title: Predicting the distribution of commercially important invertebrate stocks under future climate.
abstract: The future management of commercially exploited species is challenging because techniques used to predict the future distribution of stocks under climate change are currently inadequate. We projected the future distribution and abundance of two commercially harvested abalone species (blacklip abalone, Haliotis rubra and greenlip abalone, H. laevigata) inhabiting coastal South Australia, using multiple species distribution models (SDM) and for decadal time slices through to 2100. Projections are based on two contrasting global greenhouse gas emissions scenarios. The SDMs identified August (winter) Sea Surface Temperature (SST) as the best descriptor of abundance and forecast that warming of winter temperatures under both scenarios may be beneficial to both species by allowing increased abundance and expansion into previously uninhabited coasts. This range expansion is unlikely to be realised, however, as projected warming of March SST is projected to exceed temperatures which cause up to 10-fold increases in juvenile mortality. By linking fine-resolution forecasts of sea surface temperature under different climate change scenarios to SDMs and physiological experiments, we provide a practical first approximation of the potential impact of climate-induced change on two species of marine invertebrates in the same fishery.
authors.affiliation: Southern Seas Ecology Laboratories, School of Earth & Environmental Sciences, University of Adelaide, Adelaide, South Australia, Australia. bayden.russell@adelaide.edu.au
authors.forename: Bayden D
authors.initials: BD
authors.lastname: Russell
authors.forename: Sean D
authors.initials: SD
authors.lastname: Connell
authors.forename: Camille
authors.initials: C
authors.lastname: Mellin
authors.forename: Barry W
authors.initials: BW
authors.lastname: Brook
authors.forename: Owen W
authors.initials: OW
authors.lastname: Burnell
authors.forename: Damien A
authors.initials: DA
authors.lastname: Fordham
mesh_terms: D063147:Animal Distribution; D000818:Animals; D002980:Climate; D057231:Climate Change; D005398:Fisheries; D008954:Models, Biological; D008974:Mollusca; D009792:Oceans and Seas; D011157:Population Dynamics