The climate on our planet is changing and the range distributions of organisms are shifting in response. In aquatic environments, species might not be able to redistribute poleward or into deeper water when temperatures rise because of barriers, reduced light availability, altered water chemistry or any combination of these. How species respond to climate change may depend on physiological adaptability, but also on the population dynamics of the species. Density dependence is a ubiquitous force that governs population dynamics and regulates population growth, yet its connections to the impacts of climate change remain little known, especially in marine studies. Reductions in density below an environmental carrying capacity may cause compensatory increases in demographic parameters and population growth rate, hence masking the impacts of climate change on populations. On the other hand, climate-driven deterioration of conditions may reduce environmental carrying capacities, making compensation less likely and populations more susceptible to the effects of stochastic processes. Here we investigate the effects of climate change on Baltic blue mussels using a 17-year dataset on population density. Using a Bayesian modelling framework, we investigate the impacts of climate change, assess the magnitude and effects of density dependence, and project the likelihood of population decline by the year 2030. Our findings show negative impacts of warmer and less saline waters, both outcomes of climate change. We also show that density dependence increases the likelihood of population decline by subjecting the population to the detrimental effects of stochastic processes (i.e. low densities where random bad years can cause local extinction, negating the possibility for random good years to offset bad years). We highlight the importance of understanding, and accounting for both density dependence and climate variation when predicting the impact of climate change on keystone species, such as the Baltic blue mussel.
Keywords: Bivalvia; climate change; demographic mechanism; density dependence; population projection; salinity; stochastic process; temperature.
© 2020 British Ecological Society.