/10.1038/s41477-022-01216-9 (2022). More

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    Large carnivores and naturalness affect forest recreational value

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    Statistically enriched geospatial datasets of Brazilian municipalities for data-driven modeling

    The procedure began by obtaining the boundaries of Brazil’s municipalities, which are the most precise spatial reference units available from the Brazilian Ministry of Health of data records on diseases and health events. The boundaries were obtained from the geographic database of the Brazilian Institute of Geography and Statistics (IBGE)11, corresponding to the territorial grid of 2015, with a total of 5,570 Brazilian municipalities.A broad and diverse set of thematic data was used to compose the datasets, spanning a range of time periods (from 1981 to 2021) according to the temporal regularity of individual layers (annual, quinquennial, atemporal, or without temporal regularity), thus covering spatial and temporal variations over Brazil’s territory. It is worth noticing that during the period of 1981 to 2021 the number of municipalities grew from 3991 to 557012, which of course led to major changes to their boundaries, in addition to the creation of the state of Tocantins in 1988 as a result of the division of the state of Goiás13. Most of the changes, though, are subdivisions of one municipality into two or more municipalities. To provide statistics that are invariant over the period we would have to resort to using clusters of municipalities (“artificial municipalities”) by means of the Minimum Comparable Areas (MCA) strategy14. Due to the time-consuming process we preferred to characterize only the current territorial division, thus providing the most refined statistical characterization of Brazil’s municipalities. Still, one can find it useful to aggregate our characterization according to an MCA territorial division; for that we refer the reader to the article by Ehrl14.A total of 19 thematic layers were used, obtained from different Brazilian government and international agencies (Tables 1 and 2, illustrated by Figs. 1–4). Each layer may have multiple thematic classes or variables, depending on the nature of the theme, totaling 642 thematic classes or variables. For each class, 18 descriptive statistics were calculated (9 raw statistics plus 9 normalized by municipality’s area–Table 3) for all the available years, totaling 11,556 attributes per municipality.Table 1 Thematic layers comprising the dataset collection.Full size tableTable 2 Original data format, resulting geometry, unit and scale/resolution of the thematic layers.Full size tableFig. 1Examples of thematic layers with annual temporality in the territorial extension of the municipality of Rio de Janeiro.Full size imageFig. 2Examples of atemporal and no temporal regularity thematic layers in the territorial extension of the municipality of Rio de Janeiro.Full size imageFig. 3Examples of bioclimatic variables from Worldclim in the territorial extension of the municipality of Rio de Janeiro.Full size imageFig. 4Climate data for total precipitation, maximum, mean and minimum temperature from Worldclim in the territorial extension of the municipality of Rio de Janeiro for the month of January.Full size imageTable 3 Statistics calculated for the features/variables in the scope of the municipalities.Full size tableThe annual thematic layers for land use and land cover include 25 thematic classes from 1985 to 2020 for the entire Brazilian territory with spatial resolution of 30 m. (Except for the Fernando de Noronha archipelago, municipality geocode 260545, for which there is no land user/cover data due to the absence of historical series Landsat satellite images for that region.) These layers were produced and made available by the online platform MapBiomas15, collection 6.0. Annual land use and land cover maps were produced via automatic classification processes applied to Landsat satellite images16. The MapBiomas Project is a multi-institutional initiative coordinated by the Greenhouse Gas Emissions Estimation System (SEEG) from the Climate Observatory’s and consists of a collaborative network of cocreators including nongovernmental organizations (NGOs), universities, and companies. The objective is to produce annual land cover and land use maps of Brazil from 1985 to the present.The annual temperature and precipitation layers include 19 different types of data from 1981 to 2020 for the entire land surface, with spatial resolution of 5 km (0.05°). These fields were derived from two different observational gridded datasets, one for precipitation and another for temperature. The observed precipitation came from the Climate Hazards Group Infrared Precipitation with Stations data (CHIRPS)17, with a daily temporal resolution and a spatial resolution of approximately 5 km (0.05°). The observed temperature drawn from the NCEP Climate Forecast System Reanalysis (NCEP/CFSR)18 at a 6-hour temporal resolution and a spatial resolution of approximately 50 km (0.5°). The NCEP/CFSR gridded dataset was spatially downscaled to a higher spatial resolution of 5 km (0.05°) using bilinear interpolation in order to have