“I don’t think it will be the humans. I think we’ll go quite early on,” says Julie Gray with a laugh. I’ve just asked Gray, a plant molecular biologist at the University of Sheffield, which species she thinks would be the last ones standing if we don’t take transformative action on climate change. Even with our extraordinary capacity for innovation and adaptability, humans, it turns out, probably won’t be among the survivors.

This is partly because humans reproduce agonisingly slowly and generally just one or two at a time – as do some other favourite animals, like pandas. Organisms that can produce many offspring quickly may have a better shot at avoiding extinction.

It may seem like just a thought experiment. But discussing which species are more, or less, able to survive climate change is disturbingly concrete. As a blockbuster biodiversity report stated recently, one in every four species currently faces extinction. Much of this vulnerability is linked to climate change, which is bringing about higher temperatures, sea level rise, more variable conditions and more extreme weather, among other impacts.

You might also like:

• Could wooden buildings be a climate change solution?

• How catastrophes can change the course of humanity

• Ten simple ways to act on climate change

Some caveats are in order. While the seriousness of climate change is undeniable, it’s impossible to know exactly how those effects will play out for species vulnerability, especially far into the future. Methods of forecasting vulnerability are ever evolving, while limited and inconsistent data, plus the complex interactions of policies, land-use changes, and ecological effects, mean that projections aren’t set in stone. Climate change vulnerability assessments have had biases and blind spots (just as humans do more generally). (Read more about how our cognitive biases prevent climate action). Moreover, the indirect effects that are responsible for many climate change impacts on populations, such as in the food chain, are more complex to model than direct effects.