CLIMATE CHANGE AND EXTINCTION RISK IN AN IMPORTANT GROUP OF MARINE INVERTEBRATES (DECAPODA): INFERENCES FROM THE GEOLOGICAL PAST

A promising new strategy in conservation biology is to use the geological record to inform present day intervention priorities. We illustrate three ways in which macroevolutionary data can be used to better understand biotic responses to current and ongoing environmental change.

We present a complete phylogeny of all 16,083 species of Decapoda; an order of crustaceans of great economic importance. We use this tree in combination with Species Distribution Models (SDMs) under three IPCC climate scenarios (A1B, B1 and A2) to highlight species most at risk of extinction due to climate change. We also investigate whether there is any link between Evolutionary Distinctiveness (ED) on our phylogeny and the likelihood of extinction under each IPCC scenario.

To further explore the value of this approach, we present macroevolutionary and macroecological data from two decapod infraorders: Anomura and Caridea. In Anomura (hermit crabs), habitat influences geohistorical speciation rates, with marine species under greater threat of extinction from global warming than freshwater species. In Caridea (shrimp), species that live in commensal or parasitic association with reef organisms (such as corals) experience lower speciation rates free living species. The risk of extinction in the former group may be elevated with the ongoing destruction of the fragile ecosystems they tend to inhabit. Although we do not suggest that these relationships are ubiquitous, they highlight the importance of macroecological and macroevolutianary perspectives for understanding the effects of current and ongoing climate change.

We give examples of three ways in which a macroevolutionary perspective can inform our understanding of the likely responses of extant species to current and projected environmental changes. 1) Phylogenies underpin valuable macroevolutionary indices, including measures of Evolutionary Distinctiveness. These can be used in conjunction with SDMs to infer proportions of biodiversity currently at risk of extinction. 2) The role of past climate change upon speciation rates can be modelled. 3) Some ecological traits may render species at greater risk of extinction. A future synthesis of these approaches may enable us to identify the Earth’s most vulnerable species, and thereby to inform conservation strategies.