Intangible Losses, Damages and At-Risk Settlements: The Extent of Causality and Burden of Proof for Climate Related Loss and Damage in the Fiji Islands

Abstract

In this article, a plethora of social, cultural, legal and policy related remedies for harm caused by climate related loss and damage (L&D) were examined, particularly in rural and remote Fiji Islands. The meaning of loss and damage, and its relationship to climate mitigation and adaptation, was discussed. The concept of causality and attempt are considered to expose some criteria that the law uses to test causation in the hope to subject these to a much-needed discussion of climate change and causation affecting international law, domestic law, and climate science. A probabilistic event attribution (PEA) is explored having crucial implications in the development of PEA. When vulnerabilities and thresholds are known, changing risks can be calculated ex ante and, therefore, changing risks can be forecasted. The improvement of the methods allows geographically very specific events to be anticipated and, thus, appropriate adaptation measures can be designed. It is considered (at a conceptual level) how those harmed by loss and damage in Fiji from human-induced climate change may pursue remedies against those who have contributed to the harm. Finally, this article explores what that evidence needs to be (extent of causality and burden of proof) for loss and the damages to be awarded. It is concluded by highlighting the values of probabilistic event attribution (PEA), and how vulnerabilities in Fijian communities continue to be a deep concern. Further work needs to be done with respect to social, cultural, and biological interconnectivity that concretely underlines the importance of climate change and how it diminishes well-being and cultural integrity of Indigenous people by affecting endemic plant species. Disaster Risk Reduction (DRR) needs to be cognizant of social and cultural implications of forced migration. Causality and burden of proof within the legal context has its built-in complexities and, hence, it needs further research.