Detecting range-shifting species using their environmental preferences
redmap-admin, 30 Aug 2017.
Curtis Champion is a PhD student at the Institute for Marine and Antarctic Studies (IMAS) and CSIRO Oceans and Atmosphere. Here he explains how we can use species' preferences for specific environmental conditions to measure and monitor the effects of climate change on their distributions.
When I’m cold, I find myself mindlessly gravitating towards the warmth of the fireplace, while on those hot Summer days I’ll commonly seek out the comparative cool of a stream or the ocean. Moving around like this is an innate response to the temperature of the environment and, despite our ability as humans to regulate our own body temperature, suggests there’s a preferred range of temperatures that make us happiest – not too hot, not too cold, but juuust right.
Unlike us mammals, most marine species can’t regulate their own body temperature and instead rely on the temperature of their environment to do this for them – making it necessary for these species to follow their thermal preferences when environmental conditions change. When species find themselves outside the temperature range they are best suited to, it becomes difficult for them to reproduce, grow and feed, which results in poor competitive ability and sometimes death.
So… marine species have strong preferences for specific environmental conditions, like a preferred temperature range. But how can we apply this understanding for assessing the ecological effects of climate change in marine systems?
Well, we know that climate change is driving a rapid, global redistribution of biodiversity, and these changes are occurring fastest in marine systems (https://theconversation.com/climate-driven-species-on-the-move-are-changing-almost-everything-74752). However, it’s very difficult to detect these changes for many marine animals because historical data sets of species occurrence locations seldom exist, and when these are available the information they contain is usually highly confounded by observer biases. For example, observations of animals commonly come from locations that are easy for people to access, and may not actually represent the true range of a species.
In the absence of these high-quality data sources, we can instead turn to our understanding of species environmental preferences to infer potential changes in their distributions through time. It’s important that multiple environmental factors, and not just temperature alone, are considered when assessing the combination of conditions that different species are best suited to. Thankfully, satellite technology now allows us to remotely sense lots of environmental variables, such as sea surface temperature, dissolved oxygen and current speed. This information can be matched to the locations where a species of interest has been recorded in order to gain a thorough understanding of the overall environmental conditions that species prefers.
Understanding the combination of environmental conditions that best describe where a species has been observed helps us predict the chance of that species occurring in other locations, given some information about the environmental conditions of those locations (again, easily available from satellites). If these predictions are made regularly and over a long period of time (say, each month for 20 years), it’s possible to measure changes in the area that species are likely to be found. It’s also possible to account for the influence of natural climate variation on these predictions (like seasonal warming and cooling), and doing so can help reveal the underlying influence of human-caused climate change on species distributions.
While you might not consider your next drive to the beach on a hot Summer’s day an attempt to ‘track your thermal preference,’ it is worth considering that the location of species’ in space and time is highly dependent on preferences for environmental conditions that they have acquired through the course of evolution. Worth considering also, are the many useful applications for this understanding of species selecting for their preferred environmental conditions - like for predicting the ecological effects of climate change, or for justifying why you’re at the beach on a hot day when you should be at work.