This project collated and synthesized evidence on the development outcomes of investments in nature (protection, restoration, management, creation of ecosystem, and nature-based food production). This includes conservation interventions and more recently labelled “nature-based solutions” to societal challenges. The scope of development outcomes considered was broad, ranging from jobs, food security, empowerment, to climate change resilience for local people in poor (low- and lower-middle-income).
Themes: Economics of NbS
The aim of this project is to unpack the contribution of NbS to short term economic recovery potential (ERP), and how this relates to long term development gain, while framing these in a policy setting in a way that supports systemic change. In other words we seek to explore the extent to which NbS make economic sense, and how (or not) this contributes to climate, and biodiversity outcomes. The intention is to contribute to policy guidelines around how to integrate NbS into economic recovery packages. As well as conducting a global systematic review of reviews of the ERP of investments in NbS, we are conducting detailed case study work in Peru and Bangladesh.
This systematic evidence mapping exercise consolidated the large dispersed evidence-base on the effectiveness of NbS for addressing climatic impacts. The collated evidence-base underpins the NbS evidence platform. The objectives were to:
- Identify existing evidence of the effectiveness of NbS for addressing different climate impacts on people and economic sectors, and catalogue evidence with respect to geography, country income group, climate impact addressed, ecosystem type, and type of intervention.
- Elucidate the synergies and/or trade-offs between climate impact reduction and greenhouse gas (GHG) mitigation, ecological, and social outcomes.
- Highlight knowledge-gaps to stimulate further research, especially on the extent to which geographical regions, ecosystems, intervention types and climate impacts are understudied.
We are currently updating our platform to include the outcomes of scenario modelling studies, and working with colleagues from the department of statistics to develop AI technological to enable more regular updating of the evidence base.