Rosa McGuire

All Publications

• Increase in heat tolerance following a period of heat stress in a naturally occurring insect species JOURNAL OF ANIMAL ECOLOGY Ardelan, A., Tsai, A., Will, S., Mcguire, R., Amarasekare, P. 2023: 2039-2051

  Abstract

  Climate warming is the defining environmental crisis of the 21st century. Elucidating whether organisms can adapt to rapidly changing thermal environments is therefore a crucial research priority. We investigated warming effects on a native Hemipteran insect (Murgantia histrionica) that feeds on an endemic plant species (Isomeris arborea) of the California coastal sage scrub. Experiments conducted in 2009 quantified the temperature responses of juvenile maturation rates and stage-specific and cumulative survivorship. The intervening decade has seen some of the hottest years ever recorded, with increasing mean temperatures accompanied by an increase in the frequency of hot extremes. Experiments repeated in 2021 show a striking change in the bugs' temperature responses. In 2009, no eggs developed past the second nymphal stage at 33°C. In 2021, eggs developed into reproductive adults at 33°C. Upper thermal limits for maturation and survivorship have increased, along with a decrease in mortality risk with increasing age and temperature, and a decrease in the temperature sensitivity of mortality with increasing age. While we cannot exclude the possibility that other environmental factors occurring in concert could have affected our findings, the fact that all observed trait changes are in the direction of greater heat tolerance suggests that consistent exposure to extreme heat stress may at least be partially responsible for these changes. Harlequin bugs belong to the suborder Heteroptera, which contains a number of economically important pests, biological control agents and disease carriers. Their differential success in withstanding warming compared to beneficial holometabolous insects such as pollinators may exacerbate the decline of beneficial insects due to other causes (e.g. pollution and pesticides) with potentially serious consequences on both biodiversity and ecosystem functioning.

  View details for DOI 10.1111/1365-2656.13995

  View details for Web of Science ID 001061415300001

  View details for PubMedID 37667662

• EcoEvoApps: Interactive apps for theoretical models in ecology and evolutionary biology ECOLOGY AND EVOLUTION McGuire, R. M., Hayashi, K. T., Yan, X., Carita Vaz, M., Cinoglu, D., Cowen, M. C., Martinez-Blancas, A., Sullivan, L. L., Vazquez-Morales, S., Kandlikar, G. S. 2022; 12 (12): e9556

  Abstract

  The integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology is that theory is often developed and expressed in the form of mathematical models that can feel daunting and inaccessible for students and empiricists with variable quantitative training and attitudes towards math. A promising way to make mathematical models more approachable is to embed them into interactive tools with which one can visually evaluate model structures and directly explore model outcomes through simulation. To promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open-source, and multilingual R/Shiny apps that include model overviews, interactive model simulations, and code to implement these models directly in R. The package currently focuses on canonical models of population dynamics, species interactions, and landscape ecology. These apps help illustrate fundamental results from theoretical ecology and can serve as valuable teaching tools in classroom settings. We present data from student surveys which show that students rate these apps as useful learning tools, and that using interactive apps leads to substantial gains in students' interest and confidence in working with mathematical models. This points to the potential for interactive activities to make theoretical models more accessible to a wider audience, and thus facilitate the feedback between theory and data across ecology and evolutionary biology.

  View details for DOI 10.1002/ece3.9556

  View details for Web of Science ID 000905466000001

  View details for PubMedID 36479028

  View details for PubMedCentralID PMC9719042