From local knowledge to global patterns: a cross-cultural study of the dimensions of hazards and adaptive capacity

Understanding the human impacts of environmental hazards is a growing concern. While there is a plethora of research on climate adaptation, the literature is highly fragmented, and empirical studies are rarely carried out with global samples. This lack of comparative work limits our ability to understand general patterns in how societies adapt, thereby impeding effective policy and practice at a wider scale. To fill this gap, we outline a global comparative approach to the study of hazards that uses ethnographic data. The approach operationalizes five ecological dimensions of environmental hazards, including event type, frequency, onset speed, predictability, and severity, and investigates how they relate across a world-wide sample of 132 nonindustrial societies with significant variation in time and space. We then utilize this approach to explore how specific ecological dimensions might influence the adaptive capacity of societies to respond to events. Findings uncover generalizable patterns that exist across our global sample, suggesting that predictability enhances adaptive capacity, while temporal factors that promote uncertainty (including slow onset speed, longer event duration, and unpredictability) limit the success of adaptation efforts.

Authors

Publication Details

Journal
International Journal of Disaster Risk Reduction
Published
2025-12-05
DOI
https://doi.org/10.1016/j.ijdrr.2025.105950
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From local knowledge to global patterns: a cross-cultural study of the dimensions of hazards and adaptive capacity

Carol R. Ember, I. A. Raja, Danielle Russell, Michele J. Gelfand et al.
International Journal of Disaster Risk Reduction
Disaster Management and Resilience
article

From local knowledge to global patterns: a cross-cultural study of the dimensions of hazards and adaptive capacity

Carol R. Ember, I. A. Raja, Danielle Russell, Michele J. Gelfand, Eric C. Jones, J. Heitmann, Cynthiann Heckelsmiller, Anj Lee Droe, Samantha K. King, Sebastian Wang Gaouette
article en

Abstract

Understanding the human impacts of environmental hazards is a growing concern. While there is a plethora of research on climate adaptation, the literature is highly fragmented, and empirical studies are rarely carried out with global samples. This lack of comparative work limits our ability to understand general patterns in how societies adapt, thereby impeding effective policy and practice at a wider scale. To fill this gap, we outline a global comparative approach to the study of hazards that uses ethnographic data. The approach operationalizes five ecological dimensions of environmental hazards, including event type, frequency, onset speed, predictability, and severity, and investigates how they relate across a world-wide sample of 132 nonindustrial societies with significant variation in time and space. We then utilize this approach to explore how specific ecological dimensions might influence the adaptive capacity of societies to respond to events. Findings uncover generalizable patterns that exist across our global sample, suggesting that predictability enhances adaptive capacity, while temporal factors that promote uncertainty (including slow onset speed, longer event duration, and unpredictability) limit the success of adaptation efforts.

International Journal of Disaster Risk ReductionVol. 132
Openalex Percentile: Top 52%
Disaster Management and Resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.