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Asymmetric interactions among conspecifics can have diverse effects on population dynamics including stabilization, generation of cycles, and induction of chaotic fluctuations. A difficult challenge, however, is establishing the link between the impact of asymmetric interactions on life history and the consequences for population dynamics. The smaller tea tortrix, Adoxophyes honmai, is a good example. Larval instars differ dramatically in size and have a tendency for cannibalism, which suggests the potential for strong asymmetric interactions among instars. Yet whether these asymmetries have any role in generating the distinct single‐generation cycles observed in the field and laboratory is unclear. Here we report on the development of a new experimental approach to characterize the impact of asymmetric interactions on life history that can be directly embedded into stage‐structured population models. The experiments use donor‐replacement protocols in which focal individuals are challenged to complete their life cycles in competitive environments where the instar and density of the competitors are held constant. The experimentally derived interaction surface contains all the information about stage‐specific interactions and provides a straightforward framework for evaluating alternative ways of abstracting the interactions into traditional models of asymmetric competition. Working with the smaller tea tortrix, we found strong evidence of asymmetric interactions and identified critical “tipping points” in the competitive environment that strongly affected survival but not development. We incorporated the experimentally derived interaction surface into a stage‐structured population model and found that despite the strong impact that asymmetric interactions have on tea tortrix life history, they do not scale‐up to impact the predicted asymptotic population dynamics. Comparing these dynamics with two abstracted models of stage‐structured interactions revealed that while the quantitative details of the emergent dynamics depends on the shape of the interaction surface, the qualitative features, such as the emergence of single‐generation cycles and rapid synchronization of development among individuals, are pleasingly robust.

Seasonality has been suggested as a necessary factor for the initiation of vole population cycles in Fennoscandia. This has been well described for a latitudinal gradient. Here, we used an elevational gradient as a proxy for winter length to study how the length of the winter season correlates with the amplitude of bank vole Myodes glareolus population cycles. In addition, we studied whether the small mammalian generalist predator community present locally could explain any elevational effects. We estimated the population size of 30 local bank vole populations. We found a strong effect of elevation on the amplitude of the population cycle with local populations at around 800 m elevation having 1.5 times greater densities than populations in the valley (ca 300 m elevation). A univariate model with elevation as predictor for amplitude was twice as likely to be the best model than models including generalist predators. Our results fit well with the theories of a positive effect of winter length on the amplitude of vole population cycles in Fennoscandia, irrespective of whether the seasonal effect corresponds to a latitudinal or elevational gradient. The mechanisms may be limited resources during winter rather than generalist predators.

Intraspecific interactions can occur through many ways but the mechanisms can be broadly categorized as food exploitation and interference interactions. Identifying how intraspecific interactions impact life history is crucial to accurately predict how population density and structure influence dynamics. However, disentangling the effects of interference interactions from exploitation using experiments is challenging for most biological systems. Here we propose an approach that combines experiments with modelling to infer the pathways of intraspecific interactions in a system. First, a consumer‐resource model is built without intraspecific interactions. Then, the model is parameterized by fitting it to life‐history data from a first experiment in which food abundance was varied. Next, hypothesized scenarios of intraspecific interactions are incorporated into the model which is then used to predict life histories with increasing competitor density. Lastly, model predictions are compared against data from a second experiment which raised groups of competitors of different densities. This comparison allows us to infer the role of interference and exploitation in shaping life history. We demonstrated the approach using the smaller tea tortrix Adoxophyes honmai across a range of temperature. We investigated five scenarios of interactions that included exploitation and three pathways for interference through some effects either on energetics to represent changes in ingestion or activity, or on mortality to model deadly interactions, or on mortality and ingestion to model cannibalism. Overall, intraspecific interactions in tea tortrix are best explained by a high level of deadly interactions along with some level of interference that acts on energy such as escaping and blocking access to food. Deadly interactions increase with temperature while interference that acts on energy is strongest close to the optimal temperature for reproduction. Interestingly, exploitation is more important than interference at low competitor density. The combination of mathematical modelling and experimentation allowed us to mechanistically characterize the intraspecific interactions in tea tortrix in a way that is readily incorporated into population‐level mathematical models. The primary value of this approach, however, is that it can be applied to a much wider range of taxa than is possible with pure experimental approaches. Read the free Plain Language Summary for this article on the Journal blog.

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