Spatial variability in sustainable development trajectories in South Africa: provincial level safe and just operating spaces

Type Journal Article - Sustainability Science for Meeting Africa’s Challenges
Title Spatial variability in sustainable development trajectories in South Africa: provincial level safe and just operating spaces
Author(s)
Publication (Day/Month/Year) 2017
URL https://ueaeprints.uea.ac.uk/62840/
Abstract
The Sustainable Development Goals (SDGs)
represents the first globally agreed framework to address
human development and environmental stewardship in an
integrated way. One approach to summarising national SDG
status is our “barometer for inclusive sustainable development
in South Africa”. The barometer downscales global
social and planetary boundaries to provide status and trends
for 20 critical indicators of environmental stress and social
deprivation. In this paper, we explore the sub-national heterogeneity
in sustainable development indicators by creating
barometers defining the ‘safe and just operating space’
for South Africa’s nine provinces. Our results show that
environmental stress varies significantly and provinces
need to focus on quite different issues. Although generally
environmental stress is increasing, there are areas where it
is decreasing, most notably, marine harvesting. Social deprivation
results show more of a pattern with high levels of
deprivation in employment, income and safety across the
provinces, and historically disadvantaged provinces showing
the most deprivation overall. Although deprivation is
generally decreasing, there are notable exceptions such as
food security in six provinces. Our provincial barometers and trend plots are novel in that they present comparable
environmental and social data on key indicators over time
for all South Africa’s provinces. They are visual tools that
communicate the range of key challenges and risks that
provincial governments face, and are non-specialist and
accessible to a range of audiences. In addition, the paper
provides a critical case study of spatial disaggregation of
national data that is required for the SDGs implementation.

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