Mr Curtis Champion1,2, Dr Alistair Hobday2, Dr Sean Tracey1, Professor Gretta Pecl1
1Institute for Marine and Antarctic Studies, University of Tasmania, Forster, Australia, 2CSIRO Oceans and Atmosphere, Hobart, Australia
Climate-driven shifts in species distributions are occurring rapidly within marine systems and are predicted to continue under climate change. Animal body condition is likely to be more sensitive to variation in environmental habitat quality than the presence or absence of individuals and may be a valuable index for assessing changes in species distributions. Utilising the range-shifting kingfish (Seriola lalandi) from eastern Australia, we compared spatial predictions of oceanographic habitat quality with field-derived body condition data, quantified using Bioelectrical Impedance Analysis (BIA). These comparisons were used to: 1. assess if the body condition of individuals sampled from core oceanographic habitat differed from individuals sampled from range-edge habitat, and 2. investigate potential mismatches in kingfish occurrence and body condition data in response to sea surface temperature (SST). A significant positive relationship between kingfish body condition and oceanographic habitat quality was identified (F₁, ₈₅ = 38.62, P < 0.001; r² = 0.31), suggesting that increasing habitat quality at the poleward edge of this species’ distribution is likely to result in improved body condition at higher latitudes. The SST value corresponding to the peak in kingfish occurrence from eastern Australia was found to be ~2.5°C warmer than for the peak in body condition data, suggesting that kingfish found closer to the leading edge of their distribution are in better condition than individuals from lower latitudes. Applications of predictive fish condition models based on regional oceanographic conditions could prove valuable for forecasting climate-driven changes to the condition of high-value target species throughout their distributions.
Curtis Champion is a PhD candidate at the Institute for Marine and Antarctic Studies and CSIRO Oceans and Atmosphere in Hobart, Tasmania, graduating in 2019. Curtis is interested in developing predictive statistic models to estimate species abundance and distributions and utilising these quantitative approaches to support field-based surveys and stakeholder decision-making.