Feeding the world's growing population while bending the curve of biodiversity losses and minimizing environmental impacts of food production is on top of the global agenda. Nowadays, agricultural diversification practices, which apply farm-based agroecological principles, have been promoted as prominent solutions for sustainable food production, and maintain ecosystem services and biodiversity without compromising yield. In parallel, technological advances in agriculture have been advocated to primarily boost yield and increase farmers' incomes. Yet, to this date, agricultural diversification and technological innovations are mostly treated as two separate solutions, hence, little is known about the environmental and economic benefits when technologies are integrated within diversified agricultural systems.
In this session, we will discuss and highlight the potential uses of technologies with agricultural diversification to monitor and manage tropical crops to promote biodiversity conservation, mitigate climate change, and support people’s livelihoods. First, we will introduce a concept and synthesis of current knowledge of the use of technologies and diversification globally. We will then show how implementation of ecological tools and diverse types of technologies such as machine-learning-based monitoring technology can help to monitor biodiversity within diversified agricultural systems. In examples from Brazil, Cameroon, and China, we will highlight the use of embedded machine vision meta-bar coding technologies to understand and improve ecosystem service provisioning in cocoa agroforestry systems. We will also discuss how use of technologies and diversified farming systems can be combined to monitor bat populations to maintain biodiversity within agricultural systems and enhance natural pest control for higher yield and profits for farmers. Finally, we will look at the opportunities and challenges for implementing technologies in the diversified farming systems in the tropics to improving farmers' livelihoods.