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This supplementary material consists of the survey questionnaire and the data set that gave rise to the article: Rural Landscape Simplification and Provision of Cultural Ecosystem Services. A Case Study in the Argentine Pampas publicado en el journal EARN Economía Agraria y Recursos Naturales. Agricultural and Resource Economics https://economiaagroalimentaria.es/en/earn-journal/ DOI: https://doi.org/10.7201/earn.2023.01.01 .

Heterodontosauridae is a clade that appears early in the ornithischian fossil record, and includes small-bodied, highly specialized species characterized by an unusual heterodont dentition. Although known from relatively few taxa, the early representation of the clade and unsolved phylogenetic relationships within heterodontosaurids and among early ornithischians implies that novel information has a marked effect on broader phylogenetic hypotheses and our understanding of early diversification patterns within Ornithischia. This paper describes the cranial osteology of the heterodontosaurid Manidens condorensis based on computed micro-tomographic scans of MPEF-PV 3211 and MPEF-PV 3809. This enabled more detailed descriptions of previously recognized bones, corrections to the literature, and the identification of undescribed elements. We present a new skull reconstruction and propose an emended diagnosis in light of novel anatomical information. Areas of jaw muscle attachment were identified and compared with Heterodontosaurus and Lesothosaurus, and mandibular function among heterodontosaurids is discussed. Our results indicate that diverse skull morphologies and functions existed among Early Jurassic ornithischians, with Manidens being intermediate between the plesiomorphic cranial shape and function associated with a generalist diet in ornithischians such as Tianyulong and Lesothosaurus, and the more derived cranial construction specialized for herbivory identified in heterodontosaurids from South Africa such as Heterodontosaurus.

The dataset consists of a spreadsheet containing data on GPS surveys, dynamic topography extracted from published models (gplates.org), Shell preservation scoring, Strontium Isotopic Stratigraphy ages, and Global mean Sea Level calculations. Fil: Aguirre, Marina Laura. Universidad Nacional de La Plata. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina. Fil: Richiano, Sebastián Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Geología y Paleontología; Argentina Facultad de Ciencias Naturales y Museo

The file Corpora.txt keeps the corpus used to train the model and the different instances of the classifier. It is basically a text file with one sentence per line from the original corpus called test.tsv available at https://github.com/google-research-datasets/wiki-split.git. We eliminated punctuation marks and special characters from the original file putting each sentence per line. Enju_Output.txt holds the outputs generated by Enju in -so mode (Output in stand-off format) using Corpora.txt as input. This file has basically a natural language English per-sentence parse with a wide-coverage probabilistic for HPSG grammar. The file Supervision.txt keeps the grammatical tags of the corpus. This file holds a tag per word and each tag is situated in a single line. Sentences are separated by one empty line while tags from words in the same sentence are located in adjacent lines. The file Word_Category.txt carries the coarse-grained word category information needed by the model and introduced in it by apical dendrites. Each word in the corpus has a word-category tag which provides additional constraints to those provided by lateral dendrites. This file contains a tag per word and each tag is situated in a single line. Sentences are separated by one empty line while tags from words in the same sentence are located in adjacent lines. The file SynSemTests.xlsx keeps all the grammar classification results as well as the statistical analysis in the classification tests.