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Modeling pastoralist movement in response to environmental variables and conflict in Somaliland: Combining agent-based modeling and geospatial data.
Nelson, Erica L; Khan, Saira A; Thorve, Swapna; Greenough, P Gregg.
Afiliação
  • Nelson EL; Harvard Humanitarian Initiative, Harvard University, Cambridge, Massachusetts, United States of America.
  • Khan SA; Division of Global Emergency Medicine and Humanitarian Programs, Department of Emergency Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
  • Thorve S; Harvard Humanitarian Initiative, Harvard University, Cambridge, Massachusetts, United States of America.
  • Greenough PG; Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.
PLoS One ; 15(12): e0244185, 2020.
Article em En | MEDLINE | ID: mdl-33378352
ABSTRACT
Pastoralism is widely practiced in arid lands and is the primary means of livelihood for approximately 268 million people across Africa. Environmental, interpersonal, and transactional variables such as vegetation and water availability, conflict, ethnic tensions, and private/public land delineation influence the movements of these populations. The challenges of climate change and conflict are widely felt by nomadic pastoralists in Somalia, where resources are scarce, natural disasters are increasingly common, and protracted conflict has plagued communities for decades. Bereft of real-time data, researchers and programmatic personnel often turn to post hoc analysis to understand the interaction between climate, conflict, and migration, and design programs to address the needs of nomadic pastoralists. By designing an Agent-Based Model to simulate the movement of nomadic pastoralists based on typologically-diverse, historical data of environmental, interpersonal, and transactional variables in Somaliland and Puntland between 2008 and 2018, this study explores how pastoralists respond to changing environments. Through subsequent application of spatial analysis such as choropleth maps, kernel density mapping, and standard deviational ellipses, we characterize the resultant pastoralist population distribution in response to these variables. Outcomes demonstrate a large scale spatio-temporal trend of pastoralists migrating to the southeast of the study area with high density areas in the south of Nugaal, the northwest of Sool, and along the Ethiopian border. While minimal inter-seasonal variability is seen, multiple analyses support the consolidation of pastoralists to specifically favorable regions. Exploration of the large-scale population, climate, and conflict trends allows for cogent narratives and associative hypotheses regarding the pastoralist migration during the study period. While this model produces compelling associations between pastoralist movements and terrestrial and conflict variables, it relies heavily on assumptions and incomplete data that are not necessarily representative of realities on the ground. Given the paucity of data regarding pastoralist decision-making and migration, validation remains challenging.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pradaria / Gado / Migração Humana Tipo de estudo: Prognostic_studies Limite: Animals / Humans País/Região como assunto: Africa Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pradaria / Gado / Migração Humana Tipo de estudo: Prognostic_studies Limite: Animals / Humans País/Região como assunto: Africa Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos