HKU Ecologist applied novel statistical method to analysing

HKU Ecologist applied novel statistical method to analysing causal inference and revealed importance of climate change


An example of deep-sea soft sediment ecosystem.
Photo credit: NOAA OER and Ocean Exploration Trust; A. Thurber camera loan. Courtesy of Lisa Levin.
Which of temperature or food is more important for the richness of deep-sea animals? Dr Moriaki YASUHARA from the School of Biological Sciences, the Research Division for Ecology & Biodiversity, and The Swire Institute of Marine Science, The University of Hong Kong (HKU), in collaborating with Hideyuki DOI from University of Hyogo and Masayuki USHIO from Kyoto University, used long-term fossil dataset and novel statistical method to detect causality and found climate control of deep-sea biodiversity.
Deep-sea cover >90 % of the ocean. So, understanding biodiversity drivers in deep-sea is critically important to project future changes in the function of Earth’s ocean system. Recently, two main factors of the deep-sea biodiversity control have been actively debated, which are (1) food supply via marine snow (aka sinking particulate organic carbon originated from surface primary production) that is the main food source for deep-sea animals (given no sun light penetration and so no phytoplankton production in deep sea); and (2) climate-driven deep-sea temperature change. These two hypotheses of marine-snow or temperature control of deep-sea biodiversity are difficult to be fully tested by traditional modelling framework because the environment-diversity relationship that facilitates deep-sea biodiversity can be complex.

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