2018 ESA Annual Meeting (August 5 -- 10)

COS 39-1 - How will climate change and trophic structure affect plant (crop) and herbivore (pest) performance in a soybean-aphid-ladybug system?

Tuesday, August 7, 2018: 1:30 PM
340-341, New Orleans Ernest N. Morial Convention Center
Hsin-Yi Lee1, Ying-Jie Wang1 and Chuan-Kai Ho2, (1)Institute of Ecology and Evolutionary Biology, National Taiwan University, (2)Department of Life Science, National Taiwan University
Background/Question/Methods

While climate change (e.g., elevated temperature and CO2) and trophic structure separately affect species performance, their interactive effects remain unclear. This study empirically examined how elevated temperature, elevated CO2, and trophic structure may individually and interactively affect plant and herbivore performance in a tri-trophic agroecosystem (soybean, soybean aphids, and seven-spot ladybugs). Specifically, this study used environmental chambers to apply the following treatments. Temperature treatment included control, 2 oC, and 4 oC warming (all with daily fluctuation). CO2 treatment included control and elevation (500 and 1000 ppm, respectively). Trophic structure treatment included Tro1 (soybean), Tro2 (soybean + aphid), and Tro3 (soybean + aphid + ladybug).

Results/Conclusions

The results showed that temperature, CO2, and trophic structure individually or interactively affected plant (soybean) and herbivore (aphid) performance. For plant performance, warming generally reduced aboveground plant biomass under control CO2, but increased aboveground plant biomass under elevated CO2. Herbivore presence (Tro2) reduced aboveground plant biomass, but adding predators (ladybugs) (Tro3) recovered the reduction, suggesting a tropic cascade from predators to plants. For herbivore performance, warming or predator presence alone reduced herbivore populations, while warming, CO2 and trophic structure effects also interacted in this case. The results suggest that climate change impact assessment may need to consider the interplay between abiotic (e.g., temperature and CO2) and biotic factors (e.g., trophic interactions) in order to make a more accurate prediction.