Biodiversity in marine invertebrate responses to acute warming revealed by a comparative multi-omics approach.

Understanding species' responses to environmental change underpins our abilities to make predictions on future biodiversity under any range of scenarios. In spite of the huge biodiversity in most ecosystems, a model species approach is often taken in environmental studies. To date, we still do not know how many species we need to study to input into models and inform on ecosystem-level responses to change. In this study, we tested current paradigms on factors setting thermal limits by investigating the acute warming response of six Antarctic marine invertebrates: a crustacean Paraceradocus miersi, a brachiopod Liothyrella uva, two bivalve molluscs, Laternula elliptica, Aequiyoldia eightsii, a gastropod mollusc Marseniopsis mollis and an echinoderm Cucumaria georgiana. Each species was warmed at the rate of 1 °C h and taken to the same physiological end point (just prior to heat coma). Their molecular responses were evaluated using complementary metabolomics and transcriptomics approaches with the aim of discovering the underlying mechanisms of their resilience or sensitivity to warming. The responses were species-specific; only two showed accumulation of anaerobic end products and three exhibited the classical heat shock response with expression of HSP70 transcripts. These diverse cellular measures did not directly correlate with resilience to heat stress and suggested that each species may have a different critical point of failure. Thus, one unifying molecular mechanism underpinning response to warming could not be assigned, and no overarching paradigm was supported. This biodiversity in response makes future ecosystems predictions extremely challenging, as we clearly need to develop a macrophysiology-type approach to cellular evaluations of the environmental stress response, studying a range of well-rationalized members from different community levels and of different phylogenetic origins rather than extrapolating from one or two arbitrary model species.