the same spatial resolution as CHIRPS. (As with land use and land cover, there is no temperature/precipitation data for the Fernando de Noronha archipelago (geocode 260545).)The quinquennial layers for Population Count and Population Density were obtained from the Socioeconomic Data and Applications Center (SEDAC)19 through NASA’s Earth Observing System Data and Information System (EOSDIS), and is hosted by the Center for International Earth Science Information Network (CIESIN) at Columbia University. This dataset estimates the population count for the years 2000, 2005, 2010, 2015 and 2020, based on national censuses and population records, and is available in raster graphics with spatial resolution of 1 km. The official population demographics data from IBGE census is not used because it is available only as a tabular data aggregate count per census sector or municipality and therefore cannot yield meaningful descriptive statistics.Atemporal data include the following themes: Climatological Normals for Temperature; Altitude; Geomorphology; Soils; Phytophysiognomies; and Biome boundaries. Climatological Normals for Temperature came from Worldclim20 and correspond to observational data, representative of 1950 to 2000, which were interpolated to a resolution of 1 km. These temperature values are in degree Celsius, but for historical reasons they are scaled by a factor of 10. The used mean, minimum and maximum values of temperature include information from different remote sensors onboard the MODIS and NOAA satellites which operate to jointly capture surface temperature and air humidity values. Besides the annual temperature data, we also included climatological normal data because they provide monthly mean values for temperature. These values complement the annual information (considerably influenced by climate events like El Niño and La Niña) and serve as an important reference on seasonal temperature variation patterns, a factor that directly influences the reproduction and survival dynamics of species such as vectors. The altitude data came from NASA’s Shuttle Radar Topography Mission digital elevation model (SRTM) 1 ArcSecond Global, conceived to provide consistent high-quality near-global elevation data21. The original data are radar images with spatial resolution of 30 m, version 3, reprocessed to fix inconsistencies and fill missing data (“voids”). The other themes–Geomorphology, Soils, Phytophysiognomies, and Biome boundaries–were obtained from IBGE22. These provides regional details, and were constructed from interpretation of satellite images and various field studies throughout Brazil beginning in 199023.The layers without temporal regularity include: Mining Areas; Roads; Railways; Waterways or watercourses; Hydroelectric Plants; Dams; Conservation Units; Indigenous Lands; and Zone Climates and Regional Subunits. The Mining Areas layer has 336 classes, representing the different types of minerals explored in Brazil’s territory, provided by the Brazilian National Mining Agency (ANM). The boundaries of Conservation Units were provided by the Brazilian Ministry of Environment (MMA). The other layers are single classes of Roads, Railways, Waterways/watercourses, Hydroelectric Plants, Dams, obtained from the Continuous Cartographic Bases24 and Indigenous lands and Quilombola territories25, all this datasets from IBGE. The roads category comprises all its available classifications, covering data from subcategories such as highways and dirt roads. The same unification was adopted for the railways and waterways categories. The layer on Zone Climates and Regional Subunits represents the different climate zones in Brazil’s territory, grouped by temperature and humidity. This layer also identifies the climate types, characterized by shades and hues: tropical, subtropical, mild mesothermal, and median mesothermal26.Considering the heterogeneity of the data sources and the structural particularities of the thematic layers acquired, it was essential to conduct a pre-processing and structuring stage with the datasets in order to proceed with the calculation of the descriptive statistics. All the raw data, whose total size amounted to 195 GB, were pre-processed in QGIS v3.1027. This stage required standardizing the geospatial data’s cartographic characteristics, correcting topological errors, eliminating duplicate information, and uniformizing the attribute tables. The data were generally organized in two major groups: vector data and matrix data (raster).To be able to process the Land Use and Land Cover features at the original 30 m spatial resolution, we had first to break down each annual raster (1985 to 2020) into 5,569 smaller raster pieces, one for each municipality, by using the gdalwarp tool from the Geospatial Data Abstraction Library (GDAL). Next, we converted all the resulting rasters to vector format (geopackage) via the script gdal_polygonize.py, also from GDAL. The conversion was necessary because the vector format (geopackage) allowed the calculation of the polygons’ statistics for all the Land Use and Land Cover features, which is not possible with the raster format with the techniques and functions used (described in the Code availability section). All that pre-processing