This dataset was created in order to document the analysis of the manuscrit "Experienced climate change impacts help explain subjective well-being. Evidence from 14 nature-dependent communities". Climate change profoundly affects well-being in complex and interconnected ways. However, the relationship between climate change and well-being has been explored in only a handful of settings, most of which are industrialized. Here, we investigate the association between perceived climate change impacts, their severity, and subjective well-being, measured as life satisfaction. Using cross-culturally comparable first-hand reports from 2,488 participants across 14 nature-dependent communities, we find a negative association between site-aggregated life satisfaction and three metrics of climate change: perceptions of local impacts, reported severity, and an instrumental index. Within sites, individual-level associations between perceived severity of climate change impacts and life satisfaction are weak or absent, which could indicate that the between-site correlation reflects the overall exposure and vulnerability of each site to climate change. Further analysis suggests that site-level characteristics play a crucial role in shaping these patterns. Our findings offer a nuanced understanding of how climate change impacts relate to well-being, emphasize the multi-dimensional character of climate change impacts and underscoring the importance of local context in shaping these relationships.

Description of methods used for collection-generation of data - Data was collected from individual respondents using a globally-coordinated protocol, available at Reyes-García, V., S. Álvarez-Fernandez, P. Benyei, D. García-del-Amo, A.B. Junqueira, V. Labeyrie, X. Li, V. Porcher, A. Porcuna-Ferrer, A. Schlingmann, R. Soleymani. 2023. Local indicators of climate change impacts described by Indigenous Peoples and local communities: Study protocol. PLoS ONE 18(1): e0279847. https://doi.org/10.1371/journal.pone.0279847. Methods for processing the data - Data was entered by data collectors in a standardised online protocol. Quality-assurance procedures performed on the data - Data was checked for correctness, plausibility and coherence.