Each month, The Existential Risk Research Assessment (TERRA) uses a unique machine-learning model to predict those publications most relevant to existential risk or global catastrophic risk. The following are a selection of those papers identified this month.
Please note that we provide these citations and abstracts as a service to aid other researchers in paper discovery and that inclusion does not represent any kind of endorsement of this research by the Centre for the Study of Existential Risk or our researchers.
A number of stochastic mortality models with transitory jump effects have been proposed for the securitization of catastrophic mortality risks. Most of the studies on catastrophic mortality risk modeling assumed that the mortality jumps occur once a year or used a Poisson process for their jump frequencies. Although the timing and the frequency of catastrophic events are unknown, the history of the events might provide information about their future occurrences. In this paper, we propose a specification of the Lee–Carter model by using the renewal process and we assume that the mean time between jump arrivals is no longer constant. Our aim is to find a more realistic mortality model by incorporating the history of catastrophic events. We illustrate the proposed model with mortality data from the US, the UK, Switzerland, France, and Italy. Our proposed model fits the historical data better than the other jump models for all countries. Furthermore, we price hypothetical mortality bonds and show that the renewal process has a significant impact on the estimated prices.
Recent studies showing temporal changes in local and regional insect populations received exaggerated global media coverage. Confusing and inaccurate science communication on this important issue could have counterproductive effects on public support for insect conservation. The insect apocalypse narrative is fuelled by a limited number of studies that are restricted geographically (predominantly the United Kingdom, Europe, the United States) and taxonomically (predominantly some bees, macrolepidoptera, and ground beetles). Biases in sampling and analytical methods (e.g., categorical versus continuous time series, different diversity metrics) limit the relevance of these studies as evidence of generalized global insect decline. Rather, the value of this research lies in highlighting important areas for priority investment. We summarize research, communication, and policy priorities for evidence-based insect conservation, including key areas of knowledge to increase understanding of insect population dynamics. Importantly, we advocate for a balanced perspective in science communication to better serve both public and scientific interests.