took about 600 hours running in parallel on an Intel Core i7 computer with 8 physical CPU cores and 64 GB of RAM.The data on Temperature, Precipitation, Population Count/Density, Altitude, and Climatological Normals, also provided in matrix format, were converted to point geometry, since they are inherently points but which had been interpolated by their sources before making them available. The conversion of Altitude from raster to vector was the most computationally demanding operation due to the need to process 10.6 billion points (spread across 821 tiles of 3601 × 3601 points each) at the resolution of 30 m. It took about one month of uninterrupted parallel processing on a 20-core Intel Xeon E5-2690 machine with 128 GB of RAM.For the vector data, it was first necessary to homogenize the cartographic references using South America Albers Equal Area Conic (EPSG:102033) for data requiring calculation of areas (polygons), South America Equidistant Conic (EPSG:102032) for data requiring calculation of distances (lines), and SIRGAS 2000 Geodetic Reference (EPSG:4674) for data with restricted localization (points)28. It was also necessary to correct some topological errors in the vector data regarding the line and polygon geometries, which are artifacts introduced during the data construction/vectorization stage. The vector data correspond to the following themes: Geomorphology; Soils; Phytophysiognomies; Biome Boundaries; Mining Areas; Roads; Railways; Waterways or watercourses; Hydroelectric Plants; Dams; Conservation Units; Indigenous lands and Quilombola territories; Zone Climates and Regional Subunits.For the statistical description of the municipalities’ socioenvironmental characteristics, we calculated the measures of central tendency such as mean and median, and measures of dispersion such as maximum and minimum values, standard deviation, and percentiles. For each descriptive statistic we also calculated a corresponding normalized statistic, simply dividing the original statistics value by the municipality’s area. The values were normalized due to the wide variation in the territorial area of Brazil’s municipalities. For example, Altamira, in the state of Pará, is Brazil’s largest municipality, with an area of 159,533 km2, while Santa Cruz de Minas, in the state of Minas Gerais, is the smallest one, with only 3,565 km2 29. This wide territorial variability might otherwise skew the modeling towards the identification of distorted correlations, such as the identification of relations between higher proportions of natural or anthropic features and higher concentration of cases, which is merely due to the municipality’s larger territorial dimensions.Based on structuring of the graphic, we executed a spatial data intersection with the municipal boundaries by means of different routines from PostGIS30, an extension that adds spatial and geographic objects to the PostgreSQL object-relational database.Calculation of the descriptive statisticsThe meaning of the statistics described in Table 3 actually depends on both feature’s geometry and unit of measurement, which are reported in Table 2 for each thematic layer.For polygons, such as conservation units, the area of each unit is computed in square meters and the set of all conservation units’ areas in the municipality forms the statistical population upon which the descriptive statistics will be calculated for that municipality. This means that the minimum statistic will refer to the smallest area among the conservation units in the municipality, the mean statistic to the average area, the count statistic will refer to the number of conservation units in the municipality, and so forth. Analogously, when the feature type is line, e.g. roads, the set of all road stretches’ lengths (in meters) is the statistical population.The procedure differs a bit for point features, such as altitude and temperature. In this case, except for the count statistic (which refers to the number of points in the municipality), the actual value at each feature point is taken; for instance, the altitude and temperature at a given location. Differently from the polygons and line cases, the associated unit cannot be predefined (in square meters or meters), and it will depend on the actual unit of the underlying layer–for altitude it is meters, but for temperature it could be either Celsius or Kelvin. Some point-type features, such as hydroelectric plants, do not have a unit per se, i.e. they merely refer to a quantity. Once the set of all point-type feature values are taken, we have a statistical population of values and the calculation of the statistics proceeds exactly as described with the other two feature types.For each descriptive statistic, there is a corresponding normalized one which is calculated by dividing the statistic by the municipality’s area (in m2). Those normalized statistics complement the set of descriptive information and provide the notion of proportion or density. As an example, the statistic sum_normalized corresponds to the percentage of occupation of a given polygon-type thematic layer in the municipality, or an estimation of density for line-type layers such as roads. More

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