Climate-Informed Decision-Making in Data-Poor Environments: Managing Climate Risk Through Citizen Science Networks

Abstract

Climate change impacts have become a verifiable reality in most communities in Africa and have already shown its ruthlessness in derailing modest gains made toward sustainable development. While evidence of climate change impacts abounds, especially in key climate-sensitive sectors, not many people living in affected communities have the requisite knowledge, understanding and capacity to respond to emerging impacts. Most communities in Ghana and Africa, broadly, lack the requisite climate change knowledge resources to inform adaptation choices. Adaptation decision-making, in most cases, is reactive, speculative, and based on flawed assumptions and understandings of the climate change phenomenon. This is essentially because most countries lack the capacity to make climate-informed decisions which is also a function of the pervasive lack of efficient climate information services regime across Africa. The paucity of climate change knowledge and associated climate information services is undoubtedly an issue of institutional capacity; however, it is also a function of an enduring culture—a poor attitude toward data collection and application—in decision-making processes. Data-poor environment, or data-poverty, as implied in this work, therefore, broadly describes the absence of a data management culture in decision-making processes; however, specifically to climate change, it describes the lack of functional climate information services regime in local communities in Africa and how such omissions impede the ability of countries to make climate-informed decisions to support adaptation and resilience building. Focusing on Ghana, the paper problematizes the lack of climate information in local communities. The paper argues that Africa's climate crisis is as much a knowledge and learning challenge which requires new and innovative learning approaches to build capacities to facilitate the making of data-driven and climate-informed adaptation decisions in local communities. The paper, therefore, foregrounds citizen-science networks as avenues for community-focused and community-based climate knowledge co-producing mechanisms.