Typologies and outcomes of ecological infrastructure restoration investment models

Authors:
Stephanie Midgley

Publication Date:
2019

Abstract/Summary:
A sizable investment gap exists in South Africa for the sustainable and scaled funding of landscape-wide interventions to restore and/or rehabilitate functionally critical ecological infrastructure (EI). Such interventions have considerable potential to address water insecurity and contribute to the development of sustainable livelihoods. The analysis of existing EI restoration investment models can reveal the characteristics of the current investment landscape, provide a generalised understanding of effective implementation models amidst local complexities, establish the suitability for up- and outscaling, identify gaps, and interrogate barriers to investment. We used existing documentation and stakeholder interviews to compile an inventory of water-related EI interventions in the Berg-Breede and uMngeni catchments, South Africa. Analysis revealed eight typologies, which were refined and validated through a stakeholder process, and subjected to a post-hoc analysis to determine (dis)similarities of characteristics. Key distinguishing characteristics between contrasting typologies included the complexity and size of financial flows, the complexity of partnership arrangements, the changeability of mandates and goals at each funding step, the type of EI being restored/rehabilitated, and the model used (and constraints) for contracting workers. Four scalable typologies were identified that offer opportunities for greater investment across spatial scales with other typologies offering contextualised value in close collaboration with local communities. We conclude that a range of EI intervention typologies with differing biophysical and socioeconomic outcomes should be available to different types of investors. New models of investment from private sources are needed to augment the current, mostly public investment profile.

Resource Type:
Audio/Video, Conference Presentation, SER2019

Source:
SER Webinar Library