20 Does the Use of Local Knowledge in Complex Systems …
463
biological systems in which they live. For societies that are reliant to a significant
degree on the use of natural resources, these changes take on both direct and indirect
aspects, since for such groups livelihoods do not provide a buffer against climate,
but are highly reliant upon it. Adaptation can be best seen as a process that involves
changes in a system to increase its coping range, rather than temporary adaptation
of historically familiar measures to cope with a transient threat.”
Adaptive capacity is “the ability of countries, communities, households and individuals to adjust in order to reduce vulnerability to climate variation, moderate potential damage, cope with, and recover from the consequences, including ecosystem
responses to climate forcing” (Thomas et al. 2005:7). The greater a system’s
resilience, the more it adapts to maintain its critical functions (adaptation capacities):
“resilience is the capacity of a system to absorb disturbance and reorganize while
undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks” (Walker et al. 2004:2). Points of no-return, at which the system
is unable to maintain its critical functions even after adaptation, are described as
tipping points.
4 Role of Governance, Participation, and Local Knowledge
From anthropology to social policy, an array of terminology and concepts has been
adopted in the study of climate change adaptation and governance, as well as management of natural resources in vulnerable societies. Examples are “social learning”
(Cundill 2010), “collective action” (Ratner et al. 2017), “social capital” (Adger 2003,
2013), “role of knowledge” (Lebel 2013), and “traditional ecological knowledge
(TEK)” (Berkes et al. 2000).
“Adaptive governance” as it is used by Pahl-Wostl et al. (2012) describes
water governance for “mastering complexity” in basins worldwide, including in
sub-Saharan Africa.
Most analyses of the role of knowledge in adaptive system governance and
management find that different types of knowledge improve system outcomes. Local
knowledge (Vedwan 2006), indigenous knowledge and participation (Nyong et al.
2007), local perceptions and understanding (Byg and Salick 2009; Chapagain et al.
2009; Lebel 2013), and the combination of local and scientific knowledge (e.g., Van
Cauwenbergh 2008; Vignola et al. 2009; Raymond et al. 2010; Alexander et al.
2011) all seem to enhance system outcomes, albeit with nuances, mostly related to
the institutions and the individuals or groups managing the knowledge, as well as the
role of knowledge brokers and moderators (Berkes et al. 2000; Thomas et al. 2005;
Agrawal 2010).
Participatory management and governance is widely promoted not only in relationship to water, natural resources, and climate change, but also as a general approach
to management of goods and services in a society. However, there is limited understanding of how to achieve the benefits of participation effectively (Van Cauwenbergh
et al. 2018). Whereas methods for stakeholder analysis (e.g., Reed 2008) are routinely
463
biological systems in which they live. For societies that are reliant to a significant
degree on the use of natural resources, these changes take on both direct and indirect
aspects, since for such groups livelihoods do not provide a buffer against climate,
but are highly reliant upon it. Adaptation can be best seen as a process that involves
changes in a system to increase its coping range, rather than temporary adaptation
of historically familiar measures to cope with a transient threat.”
Adaptive capacity is “the ability of countries, communities, households and individuals to adjust in order to reduce vulnerability to climate variation, moderate potential damage, cope with, and recover from the consequences, including ecosystem
responses to climate forcing” (Thomas et al. 2005:7). The greater a system’s
resilience, the more it adapts to maintain its critical functions (adaptation capacities):
“resilience is the capacity of a system to absorb disturbance and reorganize while
undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks” (Walker et al. 2004:2). Points of no-return, at which the system
is unable to maintain its critical functions even after adaptation, are described as
tipping points.
4 Role of Governance, Participation, and Local Knowledge
From anthropology to social policy, an array of terminology and concepts has been
adopted in the study of climate change adaptation and governance, as well as management of natural resources in vulnerable societies. Examples are “social learning”
(Cundill 2010), “collective action” (Ratner et al. 2017), “social capital” (Adger 2003,
2013), “role of knowledge” (Lebel 2013), and “traditional ecological knowledge
(TEK)” (Berkes et al. 2000).
“Adaptive governance” as it is used by Pahl-Wostl et al. (2012) describes
water governance for “mastering complexity” in basins worldwide, including in
sub-Saharan Africa.
Most analyses of the role of knowledge in adaptive system governance and
management find that different types of knowledge improve system outcomes. Local
knowledge (Vedwan 2006), indigenous knowledge and participation (Nyong et al.
2007), local perceptions and understanding (Byg and Salick 2009; Chapagain et al.
2009; Lebel 2013), and the combination of local and scientific knowledge (e.g., Van
Cauwenbergh 2008; Vignola et al. 2009; Raymond et al. 2010; Alexander et al.
2011) all seem to enhance system outcomes, albeit with nuances, mostly related to
the institutions and the individuals or groups managing the knowledge, as well as the
role of knowledge brokers and moderators (Berkes et al. 2000; Thomas et al. 2005;
Agrawal 2010).
Participatory management and governance is widely promoted not only in relationship to water, natural resources, and climate change, but also as a general approach
to management of goods and services in a society. However, there is limited understanding of how to achieve the benefits of participation effectively (Van Cauwenbergh
et al. 2018). Whereas methods for stakeholder analysis (e.g., Reed 2008) are routinely