37
and economic decision-making, and centers of education and mental model development (Stafford Smith and Cribb 2009). While the dryland social-ecological context
has contributed to the formation of distinct local/traditional knowledge systems and
world views by distinct social and cultural groups, their geographic isolation often
triggers an extremely high level of social uncertainty, and little possibility for a prosperous life, economic growth and/or development (Stafford Smith et al. 2009).
Furthermore, local particularities and differences often generate unstable and disconnected governance between the local, regional, national, and international levels.
Based on this syndrome Reynolds et al. (2007) proposed the drylands development
paradigm (DDP) a useful integrative analytical framework for SESs to assess, mitigate, and inhibit land degradation and desertification consisting of five principles:
1. Social-ecological systems (SESs) are highly coupled, co-adapted, and interconnected and their dynamics can only be understood in a spatiotemporal context.
2. The underlying dynamics of SESs are controlled by a limited number of key
slow variables.
3. Crossing thresholds of these slow variables may move SES into different states
with similar structures and functions or into new regimes with changed structures and functions.
4. SESs are hierarchical, nested, and networked across multiple spatial and temporal scales.
5. Different knowledge systems including local environmental knowledge need to
be considered to allow functional coadaptation of SES.
To operationalize dryland development science in the context of the SDGS,
Stringer et al. (2017) propose to “upgrade” the DDP; they add three principles that
supposedly switch focus from research for development to research in
development:
Unpacking relationships and interactions in dryland systems and livelihood portfolios can help to identify opportunities and risks for socio-technical innovation
and investment to adapt to multiple interacting drivers of change at different
spatial and temporal scales.
Traversing scales and sectors can improve co-creation, availability of and access to
options, shaped and owned by land users and other value chain actors. This
enables more contextual, people-centered focus in assessing risks, trade-offs,
and vulnerabilities, supporting sustainable, resilient, and efficient pro-poor value
chains. A networked approach to value chains can enable context-specific analysis
and facilitate more inclusive, participatory governance reform.
Sharing knowledge, learning, and experience to empower dryland communities,
researchers, policymakers, and other stakeholders is important to reduce tradeoffs and externalities, leverage no-regrets options, and avoid unintended
consequences. This is especially important in drylands where feedbacks, uncertainties, and non-linearities characterize the system. Current knowledge is weakest in terms of understanding social processes such as social learning,
decision-making behavior, and power balances within coupled social-ecological
2 Sustainable Development Goals and Drylands: Addressing the Interconnection
and economic decision-making, and centers of education and mental model development (Stafford Smith and Cribb 2009). While the dryland social-ecological context
has contributed to the formation of distinct local/traditional knowledge systems and
world views by distinct social and cultural groups, their geographic isolation often
triggers an extremely high level of social uncertainty, and little possibility for a prosperous life, economic growth and/or development (Stafford Smith et al. 2009).
Furthermore, local particularities and differences often generate unstable and disconnected governance between the local, regional, national, and international levels.
Based on this syndrome Reynolds et al. (2007) proposed the drylands development
paradigm (DDP) a useful integrative analytical framework for SESs to assess, mitigate, and inhibit land degradation and desertification consisting of five principles:
1. Social-ecological systems (SESs) are highly coupled, co-adapted, and interconnected and their dynamics can only be understood in a spatiotemporal context.
2. The underlying dynamics of SESs are controlled by a limited number of key
slow variables.
3. Crossing thresholds of these slow variables may move SES into different states
with similar structures and functions or into new regimes with changed structures and functions.
4. SESs are hierarchical, nested, and networked across multiple spatial and temporal scales.
5. Different knowledge systems including local environmental knowledge need to
be considered to allow functional coadaptation of SES.
To operationalize dryland development science in the context of the SDGS,
Stringer et al. (2017) propose to “upgrade” the DDP; they add three principles that
supposedly switch focus from research for development to research in
development:
Unpacking relationships and interactions in dryland systems and livelihood portfolios can help to identify opportunities and risks for socio-technical innovation
and investment to adapt to multiple interacting drivers of change at different
spatial and temporal scales.
Traversing scales and sectors can improve co-creation, availability of and access to
options, shaped and owned by land users and other value chain actors. This
enables more contextual, people-centered focus in assessing risks, trade-offs,
and vulnerabilities, supporting sustainable, resilient, and efficient pro-poor value
chains. A networked approach to value chains can enable context-specific analysis
and facilitate more inclusive, participatory governance reform.
Sharing knowledge, learning, and experience to empower dryland communities,
researchers, policymakers, and other stakeholders is important to reduce tradeoffs and externalities, leverage no-regrets options, and avoid unintended
consequences. This is especially important in drylands where feedbacks, uncertainties, and non-linearities characterize the system. Current knowledge is weakest in terms of understanding social processes such as social learning,
decision-making behavior, and power balances within coupled social-ecological
2 Sustainable Development Goals and Drylands: Addressing the Interconnection