This dataset contains data and R code allowing to reproduce the multi-step modelling process carried out in the article: "Socioeconomic and land-use factors shape sustainable management in the Catalan Pyrenees". It features a collection of R scripts designed to specify a dynamical model based on the static network model of a Pyrenean social-ecological system implemented by Zango-Palau et al. (2024), explore trajectories leading to outcomes favourable to different local stakeholders' mental frameworks and identify key drivers behind the emergence of these different types of outcomes using a classification tree. Following this, the scripts subset the raw simulation outputs according to the classification tree predictions and explore the characteristics of the resulting subsets.

R, 4.3.1

Inkscape, 1.1.2

Original data sources used by Zango-Palau et al. (2024) were obtained from public databases containing hydrological, climatic, biodiversity, land use, and remote sensing–derived environmental data, as well as socioeconomic variables from the study area, covering the time period 2000-2020: • Redes de Seguimiento Del Estado e Información hidrológica, Confederación Hidrográfica del Ebro https://sig.mapama.gob.es/redes-seguimiento/index.html?herramienta=Aforos • WorldClim 2.1 https://doi.org/10.1002/joc.5086 • NASA’s Application for Extracting Analysis Ready Samples (AppEEARS) https://appeears.earthdatacloud.nasa.gov/ • Usos i cobertes del sòl de Catalunya (Grup de Recerca en Teledetecció i Sistemes d'Informació Geogràfica [Grumets, CREAF-UAB]) https://agricultura.gencat.cat/ca/detalls/Article/Usos-i-cobertes-del-sol-de-Catalunya • Catalan Monitoring Butterfly Scheme https://www.catalanbms.org/ca/itineraris/ • Spanish National Statistics Institute (INE) https://www.ine.es • Statistical Institute of Catalonia (Idescat) https://www.idescat.cat/ • Índices y Salarios Agrarios, Ministerio de Agricultura Pesca y Alimentación - Gobierno de España https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/economia/precios-percibidos-pagados-salarios/salarios-agrarios/default.aspx • Programas de Desarrollo Rural financiados por FEOGA, Ministerio de Agricultura Pesca y Alimentación - Gobierno de España https://www.fega.gob.es/sites/default/files/imported/PwfGcp/imagenes/es/DRPRESUP_2006_tcm5-18910.htm • Economic impact on the Common Agricultural Policy (CAP) subsidies in Catalonia. Summary data on payments for the 2025-2023 Rural Development Program http://data.europa.eu/88u/dataset/https-analisi-transparenciacatalunya-cat-api-views-xahw-cpn7

The files in the dataset are structured in 4 folders: (1) data: tabular data, (2) results: binary files, tabular data and images generated during the modelling process, (3) functions: R scripts implementing custom functions used in the modelling process, and (4) scripts: R scripts that read the data (or previous scripts' results) and functions, and generate results. Users can run the code following the specified order of the scripts to carry out the modelling process. The outputs (results) generated by the scripts follow the same numeration as the scripts. However, given the considerable amount of time and computational requirements for executing the scripts running simulations and classifying data into mental framework classes, we recommend loading the output RData of a script directly instead of re-running the code that generates it. Note that re-running the code might result in slight differences in the outputs compared to the originals due to differences in system environments or algorithm-specific nondeterminism.