Latin American-led climate research
Peer-reviewed methodology combining satellite data with social network analysis across five Latin American countries. Based in the Netherlands.
Published in Environmental Science and Policy (Elsevier)Affiliated with TU Delft
For institutional partners & funders
Rigorous climate and social vulnerability assessments of the Latin American coffee sector, grounded in peer-reviewed science and regional fieldwork.
Schedule a conversationFor coffee businesses & trade
Country-level risk assessments across a 10–30 year horizon, integrating environmental projections with stakeholder network analysis.
Request a country briefingFor researchers & collaborators
Join a growing network of Latin American and Caribbean researchers working on climate adaptation in the coffee sector.
View our publicationsThe challenge
Coffee-producing regions across Latin America and the Caribbean face an existential climate threat: rising temperatures at altitude, shifting precipitation, flooding, drought, and the return of leaf rust.
Yet the people who understand that threat most intimately — the farmers, the local researchers, the communities living it every day — have been systematically excluded from the conversation about how to respond. Most climate risk assessments for the sector stop at satellite observations and supply-chain modeling, treating the social dimension as anecdotal.
Dialectik was founded to close that gap. Our work is grounded in the conviction that climate adaptation without community engagement is incomplete — and that rigorous social science is as measurable, and as important, as environmental data. Addressing the crisis requires tools that treat both dimensions, the ecological and the social, with equal rigor.
Our approach
Satellite imagery, LiDAR, climate models, and hydrological analysis to map physical vulnerability across coffee-producing regions — current conditions and 10–30 year projections.
The SNPI framework quantifies stakeholder collaboration, trust-building, power-sharing, and social learning within coffee sector governance networks through rigorous network metrics.
Social and environmental dimensions are treated as co-equal analytical pillars, producing country-level vulnerability profiles, network performance scores, and adaptation recommendations.
Geographic scope
A dual-scale architecture: a regional vulnerability assessment of the Latin American and Caribbean coffee sector, anchored in country-level case studies conducted by regional researchers.
Published research
Our work is grounded in peer-reviewed research published in Environmental Science and Policy, one of the leading journals in environmental governance.
The team
Founder · Lead Researcher · Social Network Performance Indicators (SNPI)
Dr. Teodoro is the founder of Dialectik and the creator of the Social Network Performance Indicators (SNPI) framework — a systematic approach to quantifying the quality of stakeholder collaboration in environmental governance. His work has been published in Environmental Science and Policy (Elsevier) in both 2024 and 2026, and has been applied to fieldwork in El Salvador, Brazil, and Canada.
Co-founder · Geospatial Data Scientist
Dr. Diaz is Dialectik's environmental science counterpart — a Geospatial Data Scientist at TU Delft, Europe's premier technical university, and an expert in remote sensing, LiDAR observation, hydrological modeling, and drought and flood risk assessment. His work draws on satellite imagery, climate models, and large-scale environmental datasets to quantify physical vulnerability across landscapes.
Sustainability Scientist · PhD Candidate
Bridget is an interdisciplinary sustainability scientist focused on collaborative governance, water resources, and network analysis. Her research investigates how patterns of collaboration among decision-making actors reflect the spatial and logistical complexity of the environmental problems they address, drawing on social-ecological resilience thinking and a systems perspective.
Data Scientist
Rick is a data scientist with 8+ years of experience building end-to-end analytical and machine learning systems. His work spans recommender systems, time-series forecasting, statistical modeling, and applied NLP — translating messy, real-world data into evidence that supports decision-making.
Whether you represent an institutional funder, a coffee sector business, or a fellow research organization, we would welcome a conversation about how our work can support yours.
Schedule a conversation→Or write to us directly: hello@dialectik.tech
