Identifying financial actors exposed to tipping point risks

Ecosystems around the world are showing symptoms of resilience loss. With them there is an increasing risk of critical transitions or regime shifts: large, abrupt and difficult to reverse changes in the function and structure of ecosystems. When regime shifts occur they often impact the flow of benefits that people get from nature, and with them the ability of companies, cities or nations to satisfy human needs. Here we ask who is exposed to ecological regime shift risks, and by being exposed, who has the agency or power to intervene and perhaps avoid tipping points?

To answer this question we match companies whose activities imply the use or extraction of natural resources in places vulnerable to regime shifts. First, we use Earth observations to quantify resilience loss in marine systems. We also used temeprature records to quantify the probability of extreme and severe heat wave events in the oceans. Both are conditions that can reduce primary productivity and impact fisheries. Then, we identify vessels that fish in these areas of the world and match their owners and shareholders when available in public databases.

For publicly listed companies we reconstruct social networks of companies ownership and investments. The networks serve to identify financial actors exposed to ecological tipping points through several investments or regions of the world. The multilayer network can be centred around companies, shareholders, investors, or countries. Clustering at different levels of aggregation allow us to identify actors with disproportional risk exposure, but also companies, investors or countries who could make a difference in mitigating risk.