42
for example, global climate change, poverty, eutrophication, and biotic diversity.
Finally, the DPSIR framework has historically been developed and used for presenting environmental impacts caused by socio-economic driving forces. Analyses of
socio-economic system state conditions and impacts (e.g. HIV/AIDS, malaria, and
poverty) have seldom been included in such analyses—thusly not reflecting the
broad variety of sustainability challenges (Ness et al. 2010). To address many of the
deficiencies along with making the scheme more useful for targeted areas, DPSIR
has continued to be developed and augmented by scholars and practitioners to
include, amongst numerous others, the ‘EBM-DPSER’ concentrating on ecosystem
services (Kelble et al. 2013), the ‘DPSWR’ on human welfare (O’Higgins et al.
2014), the ‘eDPSEEA’ for Health (Reis et al. 2015), and the multi-level DPSIR
(Ness et al. 2010).
3.3.3 Causal Loop Diagrams
A causal loop diagram (CLD) is a general approach to the qualitative analysis of
systems; CLDs incorporate both human and social parameters into a single, sometimes sophisticated, conceptualization. They are often used as a part of a broader
participatory systems analysis approach, including problem and system boundary
definition, qualitative conceptualization creation, and quantitative system dynamics
modeling. A strength of CLDs is that they are a flexible framework where creators
identify and describe, in increasing levels of complexity, the cause-effect relationships of different sub-components of a larger system. Arrows are used to link causeeffect relationships, connecting the two components.
The diagrams use different symbols to denote different relationships. A positive
plus [+] symbol between two variables indicates a parallel behavior of the two,
meaning an increase in the causative variable also causes the effect variable to
increase; furthermore, a decrease in the causative variable denotes a decrease in the
affected variable. Conversely, a negative minus [−] symbol indicates an inverse
relationship between the two variables, meaning as the causative variable increases,
the affected variable decreases, or vice-versa. Numerous sub-components of a system can form loops, feeding back on one another, either directly or indirectly. A
loop that has a reinforcing behavior is often denoted in the diagram with ‘R’; this
signifies exponential growth of that subsystem. Loops denoted with ‘B’ indicate a
balancing behavior of the subsystem. Temporal aspects in the form of time lags can
also be identified in the CLD using two parallel lines through the center of the arrow
linking the variables. An example of a simplistic CLD for bush encroachment in
southern Africa is shown in Fig. 3.2 (SAPECS 2016). The arrangement shows the
causal relationships of two drivers of global climate change and human population
growth in the region and their ultimate impacts on such factors as woody plant
growth, land area and water availability.
B. Ness
for example, global climate change, poverty, eutrophication, and biotic diversity.
Finally, the DPSIR framework has historically been developed and used for presenting environmental impacts caused by socio-economic driving forces. Analyses of
socio-economic system state conditions and impacts (e.g. HIV/AIDS, malaria, and
poverty) have seldom been included in such analyses—thusly not reflecting the
broad variety of sustainability challenges (Ness et al. 2010). To address many of the
deficiencies along with making the scheme more useful for targeted areas, DPSIR
has continued to be developed and augmented by scholars and practitioners to
include, amongst numerous others, the ‘EBM-DPSER’ concentrating on ecosystem
services (Kelble et al. 2013), the ‘DPSWR’ on human welfare (O’Higgins et al.
2014), the ‘eDPSEEA’ for Health (Reis et al. 2015), and the multi-level DPSIR
(Ness et al. 2010).
3.3.3 Causal Loop Diagrams
A causal loop diagram (CLD) is a general approach to the qualitative analysis of
systems; CLDs incorporate both human and social parameters into a single, sometimes sophisticated, conceptualization. They are often used as a part of a broader
participatory systems analysis approach, including problem and system boundary
definition, qualitative conceptualization creation, and quantitative system dynamics
modeling. A strength of CLDs is that they are a flexible framework where creators
identify and describe, in increasing levels of complexity, the cause-effect relationships of different sub-components of a larger system. Arrows are used to link causeeffect relationships, connecting the two components.
The diagrams use different symbols to denote different relationships. A positive
plus [+] symbol between two variables indicates a parallel behavior of the two,
meaning an increase in the causative variable also causes the effect variable to
increase; furthermore, a decrease in the causative variable denotes a decrease in the
affected variable. Conversely, a negative minus [−] symbol indicates an inverse
relationship between the two variables, meaning as the causative variable increases,
the affected variable decreases, or vice-versa. Numerous sub-components of a system can form loops, feeding back on one another, either directly or indirectly. A
loop that has a reinforcing behavior is often denoted in the diagram with ‘R’; this
signifies exponential growth of that subsystem. Loops denoted with ‘B’ indicate a
balancing behavior of the subsystem. Temporal aspects in the form of time lags can
also be identified in the CLD using two parallel lines through the center of the arrow
linking the variables. An example of a simplistic CLD for bush encroachment in
southern Africa is shown in Fig. 3.2 (SAPECS 2016). The arrangement shows the
causal relationships of two drivers of global climate change and human population
growth in the region and their ultimate impacts on such factors as woody plant
growth, land area and water availability.
B. Ness