Storytelling and participatory system dynamics modelling for water resources management in Lake Atitlán of Tz'olöj Ya' in Mayan Guatemala
Notice bibliographique
Résumé
Participatory system dynamics modelling is a useful tool for sociohydrological systems management due to its inclusion of diverse viewpoints and incorporation of feedback dynamics and delays between the human and environmental spheres. We here present a case study from the Lake Atitlán watershed in Guatemala, which is unique due to its endorheic nature, very long retention time, and diversity of human societies around it (Kaqchikel, Tz’utujil and K’iche’, as well as a Hispanic minority). The lake is under pressure from several sources and has become increasingly vulnerable to eutrophication in recent years. The lake is also central to the economy and ecology of the region, with diverse stakeholders including fishers, farmers, both traditional and youth-led Mayan organisations, NGOs, businesses, and municipalities and other levels of government. While effectively all participating stakeholders agree that the lake is under threat, there exist very differing narratives regarding the most pressing threat (pollution, biodiversity, or water availability) and therefore appropriate policy options. These differences vary significantly according to the ecosystem services each stakeholder obtains from the lake, as well as their own personal experiences and worldviews. Indigenous voices have also unfortunately been historically marginalised and often excluded from decision-making in environmental management. In this context, we applied a novel methodology incorporating storytelling and narratives coupled with causal loop diagrams to incorporate the points of view of all stakeholders, whether literate or not. The results from these individual interviews were used to compare visions and possible solutions, followed by the development of a coupled human-hydrological systems model as a decision support tool. In the coupled model development process, socioeconomic processes are represented in a system dynamics model, while hydrological processes are eventually "outsourced" to an external hydrological model (such as SWAT+). Using the Tinamït software package, these two models can then be simultaneously executed with data (e.g., land use and water quality) dynamically exchanged between both models at runtime. While most studies conducted in or on Indigenous regions and their peoples are conducted in European languages that exclude these very people from meaningful decision-making, all team members (both national and international) in this research project were chosen to be functional in at least one of the mutually intelligible Mayan languages spoken in the basin, and these languages were used as the official project language (while also providing services in Spanish for Hispanic stakeholders). This key aspect to our approach ensured that all stakeholders were equally included in the process, and that Indigenous students also had equal opportunities to be hired as part of the (decision-making) research team. We discuss how this methodology led to unique contributions to the model throughout the research process, from problem definition to identification of key system processes and candidate policy scenarios, and improved the quality of both the participatory and the modelling processes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».