TY - JOUR
T1 - Adapting East and Southern Africa’s livestock to climate change
T2 - a decision making under deep uncertainty-based approach for effective actions
AU - Mohamed, Issa Awal
AU - Schaeffer, Michiel
AU - Baarsch, Florent
N1 - Publisher Copyright:
© 2024 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024/10/17
Y1 - 2024/10/17
N2 - Livestock farmers are increasingly challenged to adapt to the impacts of climate change, necessitating the selection of adaptation strategies to effectively mitigate risks and protect livelihoods. This paper introduces a framework designed specifically for guiding the selection of context-specific adaptation options in the Eastern and Southern Africa region. The framework builds on a decision tree that incorporates changes within a management system or switching to another one, enabling a nuanced evaluation of adaptation options. Driven repetitively under different scenarios of climate changes and/or climate models, the frequencies of selecting different adaptation measures vary across livestock value chains, climate zones, and systems. Responding to the evolution of the climate system, these frequencies evolve over time, affecting the selection. For instance, agroforestry emerges as an increasingly suitable option for cattle and, to a lesser extent, for goats due to the projected rise in moderate heat stress periods, particularly in tropical climates. Conversely, this frequency decreases for sheep, more susceptible to heat stress, beyond the effect of agroforestry. This framework resolves the need for more context–and time-specific decisions on adaptation. This decision tree-based framework serves as a robust decision-making tool to steer the livestock sector toward effective climate change adaptation.
AB - Livestock farmers are increasingly challenged to adapt to the impacts of climate change, necessitating the selection of adaptation strategies to effectively mitigate risks and protect livelihoods. This paper introduces a framework designed specifically for guiding the selection of context-specific adaptation options in the Eastern and Southern Africa region. The framework builds on a decision tree that incorporates changes within a management system or switching to another one, enabling a nuanced evaluation of adaptation options. Driven repetitively under different scenarios of climate changes and/or climate models, the frequencies of selecting different adaptation measures vary across livestock value chains, climate zones, and systems. Responding to the evolution of the climate system, these frequencies evolve over time, affecting the selection. For instance, agroforestry emerges as an increasingly suitable option for cattle and, to a lesser extent, for goats due to the projected rise in moderate heat stress periods, particularly in tropical climates. Conversely, this frequency decreases for sheep, more susceptible to heat stress, beyond the effect of agroforestry. This framework resolves the need for more context–and time-specific decisions on adaptation. This decision tree-based framework serves as a robust decision-making tool to steer the livestock sector toward effective climate change adaptation.
KW - Adaptation
KW - decision tree
KW - DMDU
KW - livestock
UR - http://www.scopus.com/inward/record.url?scp=85206905984&partnerID=8YFLogxK
U2 - 10.1080/17565529.2024.2415397
DO - 10.1080/17565529.2024.2415397
M3 - Article
AN - SCOPUS:85206905984
SN - 1756-5529
JO - Climate and Development
JF - Climate and Development
ER -