Using species distribution models to assess the long‐term impacts of changing oceanographic conditions on abalone density in south east Australia

Mary A Young,Adam D Miller,Molly Fredle,Stephen E Swearer,Daniel Ierodiaconou,Jutta Beher,Eric A Treml,Harry Gorfine

doi:10.1111/ecog.05181

Abstract

Warming from climate change and resulting increases in energy stored in the oceans is causing changes in the hydrodynamics and biogeochemistry of marine systems, exacerbating current challenges facing marine fisheries. Although studies have evaluated effects of rising temperatures on marine species, few have looked at these impacts along with other environmental drivers over long time periods. In this study, we associate long‐term density of blacklip abalone to changing oceanographic conditions in a climate change ‘hot‐spot’ off southeast Australia. We downscaled and hind‐casted existing hydrodynamic models to provide information on waves and currents over 25 yr and used this information to run biophysical connectivity models. We combined the connectivity models with 21 yr of data on abalone density, temperature, seafloor habitat, and the effects of a disease outbreak in an machine learning modeling approach to develop a spatio‐temporal model of abalone density. We found that the combination of temperature, connectivity, current speed, wave orbital velocity, fishery catch, depth, reef structure and a disease outbreak explain 70% of variation in abalone density and allowed us to create 30 m resolution predictive grids with 75% accuracy. An emerging hotspot analysis run on the individual predictive grids from each year detected a predominance of low‐density grids across the region, with 49.5% of cells classified as cold spots, 14.3% as hotspots and 36.2% with no significant patterns observed. This type of spatio‐temporal analysis provides important insights into how changing environmental conditions are impacting density in an important fishery species, allowing for better adaptive management in the face of future climate change.

Highlights

Almost the entire Earth is experiencing increasing surface temperatures due to climate change with a global average warming of 0.85°C over the last century and projected increases of more than 2°C by 2100 (RCP4.5; IPCC 2013)
We characterized temporal and spatial variability in oceanographic conditions along the coast of Victoria in southeastern Australia, and identified key environmental factors likely influencing the distribution of H. rubra
Our results identified a variety of influential environmental factors that, when combined, can accurately predict H. rubra distributions and indicate how distributions are changing through space and time

Summary

Introduction

Almost the entire Earth is experiencing increasing surface temperatures due to climate change with a global average warming of 0.85°C over the last century and projected increases of more than 2°C by 2100 (RCP4.5; IPCC 2013). The majority of the energy (90%) from these increases is stored in the world’s oceans (IPCC 2013), elevating temperatures and causing changes in the hydrodynamics and biogeochemistry of marine systems (IPCC 2007, Diaz and Rosenberg 2008). These changes are already having a significant impact on marine biodiversity (Pauly et al 2002, Srinivasan et al 2010, Poloczanska et al 2013). While the effects of changing temperature on fisheries around the world are being studied at increasing rates (Cheung et al 2010, Lam et al 2016, Serpetti et al 2017), other oceanographic factors associated with climate change can affect marine species’ distribution and productivity but are often overlooked (Harley et al 2006). More recent studies are examining the effects of ocean acidification on marine fisheries (Stiasny et al 2016, Fernandes et al 2017) but more oceanographic information can help further understand the effects of climate change

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Conclusion