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We reassess whether range shifts in marine organisms are occurring in a direction predicted by causation due to climate using two different methods: a global meta-analysis and a regional analysis of museum records focussing on marine molluscs. Globally we used rigorous selection criteria to investigate studies describing range shifts in marine organisms, including exclusion of single-species studies and those that inferred range shifts through shifting abundance. For each species meeting these criteria (311 species from 13 studies), the distance in kilometres moved per year was calculated, and life history characteristics such as mobility, habitat, dispersal potential and trophic level were recorded to assess if these were linked to the shifts. We also examined the potential correlation between changing sea surface temperatures and range shifts. Regionally we analysed the intertidal mollusc collection of the Australian Museum and Museum of Victoria and consulted with mollusc experts to determine if museum records could be used to detect range shifts in marine invertebrates. The global meta-analysis showed that individual species shifted on average 8.9 km polewards per year. Range shifts were not significantly related to temperature change or life history characteristics with the exception of intertidal and nearshore subtidal fauna showing poleward shifts (6.8 and 14.3 km per decade, respectively) and shelf fauna showing a slight equatorial shift (2.7 km per decade). Our regional analysis showed that 54 of the 634 mollusc species examined shifted their range into or out of the well-surveyed Sydney region. However, closer examination by mollusc experts revealed that the evidence for these shifts was unreliable, and we conclude that caution is required when using museum records in range shift studies. Overall, our study supports previous research showing a poleward shift in response to climate change, although this is an order of magnitude less than values reported in the only other meta-analysis on marine range shifts, possibly owing to the strict selection criteria applied here.

A growing need to manage marine biodiversity sustainably at local, regional and global scales cannot be met by applying existing biological data. Abiotic surrogates of biodiversity are thus increasingly valuable in filling the gaps in our knowledge of biodiversity patterns, especially identification of hotspots, habitats needed by endangered or commercially valuable species and systems or processes important to the sustained provision of ecosystem services. This review examines the use of abiotic variables as surrogates for patterns in benthic biodiversity with particular regard to how variables are tied to processes affecting species richness and how easily those variables can be measured at scales relevant to resource management decisions. Direct gradient variables such as salinity, oxygen concentration and temperature can be strong predictive variables for larger systems, although local stability of water quality may prevent usefulness of these factors at fine spatial scales. Biological productivity has complex relationships with benthic biodiversity and although the development of local and regional models cannot accurately predict outside the range of their biological sampling, remote sensing may provide useful information. Indeed, interpolated values are available for much of the world’s seas, and these are continually being refined by the collection of remote sensing and field data. Sediment variables often exhibit complex relationships with benthic biodiversity. The strength of the relationship between any one sediment variable and biodiversity may depend on the state of another sediment variable in that system. Percentage mud, percentage gravel, rugosity and compaction hold the strongest independent predictive power. Rugosity and the difference between gravel and finer sediments can be established using acoustic methods, but to quantify grain size and measure compaction, a sample is necessary. Pure spatial variables such as latitude, longitude and depth are not direct drivers of biodiversity patterns but often correspond with driving gradients and can be of some use in prediction. In such cases it would be better to identify what the spatial variable is acting as a proxy for so boundaries for that variable are not overlooked. The utility of these potential surrogates vary across spatial scales, quality of data, and management needs. A continued focus on surrogate research will address the need of marine scientists and resource managers worldwide for accurate and robust predictions, extending from simple measures of diversity to species distributions and patterns of assemblage.