Bottom-up systems approaches to optimize nature-based solutions (NbS) for climate change mitigation and adaptation (CCMA) in tropical agricultural landscapes (OP2227)

Forest landscape restoration including agroforestry is a nature- based solution (NbS) [1], widely practiced in tropical countries, for climate change mitigation and adaptation (CCMA) [2], biodiversity and human wellbeing. Yet, consensus and evidence are lacking on the optimum mix and spatial disposition of trees and forests in the agricultural matrix to deliver CCMA, particularly when balancing against trade-offs with biodiversity and human wellbeing. So far, the science has been dominated by analysis at the coarse spatial scale looking for narrowly defined carbon and biodiversity benefits [3] using oversimplified frameworks [4]. These don’t capture real landscapes, socio-economic systems and biodiversity domains in which actions are being implemented by different stakeholders [5]. The PHD will work with case partner IUCN Sustain, who worked across multiple landscapes in Africa, to adapt and apply a systems approach framework to analyse how tree:cropland configurations and management alter climate change mitigation and adaptation in rural tropical landscapes. Method steps: ‘synthesis of relevant ecological and social data and narratives and adaptation of the system model’ we recently developed (Question 1 & 2) and ‘participatory analysis of trade-offs for baseline and scenarios’ (Question 3). The focus is on systems in Tanzania, building on robust collaborations established through funded research: ‘What to plant, when and where’ (2019-21), the ‘Forest Restoration & Climate Experiment’ (2018 – 23), ‘Wildlife Corridor Restoration’ (2021-22). GCRF-Agriculture and Food System Resilience (2017-22).