Out of Time

Phenological asynchrony: a ticking time-bomb for seemingly stable populations? (2020) Simmonds et al., Ecology Letters, https://doi.org/110.1111/ele.13603

Image Credit: Ian Kirk from Broadstone, CC BY 2.0, Image Cropped

The Crux

When we think of climate change we tend to think about extreme weather events and melting ice caps, but the way in which our environment is changing is giving the planet more than just unseasonal weather. Phenology (the timing of biological events in nature) dictates when an organism begins a given part of its life cycle, and changes in phenology are one of the most frequent responses to climate change. Take bees and flowers; bees feed on the flowers of certain plant species, and in turn spread the plants’ pollen for them. They both depend on the other being around at the same time, and if flowers bloomed too early, or if the bees came around before the flowers were “ready” for them, both parties would suffer.

Such a mismatch is known as an asynchrony, and it is hypothesized to cause population declines due to the harmful impacts on one or more of the interacting species involved (see another recent post to understand how the loss of one or more interactions can lead to cascading effects throughout a local community). While many theoretical models have investigated these processes, today’s authors wanted to combine such models with long-term data on the phenology and population size of great tits (Parus major). Great tits rely on a small period of insect abundance to feed their young, and as such the more closely they can match the needs of their young to the abundance of insect populations the more they will increase their fitness.

What They Did

The authors used a modelling approach to understand the causes and consequences of asynchrony, which allowed them to predict great tit population dynamics to the end of this century. The models also predicted under which conditions asynchrony between predator and prey populations would drive the predator populations extinct. They did this under three different greenhouse gas scenarios representing low, medium, and high greenhouse gas emissions arising from human activities.

The authors combined information from a long-term study of great tit populations with phenotypic plasticity (changes in an organism due to some external factor, in this case the climate) and adaptive evolution (changes in a population over time as one or more traits are selected for due to their advantage over others). Doing so meant that they could reliably and confidently predict the hatching dynamics and trends in population size under three different climate scenarios until the end of the century.

The winter moth caterpillar (Operophtera brumata) makes up a significant part of the diet of great tit fledglings, and as such was used as the prey species in this study. (Image credit: gailhampshire, CC BY 2.0)

Did You Know: Great Tits as a Model System

The first model system I ever heard of was that of the fruit fly (Drosophila), but the most memorable system to me has always been the Great Tit. I have never worked with them, but great tits were the system used to explain ecological concepts in my first ecology course during my masters. Interestingly enough, it was an example of this exact predator-prey relationship and how climate change has resulted in the advancement of peak insect abundance. Long-term datasets like those used in this study, combined with the large species range, ease of use, and substantial knowledge of their biology makes the great tit an ideal species for many ecological and evolutionary experiments.

What They Found

The authors found that both predators (great tits) and prey (winter moth caterpillars) advanced their phenology, meaning that both great tit hatching and peak insect abundance occurred earlier in the year as the climate warmed. However, the advance of great tit hatching occurred slower than that of the advance of peak insect abundance, leading to a mismatch in predator and prey phenologies.

The “best” value for asynchrony is -13, meaning that birds hatching 13 days before peak caterpillar abundance will be the most successful. Under the low emissions scenario asynchrony only increased by ~5 days at most. Under the high emissions scenario, however, the model predicted that the great tits would hatch ~2 weeks after peak caterpillar abundance. The medium emissions scenario resulted in intermediate asynchrony values.

Asynchrony between predator and prey phenology was found to drive the predator populations extinct when peak insect abundance occurred either seven days before or 11 days after great tit hatching. Not surprisingly, the probability of extinction increased under the high emissions scenario, as this is when the greatest asynchrony was predicted to happen. 17% of the predator populations went extinct in the high emissions scenario, compared to 3.8% and 0.5% under the medium and low emissions scenarios, respectively.

Problems?

Models like those used in this paper rely on a variety of assumptions, and the assumptions in this paper greatly simplified the ecological and evolutionary conditions of the predator populations included in the model. Specifically, the authors assumed that great tit immigration occurred at a fixed rate, that the prey population would not evolve, and that competition between great tits or switching to a different diet would not occur. These simplifications have to be made in order for models like this to work, as including every possible factor from every possible source is computationally impossible. While these are not problems per se nor take away from the results of the paper, I would be interested in seeing how these other sources of potential variability would affect asynchrony in the future.

So What?

Climate change is the reality we are currently living in, and while this study isn’t telling us anything “new” it did uncover some of the mechanisms behind population collapse and species extinctions caused by climate change. Species interactions are the backbone of ecological communities, and the loss of one or more species in a network of species interactions affects not only the focal species, but the loss radiates outwards and can affect others. However, the model predictions in this study showed that under the low emissions scenario the predator populations were better able to match the changes in prey phenology. This result offers hope that if humans are able to get our emissions under control we may be able to mitigate the loss of species in the future.

Adam Hasik is an evolutionary ecologist interested in the ecological and evolutionary dynamics of host-parasite interactions. You can read more about his research and his work for Ecology for the Masses here, see his personal website here, or follow him on Twitter here.

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