Biology subjects

Lyberger, K.

Publications and source records attributed to Lyberger, K..

3 recordsLinked to original sources

bioRxiv2021

Thermal asymmetries influence effects of warming on stage and size-dependent predator-prey interactions

Climate warming directly influences the developmental and feeding rates of organisms. Changes in these rates are likely to have consequences for species interactions, particularly for organisms affected by stage- or size-dependent predation. However, because of differences in species-specific responses to warming, predicting the impact of warming on predator and prey densities can be difficult. We present a general model of stage-dependent predation with temperature-dependent vital rates to explore the effects of warming when predator and prey have different thermal optima. We found that warming generally favored the interactor with the higher thermal optimum. Part of this effect occurred due to the stage-dependent nature of the interaction, and part due to thermal asymmetries. Furthermore, large differences in thermal optima between predators and prey (i.e., a high degree of asymmetry) led to a weaker interaction. Interestingly, below the predator and prey thermal optima, warming caused prey densities to decline, even as increasing temperature improved prey performance. We also parameterize our model using values from a well-studied system, Arctia virginalis and Formica lasioides, in which the predator has a warmer optimum. Overall, our results provide a general framework for understanding stage- and temperature-dependent predator-prey interactions, and illustrate that the thermal niche of both predator and prey are important to consider when predicting the effects of climate warming.

ecology↗

bioRxiv2020

Evolution in response to extreme events: good or bad?

Climate change is predicted to increase the severity of environmental perturbations, including storms and droughts, which act as strong selective agents. These extreme events are often of finite duration (pulse disturbances). Hence, while evolution during an extreme event may be adaptive, the resulting phenotypic changes may become maladaptive when the event ends. Using individual-based models and analytic approximations that fuse quantitative genetics and demography, we explore how heritability and phenotypic variance affect population size and extinction risk in finite populations under an extreme event of fixed duration. Since more evolution leads to greater maladaptation and slower population recovery following an extreme event, slowing population recovery, greater heritability can increase extinction risk when the extreme event is short, as in random environments with low autocorrelation. Alternatively, when an extreme event is sufficiently long, heritability often helps a population persist, as under a press perturbation. We also find that when events are severe, the buffering effect of phenotypic variance can outweigh the increased load it causes. Our results highlight the importance of the length and severity of a disturbance when assessing the role of evolution on population recovery; the rapid adaptive evolution observed during extreme events may be bad for persistence.

evolutionary biology↗

bioRxiv2019

Antagonistic coevolution between multiple quantitative traits: matching interactions can be subsets of difference interactions

AO_SCPLOWBSTRACTC_SCPLOWCoevolution is one of the major drivers of complex dynamics in population ecology. Historically, antagonistic coevolution in victim-exploiter systems has been a topic of special interest, and involves traits with various genetic architectures (e.g., the number of genes involved) and effects on interactions. For example, exploiters may need to have traits that \"match\" those of victims for successful exploitation (i.e., a matching interaction), or traits that exceed those of victims (i.e., a difference interaction). Different models exist which are appropriate for different types of traits, including Mendelian (discrete) and quantitative (continuous) traits. For models with multiple Mendelian traits, recent studies have shown that antagonistic coevolutionary patterns that appear as matching interactions can arise due to multiple difference interactions with costs of having large trait values. Here we generalize their findings to quantitative traits and show, analogously, that the multidimensional difference interactions with costs sometimes behave qualitatively the same as matching interactions. While previous studies in quantitative genetics have used the dichotomy between matching and difference frameworks to explore coevolutionary dynamics, we suggest that exploring multidimensional trait space is important to examine the generality of results obtained from one-dimensional traits.

evolutionary biology↗